计算机与数字工程2025，Vol.53Issue(2)：297-302,6.DOI:10.3969/j.issn.1672-9722.2025.02.001
基于改进水母搜索优化的FastSLAM算法
FastSLAM Algorithm Based on Artificial Jellyfish Search Optimization
摘要
Abstract
Aiming at the fact that the propertyal distribution existing in the traditional FastSLAM algorithm is quite different from the actual distribution,so a large number of particles are required to better represent the posterior distribution,causing a mem-ory explosion,the FastSLAM algorithm is proposed to optimize the FastSLAM algorithm with improved jellyfish search,first of all,the particles with poor adaptability values are chaotic processed,and then the wavelet variation is added when the jellyfish position is updated,and finally the fastSLAM particle sampling is updated with the improved jellyfish optimization algorithm.The pose quali-ty of property distribution sampling is improved.Experimental analysis shows that the proposed method can effectively reduce the er-ror of robot positioning mapping and improve its work efficiency,and can be applied to the study of improving FastSLAM algorithm.关键词
FastSLAM/proposal分布/水母优化/定位建图Key words
FastSLAM/proposal distribution/jellyfish optimization/localization mapping分类
信息技术与安全科学引用本文复制引用
王林,杨光永,刘福康,徐天奇..基于改进水母搜索优化的FastSLAM算法[J].计算机与数字工程,2025,53(2):297-302,6.基金项目
国家自然科学基金项目(编号:61761049,61261022)资助. （编号:61761049,61261022）
