无人机
多转子
运动规划
计算机科学
碰撞
避碰
路径(计算)
实时计算
过程(计算)
模拟
机器人
人工智能
工程类
航空航天工程
计算机安全
计算机网络
遗传学
生物
操作系统
作者
Na Zhang,Mingcheng Zhang,Kin Huat Low
标识
DOI:10.1016/j.trc.2021.103123
摘要
Drones have been greatly developed to facilitate the progress of various industries. The safe operation of drones in the urban airspace is critical to ensure a reliable and high-efficient urban air traffic system. This work presents a fusion scheme to achieve autonomous drone collision-free path planning considering static obstacles and dynamic threats detected. Firstly, a 3D voxel jump point search (JPS) based path planning model is developed to generate the static collision-free reference path. With the optimization, the reference path is then de-diagonalized, reconstructed, and smoothed to obtain the desired path. Subsequently, a local collision resolution method is proposed to avoid near mid-air collision of the dynamic threats. The method is based on the Markov decision process (MDP) to implement real-time dynamic collision avoidance. Simulations are conducted to verify the performance of the proposed model. The simulation results demonstrate that the proposed model is effective to achieve the autonomous path planning and real-time collision resolution of multirotor drones.
科研通智能强力驱动
Strongly Powered by AbleSci AI