文章基本信息

标题：Continuous-Time Trajectory Optimization for Decentralized Multi-Robot Navigation
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作者：Shravan Krishnan ; Govind Aadithya Rajagopalan ; Sivanathan Kandhasamy 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2020
卷号：53
期号：1
页码：494-499
DOI：10.1016/j.ifacol.2020.06.083
语种：English
出版社：Elsevier
摘要：Multi-robot systems have begun to permeate into a variety of different fields, but collision-free navigation in a decentralized manner is still an arduous task. Typically, the navigation of high speed multi-robot systems demands replanning of trajectories to avoid collisions with one another. This paper presents an online replanning algorithm for trajectory optimization in labeled multi-robot scenarios. With reliable communication of states among robots, each robot predicts a smooth continuous-time trajectory for every other remaining robots. Based on the knowledge of these predicted trajectories, each robot then plans a collision-free trajectory for itself. The collision-free trajectory optimization problem is cast as a non linear program (NLP) by exploiting polynomial based trajectory generation. The algorithm was tested in simulations on Gazebo with aerial robots.
关键词：Trajectory Planning;Optimal Control;Multi-Robot Systems