Backward-Forward Search for Manipulation Planning
Robotics
2016-11-18 v1 Artificial Intelligence
Abstract
In this paper we address planning problems in high-dimensional hybrid configuration spaces, with a particular focus on manipulation planning problems involving many objects. We present the hybrid backward-forward (HBF) planning algorithm that uses a backward identification of constraints to direct the sampling of the infinite action space in a forward search from the initial state towards a goal configuration. The resulting planner is probabilistically complete and can effectively construct long manipulation plans requiring both prehensile and nonprehensile actions in cluttered environments.
Cite
@article{arxiv.1604.03468,
title = {Backward-Forward Search for Manipulation Planning},
author = {Caelan Reed Garrett and Tomas Lozano-Perez and Leslie Pack Kaelbling},
journal= {arXiv preprint arXiv:1604.03468},
year = {2016}
}
Comments
8 pages in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015