This book contains the proceedings of the 1st Latin American Congress on Automation and Robotics held at Panama City, Panama in February 2017. It gathers research work from researchers, scientists, and engineers from academia and private industry, and presents current and exciting research applications and future challenges in Latin American.

The scope of this book covers a wide range of themes associated with advances in automation and robotics research encountered in engineering and scientific research and practice. These topics are related to control algorithms, systems automation, perception, mobile robotics, computer vision, educational robotics, robotics modeling and simulation, and robotics and mechanism design. LACAR 2017 has been sponsored by SENACYT (Secretaria Nacional de Ciencia, Tecnologia e Inovacion of Panama).

Content of this proceedings discusses emerging trends in structural reliability, safety and disaster management, covering topics like total quality management, risk maintenance and design for reliability. Some papers also address chemical process reliability, reliability analysis and engineering applications in chemical process equipment systems and includes a chapter on reliability evaluation models of chemical systems. Accepted papers from 2019 International Conference on Reliability, Risk Maintenance and Engineering Management (ICRRM 2019) are part of this conference proceeding. It offers useful insights to road safety engineers, disaster management professionals involved in product design and probabilistic methods in manufacturing systems.

This book addresses cutting-edge topics in robotics and related technologies for rehabilitation, covering basic concepts and providing the reader with the information they need to solve various practical problems. Intended as a reference guide to the application of robotics in rehabilitation, it covers e.g. musculoskeletal modelling, gait analysis, biomechanics, robotics modelling and simulation, sensors, wearable devices, and the Internet of Medical Things.

This book comprises select peer-reviewed proceedings of the international conference on Research in Intelligent and Computing in Engineering (RICE 2020) held at Thu Dau Mot University, Vietnam. The volume primarily focuses on latest research and advances in various computing models such as centralized, distributed, cluster, grid, and cloud computing. Practical examples and real-life applications of wireless sensor networks, mobile ad hoc networks, and internet of things, data mining and machine learning are also covered in the book. The contents aim to enable researchers and professionals to tackle the rapidly growing needs of network applications and the various complexities associated with them.

Internet of Things (IoT) has become a valuable tool for connection and information exchange between devices. This book provides a brief introduction to this new field, focuses on wearable medical devices, and covers the basic concepts by providing the reader with enough information to solve various practical problems.

This book provides the latest applications, experiments, fundamentals concepts, and cutting-edge topics for the ehealth and wearable devices field. The book also offers topics related to Security in IoT and Wearable Devices, Wearable Devices and Internet of Medical Devices (IoMT), IoT for Medical Applications, and Tools and study cases.

The book brings new and valuable information to PhD researchers, students, professors, and professionals working in IoT and related fields.

This book gathers the proceedings of the 4th Latin American Congress on Automation and Robotics, held at San Salvador, El Salvador, on November 15–17, 2023. This book presents recent advances in the modeling, design, control, and development of autonomous and robotic systems and explores current exciting applications and future challenges of these technologies.

The scope of this book covers a wide range of research fields associated with automation and robotics encountered within engineering, scientific research, and practice. These topics are related to control theory, Robot Operating System (ROS), robot design, collaborative robots, artificial intelligence, computer vision, sensing, field and service robotics, human robot interaction and interfaces, modeling of robotic systems, industry 4.0, and the design of new robotic platforms.

Rehabilitation Robotics and Healthcare Devices presents cutting-edge topics in rehabilitation robotics and healthcare devices, covering basic concepts and providing readers with enough information to solve various practical problems. The book proves to be an excellent source to study the different emerging paradigms in rehabilitation robotics and healthcare areas, including related technologies such as sensors, wearable devices, internet of medical things, big data, machine learning for eHealth, edible sensors, robots in medicine, and exoskeleton robots for rehabilitation.

Rehabilitation robotics is an important field of study focused on improving the gait rehabilitation of people affected by neurological disorders, ictus, cerebral palsy, and spinal cord injuries, among others. The study of rehabilitation robotics includes medical activities, kinematics dynamics, and control analysis. This book presents a complete and exhaustive analysis of the kinematics and dynamics of exoskeleton robots for rehabilitation. The forward and inverse kinematics are studied using the geometric, Denavit-Hartenberg, and screw theory approach. The dynamics analysis of exoskeleton robots using Newton-Euler, Euler–Lagrange, and D'Alembert formulation are also studied. Moreover, the main control techniques for exoskeleton robots are analyzed, including robust control, impedance control, adaptive control, Lyapunov functions, and uncertainties found in dynamic systems. The book includes MATLAB applications and examples.

Rehabilitation robotics is an important field of study focused on improving the gait rehabilitation of people affected by neurological disorders, ictus, cerebral palsy, and spinal cord injuries, among others. The study of rehabilitation robotics includes medical activities, kinematics dynamics, and control analysis. This book presents a complete and exhaustive analysis of the kinematics and dynamics of exoskeleton robots for rehabilitation. The forward and inverse kinematics are studied using the geometric, Denavit-Hartenberg, and screw theory approach. The dynamics analysis of exoskeleton robots using Newton-Euler, Euler–Lagrange, and D'Alembert formulation are also studied. Moreover, the main control techniques for exoskeleton robots are analyzed, including robust control, impedance control, adaptive control, Lyapunov functions, and uncertainties found in dynamic systems. The book includes MATLAB applications and examples.

Currently, most of the world is connected through the Internet; there are no regional barriers between people, and even between things, since they can be connected and communicate through the Internet, allowing them greater capabilities and ways of use that before; this concept is known as the Internet of things. The population of elder adults in Mexico has a tendency to increase in the coming years; therefore, it is necessary to raise awareness about the promotion of healthcare and well-being of the quality of life of the elderly. The problem is how you can provide quality healthcare to people with reduced access to providers. Smarter Pills is an embedded device capable of reminding its user the moment in which his medicine should be taken. This is done using Google calendar reminders. Smart Pills is a container of pills designed to be portable. It helps the elderly to tell them when to take their medications and which one. It is a low-cost device that can be used easily by people who they take care of the elderly, and at the same time, it is intuitive for the users.

This chapter presents a comprehensive review of lower limb exoskeleton robots for rehabilitation. The most important features of each exoskeleton are discussed. In addition, a review of the applications of the exoskeletons according to different pathologies is presented. Then, challenges and issues in rehabilitation robotics are discussed as well as the exoskeleton market, sales, and forecast. This work covers different aspects of the development and current trends in robotic exoskeletons, providing as a complete review of the state-of-the-art of these devices.

In this book chapter is evinced the theoretical and experimental results regarding the adaptive control of rehabilitation robotics. In the first subsections it is explained the basics of adaptive control for different kinds of robots and mechanical systems. Meanwhile in the second part of this chapter is evinced three adaptive control strategies for rehabilitation robotics. These strategies are based on proportional-integral-derivative, sliding mode control, and backstepping adaptive control strategies. So in this way, it will be covered the main theoretical background for the adaptive control of rehabilitation robots. The ALICE robotics mechanism will be analyzed in this chapter in order to verify the stability and error convergence to zero in finite time for trajectory tracking purposes. The Lyapunov theorem is crucial to design these adaptive controllers, in order to meet the previous mentioned closed loop system requirements.

Due to the diverse kinds of uncertainties and disturbances found in rehabilitation robots, this chapter is devoted to evince diverse kinds of impedance controllers for these kinds of mechanisms. Impedance controllers consist in considering diverse kinds of environments in which the rehabilitation robot operates. These kinds of environments disturbances are generally found in the forces and torques that the patients generate for diverse kinds of mechanisms. The first step to design these kinds of mechanisms is to design a “mechanical circuit” (similar to an electrical circuit) with the equivalent circuit elements like inertia, mass, stiffness coefficient, etc. Then, as seen later, the equivalent Thevenin or Norton equivalent circuits are designed taking into consideration if the circuit is inertial, capacitive, or resistive. In this chapter, two numerical examples are shown, implementing the respective impedance controller. The first numerical example consists of the design of an impedance controller for a five bar linkage, and the second numerical example consists in designing an appropriated controller for a gait robot. Exercise to be solved appears at the end of the chapter.

In this chapter it is explained the construction of robust control Lyapunov functions. This chapter begins with the definition of robust stability and robust performance for linear and nonlinear dynamic systems in order to obtain the robust requirements to measure this index in order to ensure the best performance of the closed loop robust system. Then the construction of robust control for linear and nonlinear systems is explained in order to define the theoretical conditions for the robust control system design. One of the main contributions of this book chapter is that the robust stability conditions and robust performance are extended to the discrete time case, something that is very limited reported in the literature and that this book chapter provides a novel contribution to the field. Besides, the derivation of control laws for the continuous and discrete time cases is presented, in order to provide the reader the mathematical background to design controllers for this kind of systems. Another important contribution of this book chapter is that the derivation of optimal robust control laws is presented, in specific the design of optimal robust linear quadratic regulators for the continuous time case. Finally, illustrative examples are presented to elucidate the experimental results of this research study in order to obtain the optimal closed loop system performance.

In this chapter two robust control strategies for nonlinear dynamic systems are presented. This chapter begins with a brief review of the most common kind of uncertainties found nowadays by considering their mathematical and topological foundations. The kinds of uncertainties explained in this chapter are basically parametric, nonparametric, matched and mismatched uncertainties describing the mathematical properties, in specific, the topological properties taking into consideration that recently there are a plenty of mathematical representations due to the vast amount of uncertainties found in nonlinear and other kinds of complex dynamical systems. One important result explained in this chapter is that the well-known robust control Lyapunov functions (RCLFs) are explained by taking into consideration that the closed loop robust stability and the robust control law are found by an appropriate construction of the RCLF. Besides in this chapter is explained the theoretical background of the design of robust controllers by considering uncertainties in nonlinear dynamic systems, and by implementing the respective Lyapunov functional a suitable robust controller can be obtained in order to ensure robust stability of a closed loop system. Besides, the design of optimal robust controllers is explained by taking into consideration that a performance functional along with the respective Hamiltonian is shown in order to design the robust optimal control law by taking into consideration the uncertainties in the system. One of the main contributions of this chapter is that a robust controller is designed for systems in the Euler-Lagrange formulation by designing the Lagrangian in order to obtain the required formulation. The mass and inertia uncertainties are considered in this study with the respective topological definition, and by using an appropriate Lyapunov functional, the robust control law is found. This control law can be implemented in a variety of mechanical and robotic systems for trajectory tracking purposes. Finally, an optimal robust controller for mechanical systems is presented in this chapter by taking into consideration a Lyapunov functional and a performance functional for the robust optimal control law design. This robust optimal controller is implemented in a nonlinear forced mass-spring system, corroborating a high performance.

