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

作　　者：Hao Cheng Jin Yi Wei Xia Huayan Pu Jun Luo 

机构地区：[1]the State Key Laboratory of Mechanical Transmission for Advanced Equipment,Chongqing University,Chongqing 400044,China [2]the Department of Electronics,Information and Bioengineering,Politecnico di Milano,Milano 20133,Italy

出　　处：《Complex System Modeling and Simulation》2024年第2期210-221,共12页复杂系统建模与仿真（英文）

基　　金：This work was supported by the National Natural Science Foundation of China(No.52105244);Entrepreneurship and Innovation Support Plan of Chongqing for Returned Overseas Scholars(No.cx2023085).

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.

关 键 词：multi-robot system SURVEILLANCE memetic algorithm 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]