Research on mobile robot indoor positioning mapping based on front-end and back-end optimization

被引：2

作者：

Xu, Zhe ^{[1
,2
]}

Wu, JiaYue ^{[1
]}

Liu, QiuLi ^{[1
]}

机构：

[1] Shanghai Ocean Univ, Coll Engn Sci & Technol, Shanghai 201306, Peoples R China

[2] Shanghai Engn Res Ctr Marine Renewable Energy, Shanghai 201306, Peoples R China

来源：

JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY | 2024年

关键词：

Laser SLAM; Beetle swarm; Rao-Blackwellised particle filter; PL-ICP; Mobile robot; PARTICLE SWARM OPTIMIZATION; DIFFERENTIAL EVOLUTION; ALGORITHM; DIVERSITY; FILTER;

D O I：

10.1007/s12206-024-0434-0

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

When the traditional RBPF-SLAM algorithm is applied to indoor positioning and mapping of mobile robots, it is prone to inaccurate positioning and mapping due to the long computation time of the front-end matching algorithm and the presence of particle missing in the back-end optimization algorithm. We popose to optimize the matching efficiency of lidar using the PL-ICP algorithm in the front-end of the SLAM system. In the backend of the SLAM system, the RBPF-SLAM algorithm is optimized using an improved beetle swarm algorithm. The experimental results show that the PL-ICP algorithm can significantly reduce computation time in front-end matching. In terms of backend optimization, the improved RBPF-SLAM algorithm can significantly reduce the number of particles and resampling, effectively improving the accuracy of indoor positioning and mapping for mobile robots.

引用

页码：2555 / 2561

页数：7

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