In this chapter, the dynamics equations of motion of ALICE (Assistive Lower lImb Controlled Exoskeleton) exoskeleton robot are found. First the ALICE project is presented. Then, the D’Alembert formulation in order to find the dynamic equations of motion is applied. Finally, these equations are validated through the joint’s torque obtained with a dynamic simulation using an ALICE’s MATLAB/Simulink equivalent model, and the dataset used for testing was obtained from healthy subjects and was captured with the commercial medical equipment CODA motion system. MATLAB as programming tool and testing platform is used.

In this chapter, the dynamics analysis of ALICE (Assistive Lower lImb Controlled Exoskeleton) Rehabilitation Robot is presented. First the ALICE project is presented. Then, the recursive Newton-Euler approach in order to find the dynamic equations of motion is applied. Finally, the equations are validated comparing the joint’s torque obtained with the dynamic simulation using an ALICE’s MATLAB equivalent model, the dataset using for testing correspond to real gait data obtained from healthy subjects and were captured with the commercial medical equipment CODA motion system. MATLAB as programming tool and testing platform is used.

This chapter presents the fundamentals of exoskeleton robots and their applications. A complete review of the upper and lower limb exoskeletons robots for rehabilitation, for both commercial devices and those in the advanced stage of development, is discussed. The most important characteristics of each exoskeleton and the level of development are presented according to the technology maturity level (TRL) metric proposed by NASA. In addition, it has a review of the applications of each of them according to the types of pathologies. Finally, future trends of rehabilitation robotics are discussed.

This chapter presents the fundamentals of exoskeleton robots and their applications. A complete review of the upper and lower limb exoskeletons robots for rehabilitation, for both commercial devices and those in the advanced stage of development, is discussed. The most important characteristics of each exoskeleton and the level of development are presented according to the technology maturity level (TRL) metric proposed by NASA. In addition, it has a review of the applications of each of them according to the types of pathologies. Finally, future trends of rehabilitation robotics are discussed.

In this paper an exhaustive singularity analysis of a 3BRR planar parallel robot is performed. The Jacobian matrix using the Screw theory is obtained and an effective method for singular configurations analysis based on a condition index of the Jacobian matrix is presented. Finally, a new similarity law that allows the workspace optimization free of singular configurations and the working mode selection is presented. Furthermore, MATLAB as a testing tool and programming language is used.

This paper discusses the development of a software capable of extracting geometrical properties of sugar crystals, using artificial vision tools available in MatLab, which provides a more accessible and easier option to develop the quality control processes in sugar mills.

In this paper a complete forward kinematics analysis of a general Stewart-Gough platform is performed. A new methodology to deal with the forward kinematics problem based on a multibody formulation is presented. An iterative algorithm is proposed and the forward kinematics using a numerical method is solved. Finally, a design of a simulator using MATLAB as programming tool is presented.

In this paper a morphological analysis of the size and shape of sugar crystal for quality control inspection is performed. An algorithm for morphological characterization using digital image processing was developed and then a statistic analysis was performed. The samples were obtained from a sugar refinery and parameters of interest, such as equivalent diameter, elongation, mean aperture (MA), standard deviation and coefficient of variance (CV) were calculated. Finally, an automated tool for morphological analysis using MATLAB was developed and the results were validate by using a manual method.

In this paper a complete kinematics analysis of a 6UPS Stewart-Gough platform is performed. A new methodology to deal with the forward kinematics problem based on a multibody formulation and a numerical method is presented, resulting in a highly efficient formulation approach. The idea of a multibody formulation is basically to built for each joint that links the body of the robot, a set of equations that define the constraints on their movement so that the joint variables are included in these equations. Once the constraint function is defined, we may use a numerical method to find the kinematic solution. In order to avoid the problem reported with the orientation (Euler's Angles) of the moving platform, a generalized coordinates vector using quaternions is applied. Then, the Jacobian analysis using reciprocal screw systems is described and the workspace is determined. Finally, a design of a simulator using MATLAB as programming tool is presented.

In this paper a comprehensive review of exoskeletons for upper and lower limb rehabilitation is presented. Commercial robots with an emphasis on the pathologies they deal with are described and classified using the NASA Technology Readiness Level (TRL) metric. In addition, their movements and certifications are reviewed. Finally, future trends regarding the use of exoskeletons in the rehabilitation process are discussed.

This article describes the development of a monitoring system for the automation and temperature control of the electronics laboratory in the engineering building of the Universidad Panamericana Aguascalientes. The system is designed to turn on or off a fan using a global controller based on the data obtained by a temperature sensor, this data is sent through internet to a platform in the Google Firebase cloud and at the same time they are visualized in another monitoring platform through JSON (JavaScript Object Notation), allowing to graph in real time the temperature data and the moment of the fan turning on or off. The global controller is able to show the image of the building being monitored in real time by changing the color of the room depending on the temperature: in case it is higher than 28 degrees, the fan will turn on and the room will change color to red, if it is less than 18 degrees, it will change to blue and if it is between those two temperatures, it will change to yellow. This article proposes a novel concept of communication for the internet of things, since it allows sending information from a global controller without the possibility of storing data to another one that allows saving them through JSON.

ORTE is a robotic platform developed to restore the mobility to the shoulder complex and elbow joint of upper limb impaired patients. ORTE pretends to be an effective and objective tool for the rehabilitation staff. This work presents the kinematic analysis and dynamic modeling of ORTE, a 6 Degrees-of-Freedom upper limb rehabilitation exoskeleton. The dynamic model of the mechanism is used to find the required torques to perform a set of different trajectories of daily living activities as eating or taking an object. This allows the optimal selection of actuators for this rehabilitation system.

Musculoskeletal model is a useful tool to evaluate the complex biomechanical problems, simulate and evaluate the injuries, estimate the muscle-tendon forces, and joint the torques during motion and predict the effects of orthopedic surgeries. Moreover, the musculoskeletal model is a rich source of information to develop robotics exoskeleton aiming to restore the normal gait after some injuries. This paper presents a full musculoskeletal model in an open-source framework to perform the biomechanical analysis of the human lower limb in order to simulate both healthy and pathological gait; 14 bones, 88 Hill-type muscle-tendon segments, ten ligament segments for each knee, and six joints for each lower limb were modeled. The model allows us to simulate different injuries of the lower limb, such as ictus, stroke, and so on, by sending different signal profiles to muscle-tendon segments, emulating the functional electrical stimulation (FES). At the same time, forces and torques could be computed for muscles and joints. Hence, the proposed model can be suitable not only to perform a complete biomechanical analysis for medical purposes but also for the exoskeleton controller design and actuators dimensioning. In order to validate the model, it was exported to Simulink environment to simulate the joints range of motion, muscle moment arm, and joint torque, and then, these data were compared with the medical literature. All simulations results show that the data from the model are according to the previously published works. Furthermore, the model was validated using the real data obtained by our own gait capture system and by CODA motion software for normal and pathological gait. Finally, the goodness-of-fit of our model was assessed using the root mean square error (RMSE) and the normalized mean square error (NMSE); the values of these indices suggest that the model estimated the kinematics and kinetics parameters of healthy and pathological gait successfully.

Agriculture represents the main source of food in the world, but it also represents challenges such as population growth, urbanization and aging, global economic growth, investment, trade, and food prices and competition for natural resources. The development of technology can help us cope with these challenges. The internet of things (IoT) technology represents the future of computing and communications. These can be useful to improve traditional agriculture methods around the world. By implementing these modern technologies is possible to reduce costs and maintenance and, to increase the performance of our agriculture processes and goods. Particularly, one of this relatively new technology is the LoRa communication protocol that uses long wavelengths for the communication link to obtain long ranges. This is extremely useful in agriculture where the communicating areas are extensive crop fields and greenhouses. This paper proposes and presents the development of a mobile LoRaWANgateway device that can be applied to increase greenhouses' productivity and accuracy. The presented development includes the use of a Heltec's Mini LoRa Gateway controlled by a Raspberry Pi 3 B+. It is powered by an external Li-On battery and uses a defined number of LoRa nodes with sensors. Sensors will measure humidity and temperature and send the data, which are gathered by the mobile LoRaWAN gateway. These data are processed using third-party free online services. This document illustrates and explains the development and application of data collectors for agriculture and their advantages.

For hen breeders, hatching eggs in large quantities is a production problem, when they are incubated by hens. This paper describes the development of an intelligent system for a hen egg incubator. This incubation system, based on Arduino, LabVIEW, Google Firebase and MIT App Inventor can control temperature, humidity and egg rotation automatically. In addition, the system can help farmers to monitor the intelligent incubator remotely. Successful hatched hen eggs are typically around 87.55%, 0.41 % hatched defectively, 1.84% hatched but die at birth, and 10.20 % not hatched, so an intelligent temperature and humidity control system can improve the successful hatching rate. The objective of this system is not to offer it for sale, but to make it available for researchers and farmers so that they can replicate it and carry out experiments. In order to do this, the system was kept as simple as possible.

The popularization of solar water heaters in many houses makes it necessary to create an electronic tool for monitoring water temperature as a function of time. It should be easy to use and cost effective so most of the users can get it. This article presents the analysis of the problem, the design proposal, prototyping and test results of the development of a wireless temperature monitoring system in a domestic water heater tank. This device allows knowing the temperature of the heater in real time by using IoT (Internet of Things) technology. It uses the device's internal memory where machine learning algorithms customize settings that can trigger intelligent alarms such as water leak detection, under or over temperature, and efficiency loss. The device delivers the data to the user or to other devices (for further automation) by local Wi-Fi. The scalable architecture of IoT allows adding extra measurements for physical phenomena that affect the heater's performance, such as water flow, sun radiation and outdoor relative humidity. Those measurements can be easily integrated in a more complex system version for commercial or industrial customers.

