Motion Planning for Mobile Robots with Temporal Logic Specifications

Jianxin Zeng, Yaonan Wang, Zhiqiang Miao, Sifei Wang
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Abstract

In this paper, we propose a motion planning method for mobile robots in order to satisfy task requirements specified in linear temporal logic (LTL). The proposed method follows the traditional hierarchical planning workflow, including path planning and trajectory planning. Firstly, we propose a path planning method based on rapidly exploring random trees (RRT*) and Dubins curve. The tree derived from RRT* is expanded with the help of Buchi automaton converted by an LTL formula. The proposed method can automatically adjust the iterations of sampling according to the scale of Buchi automata. Then, we formulate an optimization problem for the generation of trajectory. We use Bezier curve to express the trajectory and use differential flatness of mobile robots to simplify the optimization problem. Finally, we validate the practicality of our method through simulations and real-world experiments.
具有时间逻辑规范的移动机器人运动规划
本文提出了一种移动机器人的运动规划方法,以满足线性时间逻辑(LTL)中规定的任务要求。该方法遵循传统的分层规划工作流程,包括路径规划和轨迹规划。首先,我们提出了一种基于快速探索随机树(RRT*)和Dubins曲线的路径规划方法。由RRT*导出的树在由LTL公式转换的Buchi自动机的帮助下展开。该方法可以根据布吉自动机的尺度自动调整采样的迭代次数。然后,我们提出了一个轨迹生成的优化问题。利用Bezier曲线来表示轨迹,利用移动机器人的微分平面度来简化优化问题。最后,通过仿真和实际实验验证了该方法的实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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