FFRob: An Efficient Heuristic for Task and Motion Planning
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Lozano-Perez_FFRob.pdf
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630.52 KB
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Author(s)
Garrett, Caelan Reed
Lozano-Perez, Tomas
Kaelbling, Leslie P
Date Issued
April 2015
Journal
Algorithmic Foundations of Robotics XI
Publisher
Springer Cham
Citation
Garrett, Caelan Reed, et al. “FFRob: An Efficient Heuristic for Task and Motion Planning.” Algorithmic Foundations of Robotics XI, edited by H. Levent Akin et al., vol. 107, Springer International Publishing, 2015, pp. 179–95.
Version
Author's final manuscript
Abstract
Manipulation problemsinvolvingmany objects present substantial challenges for motion planning algorithms due to the high dimensionality and multi-modality of the search space. Symbolic task planners can efficiently construct plans involving many entities but cannot incorporate the constraints from geometry and kinematics. In this paper, we show how to extend the heuristic ideas from one of the most successful symbolic planners in recent years, the FastForward (FF) planner, to motion planning, and to compute it efficiently. We use a multi-query roadmap structure that can be conditionalized to model different placements of movable objects. The resulting tightly integrated planner is simple and performs efficiently in a collection of tasks involving manipulation of many objects.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1007/978-3-319-16595-0_11