The Internet of Things (IoT) has shown the ability to exploit the potential of data, transforming objects of everyday life essentially into computers, by equipping them with sensors capable of measuring physical variables of the environment that surrounds them, and equipped with standards and communication protocols, acquire the ability to build an ecosystem of identifiable objects in a unique way, which generate data automatically, and with the possibility of responding to stimulus from the same environment, in a few words generate automatic responses to well defined situations. These characteristics promise great benefits to the industrial sector making reality the fourth industrial revolution better known as Industry 4.0, whose fundamental pillar is the Industrial Internet of Things (IIoT). The objective of this work is to apply the Industry 4.0 technologies for the benefit of industrial maintenance by developing a measuring instrument using open source tools with the purpose to be a support for decision-making related to machinery maintenance. Specifically, the instrument to be developed fulfills the functions of an ammeter, which is an instrument of wide industrial use. The ammeter presented has integrated ZigBee technology that allows creating Wireless Sensor Network for remotely measure the electrical current consumption of the machinery to be monitored. Because induction motors are one of the most important assets within the industry, the proposed development is intended to be a support tool for the Condition-based maintenance approach to identify on time when the motors in a manufacturing process works abnormally and thus help to prevent critical failures.

This papers deal with the direct kinematics analysis of exoskeleton robots for rehabilitation. An alternative methodology to address the direct kinematic problem based on the Screws theory is presented. Then, a Jacobian analysis is performed, and an equivalent model in Simscape Multibody (Simulink) in order to perform further dynamics and control analysis is found, MATLAB as a testing tool and programming language is used.

This paper presents how the COVID-19 pandemic has changed the course of the mobile robotics market, showing the status of mobile robots in three stages: before, during and after the COVID-19 pandemic. By analyzing these stages, it is possible to estimate what awaits this market in the future. From the many applications of mobile robots found during the COVID-19 pandemic, as will be shown later, it is clear that mobile robots will be an important part of the future influencing the accelerated growth of their market and development.

This article presents an investigation about the different applications of mobile robots in the fight against the Covid-19 pandemic. It shows the different contributions of companies around the world that seek to adapt to the new needs in order to be able to mitigate the progress of the Covid-19 using mobile robots as a tool, focusing primarily in the area of health and service.

One of the microorganisms used in the industry to generate high value products is the microalga. Due to its nonlinear dynamics and variation in time, bioprocesses that involve the use of microalgae pose challenges in modeling, controlling, and increasing their production. Normally, at the laboratory level, closed cultures of microalgae are carried out in photobioreactors. To produce biomass, the culture conditions can be controlled using a photobioreactor. This paper describes the design of an intelligent Proportional-Integral controller applied in a continuous culture of Chlorella vulgaris microalga, where the controlled variable is the dilution rate D(t). This controller is characterized by formulating the dynamics of the system with an ultra-local model. In this ultra-local model, both the uncertainties of the system dynamics and the disturbances are handled in one unified way. The performance of the intelligent Proportional-Integral controller was tested at simulation level using Matlab Environment™. In this research, the accomplishment of the controller was contemplated against disturbances, under nominal conditions and front variation of parameters. The simulations showed that the intelligent Proportional-Integral controller ensures excellent reference tracking capability. Finally, it is important to highlight the robustness of the strategy.

In this paper a complete kinematics analysis of the RV-3SB Mitsubishi robot is perform. An alternative methodology to address the kinematic problem based on the Screws theory is presented. Then, the design of a simulator to validate the methodology proposed, by comparing the values of the simulator with the real values of the robot is presented, MATLAB as a testing tool and programming language is used.

In this paper the actuation system selection for ALICE exoskeleton robot based on the torque obtained from gait analysis of healthy subject and subjects with multiple sclerosis is presented. The exoskeleton robot was designed in Autodesk Inventor considering the weight-body of an average person, then the model is exported to Simscape Multibody and the signals are set from data obtained with commercial medical equipment, CODA™ Motion Analysis System, at the Physiotherapy Clinic of the ONCE Foundation. Finally, considering the nominal and peak the torque obtained, it is proposed the electrical motors, reducers and control board from manufacturer's catalogues.

This paper contains the procedure for the implementation of an application for exam test grading in a fully automatic way, putting into practice the resources that artificial vision makes available. This application allows you to grade an exam that has been designed in a pre-established format and that has subsequently been solved by the evaluated person. The qualification process is possible through the comparison between the test already solved with the correct answers and the test that the evaluated person has completed. Python and OpenCV were used for the development of the application, the latter was necessary in the image analysis and processing stage, where the objective of the application was based on the recognition of contours and marks detected in the sample photographs. This project proposes a viable and practical option in the optimization of the exam test qualification process, saving time, and making teacher performance more efficient.

Disability is defined as a condition of the human body that limits the execution of a task or activity. According to the World Health Organization (WHO), 15% of the world's population suffers from it, recent studies indicate that the growing prevalence are a significant problem and that, consequently, the demand for rehabilitation services is rising considerably. For this reason, different authors propose the use of exoskeletons in rehabilitation therapies as an alternative solution. Thanks to the progress of this kind of technology, it is possible to create robotic systems that help people with disabilities to recover, totally or partially, the original movement of their affected limbs. This Innovative Review Article presents an exhaustive review of the main features of upper-limb exoskeletons such as Degrees of Freedom (DoF), mechanism type, rehabilitation mode, movements allowed, applications and Technology Readiness Level (TRL). Firstly, the study provides a brief description of the biomechanics of the upper limbs of the human body. Next, the material, the rehabilitation modes and the Technology Readiness Level (TRL) of each of these devices are analyzed. As a result, it was observed that aluminum and PLA are the most used materials for exoskeletons' manufacturing. In addition, it was noticed that most of these exoskeletons perform passive rehabilitation. Besides, it was identified that the most common applications are the assistance and rehabilitation in the affected limb of patients who have suffered a stroke. Finally, using TLR scale, it was determined that these mechatronic systems are between TRL5 and TRL8.

In this paper, the Jacobian analysis of the ALICE exoskeleton rehabilitation Robot is presented. The Jacobian matrix is described and the workspace is determined. Then, the Yoshikawa and Condition Index are studied to analyze the performance of the manipulator. MAT LAB as programming tool and testing platform is used.

Prosthesis designers must deal with the constant cost problems for manufacturing a prosthesis for one person. A prosthesis is subjected to the body weight of people, especially when the person leans on the prosthesis. All the weight of the person falls on the limb that is attached to the prosthesis. Therefore, it is necessary to perform the static analysis of each piece to confirm that none of these will have break points and that mechanical displacements do not negatively influence the prosthesis. The aim of this project is the proposal of a method for the design and manufacture of prostheses based on six steps, among which digital design and additive manufacturing stand out. For this, a five-step method was used, starting with digital parameterization, generative design, finite element analysis, fabrication, and recycling of the prosthesis. Digital parameterization is the use of the scanner to create a mesh with which to design the coupling of the prosthesis. With the generative design, the measurements of the prosthesis were optimized, which were based on the scan of a stump and can support the weight of 225 lb. The h method to analyze the loads based on finite elements adapted the mesh to generate the best solution and guarantee the functioning of the prosthesis. The shapes developed by generative design were manufactured with additive manufacturing using ABS with a 100% fill. By using this method, it is guaranteed that the product can be recycled and use the raw material to generate new prostheses.

This paper overviews the modeling, implementation, and mechanical characterization of an Automated Guided Vehicle (AGV) devoted to transport materials and tools in smart factories. The design is based on a differential-drive mobile robot configuration for which the mathematical model was obtained. Such model allows the simulation of the AGV’s motion and can be used to improve productivity, increase automation, and reduce transportation costs in industrial facilities. The prototype’s implementation was conducted with highly resistant materials and automated manufacturing processes. A finite element analysis (FEA) shows that the prototype is capable of transporting 700 kg loads without suffering any structural damage and that critical cases involving collisions might cause only minimal harm. An IoT approach has been considered for the AGV’s electronic architecture.

In this paper, a complete kinematics analysis of the ALICE (Assistive Lower lImb Controlled Exoskeleton) Re- habilitation Robot is performed. First the ALICE exoskeleton rehabilitation robot is presented, including its mechanical design. Then, the main features of commercial lower limb exoskeleton robots is discussed. Next, the forward kinematics using the Screw theory is presented, finally the inverse kinematics solution using a geometrical approach is presented. MATLAB® as programming tool and testing platform is used.

In this paper is shown how to implement the GNU Octave Control toolbox for autoregressive models for the identification of nonlinear dynamics system with the GNU Octave control toolbox. This paper is focused more on the linear autoregressive model which is based in the ARX structure (autoregressive external input model) for nonlinear dynamic system identification. This research study begins with the theoretical framework in which it is included the fundamentals of nonlinear dynamic system identification along with the definition of the z transform and the definition of the ARX structure for nonlinear dynamic system identification. The third section consists in the definition of the GNU Octave control toolbox that are implemented for auto-regressive model structure for nonlinear dynamic system identification. Then three numerical experiments are performed which consists in the following; first the identification by auto-regressive external model structure of a random signal and then the identification of a quadratic function. This numerical experiment section finalizes with the identification of the attitude nonlinear dynamics of a quadrotor unmanned aerial vehicle UAV, taking into account that the nonlinear dynamics of this UAV is complex because of it is highly coupled. With these numerical examples, it is evinced how to implement the GNU Octave Control toolbox function in order to perform an accurate dynamic model identification that provides a compact model in order to be used for adaptive control or only to be implemented to identify a data series with a reliable mathematical model. In this paper is show how to efficiently implement the GNU Octave Control Toolbox function describing the advantages in simplicity and efficiency for identification purposes. This paper concludes with the appropriate discussion and conclusion sections.

This paper presents some tools available for educational robotics, including the set of simple assembly and connection robots available on the market, suitable for recommended ages and designed for learning in areas of technology and science. On the other hand, the educational robotics in the salvadoran educational system is discussed. Moreover, the best way to include this type of technology in the student curriculum of each academic level, in order to obtain the best benefits and results in the salvadoran educational community is presented.

The automation of manufacturing processes is widely used as a strategy to increase productivity in repetitive tasks and to improve safety in those with a high risk of accidents and non-ergonomic procedures. The design of this automated process presents the way to increase productivity and reduce the risk associated with the grinding task in an ax manufacturing company. As an instrument for measuring improvement, we have the comparison of: ergonomic evaluation, accident rate, new grinding development method and its productive capacity.

