Journal of Computer Applications ›› 2018, Vol. 38 ›› Issue (8): 2442-2448.DOI: 10.11772/j.issn.1001-9081.2018020312

Previous Articles    

Object manipulation system with multiple stereo cameras for logistics applications

ZHANG Zekun, TANG Bing, CHEN Xiaoping   

  1. School of Computer Science and Technology, University of Science and Technology of China, Hefei Anhui 230027, China
  • Received:2018-02-05 Revised:2018-03-28 Online:2018-08-10 Published:2018-08-11
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China and Shenzhen Union Fund (U1613216), the National Natural Science Foundation of China (61573333).

面向物流分拣的多立体摄像头物体操作系统

张泽坤, 唐冰, 陈小平   

  1. 中国科学技术大学 计算机科学与技术学院, 合肥 230027
  • 通讯作者: 陈小平
  • 作者简介:张泽坤(1994-),男,安徽安庆人,硕士研究生,主要研究方向:智能机器人、计算机视觉、机器学习;唐冰(1991-),男,安徽阜阳人,硕士研究生,主要研究方向:智能机器人、多功能手爪、机器人硬件控制;陈小平(1955-),男,北京人,教授,博士生导师,博士,主要研究方向:人工智能逻辑、多主体系统、智能机器人。
  • 基金资助:
    国家自然科学基金委-深圳联合基金资助项目(U1613216);国家自然科学基金资助项目(61573333)。

Abstract: To meet the low cost and real-time requirements of logistics sorting, a systematic method was proposed to extract complete stereo information of typical objects by using multiple stereo cameras. Combining the cameras with an arm and other hardware, a validation and experiment platform was constructed to test the performance of this method. Two Microsoft Kinect cameras were used to measure the locations of objects in horizontal plane with accuracy of 3 millimeters. The stereo features and models of objects were calculated from the complete stereo information at processing rate of about 1 second per frame. Utilizing these features, the arm continuously picked 100 objects without failure. The experimental results demonstrate that the proposed method can extract the stereo features of objects with various sizes and shapes in real-time without off-line training, and based on which the arm can operate on objects with high accuracy.

Key words: logistics, stereo vision, feature extraction, intelligent picking, camera calibration

摘要: 为满足物流分拣的低成本和实时性要求,提出了基于多个立体摄像头的系统获取典型物体的完整立体信息的方法,并结合机械臂搭建了实验硬件平台。实验采用了2个微软Kinect摄像头在水平面上实现了约3 mm精度的物体定位,根据物体的立体信息建立立体模型,并计算了物体的取向、尺寸、含有的平面等多个可用于物体操作的立体特征,计算速率约为1 s/帧。根据这些信息,使用了机械臂成功进行了连续100次抓取。实验结果表明,这套方法和平台无需离线学习即可以实时提取多种尺寸和形状的物体的立体特征,机械臂可以基于此进行精度较高的物体操作。

关键词: 物流分拣, 立体视觉, 特征提取, 智能抓取, 摄像头校准

CLC Number: