Rapid Recovery from Robot Failures in Multi-Robot Visibility-Based Pursuit-Evasion
Trevor Olsen, Nicholas M. Stiffler, Jason M. O'Kane

TL;DR
This paper presents a rapid recovery algorithm for multi-robot pursuit-evasion in polygonal spaces, enabling pursuer teams to quickly adapt and replan after robot failures, improving resilience in visibility-based pursuit tasks.
Contribution
The paper introduces a novel replanning algorithm that leverages previous search information to quickly recover from robot failures in pursuit-evasion scenarios.
Findings
The proposed method recovers from robot failures faster than baseline planning from scratch.
Quantitative results demonstrate improved resilience and efficiency in pursuit tasks.
The approach effectively utilizes prior search data to reduce replanning time.
Abstract
This paper addresses the visibility-based pursuit-evasion problem where a team of pursuer robots operating in a two-dimensional polygonal space seek to establish visibility of an arbitrarily fast evader. This is a computationally challenging task for which the best known complete algorithm takes time doubly exponential in the number of robots. However, recent advances that utilize sampling-based methods have shown progress in generating feasible solutions. An aspect of this problem that has yet to be explored concerns how to ensure that the robots can recover from catastrophic failures which leave one or more robots unexpectedly incapable of continuing to contribute to the pursuit of the evader. To address this issue, we propose an algorithm that can rapidly recover from catastrophic failures. When such failures occur, a replanning occurs, leveraging both the information retained from…
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Taxonomy
TopicsGuidance and Control Systems · Computational Fluid Dynamics and Aerodynamics · Military Defense Systems Analysis
