Research Interests:
Research Interests:
Research Interests:
Research Interests:
Using Internet-based networking technologies traditional control laboratories in engineering education can be replaced with a remote or simulated experimental session. Thus, the way of studying becomes more flexible: the assistance to the... more
Using Internet-based networking technologies traditional control laboratories in engineering education can be replaced with a remote or simulated experimental session. Thus, the way of studying becomes more flexible: the assistance to the laboratories is minimized. Accessing to the application students can make experiments and obtain results with a real plant from different localizations far from the university. This paper presents
Research Interests:
Abstract This paper presents a library for V-REP simulator to incorporate the Khepera IV robot model. The library contains the model of this robot and some examples of use with its corresponding results. The library has been developed... more
Abstract This paper presents a library for V-REP simulator to incorporate the Khepera IV robot model. The library contains the model of this robot and some examples of use with its corresponding results. The library has been developed using Autodesk Inventor for the visual design and Lua language for the programming code. This library allows the implementation of experiments with one robot and multi-robots approaches. After using the library in the V-REP environment, users can transform many of the simulations into real experiments with the Khepera IV robots.
Research Interests:
Research Interests: Program Evaluation, Computer Science, Software Engineering, Information Technology, Educational Technology, and 13 moreEngineering Education, Control system, Java, Programming, Software, Computers in Education, Remote Control, Control Management, Interactive application, Software Tool, Pace, remote laboratory, and Authoring Tool
Research Interests:
Research Interests:
Research Interests:
Research Interests:
This article presents a classification system for news with Deep Learning. With this tool the news are classified in the following categories: Sports, Politics, Economics, Show and Police. Also they receives an scope: Local (Valparaíso),... more
This article presents a classification system for news with Deep Learning. With this tool the news are classified in the following categories: Sports, Politics, Economics, Show and Police. Also they receives an scope: Local (Valparaíso), National (Chile) and International (Rest of the World). The classifiers were built using a database with 542 news labeled with the previous criteria. The features were extracted with Autoencoders (AE) to train an Artificial Neural Network (ANN) of multiple classes Softmax (Softmax ANNs). Both stages were stacked following the concept of Deep Learning. The results with the data test (156 news) reach a success rate of 92.3% for the category classifier and 87.2% for the scope classifier. The general success rate for both, category and scope was 83.75%.
Research Interests:
Research Interests:
Research Interests:
The advances of information and communication technologies have impacted in control education. Virtual laboratories are increasingly been used to enhance the way that students interact with simulations. High degree of visualization and... more
The advances of information and communication technologies have impacted in control education. Virtual laboratories are increasingly been used to enhance the way that students interact with simulations. High degree of visualization and interaction offered by modern computers open the opportunity to teach theory fundamentals with a more natural approach. This work describes the use of the robot simulator V-REP and the Khepera IV library to teach interesting control problems with mobile robots. The Khepera IV library supports the new functionalities of the most recent version of the wheeled robot Khepera, which allows creating advanced 3D simulations in the V-REP environment. The article also explains how instructors can use this development to teach classical control problems in mobile robotics. In particular, the theory and practice of the problems for position control, trajectory tracking, path following and the obstacle avoidance are given in detail.
Research Interests:
Research Interests:
This article presents a navigation simulation based on computer vision of the Khepera IV robot model (KH4VREP library) in the V-REP simulator. The images acquired by the robot are processed externally by the OpenCV library through a... more
This article presents a navigation simulation based on computer vision of the Khepera IV robot model (KH4VREP library) in the V-REP simulator. The images acquired by the robot are processed externally by the OpenCV library through a script built in the Python programming language. This library has implemented many optimized machine learning algorithms and will now be implemented in the discipline of machine vision, so some robot speed control experiments are implemented to test this approach. The objective of this work is to introduce students to the control of mobile robots based on artificial vision.
Research Interests:
A new algorithm to improve the 3D positioning for low cost mobile robots is presented. The core of the algorithm is based on a Finite State Machine (FSM) which estimates the 3D position and orientation of the robots, also a low pass... more
A new algorithm to improve the 3D positioning for low cost mobile robots is presented. The core of the algorithm is based on a Finite State Machine (FSM) which estimates the 3D position and orientation of the robots, also a low pass filter and a threshold calculator are used in the system to filter and to estimate the noise in the sensors. The system sets dynamically the parameters of the algorithm and makes them independent of the noise. The algorithm has been tested with differential wheel drive robots, however it can be used with other different types of robots in a simple way. To improve the accuracy of the estimations, a new reference system based on the accelerometer of the robot is presented which reduces the accumulative error that the odometry produces.
