Study on Control Methodology of Compliant Manipulation Utilizing Additional Contact with Environment

制度:新 ; 報告番号:甲3297号 ; 学位の種類:博士(工学) ; 授与年月日:2011/2/25 ; 早大学位記番号:新560

Simplified Motion Control of a Vehicle manipulator for the Coordinated Mobile Manipulation

This paper considers a resolved kinematic motion control approach for controlling a spatial serial manipulator arm that is mounted on a vehicle base. The end-effector’s motion of the manipulator is controlled by a novel kinematic control scheme, and the performance is compared with the well-known operational-space control scheme. The proposed control scheme aims to track the given operational-space (end-effector) motion trajectory with the help of resolved configuration-space motion without using the Jacobian matrix inverse or pseudo inverse. The experimental testing results show that the suggested control scheme is as close to the conventional operational-space kinematic control scheme

Progress and Development Trend of Space Intelligent Robot Technology

Since space intelligent robots are not restricted by physiological conditions, it is an attractive choice for the development of automation technology to use them for space exploration and utilization. It is currently the key development direction of the major space powers over the world. This paper first investigates the robotic manipulators and humanoid robot systems for space station applications and reviews theories and methods for robots to achieve large-range stable motion and intelligent dexterous manipulation. Then, the intelligent robot systems for on-orbit satellite maintenance are reviewed, and the related technologies of multirobot collaboration are analyzed. Finally, we investigate the intelligent robot systems for on-orbit assembly of large-scale spatial structures and summarize the technologies of modular assembly and on-orbit manufacture. Overall, this paper reviews the technological progress and development trends of space robots, which provides a good reference for further technical research in this field

Scaled Autonomy for Networked Humanoids

Humanoid robots have been developed with the intention of aiding in environments designed for humans. As such, the control of humanoid morphology and effectiveness of human robot interaction form the two principal research issues for deploying these robots in the real world. In this thesis work, the issue of humanoid control is coupled with human robot interaction under the framework of scaled autonomy, where the human and robot exchange levels of control depending on the environment and task at hand. This scaled autonomy is approached with control algorithms for reactive stabilization of human commands and planned trajectories that encode semantically meaningful motion preferences in a sequential convex optimization framework. The control and planning algorithms have been extensively tested in the field for robustness and system verification. The RoboCup competition provides a benchmark competition for autonomous agents that are trained with a human supervisor. The kid-sized and adult-sized humanoid robots coordinate over a noisy network in a known environment with adversarial opponents, and the software and routines in this work allowed for five consecutive championships. Furthermore, the motion planning and user interfaces developed in the work have been tested in the noisy network of the DARPA Robotics Challenge (DRC) Trials and Finals in an unknown environment. Overall, the ability to extend simplified locomotion models to aid in semi-autonomous manipulation allows untrained humans to operate complex, high dimensional robots. This represents another step in the path to deploying humanoids in the real world, based on the low dimensional motion abstractions and proven performance in real world tasks like RoboCup and the DRC

Generating whole body movements for dynamics anthropomorphic systems under constraints

Cette thèse étudie la question de la génération de mouvements corps-complet pour des systèmes anthropomorphes. Elle considère le problème de la modélisation et de la commande en abordant la question difficile de la génération de mouvements ressemblant à ceux de l'homme. En premier lieu, un modèle dynamique du robot humanoïde HRP-2 est élaboré à partir de l'algorithme récursif de Newton-Euler pour les vecteurs spatiaux. Un nouveau schéma de commande dynamique est ensuite développé, en utilisant une cascade de programmes quadratiques (QP) optimisant des fonctions coûts et calculant les couples de commande en satisfaisant des contraintes d'égalité et d'inégalité. La cascade de problèmes quadratiques est définie par une pile de tâches associée à un ordre de priorité. Nous proposons ensuite une formulation unifiée des contraintes de contacts planaires et nous montrons que la méthode proposée permet de prendre en compte plusieurs contacts non coplanaires et généralise la contrainte usuelle du ZMP dans le cas où seulement les pieds sont en contact avec le sol. Nous relions ensuite les algorithmes de génération de mouvement issus de la robotique aux outils de capture du mouvement humain en développant une méthode originale de génération de mouvement visant à imiter le mouvement humain. Cette méthode est basée sur le recalage des données capturées et l'édition du mouvement en utilisant le solveur hiérarchique précédemment introduit et la définition de tâches et de contraintes dynamiques. Cette méthode originale permet d'ajuster un mouvement humain capturé pour le reproduire fidèlement sur un humanoïde en respectant sa propre dynamique. Enfin, dans le but de simuler des mouvements qui ressemblent à ceux de l'homme, nous développons un modèle anthropomorphe ayant un nombre de degrés de liberté supérieur à celui du robot humanoïde HRP2. Le solveur générique est utilisé pour simuler le mouvement sur ce nouveau modèle. Une série de tâches est définie pour décrire un scénario joué par un humain. Nous montrons, par une simple analyse qualitative du mouvement, que la prise en compte du modèle dynamique permet d'accroitre naturellement le réalisme 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