In the present work, the design of an end effector using soft robotics is exposed. With the use of flexible and soft materials, much more complex studies can be carried out due to the freedom of movement that a robot can have, whether in the marine, industrial or care field. For the development of this work, end effectors were manufactured and test experimentally. We concluded that using one of four fingers gave us a better grip when picking up objects. Unlike the other molds used, the one used to do the job was a modular mold as it gave us the advantage and ease of being able to modify its dimensions and air chamber positions. The final dimensions of the end effector were 14 cm long, 2.60 cm wide, and 1.50 cm high. The pieces to create the air chambers were 1.30 cm long, 0.3 cm wide, and 0.6 cm high. A structure was manufactured to be able to mount the end effector to a Viper 650 robot. The most relevant results that we could notice was the time it takes for it to be able to deform, which is between 5 and 7 seconds using a pressure between 1 and 2 psi. An important factor to carry out work using air pressure is to consider a certain pressure to prevent the prototype from being damaged since, when using elastic materials, its elasticity limit must be considered to avoid breaking the design.

Currently, the electricity distribution companies are responsible for taking readings to determine the energy consumption of the final consumer, this activity is performed by field personnel contractors, which is exposed to risks to their physical integrity, either by climate or social situation. Due to the above, the digitization of electric energy consumption readings of each client in the metropolitan area of San Salvador is sought. This innovation is supported by the internet with which smart energy meters are integrated through wireless networks to the technical center where the reading data will be received and thus be able to measure electricity consumption, voltage drops and time of unrecorded energy. The data collected estimates that the implementation of this system will bring benefits such as the reduction of claims and a better quality of energy service to the end user. The implementation of the Internet of Things will facilitate data extraction, reduce physical risk to field personnel, and access information quickly and securely.

This paper presents a mobile robot design that can be used to help the sanitation in wastewater centers, allowing us to inspect the unreachable and inaccessible drainage ducts, at the same time, can be used to visualize the pipeline interiors to find what causes the extrusions of the drainage. These devices can be adapted to certain sizes according to regulations and can be controller from a portable control station on the surface, either with remote access or via cable. The design should be adapted to the sewer structure to move on a certain surface and be handled easily, taking into account that the accessories and electrical appliances do not hinder the observation of the interiors in order to capture in detail what comes from a deeper and farther location.

Robotics are used daily in several tasks previously performed by humans. The evolution of the mechatronic sciences guides the industrial process to be progressively automated. Countries that lack technological development, such as Honduras, tend to linger in these areas. The objective of this paper is to develop a teleoperated robot that can be used in logistic applications. It also seeks to demonstrate that there is always an option to create solutions instead of buying imported technology at an excessive price. For this robot’s construction, possible deformation and energy consumption were considered the structure’s mass. A quantitative approach with an experimental design that is then analyzed with a “V” model was held. As a result, it was established that this type of robot could be built on a budget of 1,551.00. dollars The appropriate choice of structural materials will allow a minimum deformation with a final mass of 26.2 Kg. The teleoperation of the robot through Wi-Fi and a web server provides communication within an adjustable range, good response times, and control of an unlimited number of variables. In conclusion, industrial processes supported by robotics can achieve greater precision and profitability, being up to six times more efficient than humans.

In this paper, an adaptive robust controller for ACICE exoskeleton robot is proposed. The steps followed and the results obtained in the design of an exoskeleton leg controller are presented. Then, the performance of the designed controller is compared with the performance of a PD controller. MATLAB as programming tool and testing platform is used.

In this paper we will be described some of the technologies use in chatbots to process the natural language and the creation of a basic Chatbot prototype based on Google technologies, also the economic impact of the implementation for the Business Process Outsourcing companies in El Salvador. The prototype was created with Dialogflow which is a natural language understanding platform that makes it easy to design and integrate a conversational user interface in different formats that can parse multiple types of input, including text or audio input. It can also respond in various ways, either through text or synthetic voice, and is also part of the conversational AI offering within GCP. The main objective of BPO companies is to reduce the costs of client companies and help them grow economically, through the optimization of time and resources of their business processes. Immersed in these business processes are customer service processes. Nowadays with existing technological advances, technology is part of people’s daily lives and is used to do work more efficiently and effectively. Currently there are machines that do activities that were previously performed by humans, with this it has been possible to improve productivity and existing processes within companies.

This paper presents how the COVID-19 pandemic has changed the course of the mobile robotics market, showing the status of mobile robots in three stages: before, during and after the COVID-19 pandemic. By analyzing these stages, it is possible to estimate what awaits this market in the future. From the many applications of mobile robots found during the COVID-19 pandemic, as will be shown later, it is clear that mobile robots will be an important part of the future influencing the accelerated growth of their market and development.

Water pollution is an issue of high importance due to its direct impact on the lives of humans, animals and ecosystems. Water quality monitoring systems are implemented throughout the world to help prevent this problem, consisting mainly of stations with a system of sensors for the measurement of water quality parameters in real time. However, to cover the entire area of a large body of water, it is necessary to implement multiple stations, which is expensive and inefficient. This paper proposes the development of an aquatic surface robot capable of performing long duration missions autonomously and incorporating a sensor system to measure water quality parameters, thus facilitating the collection of data and making it easier to reach locations in a more practical way.

The research was conducted on Augmented Reality (AR), its concept, its precedents, the fields of application in which it is presented, and the advantages it has at the time this technology is implemented. It also analyzes the implementation of AR in the world in various sectors such as education, medicine, and industry. The applications of augmented reality in Honduras were identified. And the factors why Honduras has not implemented AR are analyzed. AR is a human-computer interface design strategy aimed at enhancing a user's visual perception by superimposing computer graphics on the user's view. AR has a series of devices, and software, among other elements that operate as development tools making the experience with this reality more attractive. In the fields of application four areas stand out: Education, Textile, Marketing, and Manufacturing. By evaluating the sectors and fields where AR is applied worldwide, a comparison and analysis are made to define which would be the best option to develop this technology in the best way in Honduras.

In this paper it is shown basically the most important active solar tracking systems. It is reviewed the different types of solar tracking mechanisms based on robotics platforms which are classified basically in its degrees of freedom. In this paper are evinced first the state of the art regarding the design of novel trajectory tracking system explaining first how they are implemented and the frequency in which these mechanisms are implemented in different countries of the world while showing not only their configurations. Apart, it is explained the kinds of actuator that are commonly implemented in these mechanisms, for example direct current DC motors, permanent magnet motors, etc. Another issues that is mentioned in this study is the trajectory generation based on the solar path and how this variable changes according to the season of the year. Then the main results of this study are found in which it is explained how the dynamics of these mechanisms are obtained focused on four categories of this kind of mechanisms, which are horizontal 1-axis tracker, vertical 1-axis tracker, tip-tilt two axis tracker and azimuth altitude two axis tracker. Finally, as a contribution of this paper, an experimental simulation is performed for trajectory tracking purposes of this kind of mechanism by a proportional derivative controller in order to verify the closed loop system performance by tuning the gains with a gradient descent algorithm.

The morphology of industrial robots is a topic that many researchers are analyzing. Robots cinematic of 6 and 7 DOF can be compared to determine its advantage and applicability. The purpose of this project is to compare the effect of adding a one degree of freedom end effector to a six degree of freedom robot, in order to understand the kinematic advantages that this represents. The method proposed in this work consists of adding a degree of freedom to the same robot to statistically compare if there is a significant difference between the two systems. The data for the statistical analysis were extracted by means of solidworks motion simulations. By performing the statistical tests of normality, sign test and t-student test as appropriate, it was shown that there are no significant differences in the systems. It is concluded that the kinematic characteristics are not a relevant parameter for the selection between the two systems based on the statistical tests.

In this paper it is shown two control strategies which are commonly found for active solar tracking systems. The type of solar tracking mechanisms that will be analyzed in this research are basically one, a 2-axis solar tracking system. For this strategy the dynamics of the actuator are considered in order that in this case is a DC motor in order that the dynamics of the real physical systems will be obtained as real as possible in order to facilitate the controller design and the implementation in a real setup. Then after obtaining the dynamics of the solar tracking system it is important to mention that two control strategies will be implemented for decentralized control. For the 2-axis control design it will be tested by decentralized control; in order to provide a novel contribution to the field. Among these strategies, two strategies are tested and compared. A proportional-integral-derivative PID controller and a second order sliding mode controller in order to make the respective comparative analysis and provide the conclusions of this research study.

Obtaining contact models that can optimize wheel design depends on certain variables such as impact velocity, material properties of the colliding bodies and geometric characteristics of the contact surfaces. These models can provide much in terms of stability for mobile robots. The aim of this research is to demonstrate that the wheel shape has significant impacts on the contact force calculating the spring stiffnes for linear hooke model. The method proposed is the obtention of data from simulations and a statistical analysis based on non parametric test to determine the contact force and the level penetration due to the geometry and material properties. As main result the spring stiffnes constant was approximate for different wheels geometry.

Nowadays, many sectors have been faced with the need to achieve technological and automated processes, to keep up with the new trends and remain competitive. This study describes the beginnings of artificial intelligence (AI), its concept, branches, and applications. A general context is given about the different agricultural sectors in which the focus is on, in this case, the coffee, banana, oil palm, and cocoa sectors. The research was done on the diverse applications of AI in different countries and how it helped improve the processes of these sectors. To achieve this, an average of fifteen articles were taken into consideration for each sector investigated, to have a wide variety of information that will be able to validate the veracity of implementations. It was also possible to determine which countries have applied most of these technologies in their processes. As a result, Malaysia, a country in Southeast Asia, is the one that predominates the AI studies applied to agricultural sectors. In addition, the reasons why AI has not been applied to a large extent in the agricultural sectors in Honduras and the main reasons why this process has advanced relatively gradually are also investigated.

A contagious disease can be transmitted very quickly from one person to another through direct contact or indirect contact. Today there are many doctors who become infected while monitoring their patients, this causes them to cease their work and even death. Therefore, this project has the objective of designing a robotic concept that allows remote monitoring of patients with contagious diseases, reducing direct contact between the doctor and the patient. For the design of this robot, the V methodology is proposed, which breakdown a complex prototype into a series of systems and subsystems. It is expected to obtain a robot with free obstacle locomotion applying the similarity law, thermal monitoring based on artificial vision, and facial recognition using Haar cascade. The concept was tested in solidworks motion. Finally, the proposed concept is simulated in ABS for the Housing with the capacity to withstand temperatures of up to 80 degrees Celsius and an aluminium structure with a security factor of 8.17.