Research Interests:
Research Interests:
Research Interests:
Research Interests:
The current computational advance allows the development of technological solutions using tools, such as mobile robots and programmable electronic systems. We present a design that integrates the Khepera IV mobile robot with an NVIDIA... more
The current computational advance allows the development of technological solutions using tools, such as mobile robots and programmable electronic systems. We present a design that integrates the Khepera IV mobile robot with an NVIDIA Jetson Xavier NX board. This system executes an algorithm for navigation control based on computer vision and the use of a model for object detection. Among the functionalities that this integration adds to the Khepera IV in generating guided driving are trajectory tracking for safe navigation and the detection of traffic signs for decision-making. We built a robotic platform to test the system in real time. We also compared it with a digital model of the Khepera IV in the CoppeliaSim simulator. The navigation control results show significant improvements over previous works. This is evident in both the maximum navigation speed and the hit rate of the traffic sign detection system. We also analyzed the navigation control, which achieved an average succ...
Research Interests:
Research Interests:
Recently, the scientific community has placed great emphasis on the recognition of human activity, especially in the area of health and care for the elderly. There are already practical applications of activity recognition and unusual... more
Recently, the scientific community has placed great emphasis on the recognition of human activity, especially in the area of health and care for the elderly. There are already practical applications of activity recognition and unusual conditions that use body sensors such as wrist-worn devices or neck pendants. These relatively simple devices may be prone to errors, might be uncomfortable to wear, might be forgotten or not worn, and are unable to detect more subtle conditions such as incorrect postures. Therefore, other proposed methods are based on the use of images and videos to carry out human activity recognition, even in open spaces and with multiple people. However, the resulting increase in the size and complexity involved when using image data requires the use of the most recent advanced machine learning and deep learning techniques. This paper presents an approach based on deep learning with attention to the recognition of activities from multiple frames. Feature extraction...
Research Interests:
Research Interests:
This article proposes the use of reinforcement learning (RL) algorithms to control the position of a simulated Kephera IV mobile robot in a virtual environment. The simulated environment uses the OpenAI Gym library in conjunction with... more
This article proposes the use of reinforcement learning (RL) algorithms to control the position of a simulated Kephera IV mobile robot in a virtual environment. The simulated environment uses the OpenAI Gym library in conjunction with CoppeliaSim, a 3D simulation platform, to perform the experiments and control the position of the robot. The RL agents used correspond to the deep deterministic policy gradient (DDPG) and deep Q network (DQN), and their results are compared with two control algorithms called Villela and IPC. The results obtained from the experiments in environments with and without obstacles show that DDPG and DQN manage to learn and infer the best actions in the environment, allowing us to effectively perform the position control of different target points and obtain the best results based on different metrics and indices.
Research Interests:
In recent years, much effort has been devoted to the development of applications capable of detecting different types of human activity. In this field, fall detection is particularly relevant, especially for the elderly. On the one hand,... more
In recent years, much effort has been devoted to the development of applications capable of detecting different types of human activity. In this field, fall detection is particularly relevant, especially for the elderly. On the one hand, some applications use wearable sensors that are integrated into cell phones, necklaces or smart bracelets to detect sudden movements of the person wearing the device. The main drawback of these types of systems is that these devices must be placed on a person’s body. This is a major drawback because they can be uncomfortable, in addition to the fact that these systems cannot be implemented in open spaces and with unfamiliar people. In contrast, other approaches perform activity recognition from video camera images, which have many advantages over the previous ones since the user is not required to wear the sensors. As a result, these applications can be implemented in open spaces and with unknown people. This paper presents a vision-based algorithm ...
Research Interests:
Research Interests:
This article presents the development of a model of a spherical robot that rolls to move and has a single point of support with the surface. The model was developed in the CoppeliaSim simulator, which is a versatile tool for implementing... more
This article presents the development of a model of a spherical robot that rolls to move and has a single point of support with the surface. The model was developed in the CoppeliaSim simulator, which is a versatile tool for implementing this kind of experience. The model was tested under several scenarios and control goals (i.e., position control, path-following and formation control) with control strategies such as reinforcement learning, and Villela and IPC algorithms. The results of these approaches were compared using performance indexes to analyze the performance of the model under different scenarios. The model and examples with different control scenarios are available online.
