室内移动机器人目标定位性准确匹配研究  

Research on accurate matching of target positioning for indoor mobile robot

作　　者：刘俊超 陈志军[1] 樊小朝[1] 闫学勤[1] LIU Junchao;CHEN Zhijun;FAN Xiaochao;YAN Xueqin(School of Electrical Engineering,Xinjiang University,Urumqi 830047,China)

机构地区：[1]新疆大学电气工程学院,新疆乌鲁木齐830047

出　　处：《现代电子技术》2019年第2期159-162,167,共5页Modern Electronics Technique

基　　金：国家自然科学基金资助项目(51666017);新疆维吾尔自治区自然科学基金资助项目(2016D01C062)~~

摘　　要：在室内移动机器人目标定位系统中的扫描匹配技术中,传统的迭代最近点算法存在待配准点云初始位置要求苛刻、难以找到正确对应点对的问题,因此提出一种基于Kinect传感器获取三维环境点云,根据旋转投影统计特征描述子的相似性来查找对应点对并进行扫描匹配的移动机器人目标定位方法。首先通过Kinect传感器获取物体点云图,根据特征提取算法提取点云特征;然后获取两个待匹配点云的旋转投影统计特征描述子,通过比较两个描述子之间特征的相似程度,估算它们之间的对应关系,采用距离差分矩阵算法剔除误匹配点,计算初始匹配参数;最后利用最小二乘法迭代进行ICP配准,获得点云间的最终变换矩阵,实现目标定位。实验结果表明,改进后的算法有效地提高了点云匹配效率和配准精度,得到了较精确的目标定位信息。For the scan matching technology used in the target positioning system of the indoor mobile robot,the traditional iterative closest point algorithm has a strict requirement for the initial position of the to-be registration point cloud,and is difficult to find the correct corresponding point pair. Therefore,a target positioning algorithm is proposed for the mobile robot on the basis of obtaining the 3D environment point cloud by means of the Kinect sensor,querying the corresponding point pair according to the similarities of rotational projection statistics feature descriptors,and performing scan matching. The point cloud map of an object is obtained by means of the Kinect sensor. The point cloud features are extracted by using the feature extraction algorithm. The rotational projection statistics feature descriptors of two to-be registration point clouds are obtained. The corresponding relationship between two descriptors is estimated by comparing the feature similarity degree of two descriptors. The distance difference matrix algorithm is adopted to remove mismatching points and calculate the initial matching parameter. The ICP registration is performed by using the least square iteration method,so as to obtain the final transformation matrix between point clouds and realize target positioning. The experimental results show that the improved algorithm can effectively improve the matching efficiency and registration accuracy of point clouds,and obtain comparatively accurate target positioning information.

关 键 词：扫描匹配 移动机器人 Kinect传感器 目标定位 旋转投影统计 点云匹配 

分 类 号：TN953-34[电子电信—信号与信息处理] P242[电子电信—信息与通信工程]