摘要
为提高核环境巡检机器人路径规划的效果,将一种新型智能优化算法—鹈鹕优化算法(Pelican Optimization Algorithm,POA)应用于解决该问题,并进行了实例分析。介绍了POA基本原理,给出了算法主要流程;利用4个基准测试函数对POA性能进行了验证,并与另外3种典型优化算法进行了对比分析;构建了简单和复杂的核巡检机器人两种工作环境,利用POA进行路径规划。结果表明,POA算法的寻优精度更高且计算稳定性好,在耗时更少的情况下,可以获得更短的移动路径,具有一定的优势。
In order to improve the path planning of inspection robots in the nuclear environment,a new intelligent optimization algorithm called Pelican Optimization Algorithm(POA)is applied.Firstly,the basic principle of POA is introduced,and the main flow of the algorithm is given.Secondly,the performance of POA is verified by four benchmark functions,and compared with other three typical optimization algorithms.Finally,simple working environments and complex working environments of the inspection robot in the nuclear environment are constructed,and POA is used for path planning.The results show that the POA algorithm has higher optimization accuracy and better computational stability,and can obtain shorter moving path with less time,which has certain advantages.
作者
张洁
ZHANG Jie(School of Information Engineering,Zhengzhou Tourism College,Zhengzhou 450009,China)
出处
《机械设计与研究》
CSCD
北大核心
2023年第3期27-30,34,共5页
Machine Design And Research
基金
河南省科技厅软科学项目(212400410083)。
关键词
鹈鹕优化算法
核环境
巡检机器人
路径规划
pelican optimization algorithm
nuclear environment
inspection robot
path planning
