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

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

Momentum Control with Hierarchical Inverse Dynamics on a Torque-Controlled Humanoid

Hierarchical inverse dynamics based on cascades of quadratic programs have been proposed for the control of legged robots. They have important benefits but to the best of our knowledge have never been implemented on a torque controlled humanoid where model inaccuracies, sensor noise and real-time computation requirements can be problematic. Using a reformulation of existing algorithms, we propose a simplification of the problem that allows to achieve real-time control. Momentum-based control is integrated in the task hierarchy and a LQR design approach is used to compute the desired associated closed-loop behavior and improve performance. Extensive experiments on various balancing and tracking tasks show very robust performance in the face of unknown disturbances, even when the humanoid is standing on one foot. Our results demonstrate that hierarchical inverse dynamics together with momentum control can be efficiently used for feedback control under real robot conditions.Comment: 21 pages, 11 figures, 4 tables in Autonomous Robots (2015

Planning and control for simulated robotic Sandia hand for the DARPA Robotic Challenge

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (pages 32-33).The DARPA Robotic Challenge (DRC) required the development of user interface, perception, and planning and control modules for a robotic humanoid. This paper focuses on the planning and control component for the manipulation qualification task of the virtual section of the DRC. Nonlinear algorithms were employed for the planning systems, such as the grasp optimization system and the robot state trajectory computation system. However, for closed-loop control, a linear proportional-derivative (PD) joint position controller was used. The nonlinear algorithms used for the planning systems may be improved, but their current functionality allows the successful completion of the manipulation qualification task. Also, even though PD controllers seem appropriate for the closed-loop control, PID controllers might yield a higher level of accuracy if tuned properly. In conclusion, a linear controller appears sufficient for certain control of the highly nonlinear ATLAS humanoid robot and Sandia hand as long as accurate optimization and planning systems complement such control.by Cecilia G. Cantu.S.B

Multi-contact Walking Pattern Generation based on Model Preview Control of 3D COM Accelerations

We present a multi-contact walking pattern generator based on preview-control of the 3D acceleration of the center of mass (COM). A key point in the design of our algorithm is the calculation of contact-stability constraints. Thanks to a mathematical observation on the algebraic nature of the frictional wrench cone, we show that the 3D volume of feasible COM accelerations is a always a downward-pointing cone. We reduce its computation to a convex hull of (dual) 2D points, for which optimal O(n log n) algorithms are readily available. This reformulation brings a significant speedup compared to previous methods, which allows us to compute time-varying contact-stability criteria fast enough for the control loop. Next, we propose a conservative trajectory-wide contact-stability criterion, which can be derived from COM-acceleration volumes at marginal cost and directly applied in a model-predictive controller. We finally implement this pipeline and exemplify it with the HRP-4 humanoid model in multi-contact dynamically walking scenarios

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