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Collision-Free Reactive Mission and Motion Planning for Multi-robot Systems

Author(s)
DeCastro, Jonathan A.; Alonso-Mora, Javier; Raman, Vasumathi; Rus, Daniela; Kress-Gazit, Hadas
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Abstract
This paper describes a holistic method for automatically synthesizing controllers for a team of robots operating in an environment shared with other agents. The proposed approach builds on recent advances in Reactive Mission Planning using Linear Temporal Logic, and Local Motion Planning using convex optimization. A local planner enforces the dynamic constraints of the robot and guarantees collision avoidance in 2D and 3D workspaces. A reactive mission planner takes a high-level specification that captures complex motion sequencing, and generates a correct-by-construction controller guaranteed to achieve the specified behavior and be reactive to sensor events. If there is no controller that fulfills the specification because of possible deadlock in the local planner, a minimal set of human-readable assumptions is generated as a certificate of the conditions on deadlock where the task is guaranteed. This is truly a synergistic method: the low-level motion planner enables scalability of the high-level plan synthesis with respect to dynamic obstacles, and the high-level mission planner enforces correctness of the low-level motion. We provide formal guarantees for our approach and demonstrate it via physical experiments with ground robots and simulations with a team of quadrotors.
Date issued
2017-07-27
URI
https://hdl.handle.net/1721.1/137218
Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Springer International Publishing
Citation
DeCastro, Jonathan A., Alonso-Mora, Javier, Raman, Vasumathi, Rus, Daniela and Kress-Gazit, Hadas. 2017. "Collision-Free Reactive Mission and Motion Planning for Multi-robot Systems."
Version: Author's final manuscript
ISSN
2511-1256
2511-1264

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