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arXiv 2011.07104cs.ROcs.SYeess.SY
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STL规范下高维非线性系统的轨迹优化

Trajectory Optimization for High-Dimensional Nonlinear Systems under STL Specifications

Vince Kurtz, Hai Lin

摘要:

信号时序逻辑(STL)近年来作为网络物理系统的规约语言,特别是在机器人领域得到了广泛的应用。除了表现力和易于理解之外,STL之所以吸引人,是因为合成问题--生成满足给定规范的轨迹--可以用公式表示为轨迹优化问题。不幸的是,相关的成本函数是非光滑和非凸的。因此,现有的综合方法的规模很差,高维非线性系统。本文提出了一种基于微分动态规划(DDP)的STL合成轨迹优化方法。众所周知,DDP可以很好地扩展到非常高维的非线性系统,如机器人四足动物和类人:我们表明,这些优势可以利用STL合成。我们证明了我们所提出的方法的合理性,证明了在几个基准问题上的速度比最先进的方法有数量级的提高,并证明了我们的方法对7自由度机器人手臂的完全非线性动力学的可扩展性。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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