Développement et expérimentation d'algorithmes de réorientation pour un robot sériel en chute libre

Ce mémoire présente 2 types de méthodes pour effectuer la réorientation d’un robot sériel en chute libre en utilisant les mouvements internes de celui-ci. Ces mouvements sont prescrits à partir d’algorithmes de planification de trajectoire basés sur le modèle dynamique du robot. La première méthode tente de réorienter le robot en appliquant une technique d’optimisation locale fonctionnant avec une fonction potentielle décrivant l’orientation du système, et la deuxième méthode applique des fonctions sinusoïdales aux articulations pour réorienter le robot. Pour tester les performances des méthodes en simulation, on tente de réorienter le robot pour une configuration initiale et finale identiques où toutes les membrures sont alignées mais avec le robot ayant complété une rotation de 180 degrés sur lui-même. Afin de comparer les résultats obtenus avec la réalité, un prototype de robot sériel plan flottant possédant trois membrures et deux liaisons rotoïdes est construit. Les expérimentations effectuées montrent que le prototype est capable d’atteindre les réorientations prescrites si peu de perturbations extérieures sont présentes et ce, même si le contrôle de l’orientation est effectué en boucle ouverte.

Multirobot Tethering for Localization and Control

Particle filtering has proven to be an effective localization method for wheeled autonomous vehicles. For a given map, a sensor model, and observations, occasions arise where the vehicle could equally likely be in many locations of the map. Because particle filtering algorithms may generate low confidence pose estimates under these conditions, more robust localization strategies are required to produce reliable pose estimates. This becomes more critical if the state estimate is an integral part of system control. We investigate the use of particle filter estimation techniques on a hovercraft vehicle. The marginally stable dynamics of a hovercraft require reliable state estimates for proper stability and control. We use the Monte Carlo localization method, which implements a particle filter in a recursive state estimate algorithm. An H-infinity controller, designed to accommodate the latency inherent in our state estimation, provides stability and controllability to the hovercraft. In order to eliminate the low confidence estimates produced in certain environments, a multirobot system is designed to introduce mobile environment features. By tracking and controlling the secondary robot, we can position the mobile feature throughout the environment to ensure a high confidence estimate, thus maintaining stability in the system. A laser rangefinder is the sensor the hovercraft uses to track the secondary robot, observe the environment, and facilitate successful localization and stability in motion.

Localization of a mobile robot based on odometry and natural landmarks using extended kalman filter

SANTANA, André M.; SOUZA, Anderson A. S.; BRITTO, Ricardo S.; ALSINA, Pablo J.; MEDEIROS, Adelardo A. D. Localization of a mobile robot based on odometry and natural landmarks using extended Kalman Filter. In: INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, 5., 2008, Funchal, Portugal. Proceedings... Funchal, Portugal: ICINCO, 2008.

ENABLING HARDWARE TECHNOLOGIES FOR AUTONOMY IN TINY ROBOTS: CONTROL, INTEGRATION, ACTUATION

The last two decades have seen many exciting examples of tiny robots from a few cm3 to less than one cm3. Although individually limited, a large group of these robots has the potential to work cooperatively and accomplish complex tasks. Two examples from nature that exhibit this type of cooperation are ant and bee colonies. They have the potential to assist in applications like search and rescue, military scouting, infrastructure and equipment monitoring, nano-manufacture, and possibly medicine. Most of these applications require the high level of autonomy that has been demonstrated by large robotic platforms, such as the iRobot and Honda ASIMO. However, when robot size shrinks down, current approaches to achieve the necessary functions are no longer valid. This work focused on challenges associated with the electronics and fabrication. We addressed three major technical hurdles inherent to current approaches: 1) difficulty of compact integration; 2) need for real-time and power-efficient computations; 3) unavailability of commercial tiny actuators and motion mechanisms. The aim of this work was to provide enabling hardware technologies to achieve autonomy in tiny robots. We proposed a decentralized application-specific integrated circuit (ASIC) where each component is responsible for its own operation and autonomy to the greatest extent possible. The ASIC consists of electronics modules for the fundamental functions required to fulfill the desired autonomy: actuation, control, power supply, and sensing. The actuators and mechanisms could potentially be post-fabricated on the ASIC directly. This design makes for a modular architecture. The following components were shown to work in physical implementations or simulations: 1) a tunable motion controller for ultralow frequency actuation; 2) a nonvolatile memory and programming circuit to achieve automatic and one-time programming; 3) a high-voltage circuit with the highest reported breakdown voltage in standard 0.5 μm CMOS; 4) thermal actuators fabricated using CMOS compatible process; 5) a low-power mixed-signal computational architecture for robotic dynamics simulator; 6) a frequency-boost technique to achieve low jitter in ring oscillators. These contributions will be generally enabling for other systems with strict size and power constraints such as wireless sensor nodes.

