Safe and Performant Deployment of Autonomous Systems via Model Predictive Control and Hamilton-Jacobi Reachability Analysis

Published: 20 Jun 2025, Last Modified: 20 Jun 2025RSS 2025 Workshop ReliableRoboticsEveryoneRevisionsBibTeXCC BY 4.0
Keywords: Autonomous systems, robot safety, Hamilton-Jacobi reachability analysis, model predictive control
TL;DR: We present a framework on safe and performant deployment of autonomous systems using model predictive control and Hamilton-Jacobi reachability analysis.
Abstract: While we have made significant algorithmic developments to enable autonomous systems to perform sophisticated tasks, it remains difficult for them to perform tasks effective and safely. Most existing approaches either fail to provide any safety assurances or substantially compromise task performance for safety. In this work, we develop a framework, based on model predictive control (MPC) and Hamilton-Jacobi (HJ) reachability, to optimize task performance for autonomous systems while respecting the safety constraints. Our framework guarantees recursive feasibility for the MPC controller, and it is scalable to high-dimensional systems. We demonstrate the effectiveness of our framework with two simulation studies using a 4D Dubins Car and a 6 Dof Kuka iiwa manipulator, and the experiments show that our framework significantly improves the safety constraints satisfaction of the systems over the baselines.
Submission Number: 2
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