Les petits robots humanoïdes sont généralement soumis à de nombreuses imperfections : déformations et jeux mécaniques, défauts électriques et problèmes d'asservissements moteurs. L'objet de ces travaux est l'utilisation de techniques d'apprentissage pour compenser les imperfections du robot réel. L'amélioration de la précision de l'odométrie et de la stabilité de mouvements générés est étudiée. Cette thèse est fortement guidée et inspirée par la participation de l'équipe Rhoban (Rhoban Football Club) à la compétition internationale de robotique, la RoboCup. Depuis 2011, l'équipe concourt chaque année dans la ligue des petits robots humanoïdes complètement autonomes (Humanoid Kid-Size) dans un tournoi de football robotique. L'odométrie proprioceptive estime les déplacements du robot à partir de ses capteurs internes (la caméra n'est pas utilisée) alors que l'odométrie prédictive simule les déplacements engendrés par une séquence donnée d'ordres du mouvement de marche. Deux méthodes de correction sont ici proposées pour les deux odométries. La première se fonde sur une technique de régression non paramétrique (LWPR) et un système externe de capture de mouvement. La deuxième optimise (CMA-ES) un modèle de correction linéaire sans ne nécessiter aucun autre dispositif de mesure. L'odométrie proprioceptive est essentielle à la localisation du robot sur le terrain de football alors que l'odométrie prédictive permet d'entraîner hors ligne une politique de contrôle de la marche. La synthèse de mouvements très dynamiques tels que la marche ou le tir est rendue difficile par la forte contrainte de stabilité bipède et les imperfections des servomoteurs. Des mouvements de tir sont tout d'abord générés par optimisation (CMA-ES) et évalués au travers du modèle dynamique inverse du robot. Le développement d'un simulateur physique a été commencé. Le but est de réduire la distance entre le comportement réel et désiré du robot par correction des mouvements au sein du simulateur. / Small humanoid robots are often affected by many flaws : mechanical wraps and backlashes, electrical issues and motor control problems. This work is aimed at applying machine learning methods to deal with the flaws of the real robot. More precisely, improving the odometry accuracy and generated motion stability is studied. This thesis is highly guided and inspired by the participation of the Rhoban team (Rhoban Football Club) to the international RoboCup competition. Since 2011, the team has been competing each year in a soccer tournament within the fully autonomous small humanoid robots (Kid-Size) league. Proprioceptive odometry estimates the robot displacements from its internal sensors (no camera is used) whereas predictive odometry simulates the displacements created from a sequence of walk orders. Two corrective methods are proposed for the two kinds of odometries. The first one is based on a non parametric regression (LWPR) and a motion capture setup. The second one optimizes (CMA-ES) a linear corrective model without needing any external measure system. The proprioceptive odometry is essential to the localization of the robot on the soccer field. The predictive odometry is used to train a control policy for the walk motion. The generation of very dynamic motions like walking or kicking the ball is difficult due to the biped balance constraint and the many servomotor flaws. To start, kick motions are generated by optimization (CMA-ES) and evaluated based on the inverse dynamic model of the robot. The implementation of a physics simulator has been started. The objective is make the real behaviour of the robot to catch up the target trajectory by correcting the motion within the simulator.