Integración de Arbotix, Raspberry Pi y motores Dynamixel Ax-12+ para un robot humanoide que busca y patea pelotas

En este artículo se presenta a DeBuPa (Detección Búsqueda Pateo) un humanoide de tamaño pequeño (38 cm de alto) construido con las piezas del kit Bioloid. Del kit se ha excluido la tarjeta CM-510 para sustituirla por la tarjeta controladora Arbotix, que será la que controle los 16 motores Dynamixel Ax-12+ (para mover al robot) y 2 servomotores analógicos (para mover la cámara). Además se ha agregado un mini computador Raspberry Pi, con su cámara, para que el robot pueda detectar y seguir la pelota de forma autónoma. Todos estos componentes deben ser coordinados para que se logre cumplir la tarea de detectar, seguir y patear la pelota. Por ello se hace necesaria la comunicación entre la Arbotix y la Raspberry Pi. La herramienta empleada para ello es el framework ROS (Robot Operating System). En la Raspberry Pi se usa el lenguaje C++ y se ejecuta un solo programa encargado de captar la imagen de la cámara, filtrar y procesar para encontrar la pelota, tomar la decisión de la acción a ejecutar y hacer la petición a la Arbotix para que dé la orden a los motores de ejecutar el movimiento. Para captar la imagen de la cámara se ha utilizado la librería RasPiCam CV. Para filtrar y procesar la imagen se ha usado las librerías de OpenCV. La Arbotix, además de controlar los motores, se encarga de monitorizar que el robot se encuentre balanceado, para ello usa el sensor Gyro de Robotis. Si detecta un desbalance de un cierto tamaño puede saber si se ha caído y levantarse.

Mimicking the behaviour of idiotypic AIS robot controllers using probabilistic systems

Previous work has shown that robot navigation systems that employ an architecture based upon the idiotypic network theory of the immune system have an advantage over control techniques that rely on reinforcement learning only. This is thought to be a result of intelligent behaviour selection on the part of the idiotypic robot. In this paper an attempt is made to imitate idiotypic dynamics by creating controllers that use reinforcement with a number of different probabilistic schemes to select robot behaviour. The aims are to show that the idiotypic system is not merely performing some kind of periodic random behaviour selection, and to try to gain further insight into the processes that govern the idiotypic mechanism. Trials are carried out using simulated Pioneer robots that undertake navigation exercises. Results show that a scheme that boosts the probability of selecting highly-ranked alternative behaviours to 50% during stall conditions comes closest to achieving the properties of the idiotypic system, but remains unable to match it in terms of all round performance.

Control para sistemas LPV basado en la parametrización de controladores estabilizantes

Este trabajo se enfoca en el estudio del control de sistemas Multi-Entrada Multi-Salida (MIMO) Lineales con Parámetros Variantes en el Tiempo (LPV). Los parámetros son medibles y permanecen dentro de cotas conocidas. El control por retroalimentación de salida garantiza estabilidad cuadrática (QS) y desempeño, mediante el Teorema de los vértices y el Lema de Cota Real (BRL). Se proponen condiciones para que el sistema retroalimentado sea convexo cuando se utilizan controladores estabilizantes en cada vértice. El controlador LPV resulta de la interpolación de estos controladores, y se estudia la relación entre la estabilidad y el desempeño del control de los vértices, y la estabilidad y desempeño del sistema LPV. Además, se da una forma explícita del parámetro libre de la Parametrización de Todos los Controladores Estabilizantes (PTCE) que resuelve un criterio de sensibilidad mezclada cuando se tiene un modelo de incertidumbre aditivo a la salida. Los resultados se aplican a un robot planar rotacional de dos grados de libertad, a un motor de CD y a un sistema de dos masas.

CLARK - Smart Clinic Assistant Robot for CGA

En esta presentación se exponen la arquitectura general y el estado actual de desarrollo del sistema CLARK. Dicho sistema tiene como objetivo el despliegue de un asistente robótico para ayudar a un médico en la realización de procedimientos CGA (Comprehensive Geriatric Assessment), de forma que ciertas tareas, tales como la realización de cuestionarios o pruebas de movimiento, puedan ser realizadas por el robot de forma paralela al resto del procedimiento CGA, aumentando así su eficiencia.

A second order control-volume finite-element least-squares strategy for simulating diffusion in strongly anisotropic media

An unstructured mesh �nite volume discretisation method for simulating di�usion in anisotropic media in two-dimensional space is discussed. This technique is considered as an extension of the fully implicit hybrid control-volume �nite-element method and it retains the local continuity of the ux at the control volume faces. A least squares function recon- struction technique together with a new ux decomposition strategy is used to obtain an accurate ux approximation at the control volume face, ensuring that the overall accuracy of the spatial discretisation maintains second order. This paper highlights that the new technique coincides with the traditional shape function technique when the correction term is neglected and that it signi�cantly increases the accuracy of the previous linear scheme on coarse meshes when applied to media that exhibit very strong to extreme anisotropy ratios. It is concluded that the method can be used on both regular and irregular meshes, and appears independent of the mesh quality.