Study on a bipedal walking robot that adapts to real-world obstacles and changing terrains

制度:新 ; 報告番号:甲3056号 ; 学位の種類:博士(工学) ; 授与年月日:2010/3/15 ; 早大学位記番号:新531

A study on automatic gait parameter tuning for biped walking robots

Automatic gait parameter tuning for biped walking robots is the subject of this thesis. The biped structure is one of the most versatile ones for the employment of mobile robots in the human environment. Their control is challenging because of their many DOFs and nonlinearities in their dynamics. Open loop walking with offline walk pattern generation is one of the methods for walking control. in this method the reference positions of the foot centers with respect to the body center are generated as functionals. Commonly, the tuning process for the trajectory generation is based on numerous trial and error steps. Obviously, this is a time consuming and elaborate process. In this work, online adaptation schemes for one of the trajectory parameters, "z-reference asymmetry", which is used for the compensation of uneven weight distribution of the robot in the sagittal plane, is proposed. In one of the approaches presented, this parameter is tuned online. As an alternative to parameter tuning, a functional learning scheme employing fuzzy identifiers is tested too. Fuzzy identifiers are universal function approximators. Fuzzy system parameters are adapted via back-propagation. An on-line tuning scheme for biped walk parameters however can only be successful if there is sufficient time for training without falling. The training might last hundreds of reference cycles. This implies that a mechanism for keeping the robot in continuous walk, even when the parameter settings are totally wrong, is necessary during training. In this work, virtual torsional springs which resist against deviations of the robot trunk angles from zero, are attached to the trunk center of the biped. The torques generated by the springs serve as the criteria for the tuning and help in maintaining a stable and a longer walk. The springs are removed after training. This novel approach can be applied to a wide range of control systems that involve parameter tuning. 3-D simulation techniques using C++ are employed for the model of a 12-DOF biped robot to test the proposed adaptive method. in order to visualize the walking, simulation results are animated using an OpenGL based animation environment. As a result of the simulations, a functional for the desired parameter, keeping the system in balance while walking, is generated

Planification de pas pour robots humanoïdes : approches discrètes et continues

Dans cette thèse nous nous intéressons à deux types d'approches pour la planification de pas pour robots humanoïdes : d'une part les approches discrètes où le robot n'a qu'un nombre fini de pas possibles, et d'autre part les approches où le robot se base sur des zones de faisabilité continues. Nous étudions ces problèmes à la fois du point de vue théorique et pratique. En particulier nous décrivons deux méthodes originales, cohérentes et efficaces pour la planification de pas, l'une dans le cas discret (chapitre 5) et l'autre dans le cas continu (chapitre 6). Nous validons ces méthodes en simulation ainsi qu'avec plusieurs expériences sur le robot HRP-2. ABSTRACT : In this thesis we investigate two types of approaches for footstep planning for humanoid robots: on one hand the discrete approaches where the robot has only a finite set of possible steps, and on the other hand the approaches where the robot uses continuous feasibility regions. We study these problems both on a theoretical and practical level. In particular, we describe two original, coherent and efficient methods for footstep planning, one in the discrete case (chapter 5), and one in the continuous case (chapter 6). We validate these methods in simulation and with several experiments on the robot HRP-2

Robust Execution of Bipedal Walking Tasks From Biomechanical Principles

PhD thesisEffective use of robots in unstructured environments requires that they have sufficient autonomy and agility to execute task-level commands successfully. A challenging example of such a robot is a bipedal walking machine. Such a robot should be able to walk to a particular location within a particular time, while observing foot placement constraints, and avoiding a fall, if this is physically possible. Although stable walking machines have been built, the problem of task-level control, where the tasks have stringent state-space and temporal requirements, and where significant disturbances may occur, has not been studied extensively. This thesis addresses this problem through three objectives. The first is to devise a plan specification where task requirements are expressed in a qualitative form that provides for execution flexibility. The second is to develop a task-level executive that accepts such a plan, and outputs a sequence of control actions that result in successful plan execution. The third is to provide this executive with disturbance handling ability.Development of such an executive is challenging because the biped is highly nonlinear and has limited actuation due to its limited base of support. We address these challenges with three key innovations. To address the nonlinearity, we develop a dynamic virtual model controller to linearize the biped, and thus, provide an abstracted biped that is easier to control. The controller is model-based, but uses a sliding control technique to compensate for model inaccuracy. To address the under-actuation, our system generates flow tubes, which define valid operating regions in the abstracted biped. The flow tubes represent sets of state trajectories that take into account dynamic limitations due to under-actuation, and also satisfy plan requirements. The executive keeps trajectories in the flow tubes by adjusting a small number of control parameters for key state variables in the abstracted biped, such as center of mass. Additionally, our system uses a novel strategy that employs angular momentum to enhance translational controllability of the systemÂs center of mass. We evaluate our approach using a high-fidelity biped simulation. Tests include walking with foot-placement constraints, kicking a soccer ball, and disturbance recovery