19 research outputs found
Télé-opération Corps Complet de Robots Humanoïdes
This thesis aims to investigate systems and tools for teleoperating a humanoid robot. Robotteleoperation is crucial to send and control robots in environments that are dangerous or inaccessiblefor humans (e.g., disaster response scenarios, contaminated environments, or extraterrestrialsites). The term teleoperation most commonly refers to direct and continuous control of a robot.In this case, the human operator guides the motion of the robot with her/his own physical motionor through some physical input device. One of the main challenges is to control the robot in a waythat guarantees its dynamical balance while trying to follow the human references. In addition,the human operator needs some feedback about the state of the robot and its work site through remotesensors in order to comprehend the situation or feel physically present at the site, producingeffective robot behaviors. Complications arise when the communication network is non-ideal. Inthis case the commands from human to robot together with the feedback from robot to human canbe delayed. These delays can be very disturbing for the human operator, who cannot teleoperatetheir robot avatar in an effective way.Another crucial point to consider when setting up a teleoperation system is the large numberof parameters that have to be tuned to effectively control the teleoperated robots. Machinelearning approaches and stochastic optimizers can be used to automate the learning of some of theparameters.In this thesis, we proposed a teleoperation system that has been tested on the humanoid robotiCub. We used an inertial-technology-based motion capture suit as input device to control thehumanoid and a virtual reality headset connected to the robot cameras to get some visual feedback.We first translated the human movements into equivalent robot ones by developping a motionretargeting approach that achieves human-likeness while trying to ensure the feasibility of thetransferred motion. We then implemented a whole-body controller to enable the robot to trackthe retargeted human motion. The controller has been later optimized in simulation to achieve agood tracking of the whole-body reference movements, by recurring to a multi-objective stochasticoptimizer, which allowed us to find robust solutions working on the real robot in few trials.To teleoperate walking motions, we implemented a higher-level teleoperation mode in whichthe user can use a joystick to send reference commands to the robot. We integrated this setting inthe teleoperation system, which allows the user to switch between the two different modes.A major problem preventing the deployment of such systems in real applications is the presenceof communication delays between the human input and the feedback from the robot: evena few hundred milliseconds of delay can irremediably disturb the operator, let alone a few seconds.To overcome these delays, we introduced a system in which a humanoid robot executescommands before it actually receives them, so that the visual feedback appears to be synchronizedto the operator, whereas the robot executed the commands in the past. To do so, the robot continuouslypredicts future commands by querying a machine learning model that is trained on pasttrajectories and conditioned on the last received commands.Cette thĂšse vise Ă Ă©tudier des systĂšmes et des outils pour la tĂ©lĂ©-opĂ©ration dâun robot humanoĂŻde.La tĂ©lĂ©opĂ©ration de robots est cruciale pour envoyer et contrĂŽler les robots dans des environnementsdangereux ou inaccessibles pour les humains (par exemple, des scĂ©narios dâinterventionen cas de catastrophe, des environnements contaminĂ©s ou des sites extraterrestres). Le terme tĂ©lĂ©opĂ©rationdĂ©signe le plus souvent le contrĂŽle direct et continu dâun robot. Dans ce cas, lâopĂ©rateurhumain guide le mouvement du robot avec son propre mouvement physique ou via un dispositifde contrĂŽle. Lâun des principaux dĂ©fis est de contrĂŽler le robot de maniĂšre Ă garantir son Ă©quilibredynamique tout en essayant de suivre les rĂ©fĂ©rences humaines. De plus, lâopĂ©rateur humain abesoin dâun retour dâinformation sur lâĂ©tat du robot et de son site via des capteurs Ă distance afindâapprĂ©hender la situation ou de se sentir physiquement prĂ©sent sur le site, produisant des comportementsde robot efficaces. Des complications surviennent lorsque le rĂ©seau de communicationnâest pas idĂ©al. Dans ce cas, les commandes de lâhomme au robot ainsi que la rĂ©troaction du robotĂ lâhomme peuvent ĂȘtre retardĂ©es. Ces dĂ©lais peuvent ĂȘtre trĂšs gĂȘnants pour lâopĂ©rateur humain,qui ne peut pas tĂ©lĂ©-opĂ©rer efficacement son avatar robotique.Un autre point crucial Ă considĂ©rer lors de la mise en place dâun systĂšme de tĂ©lĂ©-opĂ©rationest le grand nombre de paramĂštres qui doivent ĂȘtre rĂ©glĂ©s pour contrĂŽler efficacement les robotstĂ©lĂ©-opĂ©rĂ©s. Des approches dâapprentissage automatique et des optimiseurs stochastiques peuventĂȘtre utilisĂ©s pour automatiser lâapprentissage de certains paramĂštres.Dans cette thĂšse, nous avons proposĂ© un systĂšme de tĂ©lĂ©-opĂ©ration qui a Ă©tĂ© testĂ© sur le robothumanoĂŻde iCub. Nous avons utilisĂ© une combinaison de capture de mouvement basĂ©e sur latechnologie inertielle comme pĂ©riphĂ©rique de contrĂŽle pour lâhumanoĂŻde et un casque de rĂ©alitĂ©virtuelle connectĂ© aux camĂ©ras du robot pour obtenir un retour visuel. Nous avons dâabord traduitles mouvements humains en mouvements robotiques Ă©quivalents en dĂ©veloppant une approchede retargeting de mouvement qui atteint la ressemblance humaine tout en essayant dâassurer lafaisabilitĂ© du mouvement transfĂ©rĂ©. Nous avons ensuite implĂ©mentĂ© un contrĂŽleur du corps entierpour permettre au robot de suivre le mouvement humain reciblĂ©. Le contrĂŽleur a ensuite Ă©tĂ©optimisĂ© en simulation pour obtenir un bon suivi des mouvements de rĂ©fĂ©rence du corps entier,en recourant Ă un optimiseur stochastique multi-objectifs, ce qui nous a permis de trouver dessolutions robustes fonctionnant sur le robot rĂ©el en quelques essais.Pour tĂ©lĂ©-opĂ©rer les mouvements de marche, nous avons implĂ©mentĂ© un mode de tĂ©lĂ©-opĂ©rationde niveau supĂ©rieur dans lequel lâutilisateur peut utiliser