基于自适应金豺狼优化算法的巡检机器人路径规划

Inspection Robot Path Planning Based on Adaptive Golden Jackal Optimization

徐雯清 ¹顾大德 ¹刘有志 ¹张余平²

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作者信息

1. 广东电网有限责任公司广州供电局电力调度控制中心,广东广州 510620
2. 泰豪软件股份有限公司,江西南昌 330096
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摘要

为提升核环境巡检机器人移动路径规划效果,提出了基于自适应金豺狼优化算法(AGJO)的核环境巡检机器人路径规划新方法,并进行了实例分析.首先,介绍了 GJO算法基本原理和改进策略,给出了 AGJO算法流程;其次,通过3个基准测试函数进行了 AGJO与GJO性能对比分析;最后,构建了巡检机器人工作的两种仿真场景和一种真实场景,利用AGJO进行路径规划.结果表明,AGJO算法得到的移动路径最短,计算效率最高,具有一定的优势.

Abstract

In order to improve the path planning effect of inspection robot in nuclear environment,a new path planning method based on adaptive golden jackal optimization(AGJO)was proposed,and an example was analyzed.Firstly,the basic principle and improvement strategy of GJO algorithm are introduced,and the flow of AGJO algorithm was given.Secondly,the performance of AGJO and GJO was compared by three benchmark test functions.Finally,two simulation scenario and a real scenario of the inspection robot are constructed,and AGJO was used for path planning.The results show that the AGJO algorithm has the advantages of the shortest moving path and the highest computing efficiency.

关键词

金豺狼优化算法/自适应/核环境/机器人/路径规划

Key words

golden jackal optimization/adaptive/nuclear environment/robot/path planning

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出版年

2024

核电子学与探测技术

中核（北京）核仪器厂

核电子学与探测技术

北大核心

影响因子：0.215

ISSN：0258-0934

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