Adaptive Memetic Algorithm with Dual-Level Local Search for Cooperative Route Planning of Multi-Robot Surveillance Systems

被引:0
作者
Cheng, Hao [1 ]
Yi, Jin [1 ]
Xia, Wei [2 ]
Pu, Huayan [1 ]
Luo, Jun [1 ]
机构
[1] Chongqing Univ, State Key Lab Mech Transmiss Adv Equipment, Chongqing 400044, Peoples R China
[2] Politecn Milan, Dept Elect Informat & Bioengn, I-20133 Milan, Italy
来源
COMPLEX SYSTEM MODELING AND SIMULATION | 2024年 / 4卷 / 02期
基金
中国国家自然科学基金;
关键词
multi-robot system; surveillance; memetic algorithm;
D O I
10.23919/CSMS.2024.0006
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The heightened autonomy and robust adaptability inherent in a multi-robot system have proven pivotal in disaster search and rescue, agricultural irrigation, and environmental monitoring. This study addresses the coordination of multiple robots for the surveillance of various key target positions within an area. This involves the allocation of target positions among robots and the concurrent planning of routes for each robot. To tackle these challenges, we formulate a unified optimization model addressing both target allocation and route planning. Subsequently, we introduce an adaptive memetic algorithm featuring dual-level local search strategies. This algorithm operates independently among and within robots to effectively solve the optimization problem associated with surveillance. The proposed method's efficacy is substantiated through comparative numerical experiments and simulated experiments involving diverse scales of robot teams and different target positions.
引用
收藏
页码:210 / 221
页数:12
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