基于stackelberg多步博弈的无人机协同搜索路径规划  

Path Planning of Multi-UAVs Cooperative Search Based on Stackelberg Equilibrium

作　　者：王瑞安 魏文军[1] WANG Rui’an;WEI Wenjun(School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730000, China)

机构地区：[1]兰州交通大学自动化与电气工程学院,兰州730000

出　　处：《计算机工程与应用》2019年第8期34-39,共6页Computer Engineering and Applications

基　　金：国家自然科学基金(No.61663020);国家重点研发计划资助(No.2017YFB1201003-020)

摘　　要：考虑到现有无人机搜索问题研究中无人机、移动目标仅有一方具有远距离探测能力的设定,已经无法体现出战场环境下双方的博弈关系。针对这一不足,基于stackelberg均衡策略,结合多步预测的思想,提出了stackelberg多步博弈策略,实现了无人机、目标都具有远距离探测能力的博弈搜索。通过建立无人机、目标各自的路径收益函数,使双方能够根据不同时刻的博弈状态选择相对应的函数,实现无人机的动态路径规划。仿真结果表明所提出策略完全适用于该博弈模型,比贪婪策略具有更高的搜索效率,大大提高了目标捕获率。In view of the limitation that only one side of UAVs and targets has long-distance detection capability in past studies, it can' t reflect the two-sides game relation of the battlefield environment. In response to this deficiency, this paper proposes a multi-step game strategy based on the stackelberg equilibrium and multi-step prediction, which realizes the game search with the long-distance detection capability. The path profit function is created, both sides can select the corresponding function according to the game state at different moments, which realizes the dynamic path planning of the UAVs. The simulation results show that the proposed strategy is fully applicable to the game model of this paper and has higher search efficiency than the greedy strategy, greatly improving target capture rate.

关 键 词：无人机 目标搜索 博弈 动态路径规划 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]