[pt] Esta dissertação apresenta o desenvolvimento de um controle híbrido de um robô do tipo humanoide Atlas em regime de locomoção estática para a frente. Nos experimentos faz-se uso do ambiente de simulação Gazebo, que permite uma modelagem precisa do robô. O sistema desenvolvido é composto pela modelagem da mecânica do robô, incluindo as equações da dinâmica que permitem o controle das juntas por torque computado, e pela determinação das posições que as juntas devem assumir. Isto é realizado por agentes que utilizam o algoritmo de aprendizado por reforço Q-Learning aproximado para planejar a locomoção do robô. A definição do espaço de estados, que compõe cada agente, difere da cartesiana tradicional e é baseada no conceito de pontos cardeais para estabelecer as direções a serem seguidas até o objetivo e para evitar obstáculos. Esta definição permite o uso de um ambiente simulado reduzido para treinamento, fornecendo aos agentes um conhecimento prévio à aplicação no ambiente real e facilitando, em consequência, a convergência para uma ação dita ótima em poucas iterações. Utilizam-se, no total, três agentes: um para controlar o deslocamento do centro de massa enquanto as duas pernas estão apoiadas ao chão, e outros dois para manter o centro de massa dentro de uma área de tolerância de cada um dos pés na situação em que o robô estiver apoiado com apenas um dos pés no chão. O controle híbrido foi também concebido para reduzir as chances de queda do robô durante a caminhada mediante o uso de uma série de restrições, tanto pelo aprendizado por reforço como pelo modelo da cinemática do robô. A abordagem proposta permite um treinamento eficiente em poucas iterações, produz bons resultados e assegura a integridade do robô. / [en] This dissertation presents the development of a hybrid control for an Atlas humanoid robot moving forward in a static locomotion regime. The Gazebo simulation environment used in the experiments allows a precise modeling of the robot. The developed system consists of the robot mechanics modeling, including dynamical equations that allow the control of joints by computed-torque and the determination of positions the joints should take. This is accomplished by agents that make use of the approximate Q-Learning reinforcement learning algorithm to plan the robot s locomotion. The definition of the state space that makes up each agent differs from the traditional cartesian one and is based on the concept of cardinal points to establish the directions to be followed to the goal and avoid obstacles. This allows the use of a reduced simulated environment for training, providing the agents with prior knowledge to the application in a real environment and facilitating, as a result, convergence to a so-called optimal action in few iterations. Three agents are used: one to control the center of mass displacement when the two legs are poised on the floor and other two for keeping the center of mass within a tolerance range of each of the legs when only one foot is on the ground. In order to reduce the chance of the robot falling down while walking the hybrid control employs a number of constraints, both in the reinforcement learning part and in the robot kinematics model. The proposed approach allows an effective training in few iterations, achieves good results and ensures the integrity of the robot.

Samhällsutvecklingen går i en riktning där människor arbetar i allt närmare samarbete med artificiella agenter. För att detta samarbete ska vara på användarens villkor är det viktigt att förstå hur människor uppfattar och förhåller sig till dessa system. Hur dessa agenter bedöms moraliskt är en komponent i denna förståelse. Malle m.fl. (2015) utförde en av de första studierna kring hur normer och skuld appliceras på människa respektive robot. I samma artikel efterfrågades mer forskning kring vilka faktorer hos agenter som påverkar de moraliska bedömningarna. Föreliggande studie tog avstamp i denna frågeställning och avsåg att undersöka hur moralisk godtagbarhet och skuldbeläggning skiljde sig beroende på om agenten var en person, en humanoid robot eller ett autonomt intelligent system utan kropp (AIS). Ett mellangrupps-experiment (N = 119) användes för att undersöka hur agenterna bedömdes för sina beslut i tre olika moraliska dilemman. Deltagares rättfärdigaden bakom bedömningar samt medveten hållning utforskades som förklaringsmodell av skillnader. Medveten hållning avser Dennetts (1971) teori kring huruvida en agent förstås utifrån mentala egenskaper. Resultaten visade att person och robot erhöll liknande godtagbarhet för sina beslut medan AIS fick signifikant lägre snitt. Graden skuld som tillskrevs skiljde sig inte signifikant mellan agenterna. Analysen av deltagares rättfärdiganden gav indikationer på att skuldbedömningarna av de artificiella agenterna inte grundade sig i sådan information som antagits ligga till grund för denna typ av bedömningar. Flera rättfärdiganden påpekade också att det var någon annan än de artificiella agenterna som bar skulden för besluten. Vidare analyser indikerade på att deltagare höll medveten hållning mot person i störst utsträckning följt av robot och sedan AIS. Studien väcker frågor kring huruvida skuld som fenomen går att applicera på artificiella agenter och i vilken utsträckning distribuerad skuld är en faktor när artificiella agenter bedöms.

