控制理论与应用2011，Vol.28Issue(7)：901-906,6.
基于信息势能的鲁棒估计器及其在同时定位与地图构建问题中的应用
Robust estimator based on information potential and its application to simultaneous localization and mapping
摘要
Abstract
We present a novel robust estimator based on information potential optimization techniques and apply it to simultaneous localization and mapping on segment-based maps. Structured indoor environment can be efficiently described with Segment-based maps. Usually, in dynamic environment, sample data collected by range-finders suffer from noises and disturbances. Sample data are divided into clusters with split-and-merge. Inliers of the segment are selected according to the information contribution which is measured by information potential. After the local map is built, particle filters are adopted to update robot poses and maps. The recursive information potential reduces computations of information contribution of each sample. Simulations and experimental results validate the strong robustness of the proposed estimator, and the accuracy and efficiency of the proposed strategy based on the robust estimator.关键词
信息势能/自主机器人/鲁棒估计/定位与地图构建Key words
information potential/autonomous robot/robust estimator/localization and mapping分类
信息技术与安全科学引用本文复制引用
刘龚,任雪梅,A．B．RAD..基于信息势能的鲁棒估计器及其在同时定位与地图构建问题中的应用[J].控制理论与应用,2011,28(7):901-906,6.基金项目
国家自然科学基金资助项目（60474033,60974046）. （）