In this paper is shown the results of a research study regarding the identification of natural frequencies in bearing mechanical vibrations by wavelet decomposition. This research work is intended to show clearly and didactically the use of the free software GNU Octave in order to provide with not only a theoretically background of the problem to be solved. The intention is to verify the effectiveness on how to program code in GNU Octave to implement wavelets efficiently in order to find the natural frequencies and damping coefficient of the mechanical vibrations of a bearing. In this research study are used some datasets about the vibration of a bearing in order to find the natural frequencies and damping of the mechanical vibrations yielded by it. The procedure is to obtain the wavelet transform of the data and to obtain the required bandwidth in order to extract the damping and natural frequencies of each dataset. It is important to mention that the wavelet decomposition is useful for this purposes by implementing a minimal post-processing of the results. It is worthy to mention that besides the wavelet implementation is performed a Fourier and Bode analysis in order to verify and validate the results presented in this research study. Some numerical experiments are performed with the respective conclusions and discussions.

The end effectors are necessary because without them, the robot arm would not be able to perform its function and each one is designed to fulfill specific tasks. The objective of this research is to experiment with different combinations of materials in order to analyze their behavior, starting from the same model and under the same conditions. A hierarchical methodology was used in which the research was divided into blocks in order to analyze each part of the end effector individually before making the final tests. We started by testing the material combinations in order to see which combination gave us the most pronounced bending angle. Also, with the base part, several versions were made in order to have a final product that has congruence in all its parts and a modularity capable of changing the different types of grips and number of fingers. This was achieved by using a more flexible material in the air chamber part so that they expand more easily, while the lower part is made of a material that generates resistance and causes it to bend instead of stretching in its entirety. Resulting in a functional end effector whose parts can be replaced easily and without the need to print or mold large parts, as each finger is independent of the others.

The fourth revolution (i4.0) has begun, and with its arrival many disruptive technologies that will change our environment, it is estimated that more than seven million jobs will be affected in the next five years. i4.0 means a new range of technologies that are merging the physical, digital and biological worlds, and will alter the way we interact, work and live. Throughout the world many disciplines, economies and industries are preparing for the impact that this transition will bring. In this article, a tour of the technologies that accompany industry 4.0 is made, the implications are analyzed and some recommendations are discussed that can help us prepare for this new transition, finally some forecasts are proposed.

This project aims to automate queries through a web platform within the university, allowing students to interact with it through writing or voice using natural language thanks to artificial intelligence, and be able to ask questions about various topics such as locating places or objects within the university, as well as more specific questions about their career, project topics, or graduation practice, among others. In this way the experience within the university campus will be more enjoyable for students, faculty or staff that can be included as a user of the platform. Allowing the efficiency and effectiveness to ask questions and receive correct answers at the time. For the training, 50 articles indexed in scopus were used, which allowed for effective communication between the interpreter and the user, but with some limitations. The WIT.AI interpreter was able to demonstrate the relevance of some research topics that students can follow as a guide. The development of a web site that allows automation of manual tasks that were previously performed by university staff, such as teachers or advisors, with a platform that serves as a virtual assistant between the system and the end user, with a complex information management, having control at all times of access to this information, was achieved. By designing a voice-operated system strategically located throughout the university's facilities, students are guaranteed to be able to ask questions and receive answers in real time. This facilitates interaction between students and the application, improving the response time. Future work is needed to augment and automate more training items.

Considering that several kinds of electrical actuators are found in real physical systems, in this paper is proposed a fault identification strategy for electrical actuators with autoregressive models. As it is known, autoregressive models are those kind which their parameters are tuned in order to adjust the parameters of a transfer function in order to model the nonlinear dynamics of a physical system. So in this paper is proposed an auto- regressive model in order to identify the failures in two kinds of electrical actuators; that in this case is a permanent magnet synchronous motor. The kinds of failures which are treated in this research study are basically electrical faults, which are related to the stator failures depending in the characteristics of the motor. The auto-regressive model is used in a configuration in which this failures are detected, and then by the stability characteristics of the dynamic system which represents the motor, according to the difference of the estimated and measured outputs a threshold is selected in order to identify a failure and to determine which kind of failure occurs in the motor. Some simulation experiments are shown in this paper in order to validate the theoretical results obtained, taking into consideration that many mechanical systems such as robots use this kind of actuators.

The Internet of Things (IoT) is a growing network that encompasses a horde of Internet-connected devices, sensors, actuators and smartphones. This paper presents a solution for the application of robotic grippers in the industry to provide more delicate handling of susceptible or delicate products when handling them. This study is based on the design of an end effector to monitor the temperature and humidity data of coffee beans using IoT. The prototype design is worked out in SolidWorks CAD software while the mechanical system is divided into design and fabrication. The final effector, which was equipped with a 3d printed strain gauge that is integrated to the gripper as flex sensor and contact sensors, had great accuracy and reliability in sensing changes in flexion and contact while in use. This demonstrates the usefulness and efficiency of network connectivity and the use of the Internet of things in applications for soft robotics. It is recommended to redesign the flexion sensor and increase its size to have a wider range of resisting values, thereby avoiding imprecise data and spikes in values at low flexion angles, thus enhancing the sensor’s reading capability.

The present article provides a comprehensive analysis of the kinematics of the Delta parallel robot. A new methodology is introduced to address the direct kinematics problem based on a multibody formulation. A new algorithm to find the solution to direct kinematics using a numerical method is proposed. Then, the workspace is determined. Moreover, a simulator and a prototype are presented, MATLAB as a tool for simulation and programming is used.

Convolutional neural networks (CNNs) promise to transform modern agriculture by addressing some of the most pressing challenges. This project focuses on developing an effective CNN to automate the selection of rambutans according to maturity and minimize losses caused by premature harvesting and inclusion of low-quality fruit. As well as identifying the main limitations and challenges that arise when developing a CNN focused on this sorting process. For this purpose, a database of images captured in Honduran rambutan production farms was obtained. The database was composed of 1,540 source images that were transformed to 10,144 after Aumentación. Six object detection Modelos focused on fruit classification were then created. The best result achieved a mAP of 64.1 %, a precision of 77.2 % and a recall of 58.6 %. Finally, the main limitations for the development of such a network were identified. These were divided into the categories of dataset availability and management, data expansion and resource limitations and specific detection challenges.

This paper aims to develop a numerical method to solve the Schrodinger equation in a time-dependent dimension for mobility problem in a N-MOSFET using the finite difference method. The proposed method is implemented using the GNU Octave tool and the fsolve function to solve nonlinear algebraic equations. This method is expected to provide an accurate and efficient solution to the mobility problem in a N-MOSFET, which could have applications in fields such as quantum physics and electronic engineering.

This article provides an analysis of the state of the art of the STEAM approach in education, the different emergent methodologies that accompany this new paradigm, and the disruptive technologies that are being integrated. Then, a case of success of recommended methodologies in a robotics and disruptive technologies academy is presented. Finally, the challenges that educational institutions must face to effectively integrate STEAM education are addressed.

Parallel mechanism has a great advantage over serial mechanism, this is why day by day in the industry many of them are being made for different applications that require speed, precision and strength. Is known that synthesis of these mechanism is more complex than serial mechanism, for this reason, specifications are sought for its design that can facilitate its analysis. This document provides an analytical synthesis of a five-bar mechanism and a methodology to determine the size of the links and then check their mobility using the Grashoff criterion, furthermore, the workspace of the mechanism is calculated to check that the final effector of the mechanism arrives to the point of interest. Finally, the design of the workspace is presented in Geogebra Software as a simulation, including the final mechanism that was manufactured.

This article provides a prototype analysis for Parkin-son's disease; focused on the anomalies on the deterioration of nerve cells, which produce rhythmic shaking (tremors), generally a warning sign for a diagnosis of Parkinson's.

This study investigates the mechanical properties of polyester resin composites reinforced with sisal fibers in filament and staple forms to assess their viability as sustainable alternatives to traditional materials. Tensile tests were conducted following ASTM standards to evaluate the mechanical performance and sustainability of sisal fiber composites for potential applications in various industrial sectors, such as automotive and aerospace. The discussion addressed how sisal fibers could replace conventional materials in a sustainable wav

This paper describes the creation of the second prototype of a device that helps blind people access new technologies. The whole project is named “Optical Cane,” which is an embedded system integrating an application designed on Flutter and programmed on Visual Studio Code and Thonny. Additionally, it includes an adaptable device created with 3D modeling, an ESP32 (taking advantage of its easy access to the IoT of the shield), and multiple sensors programmed with Micro-Python. These sensors detect objects and analyze them to provide the highest possible accuracy in measuring obstacles, either through the app or by giving a tactile or sound signal. Incorporating different sensors such as ultrasonic, camera, and gyroscopic sensors helps create a rich environment, providing a friendly experience for users with visual disabilities. This prototype demonstrates that accessibility and technology can become even more affordable for people who want to enhance their perception of the world.

This paper presents the results obtained from the PayPal integration project using PHP, JavaScript, and MySQL. The purpose was to implement improvements in the purchasing processes for small and medium-sized enterprises that are in a growth phase, in order to guide them towards an approach based on audits and security. The development of this project yielded positive results and benefits, which include facilitating response times, reducing lost sales, and improving control over the management of customer data and purchase orders. In a globalized context with significant technological advancements, small and medium-sized enterprises cannot afford to fall behind. Therefore, the proposed project allowed the use of available technologies and provided access to them in a practical and more economically feasible way than the complete design of software. Additionally, improvements and adaptability points were validated through testing, according to the conditions.

