Multi-UAVs Cooperative Path Planning Method based on Improved RRT Algorithm

作者：Wei Zu, Guoliang Fan, Yang Gao, Yao Ma, Haiying Zhang, Haitao Zeng · 年份：2018 · DOI：10.1109/icma.2018.8484400 · 被引用次数：31 · 研究领域：Robotic Path Planning Algorithms、Robotics and Sensor-Based Localization、Distributed Control Multi-Agent Systems

This paper presents a cooperative path planning algorithm using improved Rapidly-exploring Random Trees (RRTs) to generate paths for multiple unmanned air vehicles (UAVs) in real time, from given starting locations to goal locations in the presence of unknown pop-up obstacles. Generating no conflicting paths in obstacle environments for a group of DAVs within a short time is a challenging task. Firstly, we propose an improved RRT by taking the maneuvering constraints of the DAVs into account and a simple and efficient path pruning method is designed to delete redundant nodes on the path. Secondly, a cooperative path planning method is developed that generate a low cost path to avoid collision when DAVs detect a dynamic teammate or pop-up obstacles. Simulation studies are carried out to show the performance of the proposed algorithm.