Contribution à la planification de mouvement pour robots humanoïdes

cette thèse porte sur des algorithmes de contrôle et de planification de mouvements pour les robots humanoïdes. Le grand nombre de paramètres caractérisant ces systèmes a conduit au développement de méthodes numériques, d'abord appliquées aux bras manipulateurs et récemment adaptées pour les structures plus complexes. On relève particulièrement les formalismes de commande cinématique et dynamique par priorité qui permettent de produire un mouvement selon une hiérarchie préétablie des tâches. Au cours de ce travail, nous avons identifié le besoin d'étendre ce formalisme afin de tenir compte de contraintes unilatérales. Nous nous sommes par ailleurs intéressés à la planification de la locomotion en fonction des tâches. Nous proposons une modélisation jointe du robot et de sa trajectoire de marche comme une structure articulée unique saisissant à la fois les degrés de liberté actionnés (articulations motorisées du robot) et non actionnés (positionnement absolu dans l'espace). L'ensemble de ces algorithmes, qui seront longuement illustrés, ont été implémentés au sein du projet HPP (Humanoid Path Planner) et validés sur le robot humanoïde HRP-2.this thesis is related to motion control and planning algorithms for humanoid robots. For such highly-parameterized systems, numerical methods are well adapted and have thus been the enter of increasing attention in the recent years. Among the prominent numerical schemes, we recognized the prioritized inverse kinematics and dynamics frameworks to hold key features to plan motion for humanoid robots, such as the possibility to control the motion while enforcing a strict priority order among tasks. We have, however, identified a lack of support of strict priority enforcement when inequality constraints are to be accounted for in the numerical schemes and we were successful in proposing a solution to this shortcoming. We also considered the problem of planning bipedal locomotion according to any given tasks. We proposed to model this problem as an inverse kinematics problem, by considering the kinematic structure of the robot and its walk path as a single unified structure that captures both the degrees of freedom of the robot which are actuated (motorized joints) and those which are not (position and orientation in space). The presented algorithms, which will be abundantly illustrated, have been implemented within the HPP (Humanoid Path Planner) project and validated on the humanoid robot HRP-2

Task driving motion control for humanoid robots

TOULOUSE3-BU Sciences (315552104) / SudocSudocFranceF

Kinematic control of redundant manipulators: generalizing the task priority framework to inequality tasks

International audienceThe redundant mechanical systems like humanoid robots are designed to fulfill multiple tasks at a time. A task, in velocity-resolved inverse kinematics, is a desired value for a function of the robot configuration that can be regulated with an Ordinary Differential Equation. When facing simultaneous tasks, the corresponding equations can be grouped in a single system, or better, sorted in priority and solved each in the solutions set of higher priority tasks. This elegant framework for hierarchical task regulation has been implemented as a sequence of Least Squares problems. Its limitation lies in the handling of inequality constraints, which are usually transformed into more restrictive equality constraints through potential fields. In this paper, we propose a new prioritized task regulation framework based on a sequence of quadratic programs (QP) that removes the limitation. At the basis of the proposed algorithm is a study of the optimal sets resulting from the sequence of QPs. The algorithm is implemented and illustrated in simulation on the humanoid robot HRP-2

Prioritizing linear equality and inequality systems: application to local motion planning for redundant robots

International audienceWe present a novel method for prioritizing both linear equality and inequality systems and provide one algo- rithm for its resolution. This algorithm can be summarized as a sequence of optimal resolutions for each linear system following their priority order. We propose an optimality criterion that is adapted to linear inequality systems and characterize the result- ing optimal sets at every priority level. We have successfully applied our method to plan local motions for the humanoid robot HPR-2. We will demonstrate the validity of the method using an original scenario where linear inequality constraints are solved at lower priority than equality constraints

Regrasp planning for pivoting manipulation by a humanoid robot

International audienceA method of regrasp planning for humanoid robot manipulation is proposed. We adopt pivoting manipulation for the humanoid robot to move a bulky object without lifting in a stable and dexterous manner. In order to carry the object to a desired place, the humanoid should sometimes move through narrow areas surrounded by obstacles. We propose a roadmap multiplexing planning to allow the robot to leave the object near narrow places and to regrasp it from another position to continue carrying. We utilize visibility probabilistic roadmap (PRM) method as a preprocessing to capture the critical configurations for regrasping. Then a diffusion method is employed to plan the overall manipulation path including regrasping. The proposed method is verified through planning simulation including whole-body motions