Diseño e implementación de un controlador de velocidad PID multivariable para un robot con configuración de triciclo

La robótica móvil constituye un área de desarrollo y explotación de interés creciente. Existen ejemplos de robótica móvil de relevancia destacada en el ámbito industrial y se estima un fuerte crecimiento en el terreno de la robótica de servicios. En la arquitectura software de todos los robots móviles suelen aparecer con frecuencia componentes que tienen asignadas competencias de gobierno, navegación, percepción, etcétera, todos ellos de importancia destacada. Sin embargo, existe un elemento, difícilmente prescindible en este tipo de robots, el cual se encarga del control de velocidad del dispositivo en sus desplazamientos. En el presente proyecto se propone desarrollar un controlador PID basado en el modelo y otro no basado en el modelo. Dichos controladores deberán operar en un robot con configuración de triciclo disponible en el Departamento de Sistemas Informáticos y deberán por tanto ser programados en lenguaje C para ejecutar en el procesador digital de señal destinado para esa actividad en el mencionado robot (dsPIC33FJ128MC802). ABSTRACT Mobile robotics constitutes an area of development and exploitation of increasing interest. There are examples of mobile robotics of outstanding importance in industry and strong growth is expected in the field of service robotics. In the software architecture of all mobile robots usually appear components which have assigned competences of government, navigation, perceptionetc., all of them of major importance. However, there is an essential element in this type of robots, which takes care of the speed control. The present project aims to develop a model-based and other non-model-based PID controller. These controllers must operate in a robot with tricycle settings, available from the Department of Computing Systems, and should therefore be programmed in C language to run on the digital signal processor dedicated to that activity in the robot (dsPIC33FJ128MC802).

Multiple Robots, Single Operator: Considerations About Information And Commanding

Multiple robot, single operator scenarios suppose a challenge in terms of human factors. Two relevant issues are keeping the situational awareness and managing the workload of operators. In order to address these problems, this work analyses the management of information and commands in multi-robot missions. About the information, this paper proposes a selection based on mission and operator states. Regarding the commands, this work reflects about the levels of automation and the methods of commanding.

A Vision-based Quadrotor Multi-robot Solution for the Indoor Autonomy Challenge of the 2013 International Micro Air Vehicle Competition

This paper presents a completely autonomous solution to participate in the Indoor Challenge of the 2013 International Micro Air Vehicle Competition (IMAV 2013). Our proposal is a multi-robot system with no centralized coordination whose robotic agents share their position estimates. The capability of each agent to navigate avoiding collisions is a consequence of the resulting emergent behavior. Each agent consists of a ground station running an instance of the proposed architecture that communicates over WiFi with an AR Drone 2.0 quadrotor. Visual markers are employed to sense and map obstacles and to improve the pose estimation based on Inertial Measurement Unit (IMU) and ground optical flow data. Based on our architecture, each robotic agent can navigate avoiding obstacles and other members of the multi-robot system. The solution is demonstrated and the achieved navigation performance is evaluated by means of experimental flights. This work also analyzes the capabilities of the presented solution in simulated flights of the IMAV 2013 Indoor Challenge. The performance of the CVG UPM team was awarded with the First Prize in the Indoor Autonomy Challenge of the IMAV 2013 competition.

Modeling a mobile robot using a grammatical model

Virtual Worlds Generator is a grammatical model that is proposed to define virtual worlds. It integrates the diversity of sensors and interaction devices, multimodality and a virtual simulation system. Its grammar allows the definition and abstraction in symbols strings of the scenes of the virtual world, independently of the hardware that is used to represent the world or to interact with it. A case study is presented to explain how to use the proposed model to formalize a robot navigation system with multimodal perception and a hybrid control scheme of the robot.

