Kinematics for Combined Quasi-Static Force and Motion Control in Multi-Limbed Robots

This paper considers how a multi-limbed robot can carry out manipulation tasks involving simultaneous and compatible end-effector velocity and force goals, while also maintaining quasi-static stance stability. The formulation marries a local optimization process with an assumption of a compliant model of the environment. For purposes of illustration, we first develop the formulation for a single fixed based manipulator arm. Some of the basic kinematic variables we previously introduced for multi-limbed robot mechanism analysis in [1] are extended to accommodate this new formulation. Using these extensions, we provide a novel definition for static equilibrium of multi-limbed robot with actuator limits, and provide general conditions that guarantee the ability to apply arbitrary end-effector forces. Using these extended definitions, we present the local optimization problem and its solution for combined manipulation and stance. We also develop, using the theory of strong alternatives, a new definition and a computable test for quasi-static stance feasibility in the presence of manipulation forces. Simulations illustrate the concepts and method

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