[1]伍明,李琳琳,魏振华,等.一种未知环境下机器人多目标跟踪算法[J].智能系统学报,2015,10(03):448-453.[doi:10.3969/j.issn.1673-4785.201405051]
 WU Ming,LI Linlin,WEI Zhenhua,et al.A robot multi-object tracking algorithm in unknown environments[J].CAAI Transactions on Intelligent Systems,2015,10(03):448-453.[doi:10.3969/j.issn.1673-4785.201405051]
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一种未知环境下机器人多目标跟踪算法(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第10卷
期数:
2015年03期
页码:
448-453
栏目:
出版日期:
2015-06-25

文章信息/Info

Title:
A robot multi-object tracking algorithm in unknown environments
作者:
伍明 李琳琳 魏振华 汪洪桥
第二炮兵工程大学 指挥信息工程系, 陕西 西安 710025
Author(s):
WU Ming LI Linlin WEI Zhenhua WANG Hongqiao
Command Information Engineering Department, The Second Artillery Engineering College, Xian 710025, China
关键词:
机器人同时定位与地图构建多目标跟踪粒子滤波联合概率数据关联Rao-Blackwellised粒子滤波Kalman滤波
Keywords:
robotsimultaneous localization and mapping (SLAM)multi-object trackingparticle filteringjoint integrated probabilistic data association (JIPDA)Rao-Blackwellized particle filteringKalman filtering
分类号:
TP242.6
DOI:
10.3969/j.issn.1673-4785.201405051
文献标志码:
A
摘要:
针对未知环境下移动机器人多目标跟踪问题,设计了一种基于联合概率数据关联的粒子滤波算法.该算法利用联合概率数据关联方法对Rao-Blackwellized粒子滤波算法进行改进,使机器人能够完成未知环境条件下对自身状态、环境特征状态和多目标状态的在线联合估计.算法将系统状态变量分为代表多目标、环境特征状态的线性变量和代表机器人状态的非线性变量,并利用联合概率数据关联Kalman滤波和粒子滤波对系统状态进行更新.通过仿真实验证明了该算法对机器人状态、环境特征状态以及多目标状态的估计准确性,验证了算法对未知环境下多目标的跟踪能力.
Abstract:
In this paper, a particle filtering algorithm based on the joint integrated probabilistic data association (JIPDA) is proposed in order to solve the problem of motile robot multi-object tracking in unknown environments. The Rao-Blackwellized particle filtering is reconstructed based on the JIPDA in the new algorithm. It allows the robot to estimate joint states of itself, environment features and multi-object states simultaneously. The algorithm divides the system variables into two parts: the lineal variable representing multi-object and environment feature states, and the non-linear variable representing robot states. The system state is updated by JIPDA Kalman filtering and particle filtering. Estimation precision of robot states, environment feature states and multi-object states is verified by simulation results, verifying the ability of multi-object tracking in unknown environments.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2014-5-23;改回日期:。
基金项目:国家自然科学基金资助项目(61202332);陕西省自然科学基础研究计划项目(2013JQ8030).
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.发表学术论文10余篇,其中被EI检索8篇.李琳琳,女,1974年生,副教授,博士,主要研究方向为信息栅格技术、多传感器网络、物联网.主持国家高技术研究项目1项,发表学术论文20余篇,其中被EI检索12篇.
通讯作者:伍明. E-mail: hyacinth531@163.com.
更新日期/Last Update: 2015-07-15