[1]伍明,孙继银.基于粒子滤波的未知环境下机器人同时定位、地图构建与目标跟踪[J].智能系统学报,2013,8(02):168-176.[doi:10.3969/j.issn.1673-4785.201202001]
 WU Ming,SUN Jiyin.Simultaneous localization, mapping and object tracking in an unknown environment using particle filtering[J].CAAI Transactions on Intelligent Systems,2013,8(02):168-176.[doi:10.3969/j.issn.1673-4785.201202001]
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基于粒子滤波的未知环境下机器人同时定位、地图构建与目标跟踪(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第8卷
期数:
2013年02期
页码:
168-176
栏目:
出版日期:
2013-04-25

文章信息/Info

Title:
Simultaneous localization, mapping and object tracking in an unknown environment using particle filtering
文章编号:
1673-4785(2013)02-0168-09
作者:
伍明 孙继银
中国人民解放军第二炮兵工程大学 指挥信息系统工程系,陕西 西安 710025
Author(s):
WU Ming SUN Jiyin
The department of commander information system, The PLA Second Artillery Engineering College, Xi’an 710025, China
关键词:
Rao-Blackwellized粒子滤波同时定位与地图构建目标跟踪
Keywords:
Rao-Blackwellized particle filter simultaneous localization and mapping object tracking
分类号:
TP242.6
DOI:
10.3969/j.issn.1673-4785.201202001
文献标志码:
A
摘要:
为了解决机器人在未知环境下的目标跟踪问题,提出了一种基于粒子滤波的机器人同时定位、地图构建与目标跟踪方法.该方法采用Rao-Blackwellized粒子滤波器对机器人位姿状态、标志柱分布和目标位置同时进行估计.该方法中,粒子群的总体分布情况表征机器人位姿状态,而每个粒子均包含2类EKF滤波器,其中一类用来完成对标志柱分布的估计,另一类用来完成对目标状态的估计,粒子的权值则由粒子状态相对于标志柱和目标状态2类相似度共同产生.通过仿真和实体机器人实验验证了该方法的有效性.
Abstract:
The proposed research paper examines a simultaneous localization, mapping, and object tracking method. The examination was in part based on a particle filter that allows a robot to track an object in an unknown environment. This method utilizies the Rao-Blackwellized particle filting to estimate the pose of robot, landmarks distribution, and object position simultaneously. The general distribution of a particle swarm represents the pose of a robot, and each particle includes two kinds of Extended Kalman Filter (EKF). One EKF estimates distribution of landmarks, while the other EKF estimates the state of the object. The weight of particle is determined by the combination of two likelihoods, one is the likelihood between particle state and landmarks, and the other is the likelihood between particle state and object state. The results of the research indicate the valid robot experimentation and simulation, confirm the proposed research approach is very effective.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2012-02-02.
网络出版日期:2012-11-16. 
基金项目:国家“863”计划资助项目(2006AA04Z258).
通信作者:伍明.
E-mail:hyacinth531@163.com.
作者简介:
伍明,男,1981年生,讲师,博士,主要研究方向为自主机器人控制、多机器人协作、机器人环境构建. 
孙继银,男,1952年生,教授、博士生导师,国家“863”计划评审专家,二炮导弹技术专家,中国计算机学会高级会员,中国计算机用户协会理事.全军先进教育工作者,享受国务院特殊津贴,多项科研成果获全军科技进步奖.发表学术论文70余篇.
更新日期/Last Update: 2013-05-26