Path Planning for Vehicle-borne System Consisting of Multi Air-ground Robots

被引:14
作者
Chen, Yang [1 ,2 ]
Ren, Shiwen [1 ,2 ]
Chen, Zhihuan [1 ,2 ]
Chen, Mengqing [1 ,2 ]
Wu, Huaiyu [1 ,2 ]
机构
[1] Wuhan Univ Sci & Technol, Inst Robot & Intelligent Syst, Wuhan 430081, Peoples R China
[2] Minist Educ, Engn Res Ctr Met Automat & Measurement Technol, Wuhan 430081, Peoples R China
关键词
Path planning; Dual UAVs system; Air-Ground cooperation; PSO; TRAVELING-SALESMAN PROBLEM; UNMANNED AIR; ALGORITHM; OPTIMIZATION; UAVS;
D O I
10.1017/S0263574719000808
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
This paper considers the path planning problem for deployment and collection of a marsupial vehicle system which consists of a ground mobile robot and two aerial flying robots. The ground mobile robot, usually unmanned ground vehicle (UGV), as a carrier, is able to deploy and harvest the aerial flying robots, and each aerial flying robot, usually unmanned aerial vehicles (UAVs), takes off from and lands on the carrier. At the same time, owing to the limited duration in the air in one flight, UAVs should return to the ground mobile robot timely for its energy-saving and recharge. This work is motivated by cooperative search and reconnaissance missions in the field of heterogeneous robot system. Especially, some targets with given positions are assumed to be visited by any of the UAVs. For the cooperative path planning problem, this paper establishes a mathematical model to solve the path of two UAVs and UGV. Many real constraints including the maximum speed of two UAVs and UGV, the minimum charging time of two UAVs, the maximum hovering time of UAVs, and the dynamic constraints among UAVs and UGV are considered. The objective function is constructed by minimizing the time for completing the whole mission. Finally, the path planning problem of the robot system is transformed into a multi-constrained optimization problem, and then the particle swarm optimization algorithm is used to obtain the path planning results. Simulations and comparisons verify the feasibility and effectiveness of the proposed method.
引用
收藏
页码:493 / 511
页数:19
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