Hamilton-Jacobi (HJ) reachability analysis is a powerful tool for analyzing the safety of autonomous systems. However, the provided safety assurances are often predicated on the assumption that once deployed, the system or its environment does not evolve. Online, however, an autonomous system might experience changes in system dynamics, control authority, external disturbances, and/or the surrounding environment, requiring updated safety assurances. Rather than restarting the safety analysis from scratch, which can be time-consuming and often intractable to perform online, we propose to compute \textit{parameter-conditioned} reachable sets. Assuming expected system and environment changes can be parameterized, we treat these parameters as virtual states in the system and leverage recent advances in high-dimensional reachability analysis to solve the corresponding reachability problem offline. This results in a family of reachable sets that is parameterized by the environment and system factors. Online, as these factors change, the system can simply query the corresponding safety function from this family to ensure system safety, enabling a real-time update of the safety assurances. Through various simulation studies, we demonstrate the capability of our approach in maintaining system safety despite the system and environment evolution.
翻译:Hamilton-Jacobi (HJ) 的可获取性分析是分析自主系统安全的有力工具,然而,提供的安全保证往往以下述假设为前提:一旦部署,系统或其环境不会演变;然而,在线,一个自主系统可能会在系统动态、控制权力、外部干扰和/或周围环境方面经历变化,需要更新安全保障。我们提议从头开始重新进行安全分析,这种分析可能耗时,而且往往难以在网上进行,而不是从头开始,从头开始进行安全分析,我们提议计算一个可获取的安全功能,以确保系统安全,从而能够实时更新安全保障。通过各种模拟研究,我们展示了在系统和环境演化的情况下如何维持系统安全的方法。