ハミルトン・ヤコビ到達可能性解析を用いた安全性・活性フィルタリング
On Safety and Liveness Filtering Using Hamilton-Jacobi Reachability Analysis
HJ到達可能性に基づくフィルタ設計を統一的に扱う枠組みを提案し、安全性・活性を保証する制御入力の最大集合を特徴づけて、滑らかさと計算コストの異なる3種の安全フィルタを構築・実機検証した。
著者: Javier Borquez, Kaustav Chakraborty, Hao Wang, Somil Bansal
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
Hamilton-Jacobi (HJ) reachability-based filtering provides a powerful framework to co-optimize performance and safety (or liveness) for autonomous systems. Under this filtering scheme, a nominal controller is minimally modified to ensure system safety or liveness. However, the resulting controllers can exhibit abrupt switching and bang-bang behavior, which is not suitable for applications of autonomous systems in the real world. This work presents a novel, unifying framework to design safety and liveness filters through reachability analysis. We explicitly characterize the maximal set of control inputs that ensures safety (or liveness) at a given state. Different safety filters can then be constructed using different subsets of this maximal set along with a projection operator to modify the nominal controller. We use the proposed framework to design three safety filters, each balancing performance, computation time, and smoothness differently. We highlight their relative strengths and limitations by applying these filters to autonomous navigation and rocket landing scenarios and on a physical robot testbed. We also discuss practical aspects associated with implementing these filters on real-world autonomous systems. Our research advances the understanding and potential application of reachability-based controllers on real-world autonomous systems.
