Stochastic Robustness Interval for Motion Planning with Signal Temporal Logic
Stochastic Robustness Interval for Motion Planning with Signal Temporal Logic
复制标题
信号时间逻辑运动规划的随机鲁棒性区间
DOI：
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Morteza Lahijanian
中科院分区：
文献类型：
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作者：
Roland Ilyes;Qi Heng Ho;Morteza Lahijanian
在这项工作中，我们提出了一种关于信号时间逻辑（STL）规范的连续时间随机轨迹的新颖鲁棒性度量。我们展示了测量的合理性，并开发了一个关于部分轨迹推理的监视器。在此基础上，提出了一种基于STL采样的不确定条件下机器人运动规划算法。在给定最小鲁棒性要求的情况下，该算法寻找满意的运动方案；或者，该算法也针对度量进行优化。我们证明了运动规划器相对于度量的概率完备性和渐近最优性，并通过几个案例研究证明了我们的方法的有效性。
In this work, we present a novel robustness measure for continuous-time stochastic trajectories with respect to Signal Temporal Logic (STL) specifications. We show the soundness of the measure and develop a monitor for reasoning about partial trajectories. Using this monitor, we introduce an STL sampling-based motion planning algorithm for robots under uncertainty. Given a minimum robustness requirement, this algorithm finds satisfying motion plans; alternatively, the algorithm also optimizes for the measure. We prove probabilistic completeness and asymptotic optimality of the motion planner with respect to the measure, and demonstrate the effectiveness of our approach on several case studies.