Research Interests:
Nuclear fusion is the process by which two or more atomic nuclei join together to form a single heavier nucleus. This is usually accompanied by the release of large quantities of energy. This energy could be cheaper, cleaner, and safer... more
Nuclear fusion is the process by which two or more atomic nuclei join together to form a single heavier nucleus. This is usually accompanied by the release of large quantities of energy. This energy could be cheaper, cleaner, and safer than other technology currently in use. Experiments in nuclear fusion generate a large number of signals that are stored in huge databases. It is impossible to do a complete analysis of this data manually, and it is essential to automate this process. That is why machine learning models have been used to this end in previous years. In the literature, several popular algorithms can be found to carry out the automatic classification of signals. Among these, ensemble methods provide a good balance between success rate and internal information about models. Specifically, AdaBoost algorithm will allow obtaining an explicit set of rules that explains the class for each input data, adding interpretability to the models. In this paper, an innovative approach ...
Research Interests:
ABSTRACT This paper presents the development, structure, implementation, and some applications of a remote laboratory for teaching automatic control concepts to engineering students. There are two applications: formation control of mobile... more
ABSTRACT This paper presents the development, structure, implementation, and some applications of a remote laboratory for teaching automatic control concepts to engineering students. There are two applications: formation control of mobile robots and a ball-plate system. In teaching control engineering, there are two main approaches to control design: model-based control and non-model-based control. Students are given insight into: 1) for model-based control: identification of real processes (i.e., dealing with noise, choosing the sampling time, observing nonlinear effects at startup, pairing input-output variables); and 2) for non-model-based control: the advantages and disadvantages of auto-tuning techniques. The paper concludes by presenting an evaluation of these remote labs and discussing the advantages of using them as complementary tools for teaching control engineering at the Bachelor's and Master's level.
Research Interests:
Research Interests: Computer Science, Distributed Computing, Scheduling, Multi Agent System, Wireless Network, and 10 moreMobile Robots, Multi Agent Systems, ROBOT, Formation Control, Network Mobility, Interactive Simulation, Simulation Tool, Electrical And Electronic Engineering, Agent Communication, and Drag and Drop
Scientists and astronomers have attached Scientists and astronomers have attached great importance to the task of discovering new exoplanets, even more so if they are in the habitable zone. To date, more than 4300 exoplanets have been... more
Scientists and astronomers have attached Scientists and astronomers have attached great importance to the task of discovering new exoplanets, even more so if they are in the habitable zone. To date, more than 4300 exoplanets have been confirmed by NASA, using various discovery techniques, including planetary transits, in addition to the use of various databases provided by space and ground-based telescopes. This article proposes the development of a deep learning system for detecting planetary transits in Kepler Telescope lightcurves. The approach is based on related work from the literature and enhanced to validation with real lightcurves. A CNN classification model is trained from a mixture of real and synthetic data, and validated only with real data and different from those used in the training stage. The best ratio of synthetic data is determined by the perform of an optimisation technique and a sensitivity analysis. The precision, accuracy and true positive rate of the best mo...
Research Interests:
El entorno colaborativo desarrollado permite realizar un envío de tareas a ser procesadas en clusters de supercomputación, sin necesidad de que los usuarios de las mismas deban conocer la infraestructura subyacente o estar familiarizados... more
El entorno colaborativo desarrollado permite realizar un envío de tareas a ser procesadas en clusters de supercomputación, sin necesidad de que los usuarios de las mismas deban conocer la infraestructura subyacente o estar familiarizados con las órdenes de más bajo nivel necesarias para interactuar con estos sistemas.
En los últimos años la robótica ha tenido un gran impacto en los entornos educativos a todos los niveles. En estos ámbitos los simuladores han jugado un papel fundamental en el uso de la Robótica en el proceso de enseñanza - aprendizaje.... more
En los últimos años la robótica ha tenido un gran impacto en los entornos educativos a todos los niveles. En estos ámbitos los simuladores han jugado un papel fundamental en el uso de la Robótica en el proceso de enseñanza - aprendizaje. El presente artículo describe el diseño, la implementación y las pruebas de un modelo del robot Khepera IV para incorporarlo al simulador V-REP. El objetivo fundamental es obtener una herramienta lista para ser usada en enseñanza de la Robótica en el Área la de Ingeniería de Control.