The Coffee Berry Borer (CBB), Hypothenemus hampei, is one of the most serious threats to global coffee production. This study provides a thorough analysis of the different types of traps used for detecting and controlling the CBB, outlines the development of a preliminary electronic device capable of capturing images of the pest in coffee plantations, and details the creation of a dedicated database. Through a systematic literature review of 13 relevant studies, we examined various trap designs and attractant combinations used for CBB detection. Additionally, we developed a prototype device equipped with an ESP32-CAM microcontroller and solar power capability for continuous field monitoring. The device captures high-resolution images at 15-minute intervals. A preliminary database of 500 images was created. Our findings suggest that effective trap placement typically ranges from 1.2 to 1.5 meters above ground, with a 3:1 methanol-ethanol mixture serving as the optimal attractant. This research contributes to the development of automated CBB monitoring systems and establishes a foundation for future applications of artificial intelligence (AI) in pest management strategies.

This study explores how effective VIS-NIR spectroscopy, combined with machine learning and deep learning techniques, is in classifying various apple varieties gathered from two distinct locations. The study analyzed the diffuse reflectance spectra of three types of Chinese apples: the Fuji apple, the Red Star apple, and the Gala apple. Each apple variety was collected in two distinct collection locations: Shandong and Shaanxi. To achieve this, a comparison between machine learning methods (partial least squares discriminant analysis (PLS-DA) and deep learning methods (artificial neural networks discriminant analysis (ANN-DA)) has been performed. The results show that the ANN-DA models outperform the PLS-DA and SVM models. For the entire sample set, the fact of having three different apple varieties makes all three algorithms the task of classifying correctly more difficult. When the two locations are classified using samples from the same variety, ANN has an accuracy in the calibration and prediction sets of 100%, except for the fuji variety, which reaches 94%. These results show that NIR spectroscopy coupled with Machine Learning or Deep Learning models is a capable method for identifying the apple growing region even for industrial-scale adoption.

This study analyzes the technical, economic, and social barriers limiting access to artificial intelligence (AI) in less developed regions. Using a non-experimental, quantitative approach, methods such as interviews and content analysis are employed to understand perceptions and contexts surrounding AI democratization. The research design does not aim to manipulate variables but rather to analyze existing relationships. Only 30% of countries, mainly in North America, Europe, and parts of Asia, have significant access to advanced technologies, while less than 20% have implemented national AI policies. Barriers include a lack of infrastructure and high costs, restricting AI adoption in underdeveloped areas. Additionally, ethical implications, such as privacy, transparency, and fairness, are highlighted. To democratize AI, it is crucial to include diverse communities in its design and establish policies that promote equitable access.

Agriculture plays a fundamental role in Central America’s economy, yet it faces significant challenges that demand attention. This study aims to examine the technologies and research applied within the context of Agriculture 4.0 in the Central American region, evaluating its adoption and providing a comprehensive overview of the integration of emerging technologies. The analysis highlights that Costa Rica leads research in Agriculture 4.0 in the region, followed by Panama, with a particular focus on crops such as coffee and rice. Despite the increase in scientific production, there remains a notable lack of research in emerging technological areas. Improving agriculture in Central America necessitates investment in modern agricultural technology, promotion of sustainable practices, and enhancement of farmers’ skills. The implementation of Agriculture 4.0, leveraging artificial intelligence, IoT, IoUT, UGVs, digital twins, remote sensing, wireless sensor networks, and automation, is crucial for the sector’s advancement. Additionally, it is imperative to promote agricultural scientific research to develop crops resilient to climate change and more efficient production methods.

This article examines how artificial intelligence is reshaping education through personalized learning, administrative automation, and immersive technologies. It highlights innovations such as intelligent tutoring systems, automatic assessment, and VR/AR tools, while addressing opportunities and challenges related to ethics, privacy, and equity. The study underscores AI’s potential to enhance educational effectiveness and adapt teaching methods in STEAM education.

This paper presents a comprehensive analysis of electromobility trends and policies across Central America, focusing on Guatemala, El Salvador, Honduras, Nicaragua, Costa Rica, and Panama. We examine the current state of electric vehicle (EV) adoption, charging infrastructure development, and policy frameworks in each country. The study highlights significant progress in countries like Costa Rica and Panama, which have implemented robust incentive structures and ambitious targets for EV integration. We also discuss challenges faced by the region, including the need for expanded charging networks and regulatory harmonization. The paper explores the role of public-private partnerships in accelerating EV adoption and the importance of renewable energy integration to maximize environmental benefits. Our analysis reveals a growing momentum towards electromobility in Central America, driven by climate commitments, energy security concerns, and economic opportunities. We conclude by identifying key future trends and policy recommendations to further advance electromobility in the region.

This paper presents the development of an Inertial Measurement Unit (IMU)-based gait acquisition system designed for biomechanical analysis. The proposed system uses IMU sensors to capture and analyze gait patterns, providing detailed insights into human movement that are critical for applications such as exoskeleton design and rehabilitation. The data acquisition process is enhanced by the implementation of a Kalman filter, which ensures accurate and reliable processing of sensor data. The suitability of the system for comprehensive biomechanical studies is demonstrated by comparing previously published works, making it a valuable tool for both clinical and research applications in the field of human motion analysis.

The design and development of a robot capable of climbing stairs and moving on uneven terrains represents a significant advancement in the field of robotics, particularly in applications where adaptability in challenging environments is crucial. This type of robot becomes an invaluable tool in a variety of scenarios, from search and rescue operations in disaster-affected areas to exploration tasks in unknown or inaccessible terrains for humans. What sets this robot apart is its efficient rotational capacity across various surfaces. This capability not only allows it to navigate obstacles more effectively but also enhances its practical utility when faced with varied and difficult terrains. Its ability to adapt to different types of surfaces, whether smooth, rough, inclined, or irregular, makes it extremely versatile and suitable for a wide range of applications. Furthermore, the efficiency in the robot's rotational capacity not only enhances its mobility but can also have significant implications in terms of energy consumption and durability. An optimized rotation system can reduce the load on the robot's components and prolong its lifespan, making it a more sustainable and economically viable long-term solution.

Optimization challenges in industrial engineering, particularly in economic order quantity (EOQ) and materials requirement planning (MRP), have traditionally been complex. This research addresses critical limitations in existing production and inventory management models by addressing recent computational advancements. We propose a comprehensive approach to resolving large-scale industrial engineering optimization problems by integrating high-level programming languages and advanced optimization tools. The study focuses on developing a generic Python-based optimization algorithm using a reference optimization model and Gurobi solver, with primary contributions including: (i) systematic exploration of optimization methods in industrial engineering; (ii) development of a flexible, scalable optimization approach; (iii) demonstration of computational techniques' potential in solving complex production planning challenges. By bridging theoretical optimization models with practical implementation, this research offers a cost-effective solution that extends beyond traditional limitations of economic order quantity and production lot sizing methodologies.

This paper analyzes the synergy between nuclear energy and green hydrogen production, highlighting thoriumbased nuclear fission as a stable, low-carbon energy source to power electrolysis processes. It assesses the viability of green hydrogen in hard-to-decarbonize sectors such as the steel industry, ammonia production, heavy transport, and industrial and agricultural machinery. The analysis emphasizes benefits in energy efficiency while also identifying key challenges, including high initial investment, the need for strong regulatory frameworks, and public acceptance of nuclear energy. Finally, future research directions are proposed to validate and optimize this technological alternative.

This study presents a comprehensive kinematic analysis of a five-bar parallel robot, using vector analysis as the primary tool to solve both the forward and inverse kinematics of the mechanism. Through this approach, the geometric relationships and constraints imposed by the robot's links and joints are addressed, allowing for the determination of the end-effector's positions and orientations as functions of the input angles. To validate the obtained results, a comparison is made between the positions calculated using the vector model and those generated through a five-bar parallel robot simulator developed in GeoGebra. Additionally, a Matlab-based software is implemented to simulate the robot's kinematics, providing an additional platform for result verification. Finally, the advantages and limitations of vector analysis are discussed in comparison to other kinematic solution methods, such as numerical and algebraic approaches, highlighting applications and potential areas for improvement in the field of parallel robots.

This article presents a systematic review on the application of Large Language Models in smart manufacturing, highlighting their potential to transform key industrial processes such as predictive maintenance, human-machine interaction, automated documentation, and decision optimization. Recent cases across various domains, including electronic design, industrial programming, and decision support systems, are analyzed, demonstrating the versatility of LLMs in processing large volumes of data, enabling natural communication with operators, and generating proactive recommendations. The review also identifies significant barriers to adoption in Latin America, including limitations in technological infrastructure, insufficient investment, and limited availability of specialized AI personnel. This study emphasizes the need for public policies, professional training, and collaboration among academy, industry, and government to promote the effective and sustainable implementation of LLMs, adapted to local contexts and capable of closing existing gaps in the region.

Artificial Intelligence (AI) has become a transformative tool in education, particularly in STEAM (Science, Technology, Engineering, Arts, and Mathematics) disciplines. This paper examines the integration of AIBOT, an advanced Intelligent Tutoring System (ITS) and adaptive learning platform, within the STEAM Robotics Academy to personalize learning experiences, enhance student engagement, and address diverse educational needs. By leveraging AIBOT’s capabilities, such as step-by-step guidance, real-time feedback, simulation environments, and performance analysis, the study highlights its potential to revolutionize STEAM education. Additionally, the paper explores challenges such as ethical considerations, teacher training, and infrastructure requirements, offering actionable insights for educators, policymakers, and technologists. This analysis contributes to the growing body of knowledge on AI’s role in transforming education and fostering innovation in STEAM fields.

Marine monitoring is essential for the conservation of ecosystems and the sustainable management of marine resources, especially in Latin America, which has extensive and diverse maritime areas. This article presents a systematic review of recent technological advances applied to marine monitoring in the region, covering the Internet of Things (IoT), remote sensing, artificial intelligence, drones, and marine robotics. Using the PRISMA methodology, key technologies, their geographical distribution, and the challenges in their implementation are identified. The results highlight the need to integrate innovative technologies and promote regional collaboration to strengthen marine monitoring systems, supporting the Blue Economy and sustainable environmental management.

The analysis and classification of white blood cells (leukocytes) are critical for diagnosing numerous diseases, as they constitute the immune system’s primary defense mechanism. Manual leukocyte differential counting is labor-intensive, requires skilled microscopy personnel, and is susceptible to human error—particularly when a single specialist must process large volumes of blood smears. This work presents an automated classification algorithm based on K-means clustering, aimed specifically at distinguishing agranulocytes into lymphocytes and monocytes, which are key indicators in the diagnosis of infections such as mononucleosis, tuberculosis, and hepatitis. A central feature of this approach is its emphasis on local technological development, minimizing reliance on costly foreign commercial solutions. Preliminary results confirm the method’s feasibility, achieving an overall accuracy of 77%, with a precision of 93% and a recall of 77%. These outcomes support the advancement of local expertise for transparent, customizable, and accessible biomedical applications.

