自动化学报2005，Vol.31Issue(6)：833-838,6.
机器人定位中的自适应粒子滤波算法
Novel Adaptive Particle Filters in Robot Localization
摘要
Abstract
The research of robot localization aims at accuracy, simplicity and robustness. This article improves the performance of particle filters in robot localization via the utilization of novel adaptive technique. The proposed algorithm introduces probability retracing to initialize particle sets, uses consecutive window filtering to update particle sets, and refreshes the size of particle set according to the estimation state. Extensive simulations show that the proposed algorithm is much more effective than the traditional particle filters. The proposed algorithm successfully solves the nonlinear, non-Gaussian state estimation problem of robot localization.关键词
Robot localization/particle filters/K-L distance/probability retrievalKey words
Robot localization/particle filters/K-L distance/probability retrieval分类
信息技术与安全科学引用本文复制引用
蒋正伟,谷源涛..机器人定位中的自适应粒子滤波算法[J].自动化学报,2005,31(6):833-838,6.基金项目
Supported by National Natural Science Foundation of P. R. China (60402030) （60402030）
