摘要： 当前基于迭代最近点拼接的同时定位与建图算法,存在误差积累、无法满足大范围定位精度的缺陷。为此,提出一种融合多帧迭代最近点和图优化的算法。在时域上处理点云拼接问题,将单帧迭代最近点算法推广到多帧进行最近点迭代,提取同一地点在不同时刻的数据特征,形成多个封闭循环,再运用基于最小二乘的图优化方法对点云拼接后的全网数据进行全局优化,消除累计误差,提升整体的定位精度。采用鲁巷和密歇根的数据进行测试,结果表明,该方法在一定程度上减少了匹配误差,平均误差为1. 0 m,最小误差为0. 2 m,可以满足大范围同步定位与建图的精度需求。
关键词:
多帧迭代最近点,
图优化,
机器人,
雷达,
点云,
同时定位与建图
Abstract: Point(ICP),which exits error accumulation and can not meet the demand of wide range of SLAM positioning
accuracy,a fused ICP and graph optimization algorithm is proposed. Through the ICP and graph optimization,data
characteristic of the same site in different time is extracted,loop closure is formed,and global optimization based on leastsquare is done. The method is tested with real datasets. Result shows that the method can decrease mapping error by some certain and increase global accuracy demand of SLAM,mean error is 1. 0 m,and least error is 0. 2 m.
Key words:
multiple frames Interative Closest point(ICP),
graph optimization,
robot;radar,
point cloud;Simultaneous
Localization and Mapping(SLAM)
中图分类号:
吕瑞,李明,汪明阔,刘欢欢,薛静远. 一种融合多帧ICP 和图优化的算法研究[J]. 计算机工程, doi: 10.3969/j.issn.1000-3428.2014.09.046.
LV Rui,LI Ming,WANG Ming-kuo,LIU Huan-huan,XUE Jing-yuan. Research on a Algorithm Fused with Multiple Frames ICP and Graph Optimization[J]. Computer Engineering, doi: 10.3969/j.issn.1000-3428.2014.09.046.