Natural disasters continue to pose significant threats to human life, often leaving victims trapped under collapsed structures where time-sensitive response is critical. Search and Rescue (SAR) robots have emerged as essential tools to support emergency teams by accessing hazardous or unreachable areas. This paper presents the design, construction, and functional validation of BMO 2.0, a ground-based mobile rescue robot designed to assist in victim localization and environmental monitoring in disaster scenarios. The robot features a modular 3D-printed chassis, optimized for low center of gravity and structural robustness. It integrates a hybrid sensory system, including a thermal camera (MLX90640), a vision module (ESP32-CAM), gas and environmental sensors (MQ-2, aht21), a PIR motion sensor, and an inertial measurement unit (MPU-6050). The core of the system is managed by an Arduino Mega microcontroller and an ESP8266 module for Wi-Fi-based communication with a custom mobile application. The robot was tested in simulated post-disaster environments, demonstrating stable locomotion, real-time wireless data transmission, and accurate thermal and presence detection. The results confirm the viability of BMO 2.0 as a low-cost, adaptable solution for preliminary SAR operations, particularly in regions with limited access to commercial robotic systems.

The integration of trainable molecular algorithms within biological computing frameworks using DNA represents a transformative advance in unconventional computing paradigms. By leveraging the inherent parallelism, high storage density, and biochemical specificity of DNA molecules, these systems enable the execution of computational processes that transcend traditional silicon-based architectures. This work explores recent advances in the design and implementation of DNA-based learning systems capable of performing logical operations, adaptive decision-making, and basic machine learning tasks in biochemical environments. Additionally, the main challenges in the field are addressed, including kinetic unpredictability, molecular noise propagation, limited scalability, and constraints in the interface between molecular and electronic systems. Finally, future perspectives on the training of molecular algorithms are discussed, such as programmable biochemical networks, adaptive molecular memory, and the development of biochemical compilation toolchains. These advances pave the way toward autonomous and intelligent molecular systems with applications in biosensing, therapeutic diagnostics, and next-generation hybrid computing architectures.

This paper presents a dynamic analysis of the ALICE exoskeleton using the Lagrange-Euler formulation. The study begins with a detailed description of the mechanism, highlighting its structural characteristics and mechanical properties. Then, the equations of motion are derived, and the Lagrange-Euler method is applied to model the system dynamics. To validate the proposed model, gait data were collected from five healthy subjects using a custom-developed gait acquisition system. The experimentally obtained data were then used to verify the accuracy and applicability of the derived equations, demonstrating the effectiveness of the proposed approach for analyzing and modeling lower-limb exoskeleton dynamics.

This systematic review analyzes the use of eye-tracking technology for the detection and monitoring of neurodegenerative diseases using PRISMA methodology. Based on a vigorous analysis of 16 high quality studies, the review highlights the potential of eye tracking as a non-invasive diagnostic tool, particularly for diseases such as Alzheimer’s and Parkinson’s disease. The findings indicate high diagnostic accuracy in distinguishing between patients and healthy controls, with significant promise for early detection. Technological advances, including wearable eye trackers and the integration of artificial intelligence with machine learning algorithms such as Random Forest, SVM and CNN, substantially improve the feasibility of its clinical application. However, critical needs for protocol standardization and longitudinal validation are identified to facilitate its widespread adoption in clinical practice.

Equitable access to energy remains a persistent challenge in El Salvador, where despite renewable sources accounting for nearly 70% of the electricity matrix, high levels of energy poverty continue to affect predominantly rural and low-income communities. This paper presents the case of the AD ASTRA 2024 Project, a community intervention that implemented solar lighting and pumping systems in six communities within the metropolitan area of San Salvador, combining technical solutions with training processes and citizen participation. A methodology based on Design Thinking, participatory diagnosis, and sustainable project management was applied, involving the active engagement of youth previously trained in renewable energies. Results demonstrate a significant improvement in perceived security (100%), strengthening of social fabric, and an estimated annual reduction of 5.8 tons of CO2 emissions, with an economic payback period between 3 and 5 years. The experience evidences that solar energy, integrated with community empowerment processes, can act as a catalyst for social, economic, and environmental development in vulnerable contexts, offering a replicable model for the Latin American region.

This paper presents the design and construction of a SCARA (Selective Compliance Assembly Robot Arm) robot aimed at automated assembly tasks. The work addresses mechanical design, actuator selection, control architecture, and experimental validation of the system. The developed prototype enables precise and repetitive operations, making it viable for low-cost production lines. The final result demonstrates that, through the use of accessible technologies such as 3D printing and open-source platforms, it is possible to develop functional prototypes with a high degree of customization and applicability in real manufacturing environments.

This paper presents the development and evaluation of an innovative educational application using Augmented Reality (AR) and robotic kit called “Edarr” that leverages to enhance STEM (Science, Technology, Engineering, and Mathematics) learning among children and young people. The application is designed to introduce foundational concepts in robotics and related STEM areas through interactive and immersive AR experiences. By combining visual engagement with hands-on activities, the project aims to foster curiosity, improve understanding, and face one of the biggest challenges in technology education: bridge the gap between theoretical knowledge and practical application. Initial testing with target age groups indicates increased motivation, higher retention of concepts, and a more inclusive learning environment. This project highlights the potential of AR as a transformative tool in education, particularly for preparing the next generation for the challenges of a technology-driven world.

The digital transformation of the power sector is reshaping the operation, supervision, and planning of distribution networks. In this context, Smart Transformers emerge as a key technology to achieve greater efficiency, reliability, and flexibility in increasingly dynamic and decentralized systems. By integrating real-time monitoring, control, and communication technologies, these devices enable more responsive and intelligent grid management. In Latin America, the adoption of Smart Transformers represents a strategic opportunity to modernize aging infrastructure, traditionally based on conventional transformers with limited visibility and control. However, their implementation faces significant challenges, including high initial costs, outdated regulations, and technical skill gaps. This paper provides a comprehensive overview of Smart Transformers, highlighting their functionalities, key features, and differences compared to traditional transformers based on a literature review and analysis of regional pilot projects. It also analyzes the opportunities and barriers for their deployment in Latin America, drawing on real-world case studies from Brazil, Mexico, and Colombia. Finally, it outlines future perspectives and strategic actions to facilitate a gradual transition toward a more digital, resilient, and interoperable electrical grid.

This project addresses the limitations of current soft gripper end effectors that do not rely on compressed air and struggle to handle fragile foods and solid objects. The lack of research on “soft grippers” based on shape and materials hinders their industrial use and prevents cost savings from eliminating compressed air. To overcome this, a two-finger gripper with a TPU interior will be developed, using the V-Model methodology for structured development and validation. Initial prototypes will be created with PLA, followed by TPU for behavior analysis, with extrusion and line width adjustments to enhance strength and adaptability. A textured surface will be applied for optimal non-slip grip. The results demonstrate that the structure can withstand prolonged use with minimal wear and deformation, even when handling fragile or weighted objects. The project concludes that leveraging 3D printing and the honeycomb principle for soft gripper prototypes significantly improves industrial processing capabilities, offering a cost-effective and efficient solution with potential for future enhancements and diverse applications.

Fused Deposition Modeling (FDM) 3D printing with Thermoplastic Polyurethane (TPU) has recently been used to fabricate soft robotic actuators and grippers, offering an alternative to traditional silicone casting, which is time-consuming and involves complex manufacturing steps. However, 3D printing soft robotic actuators and grippers using highly-flexible TPU (Shore hardness of 60A and 70A) remains unexplored. Although 60A and 70A TPUs are expected to provide excellent features for soft robots, designing and simulating soft robots using these TPU grades requires information about their best-fitting hyperelastic model, parameters, and material properties, which are hitherto unknown. Therefore, we characterize the 60A and 70A TPU behavior using uniaxial tensile tests and identify the best-fitting hyperelastic model with its appropriate parameters. We then demonstrated the feasibility of using these materials by 3D printing high-fidelity soft grippers using 60A and 70A TPU. Compared to a traditional silicone-based soft gripper of a similar size and shape, the proposed 3D printed TPU soft gripper can grasp objects over five times heavier and achieve more than twice the bending angle, while significantly reducing fabrication time and complexity. We also compared the bending angles of 60A and 70A TPU with 85A TPU soft fingers to demonstrate the importance of low-Shore-hardness materials. Furthermore, we compared the experimentally measured bending behavior of the TPU soft fingers with simulation results using the obtained hyperelastic parameters and found that they closely match the experimental results.

Abstract: This systematic literature review examines the state of the art in responsible artificial intelligence (AI) applications within healthcare. The study analyzes the most relevant publications on explainable AI (XAI) implementations and ethical considerations in medicine from 2022 to 2025, providing a comprehensive update to the current body of knowledge. Through screening and selection processes, 21 papers were identified and examined in detail to assess advancements, challenges, and emerging trends in explainable AI adoption across various medical domains including medical imaging, cancer diagnosis and digital pathology. The review highlights explainability methods and implementation barriers for trustworthy AI integration in clinical practice.

Keywords: Artificial intelligence, explainable AI, AI governance, ethical AI, responsible AI, algorithmic ethics, healthcare, medicine, medical care, systematic literature review.

Abstract—The reliable and cost-effective decarbonization of power systems requires innovative strategies to address the
increasing challenge of renewable energy curtailment. This study investigates the application of Autoregressive with Exogenous Variables (ARX) models to predict renewable curtailment under the extreme conditions of the COVID-19 pandemic in Honduras. Usiung daily reports of renewable generation limitations, the data was processed to generate monthly summaries of curtailed energy and identify the most affected plants. The ARX model was simulated with varying polynomial orders to optimize computational efficiency, while Root Mean Square Error (RMSE) and Fit Index (FIT) were employed as evaluation criteria. Results show that the proposed ARX model achieves high accuracy, with prediction errors below 3%, effectively capturing curtailment dynamics at both system and plant levels. Critical network points were identified at the CINCO ESTRELLAS and MARCOVIA plants, underscoring the need to target interconnections to enhance renewable integration. These findings validate the ARX model as a robust forecasting tool for renewable curtailment and highlight its potential to support operational planning, improve system flexibility, and reduce clean energy losses.

