论文标题
在STL规格下针对高维非线性系统的轨迹优化
Trajectory Optimization for High-Dimensional Nonlinear Systems under STL Specifications
论文作者
论文摘要
近年来，信号时间逻辑（STL）作为网络物理系统（尤其是机器人技术）的规范语言已广受欢迎。 STL除了表现出易于理解外，还具有吸引力，因为合成问题 - 生成满足给定规范的轨迹 - 可以作为轨迹优化问题提出。不幸的是，相关的成本函数是非平滑的和非凸面。结果，现有的合成方法尺寸较差，至高维非线性系统。在这封信中，我们为基于差分动态编程（DDP）的STL合成提供了一种新的轨迹优化方法。众所周知，DDP可以很好地缩放到极高的高维非线性系统（例如机器人四倍体和人形生物）：我们表明这些优势可以用于STL合成。我们证明了我们提出的方法的合理性，证明了在几个基准问题上的最先进的速度速度提高，并证明了我们对7度自由机器人机器人的完整非线性动力学方法的可扩展性。
Signal Temporal Logic (STL) has gained popularity in recent years as a specification language for cyber-physical systems, especially in robotics. Beyond being expressive and easy to understand, STL is appealing because the synthesis problem---generating a trajectory that satisfies a given specification---can be formulated as a trajectory optimization problem. Unfortunately, the associated cost function is nonsmooth and non-convex. As a result, existing synthesis methods scale poorly to high-dimensional nonlinear systems. In this letter, we present a new trajectory optimization approach for STL synthesis based on Differential Dynamic Programming (DDP). It is well known that DDP scales well to extremely high-dimensional nonlinear systems like robotic quadrupeds and humanoids: we show that these advantages can be harnessed for STL synthesis. We prove the soundness of our proposed approach, demonstrate order-of-magnitude speed improvements over the state-of-the-art on several benchmark problems, and demonstrate the scalability of our approach to the full nonlinear dynamics of a 7 degree-of-freedom robot arm.
