Model Checking for Closed-Loop Robot Reactive Planning

Christopher Chandler
(School of Computing Science, University of Glasgow)
Bernd Porr
(School of Biomedical Engineering, University of Glasgow)
Alice Miller
(School of Computing Science, University of Glasgow)
Giulia Lafratta
(School of Engineering, University of Glasgow)

In this paper, we show how model checking can be used to create multi-step plans for a differential drive wheeled robot so that it can avoid immediate danger. Using a small, purpose built model checking algorithm in situ we generate plans in real-time in a way that reflects the egocentric reactive response of simple biological agents. Our approach is based on chaining temporary control systems which are spawned to eliminate disturbances in the local environment that disrupt an autonomous agent from its preferred action (or resting state). The method involves a novel discretization of 2D LiDAR data which is sensitive to bounded stochastic variations in the immediate environment. We operationalise multi-step planning using invariant checking by forward depth-first search, using a cul-de-sac scenario as a first test case. Our results demonstrate that model checking can be used to plan efficient trajectories for local obstacle avoidance, improving on the performance of a reactive agent which can only plan one step. We achieve this in near real-time using no pre-computed data. While our method has limitations, we believe our approach shows promise as an avenue for the development of safe, reliable and transparent trajectory planning in the context of autonomous vehicles.

In Marie Farrell, Matt Luckcuck, Mario Gleirscher and Maike Schwammberger: Proceedings Fifth International Workshop on Formal Methods for Autonomous Systems (FMAS 2023), Leiden, The Netherlands, 15th and 16th of November 2023, Electronic Proceedings in Theoretical Computer Science 395, pp. 77–94.
Published: 15th November 2023.

ArXived at: https://dx.doi.org/10.4204/EPTCS.395.6 bibtex PDF
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