唐宏伟,孙炜,杨凯,林安平,吕云峰,程熙.基于SURF特征的多机器人栅格地图拼接方法[J].电子测量与仪器学报,2017,31(6):859-868 |
基于SURF特征的多机器人栅格地图拼接方法 |
Grid map merging approach of multi robot based on SURF feature |
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DOI:10.13382/j.jemi.2017.06.007 |
中文关键词: 多移动机器人 栅格地图拼接 最小化问题 SURF特征 ICP算法 |
英文关键词:multiple mobile robot grid map merging minimization problem SURF feature ICP algorithm |
基金项目:国家科技支撑计划(2015BAF11B01)、湖南省杰出青年基金(14JJ1011)、湖南省科技计划(2016TP1023)、湖南省教育厅科学研究(14C1015)资助项目 |
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Author | Institution |
Tang Hongwei | 1. National Engineering Laboratory for Robot Visual Perception and Control Technology, Hunan University, Changsha 410082, China;
2. Hunan Provincial Key Laboratory of Grids Operation and Control on MultiPower Sources Area, Shaoyang University, Shaoyang 422000, China |
Sun Wei | National Engineering Laboratory for Robot Visual Perception and Control Technology, Hunan University, Changsha 410082, China |
Yang Kai | Network Security and Technical Reconnaissance Detachment, Changsha Public Security Bureau, Changsha 410007,China |
Lin Anping | National Engineering Laboratory for Robot Visual Perception and Control Technology, Hunan University, Changsha 410082, China |
Lv Yunfeng | National Engineering Laboratory for Robot Visual Perception and Control Technology, Hunan University, Changsha 410082, China |
Cheng Xi | National Engineering Laboratory for Robot Visual Perception and Control Technology, Hunan University, Changsha 410082, China |
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中文摘要: |
实现地图拼接是多机器人协作创建地图的一项关键技术。研究了一种基于加速鲁棒特征(SURF)的多机器人栅格地图拼接方法,该方法通过对机器人运动坐标系进行刚体变换,将栅格地图拼接问题用图像配准的最小化问题来表示并建立数学模型。首先利用一种改进的SURF算法从待拼接地图中提取特征,然后利用随机抽样一致性(RANSAC)算法剔除误匹配得到初始拼接参数,并将拼接参数作为ICP算法的初值来求解目标函数。最后分别利用公开数据集和Turletbot2移动机器人进行了实验,结果表明该方法能对多机器人建立的栅格地图实现可靠拼接,鲁棒性好且精度高,拼接速度快适用于较大规模环境栅格地图拼接。 |
英文摘要: |
Map merging is a crucial technology for cooperative mapping of multi robot system. A multi robot grid map merging method based on SURF (speeded up robust features) algorithm is studied. In the approach, the robot motion coordinate system is transformed into a rigid body. The mathematical model of the grid map merging problem is establishmented as minimization problem of image registration. Firstly, an improved SURF algorithm is used to extract the features from the grid maps. Secondly, the RANSAC (random sampling consensus) algorithm is employed to eliminate the mismatch and get the initial merging parameters, and the merging parameter is used as the initial value of the ICP (iterative nearest point) algorithm to solve the objective function. Finally, the open datasets and the Turletbot2 mobile robots are adopted for experiments. The experimental results verify that the proposed method can achieve good robustness and high accuracy in the grid map merging by multi robots, the fast speed of map merging indicates that it is suitable for large scale environment. |
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