避障
运动规划
障碍物
路径(计算)
避碰
任意角度路径规划
计算机科学
向光性
实时计算
机器人
算法
模拟
控制理论(社会学)
移动机器人
人工智能
蓝光
碰撞
程序设计语言
法学
控制(管理)
物理
光学
计算机安全
政治学
作者
Yaoming Zhou,Yu Su,Anhuan Xie,Lingyu Kong
标识
DOI:10.1016/j.cja.2020.12.018
摘要
In this paper, a bio-inspired path planning algorithm in 3D space is proposed. The algorithm imitates the basic mechanisms of plant growth, including phototropism, negative geotropism and branching. The algorithm proposed in this paper solves the dynamic obstacle avoidance path planning problem of Unmanned Aerial Vehicle (UAV) in the case of unknown environment maps. Compared with other path planning algorithms, the algorithm has the advantages of fast path planning speed and fewer route points, and can achieve the effect of low delay real-time path planning. The feasibility of the algorithm is verified in the Gazebo simulator based on the Robot Operating System (ROS) platform. Finally, an actual UAV autonomous obstacle avoidance path planning experimental platform is built, and a UAV obstacle avoidance path planning flight test is carried out based on this actual environment.
科研通智能强力驱动
Strongly Powered by AbleSci AI