Task and Motion Planning Is PSPACE-Complete
Author(s)
Vega-Brown, William R; Roy, Nicholas
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We present a new representation for task and motion planning that uses constraints to capture both continuous and discrete phenomena in a unified framework. We show that we can decide if a feasible plan exists for a given problem instance using only polynomial space if the constraints are semialgebraic and all actions have uniform stratified accessibility, a technical condition closely related to both controllability and to the existence of a symbolic representation of a planning domain. We show that there cannot exist an algorithm that solves the more general problem of deciding if a plan exists for an instance with arbitrary semialgebraic constraints. Finally, we show that our formalism is universal, in the sense that every deterministic robotic planning problem can be well-approximated within our formalism. Together, these results imply task and motion planning is PSPACE-complete.
Date issued
2020-04Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence LaboratoryJournal
Proceedings of the AAAI Conference on Artificial Intelligence
Publisher
Association for the Advancement of Artificial Intelligence (AAAI)
Citation
Vega-Brown, William and Nicholas Roy. "Task and Motion Planning Is PSPACE-Complete." Proceedings of the AAAI Conference on Artificial Intelligence 34, 6 (April 2020): 10385-10392. © 2020 Association for the Advancement of Artificial Intelligence
Version: Author's final manuscript
ISSN
2374-3468
2159-5399