[1]张雪华,刘华平,孙富春,等.采用Kinect的移动机器人目标跟踪[J].智能系统学报,2014,9(01):34-39.[doi:10.3969/j.issn.1673-4785.201305080]
　ZHANG Xuehua,LIU Huaping,SUN Fuchun,et al.Target tracking of mobile robot using Kinect[J].CAAI Transactions on Intelligent Systems,2014,9(01):34-39.[doi:10.3969/j.issn.1673-4785.201305080]
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第9卷
期数:
2014年01期
页码:
34-39
栏目:
学术论文—智能系统
出版日期:
2014-02-25

文章信息/Info

Title:
Target tracking of mobile robot using Kinect
作者:
张雪华1; 2;  刘华平2;  孙富春2;  高蒙1;  贺超2
1. 石家庄铁道大学 电气与电子工程学院, 河北 石家庄 050043;
2. 清华大学 智能技术与系统国家重点实验室, 北京 100084
Author(s):
ZHANG Xuehua1; 2;  LIU Huaping2;  SUN Fuchun2;  GAO Meng1;  HE Chao2
1. College of Electrical and Electronic Engineering, Shijiazhuang Railway University, Shijiazhuang 050043, China;
2. Key Laboratory of Intelligent Technology and Systems, Tsinghua University, Beijing 100084, China
关键词:
Kinect; 粒子滤波算法; 移动机器人; 深度信息; 颜色信息
Keywords:
Kinect; particle filter algorithm; mobile robot; depth information; color infumation
分类号:
TP242
DOI:
10.3969/j.issn.1673-4785.201305080
摘要:
由于基于颜色特征的目标跟踪方法容易受颜色相近的物体影响, 造成目标丢失, 为了改善这一现象, 利用Kinect视觉传感器获取目标的深度信息和颜色信息来计算目标跟踪算法中的粒子权值, 从而对基于颜色特征的粒子滤波算法进行改进。为了简化目标跟踪算法中的直方图计算, 利用增量式直方图计算的方法, 以提高目标跟踪过程中的运算速度。最后通过实验证明结合目标的颜色和深度信息的方法能够很好地克服目标跟踪过程中颜色相近物体的干扰, 并将改进的目标跟踪算法应用到移动机器人中, 验证了该算法的快速性和鲁棒性。
Abstract:
The target tracking method based on color features is susceptible to the effects of similar color objects, which leads to the loss of the target. In order to overcome this phenomenon, in this paper, the Kinect vision sensor is used to obtain the target depth information and color information to calculate the weights of particles in the target tracking algorithm, and therefore to improve the particle filter algorithm which is based on the color feature. In order to simplify the histogram calculation of the target tracking algorithm, an incremental histogram calculation method is proposed to improve the computational speed of the target tracking process. Finally, through experimentation, the combination of color and depth information of the target can be shown to easily overcome the interference to the target tracking process by similar color objects, and the improved target tracking algorithm is applied to the mobile robot, verifying the rapidness and robustness of the mobile robot target tracking algorithm.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2013-06-04。
基金项目:国家"863"计划资助项目(G2013CB329403);国家自然科学基金资助项目(91120011);清华大学自主科研计划资助项目(2011THZ0).
作者简介:刘华平,男,1976年生,副教授,主要研究方向为智能控制及机器人、计算机视觉等;孙富春,男,教授,博士生导师,IEEE高级会员,中国人工智能学会理事、智能控制与智能管理专业委员会副主任兼秘书长。主要研究方向为智能控制、机器人与飞行器的导航与控制、网络控制系统、人工认知系统的信息感知和处理等。曾获全国优秀博士论文奖、教育部新世纪人才奖、国家杰出青年基金、北京市科学技术进步二等奖等。发表学术论文120余篇,其中被SCI检索52篇。
通讯作者:张雪华,女,1988年生,硕士研究生,主要研究方向为智能控制及机器人.E-mail:lovelywaiwai1988@sina.com.
更新日期/Last Update: 1900-01-01