Planification de mouvements et manipulation d'objets par des torses humanoïdes

L’apparition de robots de service de plus en plus complexes ouvre de nouvelles perspectives quant aux tâches de manipulation d’objets. Malgré les progrès récents des techniques de planification de mouvement, peu d'entre elles s'intéressent directement à des systèmes multi-bras comme les torses humanoïdes. Notre contribution à travers cette thèse porte sur trois aspects. Nous proposons une technique de planification de mouvement performante basée sur la coordination des mouvements du système multi-bras. Elle exploite au mieux la structure du système en la divisant en parties élémentaires dont les mouvements sont planifiés indépendamment du reste du système. La fusion des différents réseaux élémentaires générés est ensuite réalisée dans le but d’obtenir un graphe prenant en compte le robot tout entier. Une seconde contribution porte sur l'extension des méthodes de planification pour des robots présentant des chaînes cinématiques fermées. Ces boucles cinématiques apparaissent dans le système lorsque, par exemple, le torse humanoïde saisit un objet avec plusieurs bras. Cette méthode traite explicitement les configurations singulières des manipulateurs, offrant ainsi une meilleure maniabilité de l’objet. Finalement, nous proposons deux approches pour la planification de tâches de manipulation d'objets par un torse humanoïde. La première concerne la résolution d’une tâche de prise et pose d'objets par un torse humanoïde à deux bras dans le cas où les contraintes imposées par la tâche nécessitent le passage par une double prise afin de transférer l'objet d'une main à l'autre. La seconde porte sur la résolution du même type de tâche par un manipulateur mobile. La thèse, effectuée dans le cadre du projet européen Phriends, présente les résultats d'expérimentations réalisées sur le robot Justin, démonstrateur du projet. ABSTRACT : The emergence of new more and more complex service robots opens new research fields on objet manipulation. Despite the recent progresses in motion planning techniques, few of them deal directly with multi-arm systems like humanoid torsos. Our contribution through this thesis focuses on three aspects. We present an efficient motion planning technique based on the multi-arm system motion coordination. It takes advantage of the system's structure by dividing it into elementary parts of which movements are planned independently of the rest of the system. Generated elementary networks are then fused to obtain a roadmap that takes into account the whole robot. The second contribution consists of the extension of motion planning methods for a robot under loop closure constraints. These kinematic loops appear in the system when, for example, the humanoid torso grasps an objet with two arms. This method treats explicitly the singular configurations of the manipulators, providing better handling of the object. Finally, we present two approaches for planning object manipulation tasks by humanoid torsos. The first concerns solving pick and place task by humanoid torso where the imposed task constraints require a passage through a double grasp to transfer the object from one hand to the other. The second approach concerns the resolution of the same type of task by a mobile manipulator. The presented methods have been integrated on a real platform, Justin, and validated with experiments in the frame of E.U. FP-6 PHRIENDS project

Inverse Kinematic Analysis of Robot Manipulators

An important part of industrial robot manipulators is to achieve desired position and orientation of end effector or tool so as to complete the pre-specified task. To achieve the above stated goal one should have the sound knowledge of inverse kinematic problem. The problem of getting inverse kinematic solution has been on the outline of various researchers and is deliberated as thorough researched and mature problem. There are many fields of applications of robot manipulators to execute the given tasks such as material handling, pick-n-place, planetary and undersea explorations, space manipulation, and hazardous field etc. Moreover, medical field robotics catches applications in rehabilitation and surgery that involve kinematic, dynamic and control operations. Therefore, industrial robot manipulators are required to have proper knowledge of its joint variables as well as understanding of kinematic parameters. The motion of the end effector or manipulator is controlled by their joint actuator and this produces the required motion in each joints. Therefore, the controller should always supply an accurate value of joint variables analogous to the end effector position. Even though industrial robots are in the advanced stage, some of the basic problems in kinematics are still unsolved and constitute an active focus for research. Among these unsolved problems, the direct kinematics problem for parallel mechanism and inverse kinematics for serial chains constitute a decent share of research domain. The forward kinematics of robot manipulator is simpler problem and it has unique or closed form solution. The forward kinematics can be given by the conversion of joint space to Cartesian space of the manipulator. On the other hand inverse kinematics can be determined by the conversion of Cartesian space to joint space. The inverse kinematic of the robot manipulator does not provide the closed form solution. Hence, industrial manipulator can achieve a desired task or end effector position in more than one configuration. Therefore, to achieve exact solution of the joint variables has been the main concern to the researchers. A brief introduction of industrial robot manipulators, evolution and classification is presented. The basic configurations of robot manipulator are demonstrated and their benefits and drawbacks are deliberated along with the applications. The difficulties to solve forward and inverse kinematics of robot manipulator are discussed and solution of inverse kinematic is introduced through conventional methods. In order to accomplish the desired objective of the work and attain the solution of inverse kinematic problem an efficient study of the existing tools and techniques has been done. A review of literature survey and various tools used to solve inverse kinematic problem on different aspects is discussed. The various approaches of inverse kinematic solution is categorized in four sections namely structural analysis of mechanism, conventional approaches, intelligence or soft computing approaches and optimization based approaches. A portion of important and more significant literatures are thoroughly discussed and brief investigation is made on conclusions and gaps with respect to the inverse kinematic solution of industrial robot manipulators. Based on the survey of tools and techniques used for the kinematic analysis the broad objective of the present research work is presented as; to carry out the kinematic analyses of different configurations of industrial robot manipulators. The mathematical modelling of selected robot manipulator using existing tools and techniques has to be made for the comparative study of proposed method. On the other hand, development of new algorithm and their mathematical modelling for the solution of inverse kinematic problem has to be made for the analysis of quality and efficiency of the obtained solutions. Therefore, the study of appropriate tools and techniques used for the solution of inverse kinematic problems and comparison with proposed method is considered. Moreover, recommendation of the appropriate method for the solution of inverse kinematic problem is presented in the work. Apart from the forward kinematic analysis, the inverse kinematic analysis is quite complex, due to its non-linear formulations and having multiple solutions. There is no unique solution for the inverse kinematics thus necessitating application of appropriate predictive models from the soft computing domain. Artificial neural network (ANN) can be gainfully used to yield the desired results. Therefore, in the present work several models of artificial neural network (ANN) are used for the solution of the inverse kinematic problem. This model of ANN does not rely on higher mathematical formulations and are adept to solve NP-hard, non-linear and higher degree of polynomial equations. Although intelligent approaches are not new in this field but some selected models of ANN and their hybridization has been presented for the comparative evaluation of inverse kinematic. The hybridization scheme of ANN and an investigation has been made on accuracies of adopted algorithms. On the other hand, any Optimization algorithms which are capable of solving various multimodal functions can be implemented to solve the inverse kinematic problem. To overcome the problem of conventional tool and intelligent based method the optimization based approach can be implemented. In general, the optimization based approaches are more stable and often converge to the global solution. The major problem of ANN based approaches are its slow convergence and often stuck in local optimum point. Therefore, in present work different optimization based approaches are considered. The formulation of the objective function and associated constrained are discussed thoroughly. The comparison of all adopted algorithms on the basis of number of solutions, mathematical operations and computational time has been presented. The thesis concludes the summary with contributions and scope of the future research work