Keywords—renewable energy curtailment, ARX model, forecasting, COVID-19, Honduras case study

In this paper an exhaustive singularity analysis of a 3RRR planar parallel robot is performed. The Jacobian matrix using the Screw theory is obtained and an effective method for singular configurations analysis based on a condition index of the Jacobian matrix is presented. Finally, a new similarity law that allows the workspace optimization free of singular configurations and the working mode selection is presented. Furthermore, MATLAB as a testing tool and programming language is used.

En este artículo se propone una nueva técnica para la obtención de un modelo dinámico de robots 3RRR a partir de un modelo cinemático basado en teoría de screws, la cual permite obtener la cinemática de un robot ya sea ésta abierta o cerrada. Primero se obtiene el modelo cinemático de una forma compacta y a partir de éste se llega al modelo dinámico aplicando el método de Euler Lagrange, con ello se transfieren las características de simplicidad y compacidad del modelo cinemático al dinámico. El modelo dinámico se obtiene inicialmente para las juntas actuadas y luego para las coordenadas del efector a través de sus interrelaciones. Para comprobar la efectividad de este desarrollo teórico se prueba el modelo obtenido con un controlador proporcional-derivativo (PD) ya que provee de una estrategia de control simple que luego puede ser extendida a controladores más efectivos

Un exoesqueleto robótico es un dispositivo electromecánico utilizado para aumentar la capacidad física de una persona, como ayuda a la locomoción o para procesos de rehabilitación de la marcha. En el caso de los exoesqueletos de rehabilitación se requiere que el sistema de control sea capaz de adaptarse adecuadamente a la evolución del paciente con el fin de optimizar su recuperación, esto implica el diseño de controladores robustos y precisos. En este trabajo se presenta el análisis cinemático, análisis dinámico y evaluación del sistema de control del exoesqueleto de rehabilitación ALICE. Dentro de las técnicas de control presentadas se encuentran: el controlador PD, PD adaptativo, y el controlador en modo deslizante. Además, se realiza un análisis de estabilidad utilizando el criterio de Lyapunov. Para probar el rendimiento de los reguladores, se utiliza un conjunto de datos de la Escuela de Fisioterapia de la ONCE de Madrid, correspondiente a personas sanas y personas con esclerosis múltiple. Se utiliza MATLAB como software de simulación y lenguaje de programación.

Mechatronics and Robotics (MaR) have recently gained importance in product development and manufacturing settings and applications. Therefore, the Center for Space Emerging Technologies (C-SET) has managed an international multi-disciplinary study to present, historically, the first Latin American general review of industrial, collaborative, and mobile robotics, with the support of North American and European researchers and institutions. The methodology is developed by considering literature extracted from Scopus, Web of Science, and Aerospace Research Central and adding reports written by companies and government organizations. This describes the state-of-the-art of MaR until the year 2023 in the 3 Sub-Regions: North America, Central America, and South America, having achieved important results related to the academy, industry, government, and entrepreneurship; thus, the statistics shown in this manuscript are unique. Also, this article explores the potential for further work and advantages described by robotic companies such as ABB, KUKA, and Mecademic and the use of the Robot Operating System (ROS) in order to promote research, development, and innovation. In addition, the integration with industry 4.0 and digital manufacturing, architecture and construction, aerospace, smart agriculture, artificial intelligence, and computational social science (human-robot interaction) is analyzed to show the promising features of these growing tech areas, considering the improvements to increase production, manufacturing, and education in the Region. Finally, regarding the information presented, Latin America is considered an important location for investments to increase production and product development, taking into account the further proposal for the creation of the LATAM Consortium for Advanced Robotics and Mechatronics, which could support and work on roboethics and education/R+D+I law and regulations in the Region. Doi: 10.28991/ESJ-2023-07-04-025 Full Text: PDF

This paper presents the design and synthesis of a dynamic output feedback neural network controller for a non-holonomic mobile robot. First, the dynamic model of a non-holonomic mobile robot is presented, in which these constraints are considered for the mathematical derivation of a feasible representation of this kind of robot. Then, two control strategies are provided based on kinematic control for this kind of robot. The first control strategy is based on driftless control; this means that considering that the velocity vector of the mobile robot is orthogonal to its restriction, a dynamic output feedback and neural network controller is designed so that the control action would be zero only when the velocity of the mobile robot is zero. The Lyapunov stability theorem is implemented in order to find a suitable control law. Then, another control strategy is designed for trajectory-tracking purposes, in which similar to the driftless controller, a kinematic control scheme is provided that is suitable to implement in more sophisticated hardware. In both control strategies, a dynamic control law is provided along with a feedforward neural network controller, so in this way, by the Lyapunov theory, the stability and convergence to the origin of the mobile robot position coordinates are ensured. Finally, two numerical experiments are presented in order to validate the theoretical results synthesized in this research study. Discussions and conclusions are provided in order to analyze the results found in this research study.

This paper shows the dynamic modeling and design of a passivity-based controller for the RV-3SB robot. Firstly, the dynamic modeling of a Mitsubishi RV-3SB robot is conducted using Euler–Lagrange formulation in order to obtain a decoupled dynamic model, considering the actuator orientation besides the position of the analyzed robot. It is important to remark that the dynamic model of the RV-3SB robot is conducted based on kinematic model obtention, which is developed by the implementation of screw theory. Then, the passivity-based controller is obtained by separating the end effector variables and the actuator variables by making an appropriate coordinate transformation. The passivity-based controller is obtained by selecting an appropriate storage function, and by using Lyapunov theory, the passivity-based control law is obtained in order to drive the error variable, which is the difference between the measured end effector position variable and the desired end effector position variable. The passivity-based controller makes the error variable reach the origin in finite time, taking into consideration the dissipation properties of the proposed controller in order to stabilize the desired end effector position. A numerical simulation experiment is performed in order to validate the theoretical results obtained in this research. Using numerical experimentation, it is verified that the proposed control strategy is efficient and effective in driving the error variable to the origin in comparison with other modified techniques found in the literature. Finally, an appropriate discussion and conclusion of this research study are provided.

Existing direct and inverse kinematic models of planar parallel robots assume that the robot’s active joints are all at the bases. However, this approach becomes excessively complex when modeling a planar parallel robot in which the active joints are within one single kinematic chain. To address this problem, our article unveils an alternative for a 3RRR symmetric planar robot modeling technique for the derivation of the robot workspace and the analysis of its direct and inverse kinematics. The workspace was defined using a system of inequalities, and the direct and inverse kinematics models were generated using vectorial analysis and an optimized geometrical approach, respectively. The resulting models are systematically presented and validated. Two final model renditions are delivered supplying a thorough equation analysis and an applicability discussion based on the importance of the robot’s mobile platform orientation. The advantages of this model are discussed in comparison to the traditional modeling approach: whereas conventional techniques require the solution of complex eighth-degree polynomials for the analysis of the active joint configuration of these robots, these models provide an efficient back-of-the-envelope analysis approach that requires the solution of a simple second-degree polynomial.

This study presents a Systematic Literature Review (SLR) on the management of Coffee Berry Borer (CBB) and Coffee Leaf Rust (CLR) in Coffee Agroforestry Systems (CAFS). Despite extensive research on pest and disease management in CAFS, there is a notable absence of literature reviews or bibliometric analyses regarding the study of the CBB and CLR. The novelty of this work lies in offering a comprehensive synthesis of recent research and identifying the technologies employed in these studies, providing valuable insights for future developments in the field. Using the PRISMA protocol and Bibliometrix tool, the research analyzed 51 relevant studies from Web of Science and Scopus databases, covering the period from 2002 to August 2024. The analysis revealed an increasing trend in publications on CBB and CLR in CAFS in recent years. Traditional techniques, such as visual plant observation, pheromone traps, and spore sedimentation traps, remain prevalent. However, the use of advanced technologies in CAFS is still limited. Findings highlight the significant impact of shade on pest dynamics, the importance of biodiversity in pest control, and the need for integrated pest management strategies. The study concludes that while traditional techniques play a crucial role in pest and disease monitoring in CAFS, there is significant untapped potential in integrating advanced technologies such as sensors, UAVs, IoT, robotics, and AI. The limited use of these technologies in CAFS underscores the need for future research to drive their adoption and optimization, aiming to improve sustainable pest and disease management in these complex systems.

This work presents the design and implementation of a data-driven Nonlinear Model Predictive Control (NMPC) framework for an Uncrewed Aerial Vehicle (UAV) equipped with a 3-DOF robotic arm. Real-world data was collected using the Matrice 100 platform and Dynamixel MX-28AR actuators to identify a high-dimensional linear model via Dynamic Mode Decomposition with Control (DMDc), capturing the interactions between the aerial vehicle and the manipulator across 21 state variables. This DMDc-based model is embedded within the NMPC formulation to predict system behavior over finite horizons. The UAV’s orientation is represented using quaternions, enabling continuous and singularity-free attitude control. Additionally, the redundancy of the UAV-manipulator system allows for the integration of secondary objectives into the cost function, supporting flexible task execution. To meet real-time requirements, the control problem is solved using the Acados solver. The resulting controller achieves high-precision tracking while managing internal constraints, demonstrating the potential of data-driven NMPC in aerial manipulation tasks.

In this study, we propose a novel method that integrates Nonlinear Model Predictive Contour Control (NMPCC) with an Exponentially Stabilizing Control Lyapunov Function (ES-CLF) and Exponential Higher-Order Control Barrier Functions to achieve stable path-following and obstacle avoidance in UAV systems. This framework enables uncrewed aerial vehicles (UAVs) to safely navigate around both static and dynamic obstacles while strictly adhering to desired paths. The quaternion-based formulation ensures precise orientation and attitude control, while a robust optimization solver enforces the constraints imposed by the Control Lyapunov Function (CLF) and Control Barrier Functions (CBF), ensuring reliable real-time performance. The proposed method was experimentally validated using a DJI Matrice 100 quadrotor platform, considering scenarios with prior knowledge of obstacle locations. Results demonstrate the controller’s effectiveness in minimizing orthogonal and tangential tracking errors, ensuring stability and safety in complex environments.