航空科学技术2025，Vol.36Issue(3)：10-19,10.DOI:10.19452/j.issn1007-5453.2025.03.002
基于改进人工蜂群算法的地下空间空地协同探测传感器优化配置
Optimized Configuration of Sensors for Air-ground Collaborative Detection in Underground Spaces Using an Improved Artificial Bee Colony Algorithm
摘要
Abstract
To address the issue of existing robotic sensor configuration being heavily reliant on engineering experience and subjective judgment,leading to a lack of scientific rigor,a model for a multi-heterogeneous robot sensor configuration is constructed in this paper,and an improved artificial bee colony algorithm is proposed to achieve the optimal configuration of four types of air-ground heterogeneous robot sensors.A mathematical model of an air-ground heterogeneous robot sensor configuration is constructed by taking into account factors such as sensor coverage,close-range recognition accuracy,sensor weight,robotic payload,sensor number constraints,and information dimensions.On this basis,the discrete distance decay function,the information dimension reward factor,the redundancy dimension penalty factor,and the horizontal perspective effective superposition function are defined to represent the actual configuration process more rationally.Furthermore,the artificial bee colony algorithm is enhanced by incorporating the triangle random walk strategy and Lévy flights.Integrate feasibility criteria to address constraints and improve the algorithm's local search capability.The results of simulation experiments verify the feasibility and effectiveness of constructing models and proposed algorithms in this paper.关键词
空地协同探测/地下空间/传感器优化配置/改进的人工蜂群算法/三角游走策略/莱维飞行Key words
air-ground collaborative detection/underground spaces/optimal configuration of sensors/improved artificial bee colony algorithm/triangle random walk strategy/Lévy flights分类
计算机与自动化引用本文复制引用
柏荣奕,陈谋,周同乐,雍可南,韩增亮..基于改进人工蜂群算法的地下空间空地协同探测传感器优化配置[J].航空科学技术,2025,36(3):10-19,10.基金项目
"智能机器人"专项(2023YFB4704400) （2023YFB4704400）
国家自然科学基金(U2013201) （U2013201）
江苏省基础研究计划自然科学基金(BK20220885) （BK20220885）
中国博士后科学基金(GZC20242230) "Intelligent Robotics"Project(2023YFB4704400) （GZC20242230）
National Natural Science Foundation of China(U2013201) （U2013201）
Ji-angsu Provincial Basic Research Plan Natural Science Foundation(BK20220885) （BK20220885）
China Postdoctoral Science Foundation(GZC20242230) （GZC20242230）
