董方新,蔡军,解杨敏.立体视觉和三维激光系统的联合标定方法[J].仪器仪表学报,2017,(10):2589-2596
立体视觉和三维激光系统的联合标定方法
Joint calibration method for stereo vision system and 3D laser system
  
DOI:
中文关键词:  双目立体视觉  三维激光扫描  数据融合  联合标定
英文关键词:binocular stereo vision  3D laser scanning  data fusion  joint calibration
基金项目:国家自然科学基金(61503234)项目资助
作者单位
董方新 上海大学机电工程与自动化学院 上海市机械自动化及机器人重点实验室上海200072 
蔡军 上海大学机电工程与自动化学院 上海市机械自动化及机器人重点实验室上海200072 
解杨敏 上海大学机电工程与自动化学院 上海市机械自动化及机器人重点实验室上海200072 
AuthorInstitution
Dong Fangxin School of Mechatronic Engineering and Automation, Shanghai Key Laboratory of Manufacturing Automation and Robotics, Shanghai University, Shanghai 200072, China 
Cai Jun School of Mechatronic Engineering and Automation, Shanghai Key Laboratory of Manufacturing Automation and Robotics, Shanghai University, Shanghai 200072, China 
Xie Yangmin School of Mechatronic Engineering and Automation, Shanghai Key Laboratory of Manufacturing Automation and Robotics, Shanghai University, Shanghai 200072, China 
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中文摘要:
      双目立体视觉和三维激光扫描是移动机器人环境探测与建模的常见传感测量方法。为实现两个系统的数据融合应用,必须为二者的测量坐标系建立数学关系,即对其进行传感器之间的位姿联合标定。为此提出了一种基于三维特征点距离匹配的联合标定新方法,设计了一种镂空棋盘格作为标定板。使用双目立体相机提取棋盘格角点三维坐标信息,使用激光测距雷达扫描获取镂空区域中心点三维坐标,最终通过最小化两组特征点的理论与实际测量距离的平方差获取两传感器坐标系之间的旋转矩阵和平移向量。进行的联合标定测量实验结果表明了该方法的准确性和可靠性。
英文摘要:
      Binocular stereo vision and 3D laser scanning techniques are the common sensor measurement methods in environment detection and modeling for mobile robots. In order to realize the data fusion application of the two systems, it is necessary to establish the mathematic relationship between the two local measurement coordinate systems, which is the position and pose joint calibration between the sensors. This paper proposes a new method for the joint calibration based on the distance matching among 3D feature points. A calibration board is designed, which is basically a black white chess board with hollow holes. The binocular stereo vision cameras are used to extract the 3D coordinate information of the corner points of the chess board, and a laser ranging radar is used to scan and acquire the 3D coordinates of the centers of the hollow area. Through minimizing the squared difference of the theoretical and measured distances of two groups of the feature points, the rotation matrix and translation vector of the two sensor coordinate systems are obtained. The joint measurement experiment results show the accuracy and reliability of the proposed method.
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