Anytime multi-task motion planning for humanoid robots
Xianchao Long, Murphy Wonsick, Velin Dimitrov, Taşkın Padır
Abstract
This paper introduces an anytime synthesized motion planning algorithm for humanoid robots unifying locomotion and manipulation planning. It generates an entire set of motions to finish specific tasks in an environment containing obstacles by exploiting a powerful inverse kinematics (IK) engine. The IK engine can compute solutions allowing the robot to reposition its feet for meeting the task requirements. The presented planning algorithm has two primary beneficial capabilities. First, it is capable of generating a motion plan to complete a task handling multiple ordered or unordered actions. Second, it produces an initial solution very quickly, and then searches for the opportunity to improve the the solution during execution. The performance of the proposed algorithm is evaluated on the NASA-JSC Valkyrie humanoid robot by demonstrating an object pick up task in simulation and a box pick-and-place task in the real world.
BibTeX
@inproceedings{iros2017_anytimemultitask,
title = {Anytime multi-task motion planning for humanoid robots},
author = {Xianchao Long and Murphy Wonsick and Velin Dimitrov and Taşkın Padır},
booktitle = {IROS 2017},
year = {2017}
}