Timed-Elastic-Band Based Variable Splitting for Autonomous Trajectory Planning
CoRR(2024)
摘要
Existing trajectory planning methods are struggling to handle the issue of
autonomous track swinging during navigation, resulting in significant errors
when reaching the destination. In this article, we address autonomous
trajectory planning problems, which aims at developing innovative solutions to
enhance the adaptability and robustness of unmanned systems in navigating
complex and dynamic environments. We first introduce the variable splitting
(VS) method as a constrained optimization method to reimagine the renowned
Timed-Elastic-Band (TEB) algorithm, resulting in a novel collision avoidance
approach named Timed-Elastic-Band based variable splitting (TEB-VS). The
proposed TEB-VS demonstrates superior navigation stability, while maintaining
nearly identical resource consumption to TEB. We then analyze the convergence
of the proposed TEB-VS method. To evaluate the effectiveness and efficiency of
TEB-VS, extensive experiments have been conducted using TurtleBot2 in both
simulated environments and real-world datasets.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要