System for robot control inspired by the functionality and organisation of the human nervous system

This paper presents a model of a control system for robot systems inspired by the functionality and organisation of human neuroregulatory system. Our model was specified using software agents within a formal framework and implemented through Web Services. This approach allows the implementation of the control logic of a robot system with relative ease, in an incremental way, using the addition of new control centres to the system as its behaviour is observed or needs to be detailed with greater precision, without the need to modify existing functionality. The tests performed verify that the proposed model has the general characteristics of biological systems together with the desirable features of software, such as robustness, flexibility, reuse and decoupling.

An experience on mechatronics teaching on undergraduate students by means of the Skybot platform: from classroom to robot competition

This paper analyzes the learning experiences and opinions from a group of undergraduate students in a course about Robotics. The contents of this course were taught as a set of seminars. In each seminar, the student learned interdisciplinary knowledge of computer science, control engineering, electronics and other fields related to Robotics. The aim of this course is that the students are able to design and implement their own and custom robotic solution for a series of tests planned by the teachers. These tests measure the behavior and mechatronic features of the students' robots. Finally, the students' robots are confronted with some competitions. In this paper, the low-cost robotic architecture used by the students, the contents of the course, the tests to compare the solutions of students and the opinion of them are amply discussed.

A grammatical approach to the modeling of an autonomous robot

Virtual Worlds Generator is a grammatical model that is proposed to define virtual worlds. It integrates the diversity of sensors and interaction devices, multimodality and a virtual simulation system. Its grammar allows the definition and abstraction in symbols strings of the scenes of the virtual world, independently of the hardware that is used to represent the world or to interact with it. A case study is presented to explain how to use the proposed model to formalize a robot navigation system with multimodal perception and a hybrid control scheme of the robot. The result is an instance of the model grammar that implements the robotic system and is independent of the sensing devices used for perception and interaction. As a conclusion the Virtual Worlds Generator adds value in the simulation of virtual worlds since the definition can be done formally and independently of the peculiarities of the supporting devices.

Event-based visual servoing

Traditional visual servoing systems have been widely studied in the last years. These systems control the position of the camera attached to the robot end-effector guiding it from any position to the desired one. These controllers can be improved by using the event-based control paradigm. The system proposed in this paper is based on the idea of activating the visual controller only when something significant has occurred in the system (e.g. when any visual feature can be loosen because it is going outside the frame). Different event triggers have been defined in the image space in order to activate or deactivate the visual controller. The tests implemented to validate the proposal have proved that this new scheme avoids visual features to go out of the image whereas the system complexity is reduced considerably. Events can be used in the future to change different parameters of the visual servoing systems.

Active Visual Features Based on Events to Guide Robot Manipulators in Tracking Tasks

Traditional visual servoing systems do not deal with the topic of moving objects tracking. When these systems are employed to track a moving object, depending on the object velocity, visual features can go out of the image, causing the fail of the tracking task. This occurs specially when the object and the robot are both stopped and then the object starts the movement. In this work, we have employed a retina camera based on Address Event Representation (AER) in order to use events as input in the visual servoing system. The events launched by the camera indicate a pixel movement. Event visual information is processed only at the moment it occurs, reducing the response time of visual servoing systems when they are used to track moving objects.

RGBD Human-Hand recognition for the Interaction with Robot-Hand

New low cost sensors and the new open free libraries for 3D image processing are permitting to achieve important advances for robot vision applications such as tridimensional object recognition, semantic mapping, navigation and localization of robots, human detection and/or gesture recognition for human-machine interaction. In this paper, a method to recognize the human hand and to track the fingers is proposed. This new method is based on point clouds from range images, RGBD. It does not require visual marks, camera calibration, environment knowledge and complex expensive acquisition systems. Furthermore, this method has been implemented to create a human interface in order to move a robot hand. The human hand is recognized and the movement of the fingers is analyzed. Afterwards, it is imitated from a Barret hand, using communication events programmed from ROS.

