智能系统学报Issue(3)：460-464,5.DOI:10.3969/j.issn.1673-4785.201404024
改进RBP F的移动机器人同步定位与地图构建
Simultaneous localization and mapping of an improved RBPF based mobile robot
摘要
Abstract
As in the research of simultaneous localization and mapping ( SLAM) of mobile robot applying traditional Rao⁃Blackwellized particle filter, the computational complexity is too high and memory space usage is too large, which causes poor real⁃time performance, an improved approach is proposed. Among a group of particles gathering in a particular state, the statistical properties of particles are identical. By applying the Kalman updating step to one representative particle in the group of particles, and using it repeatedly in the same group, the complexity is re⁃duced and arithmetic speed is improved. Combining the proposed distribution and adaptive resampling methods from the Gmapping algorithm, the results of actual experiment carried out with Pioneer III robot and ROS platform illus⁃trate that the real⁃time performance of the proposal could be enhanced while ensuring the quality of grid map.关键词
移动机器人/Rao-Blackwellized粒子滤波器/同步定位与地图构建( SLAM)/Gmapping算法/自适应重采样技术Key words
mobile robot/Rao-Blackwellized particle filter/simultaneous localization and mapping ( SLAM )/Gmapping algorithm/adaptive resampling methods分类
信息技术与安全科学引用本文复制引用
罗元,余佳航,汪龙峰,王运凯..改进RBP F的移动机器人同步定位与地图构建[J].智能系统学报,2015,(3):460-464,5.基金项目
国家自然科学基金资助项目（51075420）；重庆市教委科学技术研究项目（ KJ120519）． （）
