センシング・通信危険地帯における耐故障マルチロボット目標追跡
Resilient Multi-Robot Target Tracking with Sensing and Communication Danger Zones
未知のセンシング・通信危険地帯で確率的・一時的な故障が起きる環境に対し、ソフトチャンス制約付き非線形最適化で追跡性能と耐故障性を動的に両立する協調枠組みを提案し、実機実験で検証した。
著者: Peihan Li, Yuwei Wu, Jiazhen Liu, Gaurav S. Sukhatme, Vijay Kumar, Lifeng Zhou
分類: cs.RO
原文アブストラクト
Multi-robot collaboration for target tracking in adversarial environments poses significant challenges, including system failures, dynamic priority shifts, and other unpredictable factors. These challenges become even more pronounced when the environment is unknown. In this paper, we propose a resilient coordination framework for multi-robot, multi-target tracking in environments with unknown sensing and communication danger zones. We consider scenarios where failures caused by these danger zones are probabilistic and temporary, allowing robots to escape from danger zones to minimize the risk of future failures. We formulate this problem as a nonlinear optimization with soft chance constraints, enabling real-time adjustments to robot behaviors based on varying types of dangers and failures. This approach dynamically balances target tracking performance and resilience, adapting to evolving sensing and communication conditions in real-time. To validate the effectiveness of the proposed method, we assess its performance across various tracking scenarios, benchmark it against methods without resilient adaptation and collaboration, and conduct several real-world experiments.
