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Abstract

This paper emphasizes on the capacity of a humanoid robot to perform tasks that are difficult for other types of robots. It deals with manipulation of bulky objects. Such tasks require complicated manipulations involving the whole-body and line coordination between legs, arms and torso motions. We introduce here a whole-body motion planner that allows a humanoid robot to autonomously plan a pivoting strategy that accounts for the various constraints: collision avoidance, legs-arms coordination and stability control. Based on a previous result by the authors [1] proving the small-time controllability of a pivoting system, the planner is proven to inherit from the probabilistic completeness of the sampling- based motion planning method it is built on. The geometric and kinematic capacity of the proposed planner is mainly demonstrated through simulations and experiments.

Abstract

In this paper, we present a recursive method for the optimization of humanoid robot motions. The method is based on an efficient dynamics algorithm, which allows the calculation of the gradient function with respect to the control parameters analytically. The algorithm makes use of the theory of Lie groups and Lie algebra. The main objective of this method is to smooth the pre-calculated humanoid motions by minimizing the efforts, and at the same time improving the stability of the humanoid robot during the execution of the planned tasks. Experimental results using HRP-2 platform are provided to validate the proposed method.

Abstract

Despite the theoretically infinite number of possible trajectories a human may take to reach a distant doorway, we observed that locomotor trajectories corresponding to this task were actually stereotyped, both at the geometric and the kinematic levels. In this paper, we propose a computational model for the formation of human locomotor trajectories. Our model is adapted from smoothness maximization models that have been studied in the context of hand trajectory generation. The trajectories predicted by our model are very similar to the experimentally recorded ones. We discuss the theoretical implications of this result in the context of movement planning and control in humans. In particular, this result supports the hypothesis that common principles, such as smoothness maximization, may govern the generation of very different types of movements (in this case, hand movements and whole-body movements).

Mots-Clés / Keywords

Abstract

Human locomotion was investigated in a goal-oriented task where subjects had to walk to and through a doorway starting from a fixed position and orientation in space. The door was located at different positions and orientations in space, resulting in a total of 40 targets. While no specific constraint was provided to subjects in terms of the path they were to follow or the expected walking speeds, all of them generated very similar trajectories in terms of both path geometry and velocity profiles. These results are reminiscent of the stereotyped properties of the hand trajectories observed in arm reaching movements in studies over the last 20 years. This observation supports the hypothesis that common constraining mechanisms govern the generation of segmental and whole-body trajectories. In contrast, we observed that the subjects placed their feet at different spatial positions across repetitions, making unlikely the hypothesis that goal-oriented locomotion is planned as a succession of steps. Rather, our results suggest that common planning and/or control strategies underlie the formation of the whole locomotor trajectory during a spatially oriented task.

Mots-Clés / Keywords

Abstract

In this paper, we present a recursive optimization method of humanoid motions. The method is based on an efficient dynamics algorithm, which allows the calculation of the gradient function with respect to the control parameters analytically. The algorithm makes use of the theory of Lie groups and Lie algebra. The main objective of this method is to smooth the pre-calculated humanoid motions by minimizing the efforts, and at the same time improving the stability of the humanoid robot during the execution of the planned tasks. Experimental results using HRP-2 platform are provided to validate the proposed method.

Mots-Clés / Keywords

Abstract

This paper reports current experiments conducted on HRP-2 based research on robot autonomy. The contribution of the paper is not focused on a specific area but its objective is to highlight the critical issues that had to be solved to allow the humanoid robot HRP-2 to understand and execute the order "give me the purple ball" in an autonomous way. Such an experiment requires: simple object recognition and localization, motion planning and control, natural spoken language supervision, simple action supervisor and control architecture.

Abstract

Pivoting manipulation has such advantages as dexterity and safety over other methods to move bulky or heavy objects. In this paper we aim to show that a polyhedral object can be displaced to arbitrary position and orientation on a plane (i.e. such a pivoting system is controllable). More than that we show it is small time controllable, i.e. the reachable space from a starting point contains always a neighbor no matter how cluttered the environment is. As a consequence of this analysis, we propose a steering method to plan a manipulation path to be performed by a humanoid robot: first we use a classical nonholonomic path planner that accounts for the robot motion constraints, and then we transform that path into a sequence of pivoting operations. While the feasibility of elementary pivoting tasks has been already experienced by the humanoid robot HRP-2 [2], we present here the very first simulations of the plans generated by our steering method.

Abstract

AbstractIn this paper we outlook current state of the art in the emerging research field of motion planning for humanoid robots.We will first introduce related research activities in several aspects of motion planning for humanoid robots, which include integration of dynamics and other 3D motion planning for wholebody motion and various tasks. We also mention locomotion planning and local whole-body dynamic motion generation. We next present two related ongoing research projects conducted at JRL-France. The first part shows results 3D wholebody humanoid motion planning for simultaneous locomotion and dynamic manipulation. A two-stage planning method is adopted to generate for stable locomotion and task execution, by integrating geometric and kinematic motion planner and dynamic pattern generator. The second work provides a general framework of task-driven whole-body motion generation including stepping. In that research tasks are given to the IK solver to generate whole-body motions by taking account of monitored criteria and task priorities. A dynamic walking pattern generator provides the stepping motion that is combined with task achieving motion using the same IK solver. Finally we comment perspectives for future direction of motion planning for humanoid robots.