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作 者:李忠发 杨光[1] 马磊[1] 孙永奎[1] LI Zhong-fa;YANG Guang;MA Lei;SUN Yong-kui(School of Electrical Engineering,Southwest Jiaotong University,Chengdu 610031,China)
出 处:《计算机科学》2020年第S01期599-602,共4页Computer Science
基 金:国家自然科学基金委员会-中国工程物理研究院联合基金(NSAF联合基金)(U1730105)。
摘 要:由于变电站环境复杂,人工巡检强度大、效率低,文中研究了巡检机器人的硬件框架,基于自适应蒙特卡洛算法(Adaptive Monte Carlo Localization,AMCL)完成巡检机器人的定位研究;针对自适应蒙特卡洛算法在实际工程中应用的不足,给出了相应的解决策略;就AMCL算法无法快速进行定位,恢复设计了一种基于数据库的重定位方法,利用数据库存储定位值,当定位失匹配时,获取数据库存储的定位值用于初始化粒子,从而实现快速恢复定位。实验结果表明,改进后的AMCL算法在定位丢失后恢复定位的性能明显优于原始AMCL算法。The environment of substation is complex,and the manual inspection is labour-intensive and inefficiency.The hardware framework of the inspection robot is studied,and the positioning research of the inspection robot is completed based on the Adaptive Monte Carlo Localization(AMCL).This paper provides the corresponding solution in regard to the deficiency of Adaptive Monte Carlo Localization(AMCL)in the practical application of engineering.Considering AMCL can’t restore the location rapidly,a new method of relocation based on database has been put forward,which uses the database to store location values.When the location mismatches,the location value stored in database is used for initializing particles,so as to realize rapid restoration of location.Experiments have proven that compared to the primary AMCL algorithm,the improved AMCL algorithm is more competent in restoration of location after the loss of location.
分 类 号:TP242[自动化与计算机技术—检测技术与自动化装置]
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