智能变电站巡检机器人路径规划的改进ABC算法及其应用研究
Research on Improved ABC Algorithm for Path Planning of Intelligent Substation Inspection Robot and Its Application
洪天星1
作者信息
- 1. 龙岩学院 物理与机电工程学院,福建 龙岩 364012
- 折叠
摘要
为提升智能变电站巡检机器人的路径规划的效率,针对传统人工蜂群算法(ABC)的缺点,通过反向学习策略改进初始种群,利用精英反向学习优化算法的时间滞后性,同时借助差分算法的变异思维改进蜜源更新环节,提高算法的深度挖掘性能和全局寻优性能.实验数据表明,改进的ABC算法能够有效降低73.3％的巡检路径规划时间,巡检准确率可达95.2％,该算法可以提高智能变电站巡检机器人路径规划的效率,对提升智能变电站巡检机器人的智能化水平具有积极影响.
Abstract
In order to improve the efficiency of path planning of intelligent substation inspection robots,in view of the shortcomings of the traditional artificial bee colony algorithm (ABC),the reverse learning strategy was adopted to improve the initial population. The time lag of the elite reverse learning optimization algorithm was used,and the honey source updating process was improved by the variation thinking of the difference algorithm,so as to improve the deep mining performance and global optimization performance of the algorithm. Experimental data show that the improved ABC algorithm can effectively reduce the inspection path planning time by 73.3％,and the inspection accuracy can reach 95.2％. This algorithm can improve the efficiency of path planning for intelligent substation inspection robots,and has a positive impact on enhancing the intelligence level of intelligent substation inspection robots.
关键词
变电站/巡检机器人/路径规划/改进人工蜂群算法/搜索能力/全局优化Key words
Substation/inspection robot/path planning/improve the ABC algorithm/search ability/Global Optimization引用本文复制引用
出版年
2024
NETL
NSTL
万方数据