机器人2012，Vol.34Issue(6)：652-659,744,9.DOI:10.3724/SP.J.1218.2012.00652
一种针对人形足球机器人的分域自适应蒙特卡洛定位方法
Subsectional Adaptive Monte Carlo Localization for Humanoid Soccer Robot
摘要
Abstract
A subsectional adaptive Monte Carlo localization method is presented to overcome some shortcomings in regular Monte Carlo localization, such as particle degeneracy and the kidnap problem. Firstly, two feature variables are proposed to describe distribution of particle set and its difference from the real posture. Secondly, four states (global localization, local localization, local tracking and fault-tolerant localization) are identified by the combination of the variable values during the whole process of localization, and different strategies are designed for each state in order to adjust parameters and resampling rules adaptively. Finally, the results of physical and simulative experiments based on adult-size humanoid soccer robot system show that the proposed method is effective in achieving an accurate and real-time localization. Furthermore, this method can enhance the robustness of localization system by solving the kidnap problem efficiently.关键词
自适应蒙特卡洛定位/绑架问题/分域控制/人形足球比赛机器人Key words
adaptive Monte Carlo localization/ kidnap problem/ subsectional control/ humanoid soccer robot分类
信息技术与安全科学引用本文复制引用
洪伟,周长久,田彦涛..一种针对人形足球机器人的分域自适应蒙特卡洛定位方法[J].机器人,2012,34(6):652-659,744,9.基金项目
吉林大学"985工程"工程仿生科技创新平台项目 （）
吉林大学基本科研业务费资助项目(200903312). （200903312）
