当前位置>主页 > 期刊在线 > 计算机技术 >

计算机技术22年18期

无人机覆盖路径规划中基于能量感知网格 的三维避障算法的研究
赵其定¹,汪夏荣²
(1. 江西经济管理干部学院 飞行技术学院,江西 南昌 330088;2. 深圳市大疆创新科技有限公司,上海 200120)

摘  要:无人机飞行过程中,路线上会出现一些障碍物,障碍物会威胁无人机的飞行安全。在无人机执行任务时,路径规划需要进行动态调整以实现快速准确地避开障碍。在对无人机避障算法进行研究中,在无人机飞行的规划路径中利用摄像机捕捉包含障碍物的视图,通过能量感知网格确定无人机移动到新的位置上,以便绕过路径中的障碍物。仿真结果显示,与利用二维避障方法相比,三维场景信息避障的无人机在节约能量和完成时间上都有所提高。


关键词:无人机;路径规划:能量感知;三维避障



DOI:10.19850/j.cnki.2096-4706.2022.18.018


基金项目:江西经济管理干部学院院级项目 (2021YJYB21);江西省教育厅教育科技项目(GJJ216212)


中图分类号:TP391;V279                               文献标识码:A                                文章编号:2096-4706(2022)18-0075-06


Research on 3D Obstacle Avoidance Algorithm Based on Energy-Aware Grid in UAV Coverage Path Planning

ZHAO Qiding1, WANG Xiarong2

(1.School of Flight Technology, Jiangxi Institute of Economic Administrators, Nanchang 330088, China; 2.DJ-Innovations Co., Ltd., Shanghai 200120, China)

Abstract: During the flight process of the UAV, some obstacles will appear on the route, and the obstacles will threaten the flight safety of the UAV. During the execution of missions of UAV, the path planning needs to be adjusted dynamically to realize obstacle avoidance quickly and accurately. In the research of UAV obstacle avoidance algorithm, the camera is used to capture the view containing obstacles in the planned path of UAV flight, and the UAV is determined to move to a new position through the energy-aware grid in order to bypass the obstacles in the path. The simulation results show that compared with using the 2D obstacle avoidance method, the UAV with 3D scene information obstacle avoidance has improved in energy saving and completion time.

Keywords: UAV; path planning; energy-aware; 3D obstacle avoidance


参考文献:

[1] GRAMAJO G,SHANKAR P.An Efficient Energy Constraint Based UAV Path Planning for Search and Coverage [J].International Journal of Aerospace Engineering,2017,2017:1-13.

[2] AL-KAFF A,GARCÍA F,MARTÍN D,et al.Obstacle Detection and Avoidance System Based on Monocular Camera and Size Expansion Algorithm for UAVs [J].Sensors,2017,17(5):1061- 1061.

[3] 袁建华,李尚 . 无人机三维路径规划及避障方法 [J]. 信息与控制,2021,50(1):95-101.

[4] MYUNGWHAN C,AREEYA R,TAESHIK S,et al.Velocity Obstacle Based 3D Collision Avoidance Scheme for LowCost Micro UAVs [J].Sustainability,2017,9(7):1174.

[5] 张世勇,张雪波,苑晶,等 . 旋翼无人机环境覆盖与探索规划方法综述 [J]. 控制与决策,2022,37(3):513-529.

[6] 朱大奇,朱婷婷,颜明重 . 基于改进神经网络的多 AUV 全覆盖路径规划 [J]. 系统仿真学报,2020,32(8):1505-1514.

[7] MODARES J,GHANEI F,MASTRONARDE N,et al.UBANC Planner:Energy Efficient Coverage Path Planning with Multiple Drones [C]//2017 IEEE International Conference on Robotics and Automation (ICRA).Singapore:IEEE,2017:6182-6189.

[8] 贺利乐,刘小罗,黄天柱,等 . 移动机器人全覆盖路径规划算法研究 [J]. 机械设计与制造,2021(3):280-284.

[9] IACONO M,SGORBISSA A.Path Following and Obstacle Avoidance for an Autonomous UAV Using a Depth Camera [J].Rob Auton Syst,2018,106:38-46.

[10] 张启钱,许卫卫,张洪海,等 . 复杂低空物流无人机路径规划 [J]. 北京航空航天大学学报,2020,46(7):1275-1286. 


作者简介:赵其定(1991—),男,汉族,江西南昌人,助教,硕士研究生,研究方向:智能机器人控制系统;汪夏荣(1991—),男,汉族,上海人,工程师,硕士研究生,研究方向:智能无人机控制系统。