论文标题
与范围兼容的控制障碍功能
Extent-Compatible Control Barrier Functions
论文作者
论文摘要
在状态空间的安全区域上，通常会通过设置不变性约束来执行动力系统的安全要求。控制障碍功能是确保设置不变性的类似Lyapunov的功能，是执行此类约束并确保安全性的有效工具，当系统被表示为状态空间中的点。在本文中，我们介绍了与程度兼容的控制屏障功能，以此作为对系统安全性的工具，包括其物理世界中的体积（范围）。为了实施与程度兼容的控制屏障功能框架，提出了基于平方的优化程序。由于规程计划的总和可能在计算上是过时的，因此我们还引入了一种基于抽样的方法，以保留基于传统屏障函数的二次程序控制器的计算优势。我们证明，拟议的基于抽样的控制器保留了安全保证。还提供了模拟和机器人实施结果。
Safety requirements in dynamical systems are commonly enforced with set invariance constraints over a safe region of the state space. Control barrier functions, which are Lyapunov-like functions for guaranteeing set invariance, are an effective tool to enforce such constraints and guarantee safety when the system is represented as a point in the state space. In this paper, we introduce extent-compatible control barrier functions as a tool to enforce safety for the system including its volume (extent) in the physical world. In order to implement the extent-compatible control barrier functions framework, a sum-of-squares based optimization program is proposed. Since sum-of-squares programs can be computationally prohibitive, we additionally introduce a sampling based method in order to retain the computational advantage of a traditional barrier function based quadratic program controller. We prove that the proposed sampling based controller retains the guarantee for safety. Simulation and robotic implementation results are also provided.
