摘要
针对室外非结构化3D环境,研究了基于激光扫描的移动机器人实时地形建模问题.考虑了建模过程中可能存在的多源不确定性误差,将其建模为零均值高斯噪声,由此建立多级坐标变换矩阵将激光扫描数据转化为全局坐标系中的概率化高程估计,并根据置信区间将得到的高程估计关联至多个地形网格,在此基础上对关联网格内分配的高程估计进行概率融合,实现了局部高程地图的更新.此外,采用局部窗口检测方法对地形遮挡问题进行了处理,并同时解决了室外环境下移动机器人的3D定位问题.实验结果表明了该算法的实时性和有效性.
The real-time terrain modeling problem of mobile robot with a laser scanner in outdoor unstructured 3D envi- ronments is studied. The underlying uncertainties from multiple sources during modeling are taken into account and modeled as zero-mean Gaussian noises, and subsequently the multi-level coordinate transformation matrixes are created to convert the measurements from laser scanner into probabilistic elevation estimations in the global coordinate systems, which will be associated with several terrain cells according to the confidence interval of the estimation. The elevation estimations assigned to each cell can be fused through a probabilistic approach to update the map locally. In addition, a local measurement window is defined to detect the occlusions, and the 3D localization of the mobile robot in outdoor environment is solved simultaneously. Experimental results demonstrate the real-time performance and effectiveness of the proposed method.
出处
《机器人》
EI
CSCD
北大核心
2012年第3期321-328,336,共9页
Robot
基金
国家自然科学基金资助项目(61005092)
教育部博士点新教师基金资助项目(20100092120026)
关键词
移动机器人
环境建模
定位
高斯噪声
地形估计
mobile robot
environment modeling
localization
Gaussian noise
terrain estimation