Research Interests:
ABSTRACT This paper describes the development of a motivating and innovative multi-robot formation control platform for laboratory experiments with mobile robots. The platform is composed of two components: a simulator and an environment... more
ABSTRACT This paper describes the development of a motivating and innovative multi-robot formation control platform for laboratory experiments with mobile robots. The platform is composed of two components: a simulator and an environment to experiment with low cost wheeled mobile robots. The environment constitutes a ready to use test tool that provides to engineering students the opportunity to simulate and test many different formation and cooperation control strategies with a real system. Currently the platform is used in the Systems and Control Engineering Master program offered by the National University of Distance Education (UNED) and the Complutense University of Madrid (UCM) in Spain. The use of the platform exposes students to hands-on laboratory sessions, contributing to their development as engineers.
Research Interests:
Using Internet-based networking technologies traditional control laboratories in engineering education can be replaced with a remote or simulated experimental session. Thus, the way of studying becomes more flexible: the assistance to the... more
Using Internet-based networking technologies traditional control laboratories in engineering education can be replaced with a remote or simulated experimental session. Thus, the way of studying becomes more flexible: the assistance to the laboratories is minimized. Accessing to the application students can make experiments and obtain results with a real plant from different localizations far from the university. This paper presents
Research Interests:
Research Interests:
Research Interests:
Research Interests:
This article presents a navigation simulation based on computer vision of the Khepera IV robot model (KH4VREP library) in the V-REP simulator. The images acquired by the robot are processed externally by the OpenCV library through a... more
This article presents a navigation simulation based on computer vision of the Khepera IV robot model (KH4VREP library) in the V-REP simulator. The images acquired by the robot are processed externally by the OpenCV library through a script built in the Python programming language. This library has implemented many optimized machine learning algorithms and will now be implemented in the discipline of machine vision, so some robot speed control experiments are implemented to test this approach. The objective of this work is to introduce students to the control of mobile robots based on artificial vision.
Research Interests:
Abstract: In this paper, a new event-based control strategy for mobile robots is presented. It has been designed to work in wireless environments where a centralized controller has to interchange information with the robots over an RF... more
Abstract: In this paper, a new event-based control strategy for mobile robots is presented. It has been designed to work in wireless environments where a centralized controller has to interchange information with the robots over an RF (radio frequency) interface. The event-based architectures have been developed for differential wheeled robots, although they can be applied to other kinds of robots in a simple way. The solution has been checked over classical navigation algorithms, like wall following and obstacle avoidance, using scenarios with a unique or multiple robots. A comparison between the proposed architectures and the classical discrete-time strategy is also carried out. The experimental results shows that the proposed solution has a higher efficiency in communication resource usage than the classical discrete-time strategy with the same accuracy.
Research Interests:
Research Interests:
La educacion a distancia es la modalidad educativa en la cual los estudiantes y el profesor no necesitan compartir el mismo espacio fisico durante el proceso de ensenanza-aprendizaje. A partir de la decada de los 90 con el desarrollo de... more
La educacion a distancia es la modalidad educativa en la cual los estudiantes y el profesor no necesitan compartir el mismo espacio fisico durante el proceso de ensenanza-aprendizaje. A partir de la decada de los 90 con el desarrollo de las redes de comunicaciones e Internet se hace cada vez mas patente la emergencia de un nuevo modelo de educacion, que muchos creen que va a hacer converger la educacion presencial o tradicional y la educacion a distancia, influido directamente por las Tecnologias de la Informacion y las Comunicaciones (TICs). En la actualidad muchas universidades usan la educacion a distancia como metodo en proceso de ensenanza aprendizaje en varias especialidades. En este contexto los experimentos de laboratorio pueden ser adaptados para que los estudiantes puedan acceder a ellos a traves de Internet. Ademas las practicas de laboratorio pueden ser complementadas con una simulacion del proceso al que el estudiante se enfrentara durante la experimentacion con la plan...
Research Interests:
Research Interests:
This article presents a classification system for news with Deep Learning. With this tool the news are classified in the following categories: Sports, Politics, Economics, Show and Police. Also they receives an scope: Local (Valparaíso),... more
This article presents a classification system for news with Deep Learning. With this tool the news are classified in the following categories: Sports, Politics, Economics, Show and Police. Also they receives an scope: Local (Valparaíso), National (Chile) and International (Rest of the World). The classifiers were built using a database with 542 news labeled with the previous criteria. The features were extracted with Autoencoders (AE) to train an Artificial Neural Network (ANN) of multiple classes Softmax (Softmax ANNs). Both stages were stacked following the concept of Deep Learning. The results with the data test (156 news) reach a success rate of 92.3% for the category classifier and 87.2% for the scope classifier. The general success rate for both, category and scope was 83.75%.