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.
Jonathan DeCastro and Javier Alonso-Mora contributed equally to this work
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Acknowledgements
This work was supported in part by NSF Expeditions in Computer Augmented Program Engineering (ExCAPE), ONR MURI Antidote N00014-09-1-1031, SMARTS N00014-09-1051, the Boeing Company and TerraSwarm, one of six centers of STARnet, a Semiconductor Research Corporation program sponsored by MARCO and DARPA.
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DeCastro, J.A., Alonso-Mora, J., Raman, V., Rus, D., Kress-Gazit, H. (2018). Collision-Free Reactive Mission and Motion Planning for Multi-robot Systems. In: Bicchi, A., Burgard, W. (eds) Robotics Research. Springer Proceedings in Advanced Robotics, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-319-51532-8_28
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DOI: https://doi.org/10.1007/978-3-319-51532-8_28
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