论文标题
可证明对障碍物环境中拉格朗日系统的安全控制
Provably Safe Control of Lagrangian Systems in Obstacle-Scattered Environments
论文作者
论文摘要
我们提出了一项混合反馈控制法,该法律保证在有障碍的环境中为一类拉格朗日系统提供安全性和渐近稳定性。我们的方法不需要执行轨迹计划和实施轨迹追踪反馈控制法,而是需要在环境中的一系列位置(路径计划)和无障碍空间的抽象。然后将遵循路径计划的问题解释为一系列避免范围的问题:系统需要连续到达路径计划的每个位置,同时留在安全区域内。无障碍物椭圆形被用作定义此类安全区域的一种方式,每个区域都封闭了两个连续的位置。可行的控制屏障函数(CBF)直接由几何约束,椭圆形,确保向前不变性及其安全。通过渐近稳定对照Lyapunov函数(CLFS)来确保到每个位置的能力。然后将CBF和CLFS编码为二次程序(QP),而无需放松变量。此外,我们还提出了一种开关机制,即使在QPS之间过渡时,也可以保证控制定律正确且定义明确。模拟显示了在两个复杂情况下提出的方法的有效性。
We propose a hybrid feedback control law that guarantees both safety and asymptotic stability for a class of Lagrangian systems in environments with obstacles. Rather than performing trajectory planning and implementing a trajectory-tracking feedback control law, our approach requires a sequence of locations in the environment (a path plan) and an abstraction of the obstacle-free space. The problem of following a path plan is then interpreted as a sequence of reach-avoid problems: the system is required to consecutively reach each location of the path plan while staying within safe regions. Obstacle-free ellipsoids are used as a way of defining such safe regions, each of which encloses two consecutive locations. Feasible Control Barrier Functions (CBFs) are created directly from geometric constraints, the ellipsoids, ensuring forward-invariance, and therefore safety. Reachability to each location is guaranteed by asymptotically stabilizing Control Lyapunov Functions (CLFs). Both CBFs and CLFs are then encoded into quadratic programs (QPs) without the need of relaxation variables. Furthermore, we also propose a switching mechanism that guarantees the control law is correct and well-defined even when transitioning between QPs. Simulations show the effectiveness of the proposed approach in two complex scenarios.