论文标题
将基于可及性的安全性融合到计划和控制多代理互动的安全性
Infusing Reachability-Based Safety into Planning and Control for Multi-agent Interactions
论文作者
论文摘要
在机器人的自主堆栈中，计划者和控制器通常是单独设计的，并且可以实现不同的目的。因此，在确保机器人的安全性方面通常会扩散责任。我们建议计划者和控制者应共享对安全性的相同解释，但以不同但互补的方式应用此知识。为了实现这一目标，我们在计划级别使用汉密尔顿 - 雅各比（HJ）的可及性理论，为机器人规划师提供远见，以避免进入可能不可避免的碰撞进入地区。但是，仅此一项就不能保证安全。结合使用HJ可达性计划者，我们提出了一个最小间隔的多代理保留控制器，也通过HJ-RECH性能理论得出。安全控制器可维持机器人的安全性，而不会导致计划师的性能过高。我们在多道高速公路方案中证明了我们提出的方法的好处，在该方案中，机器人汽车被奖励以尽快浏览流量，并且我们表明我们的方法提供了强大的安全性保证，但与其他安全控制器相比，我们的方法可以达到最高的性能。
Within a robot autonomy stack, the planner and controller are typically designed separately, and serve different purposes. As such, there is often a diffusion of responsibilities when it comes to ensuring safety for the robot. We propose that a planner and controller should share the same interpretation of safety but apply this knowledge in a different yet complementary way. To achieve this, we use Hamilton-Jacobi (HJ) reachability theory at the planning level to provide the robot planner with the foresight to avoid entering regions with possible inevitable collision. However, this alone does not guarantee safety. In conjunction with this HJ reachability-infused planner, we propose a minimally-interventional multi-agent safety-preserving controller also derived via HJ-reachability theory. The safety controller maintains safety for the robot without unduly impacting planner performance. We demonstrate the benefits of our proposed approach in a multi-agent highway scenario where a robot car is rewarded to navigate through traffic as fast as possible, and we show that our approach provides strong safety assurances yet achieves the highest performance compared to other safety controllers.
