The paper introduces the PARC method for safe trajectory planning near obstacles. It leverages a simplified planning model and tracking error estimation to ensure goal-reaching while avoiding collisions. Extensive numerical experiments demonstrate the effectiveness of PARC in various robotic scenarios.
Autonomous mobile robots face challenges in reaching goals while ensuring safety, especially when obstacles are near. The reach-avoid problem is addressed using a novel approach called Piecewise Affine Reach-avoid Computation (PARC). This method tightens the reachable set approximation to improve conservativeness and enable safe trajectory planning.
Existing safe planning approaches often introduce numerical errors that hinder goal-reaching capabilities. PARC aims to mitigate these errors by incorporating tracking error estimates into the computation process. By underapproximating reachable sets and overapproximating avoid sets, PARC provides provably-safe extreme vehicle maneuvers in challenging scenarios.
The proposed PARC method demonstrates superior performance compared to state-of-the-art reach-avoid methods through extensive numerical experiments. By efficiently computing reachable sets and incorporating tracking error, PARC enables safe trajectory planning near danger with improved accuracy and reliability.
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by Long Kiu Chu... في arxiv.org 03-13-2024
https://arxiv.org/pdf/2402.15604.pdfاستفسارات أعمق