9,087 research outputs found

    Generation of dynamic motion for anthropomorphic systems under prioritized equality and inequality constraints

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    In this paper, we propose a solution to compute full-dynamic motions for a humanoid robot, accounting for various kinds of constraints such as dynamic balance or joint limits. As a first step, we propose a unification of task-based control schemes, in inverse kinematics or inverse dynamics. Based on this unification, we generalize the cascade of quadratic programs that were developed for inverse kinematics only. Then, we apply the solution to generate, in simulation, wholebody motions for a humanoid robot in unilateral contact with the ground, while ensuring the dynamic balance on a non horizontal surface

    Dynamic whole-body motion generation under rigid contacts and other unilateral constraints

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    The most widely used technique for generating wholebody motions on a humanoid robot accounting for various tasks and constraints is inverse kinematics. Based on the task-function approach, this class of methods enables the coordination of robot movements to execute several tasks in parallel and account for the sensor feedback in real time, thanks to the low computation cost. To some extent, it also enables us to deal with some of the robot constraints (e.g., joint limits or visibility) and manage the quasi-static balance of the robot. In order to fully use the whole range of possible motions, this paper proposes extending the task-function approach to handle the full dynamics of the robot multibody along with any constraint written as equality or inequality of the state and control variables. The definition of multiple objectives is made possible by ordering them inside a strict hierarchy. Several models of contact with the environment can be implemented in the framework. We propose a reduced formulation of the multiple rigid planar contact that keeps a low computation cost. The efficiency of this approach is illustrated by presenting several multicontact dynamic motions in simulation and on the real HRP-2 robot

    Generating whole body movements for dynamics anthropomorphic systems under constraints

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    Cette thĂšse Ă©tudie la question de la gĂ©nĂ©ration de mouvements corps-complet pour des systĂšmes anthropomorphes. Elle considĂšre le problĂšme de la modĂ©lisation et de la commande en abordant la question difficile de la gĂ©nĂ©ration de mouvements ressemblant Ă  ceux de l'homme. En premier lieu, un modĂšle dynamique du robot humanoĂŻde HRP-2 est Ă©laborĂ© Ă  partir de l'algorithme rĂ©cursif de Newton-Euler pour les vecteurs spatiaux. Un nouveau schĂ©ma de commande dynamique est ensuite dĂ©veloppĂ©, en utilisant une cascade de programmes quadratiques (QP) optimisant des fonctions coĂ»ts et calculant les couples de commande en satisfaisant des contraintes d'Ă©galitĂ© et d'inĂ©galitĂ©. La cascade de problĂšmes quadratiques est dĂ©finie par une pile de tĂąches associĂ©e Ă  un ordre de prioritĂ©. Nous proposons ensuite une formulation unifiĂ©e des contraintes de contacts planaires et nous montrons que la mĂ©thode proposĂ©e permet de prendre en compte plusieurs contacts non coplanaires et gĂ©nĂ©ralise la contrainte usuelle du ZMP dans le cas oĂč seulement les pieds sont en contact avec le sol. Nous relions ensuite les algorithmes de gĂ©nĂ©ration de mouvement issus de la robotique aux outils de capture du mouvement humain en dĂ©veloppant une mĂ©thode originale de gĂ©nĂ©ration de mouvement visant Ă  imiter le mouvement humain. Cette mĂ©thode est basĂ©e sur le recalage des donnĂ©es capturĂ©es et l'Ă©dition du mouvement en utilisant le solveur hiĂ©rarchique prĂ©cĂ©demment introduit et la dĂ©finition de tĂąches et de contraintes dynamiques. Cette mĂ©thode originale permet d'ajuster un mouvement humain capturĂ© pour le reproduire fidĂšlement sur un humanoĂŻde en respectant sa propre dynamique. Enfin, dans le but de simuler des mouvements qui ressemblent Ă  ceux de l'homme, nous dĂ©veloppons un modĂšle anthropomorphe ayant un nombre de degrĂ©s de libertĂ© supĂ©rieur Ă  celui du robot humanoĂŻde HRP2. Le solveur gĂ©nĂ©rique est utilisĂ© pour simuler le mouvement sur ce nouveau modĂšle. Une sĂ©rie de tĂąches est dĂ©finie pour dĂ©crire un scĂ©nario jouĂ© par un humain. Nous montrons, par une simple analyse qualitative du mouvement, que la prise en compte du modĂšle dynamique permet d'accroitre naturellement le rĂ©alisme du mouvement.This thesis studies the question of whole body motion generation for anthropomorphic systems. Within this work, the problem of modeling and control is considered by addressing the difficult issue of generating human-like motion. First, a dynamic model of the humanoid robot HRP-2 is elaborated based on the recursive Newton-Euler algorithm for spatial vectors. A new dynamic control scheme is then developed adopting a cascade of quadratic programs (QP) optimizing the cost functions and computing the torque control while satisfying equality and inequality constraints. The cascade of the quadratic programs is defined by a stack of tasks associated to a priority order. Next, we propose a unified formulation of the planar contact constraints, and we demonstrate that the proposed method allows taking into account multiple non coplanar contacts and generalizes the common ZMP constraint when only the feet are in contact with the ground. Then, we link the algorithms of motion generation resulting from robotics to the human motion capture tools by developing an original method of motion generation aiming at the imitation of the human motion. This method is based on the reshaping of the captured data and the motion editing by using the hierarchical solver previously introduced and the definition of dynamic tasks and constraints. This original method allows adjusting a captured human motion in order to reliably reproduce it on a humanoid while respecting its own dynamics. Finally, in order to simulate movements resembling to those of humans, we develop an anthropomorphic model with higher number of degrees of freedom than the one of HRP-2. The generic solver is used to simulate motion on this new model. A sequence of tasks is defined to describe a scenario played by a human. By a simple qualitative analysis of motion, we demonstrate that taking into account the dynamics provides a natural way to generate human-like movements
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