标题： 通过模型预测控制和哈密顿-雅可比可达性分析实现自主系统的安全且高效部署 显示英文标题

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

摘要： 尽管我们在算法方面取得了重大进展，使自主系统能够执行复杂的任务，但它们仍然难以有效地和安全地执行任务。 现有的大多数方法要么无法提供任何安全保证，要么为了安全而显著降低任务性能。 在本工作中，我们开发了一个框架，基于模型预测控制（MPC）和哈密顿-雅可比（HJ）可达性，以优化自主系统的任务性能，同时遵守安全约束。 我们的框架保证了MPC控制器的递归可行性，并且可以扩展到高维系统。 我们通过两个仿真研究验证了框架的有效性，分别使用了4D Dubins汽车和6自由度Kuka iiwa机械臂，实验结果表明，与基线方法相比，我们的框架显著提高了系统的安全约束满足率。 显示英文摘要

摘要： 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.