La enseñanza de robótica en el Máster en Automática y Robótica mediante un robot modular

Este trabajo muestra cómo se realiza la enseñanza de robótica mediante un robot modular y los resultados educativos obtenidos en el Máster Universitario en Automática y Robótica de la Escuela Politécnica Superior de la Universidad de Alicante. En el artículo se describen los resultados obtenidos con el uso de este robot modular tanto en competencias genéricas como específicas, en las enseñanzas de electrónica, control y programación del Máster. En este artículo se exponen los objetivos de aprendizaje para cada uno de ellos, su aplicación a la enseñanza y los resultados educativos obtenidos. En los resultados del estudio, cabe destacar que el alumno ha mostrado mayor interés y ha fomentado su aprendizaje autónomo. Para ello, el robot modular se construyó con herramientas para fomentar este tipo de enseñanza y aprendizaje, tales como comunicaciones interactivas para monitorizar, cambiar y adaptar diversos parámetros de control y potencia del robot.

Desarrollo de un robot modular para la enseñanza en el Máster en Automática y Robótica

Este trabajo presenta el diseño, construcción y programación de un robot modular para el desarrollo tanto de competencias genéricas como específicas, en las enseñanzas de electrónica, control y programación del Master de Automática y Robótica de la Escuela Politécnica Superior de la Universidad de Alicante. En este trabajo se exponen los diferentes módulos propuestos, así como los objetivos de aprendizaje para cada uno de ellos. Uno de los factores más importantes a destacar en el presente estudio es el posible desarrollo de la creatividad y el aprendizaje autónomo. Para ello, se desarrollará especialmente un módulo de comunicación por bluetooth que servirá para monitorizar, cambiar y adaptar on-line diversos parámetros de control y potencia del robot. Además, dicha herramienta se ha introducido como parte de la metodología en las asignaturas del Máster de Electromecánica y Sistemas de Control Automático. En esta memoria se mostrarán los distintos resultados obtenidos durante y en la finalización de este trabajo.

3D Visual Data-Driven Spatiotemporal Deformations for Non-Rigid Object Grasping Using Robot Hands

Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object’s surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand’s fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments.

Computational models for improved diagnosis and prognosis of stroke using robot-based biomarkers

Stroke is a leading cause of death and permanent disability worldwide, affecting millions of individuals. Traditional clinical scores for assessment of stroke-related impairments are inherently subjective and limited by inter-rater and intra-rater reliability, as well as floor and ceiling effects. In contrast, robotic technologies provide objective, highly repeatable tools for quantification of neurological impairments following stroke. KINARM is an exoskeleton robotic device that provides objective, reliable tools for assessment of sensorimotor, proprioceptive and cognitive brain function by means of a battery of behavioral tasks. As such, KINARM is particularly useful for assessment of neurological impairments following stroke. This thesis introduces a computational framework for assessment of neurological impairments using the data provided by KINARM. This is done by achieving two main objectives. First, to investigate how robotic measurements can be used to estimate current and future abilities to perform daily activities for subjects with stroke. We are able to predict clinical scores related to activities of daily living at present and future time points using a set of robotic biomarkers. The findings of this analysis provide a proof of principle that robotic evaluation can be an effective tool for clinical decision support and target-based rehabilitation therapy. The second main objective of this thesis is to address the emerging problem of long assessment time, which can potentially lead to fatigue when assessing subjects with stroke. To address this issue, we examine two time reduction strategies. The first strategy focuses on task selection, whereby KINARM tasks are arranged in a hierarchical structure so that an earlier task in the assessment procedure can be used to decide whether or not subsequent tasks should be performed. The second strategy focuses on time reduction on the longest two individual KINARM tasks. Both reduction strategies are shown to provide significant time savings, ranging from 30% to 90% using task selection and 50% using individual task reductions, thereby establishing a framework for reduction of assessment time on a broader set of KINARM tasks. All in all, findings of this thesis establish an improved platform for diagnosis and prognosis of stroke using robot-based biomarkers.