un joystick pour envoyer des commandesde rĂ©fĂ©rence au robot. Nous avons intĂ©grĂ© ce paramĂštre dans le systĂšme de tĂ©lĂ©-opĂ©ration, ce quipermet Ă lâutilisateur de basculer entre les deux modes diffĂ©rents.Un problĂšme majeur empĂȘchant le dĂ©ploiement de tels systĂšmes dans des applications rĂ©ellesest la prĂ©sence de retards de communication entre lâentrĂ©e humaine et le retour du robot: mĂȘmequelques centaines de millisecondes de retard peuvent irrĂ©mĂ©diablement perturber lâopĂ©rateur,encore plus quelques secondes. Pour surmonter ces retards, nous avons introduit un systĂšme danslequel un robot humanoĂŻde exĂ©cute des commandes avant de les recevoir, de sorte que le retourvisuel semble ĂȘtre synchronisĂ© avec lâopĂ©rateur, alors que le robot exĂ©cutait les commandes dansle passĂ©. Pour ce faire, le robot prĂ©dit en permanence les commandes futures en interrogeant unmodĂšle dâapprentissage automatique formĂ© sur les trajectoires passĂ©es et conditionnĂ© aux derniĂšrescommandes reçues
Teleprogramming: Overcoming Communication Delays in Remote Manipulation (Dissertation Proposal)
Modern industrial processes (nuclear, chemical industry), public service needs (firefighting, rescuing), and research interests (undersea, outer space exploration) have established a clear need to perform work remotely. Whereas a purely autonomous manipulative capability would solve the problem, its realization is beyond the state of the art in robotics [Stark et al.,1988]. Some of the problems plaguing the development of autonomous systems are: a) anticipation, detection, and correction of the multitude of possible error conditions arising during task execution, b) development of general strategy planning techniques transcending any particular limited task domain, c) providing the robot system with real-time adaptive behavior to accommodate changes in the remote environment, d) allowing for on-line learning and performance improvement through experience , etc. The classical approach to tackle some of these problems has been to introduce problem solvers and expert systems as part of the remote robot workcell control system. However, such systems tend to be limited in scope (to remain intellectually and implementationally manageable), too slow to be useful in real-time robot task execution, and generally fail to adequately represent and model the complexities of the real world environment. These problems become particularly severe when only partial information about the remote environment is available
GPU Computing for Cognitive Robotics
This thesis presents the first investigation of the impact of GPU
computing on cognitive robotics by providing a series of novel experiments in
the area of action and language acquisition in humanoid robots and computer
vision. Cognitive robotics is concerned with endowing robots with high-level
cognitive capabilities to enable the achievement of complex goals in complex
environments. Reaching the ultimate goal of developing cognitive robots will
require tremendous amounts of computational power, which was until
recently provided mostly by standard CPU processors. CPU cores are
optimised for serial code execution at the expense of parallel execution, which
renders them relatively inefficient when it comes to high-performance
computing applications. The ever-increasing market demand for
high-performance, real-time 3D graphics has evolved the GPU into a highly
parallel, multithreaded, many-core processor extraordinary computational
power and very high memory bandwidth. These vast computational resources
of modern GPUs can now be used by the most of the cognitive robotics models
as they tend to be inherently parallel. Various interesting and insightful
cognitive models were developed and addressed important scientific questions
concerning action-language acquisition and computer vision. While they have
provided us with important scientific insights, their complexity and
application has not improved much over the last years. The experimental
tasks as well as the scale of these models are often minimised to avoid
excessive training times that grow exponentially with the number of neurons
and the training data. This impedes further progress and development of
complex neurocontrollers that would be able to take the cognitive robotics
research a step closer to reaching the ultimate goal of creating intelligent
machines. This thesis presents several cases where the application of the GPU
computing on cognitive robotics algorithms resulted in the development of
large-scale neurocontrollers of previously unseen complexity enabling the
conducting of the novel experiments described herein.European Commission Seventh Framework
Programm
Office of Exploration: Exploration studies technical report. Volume 2: Studies approach and results
The NASA Office of Exploration has been tasked with defining and recommending alternatives for an early 1990's national decision on a focused program of human exploration of the solar system. The Mission Analysis and System Engineering (MASE) group, which is managed by the Exploration Studies Office at the Johnson Space Center, is responsible for coordinating the technical studies necessary for accomplishing such a task. This technical report describes the process that has been developed in a case study approach. The four case studies that were developed in FY88 include: (1) human expedition to Phobos; (2) human expeditions to Mars; (3) lunar observatory; and (4) lunar outpost to early Mars evolution. The final outcome of this effort is a set of programmatic and technical conclusions and recommendations for the following year's work. Volume 2 describes the case study process, the technical results of each of the case studies, and opportunities for additional study. Included in the discussion of each case study is a description of the mission key features and profile. Mission definition and manifesting are detailed, followed by a description of the mission architecture and infrastructure. Systems concepts for the required orbital nodes, transportation systems, and planetary surface systems are discussed. Prerequisite implementation plans resulting from the synthesized case studies are described and in-depth assessments are presented