The 3D map building of the mobile robot

The map building is the prerequisite in the mobile robots' autonomous operation in an unknown environment. Most current mobile robots mainly use the 2D map, and the others which use the 3D map have some shortcomings such as the complex data processing algorithm, large computation and time-consuming and so on. The paper presents a 3D data scanning system that combined with the 2D laser radar and the precise rotation head to capture the information of the unknown environment, and building a coordinate system model for calculating the transform matrixes of each coordinate system. Then the pose of the robot got by the odometer and electronic compass, the improved ICP algorithm and the transform matrixes are combined to process the environment information for getting the 3D point cloud, finally the 3D point cloud is displayed on the OpenGL. At last, the experiment about the 3D map building is gone on in the laboratory corridor and the indoor environment. The experimental results show that this 3D data scanning system has higher efficiency and accuracy, and can better reflect the real situation of the environment.

[1]  Alberto Valero-Gomez,et al.  3D feature based mapping towards mobile robots' enhanced performance in rescue missions , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[2]  Jianhua Wang,et al.  3D reconstruction embedded system based on laser scanner for mobile robot , 2008, 2008 3rd IEEE Conference on Industrial Electronics and Applications.

[3]  Huosheng Hu,et al.  3D Laser range scanner with hemispherical field of view for robot navigation , 2008, 2008 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.

[4]  Jizhong Xiao,et al.  3 D Laser Scan Registration of Dual-Robot System Using Vision , 2009 .

[5]  M. Tomono,et al.  Environment modeling by a mobile robot with a laser range finder and a monocular camera , 2005, IEEE Workshop on Advanced Robotics and its Social Impacts, 2005..

[6]  Ryo Kurazume,et al.  Autonomously generating a 3D map of unknown environment by using mobile robots equipped with LRF , 2009, 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[7]  Diego Viejo,et al.  3D plane-based egomotion for SLAM on semi-structured environment , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[8]  Masahiro Tomono,et al.  3-D Object Map Building Using Dense Object Models with SIFT-based Recognition Features , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[9]  Yong-Moo Kwon,et al.  Indoor Modeling for Interactive Robot Service , 2006, 2006 SICE-ICASE International Joint Conference.

[10]  Mahdi Jadaliha,et al.  Recursive line extraction algorithm from 2d laser scanner applied to navigation a mobile robot , 2009, 2008 IEEE International Conference on Robotics and Biomimetics.