Made available in DSpace on 2014-12-17T14:55:48Z (GMT). No. of bitstreams: 1 MarceloBN.pdf: 1368278 bytes, checksum: e9f6ea9d9353cb33144a3fc036bd57dc (MD5) Previous issue date: 2005-12-20 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / This work proposes a method to localize a simple humanoid robot, without embedded sensors, using images taken from an extern camera and image processing techniques. Once the robot is localized relative to the camera, supposing we know the position of the camera relative to the world, we can compute the position of the robot relative to the world. To make the camera move in the work space, we will use another mobile robot with wheels, which has a precise locating system, and will place the camera on it. Once the humanoid is localized in the work space, we can take the necessary actions to move it. Simultaneously, we will move the camera robot, so it will take good images of the humanoid. The mainly contributions of this work are: the idea of using another mobile robot to aid the navigation of a humanoid robot without and advanced embedded electronics; chosing of the intrinsic and extrinsic calibration methods appropriated to the task, especially in the real time part; and the collaborative algorithm of simultaneous navigation of the robots / Este trabalho prop?e um m?todo para localizar um rob? human?ide simples, sem sensores embarcados, utilizando imagens obtidas por uma c?mera externa e t?cnicas de processamento de imagens. Localizando o rob? em rela??o ? c?mera, e supondo conhecida a posi??o da c?mera em rela??o ao mundo, podemos determinar a posi??o do rob? human?ide em rela??o ao mundo. Para que a posi??o da c?mera n?o seja fixa, utilizamos um outro rob? m?vel com rodas, dotado de um sistema de localiza??o preciso, sobre o qual ser? colocada a c?mera. Uma vez que o human?ide seja localizado no ambiente de trabalho, podemos tomar as a??es necess?rias para realizar a sua movimenta??o. Simultaneamente, movimentamos o rob? que cont?m a c?mera, de forma que este tenha uma boa visada do human?ide. As principais contribui??es deste trabalho s?o: a id?ia de utilizar um segundo rob? m?vel para auxiliar a movimenta??o de um rob? human?ide sem eletr?nica embarcada avan?ada; a escolha de m?todos de calibra??o dos par?metros intr?nsecos e extr?nsecos da c?mera apropriados para a aplica??o em quest?o, especialmente na parte em tempo real; e o algoritmo colaborativo de movimenta??o simult?nea dos dois rob?s

Biped robots with serial links driven by an electric motor experience problems because the motor and transmission are installed in each joint, causing the legs to become very heavy. Previous solutions involved robots using servo valves, a type of highly responsive proportional valve. However, high supply pressure is necessary to realize high responsiveness and the resulting energy losses are large. To address this problem, we proposed a hydraulic direct-drive system in which the pump controls the cylinder meter-in flow, while a proportional valve controls the meter-out flow. Furthermore, our hydraulic interlocking drive system connects two hydraulic direct-drive systems for biped humanoid robots and concentrates the pump output on one side cylinder. The meter-in flow rate of the other side cylinder is controlled by the meter-out flow rate of the cylinder on which the pump is concentrated. A comparison of the walking simulation performance with that of the conventional independent system shows that our proposed system reduces the motor output power by 24.3%. These results prove the feasibility of constructing a two-legged robot without having to incorporate highly responsive servo valves.

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Robot assisted therapy is becoming increasingly popular. Research has proven it can be of benefit to persons dealing with a variety of disorders, such as Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD), and it can also provide a source of emotional support e.g. to persons living in seniors’ residences. The advancement in technology and a decrease in cost of products related to consumer electronics, computing and communication has enabled the development of more advanced social robots at a lower cost. This brings us closer to developing such tools at a price that makes them affordable to lower income individuals and families. Currently, in several cases, intensive treatment for patients with certain disorders (to the level of becoming effective) is practically not possible through the public health system due to resource limitations and a large existing backlog. Pursuing treatment through the private sector is expensive and unattainable for those with a lower income, placing them at a disadvantage. Design and effective integration of technology, such as using social robots in treatment, reduces the cost considerably, potentially making it financially accessible to lower income individuals and families in need. The Objective of the research reported in this manuscript is to design and implement a social robot that meets the low-cost criteria, while also containing the required functions to support children with ASD. The design considered contains knowledge acquired in the past through research involving the use of various types of technology for the treatment of mental and/or emotional disabilities.