上海交通大学学报(自然版) ›› 2014, Vol. 48 ›› Issue (07): 1039-1045.

• 自动化技术、计算机技术 • 上一篇    下一篇

CTF定位策略下基于多特征的智能机器人目标跟踪

贾松敏1,王爽1,王丽佳1,2,李秀智1
  

  1. (1.北京工业大学 电子信息与控制工程学院,北京 100124;2.河北工业职业技术学院 信息工程与自动化系,河北 石家庄 050000)
     
     
     
  • 收稿日期:2013-07-02 出版日期:2014-07-28 发布日期:2014-07-28
  • 基金资助:

    国家自然科学基金资助项目(61175087;61105033),北京市自然科学基金重点项目(B类,KZ201110005004),国家教育部留学回国人员科研启动基金(第40批)

Human Tracking Based on MultiFeature for Intelligent Robot Under the CTF Locating Strategy

JIA Songmin1,WANG Shuang1,WANG Lijia1,2,LI Xiuzhi1
  

  1. (1. College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China; 2. Department of Information Engineering and Automation, Hebei College of Industry and Technology, Shijiazhuang 050000, China)
  • Received:2013-07-02 Online:2014-07-28 Published:2014-07-28

摘要:

针对复杂环境下机器人目标跟踪问题,提出由粗到精定位策略下基于多特征的智能机器人目标跟踪方法. 该方法首先利用射频识别系统实现目标粗定位,然后采用自适应模板匹配算法、改进核函数的连续自适应均值飘移算法及扩展卡尔曼滤波算法提取目标头肩形状、衣服颜色与运动特征,实现精确定位. 最后根据人机运动状态设计基于模糊规则的智能调速控制器,实时自动调整机器人的基准线速度与转弯增益,以稳定跟随运动目标. 实验结果表明,该方法能有效保持人机之间的安全距离,对遮挡、相近颜色背景干扰及目标突然转弯的跟踪问题有较强的鲁棒性.
 
 

关键词: 智能机器人, 目标跟踪, 由粗到精定位策略, 多特征

Abstract:

To realize a human tracking task in a cluttered environment, a method of multifeature based human tracking under the CTF(coarsetofine) locating strategy was proposed. The proposed method located the target from a RFID system coarsely. Then, the silhouette of the headshoulder, the cloth color and motion feature were extracted to locate the target accurately by using the processing techniques including adaptive template matching algorithm, improved Camshift and Extended Kalman Filter. At last, an intelligent gear shift controller based on fuzzy rules considering the motion state of the target and the robot was utilized to drive the robot. The experimental results show that the presented method can keep the robot in a suitable distance from the target and handle the problem of occlusion, a sudden turn, and complicated background.
Key words:

Key words: intelligent robot, target tracking, coarse-to-fine (CTF) locating strategy, multifeature

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