Parameter-Conditioned Reachable Sets for Updating Safety Assurances Online
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Abstract (arXiv)
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 textitparameter-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.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Sep 2022.
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Citing papers per year: 2023: 2; 2024: 4; 2025: 4; 2026: 1.
11 papers.
- 2023The Safety Filter: A Unified View of Safety-Critical Control in Autonomous Systemscited by 77
- 2025Generalizing Safety Beyond Collision-Avoidance via Latent-Space Reachability Analysiscited by 44
- 2024SAFE-GIL: SAFEty Guided Imitation Learning for Robotic Systemscited by 13
- 2023Deception Game: Closing the Safety-Learning Loop in Interactive Robot Autonomycited by 9
- 2024One Filter to Deploy Them All: Robust Safety for Quadrupedal Navigation in Unknown Environmentscited by 8
- 2025AnySafe: Adapting Latent Safety Filters at Runtime via Safety Constraint Parameterization in the Latent Spacecited by 5
- 2024Learning Maximal Safe Sets Using Hypernetworks for MPC-based Local Trajectory Planning in Unknown Environmentscited by 3
- 2025Reachability Barrier Networks: Learning Hamilton-Jacobi Solutions for Smooth and Flexible Control Barrier Functionscited by 3
- 2025Residual Neural Terminal Constraint for MPC-based Collision Avoidance in Dynamic Environmentscited by 3
- 2026Permissive Safety Through Trusted Inference: Verifiable Belief-Space Neural Safety Filters for Assured Interactive Roboticscited by 1
- 2024Gait Switching and Enhanced Stabilization of Walking Robots with Deep Learning-based Reachability: A Case Study on Two-link Walkercited by 0
- 2026Permissive Safety Through Trusted Inference: Verifiable Belief-Space Neural Safety Filters for Assured Interactive Robotics1 Jun 2026
- 2025AnySafe: Adapting Latent Safety Filters at Runtime via Safety Constraint Parameterization in the Latent Space23 Sep 2025
- 2025Residual Neural Terminal Constraint for MPC-based Collision Avoidance in Dynamic Environments5 Aug 2025
- 2025Reachability Barrier Networks: Learning Hamilton-Jacobi Solutions for Smooth and Flexible Control Barrier Functions16 May 2025
- 2025Generalizing Safety Beyond Collision-Avoidance via Latent-Space Reachability Analysis2 Feb 2025
- 2024One Filter to Deploy Them All: Robust Safety for Quadrupedal Navigation in Unknown Environments13 Dec 2024
- 2024Learning Maximal Safe Sets Using Hypernetworks for MPC-based Local Trajectory Planning in Unknown Environments26 Oct 2024
- 2024Gait Switching and Enhanced Stabilization of Walking Robots with Deep Learning-based Reachability: A Case Study on Two-link Walker10 Sep 2024
- 2024SAFE-GIL: SAFEty Guided Imitation Learning for Robotic Systems8 Apr 2024
- 2023The Safety Filter: A Unified View of Safety-Critical Control in Autonomous Systems11 Sep 2023
- 2023Deception Game: Closing the Safety-Learning Loop in Interactive Robot Autonomy3 Sep 2023