Author:
Suzuki Taro, ,Amano Yoshiharu,Hashizume Takumi
Abstract
This paper describes outdoor localization for a mobile robot using a laser scanner and three-dimensional (3D) point cloud data. A Mobile Mapping System (MMS) measures outdoor 3D point clouds easily and precisely. The full six-dimensional state of a mobile robot is estimated combining dead reckoning and 3D point cloud data. Two-dimensional (2D) position and orientation are extended to 3D using 3D point clouds assuming that the mobile robot remains in continuous contact with the road surface. Our approach applies a particle filter to correct position error in the laser measurement model in 3D point cloud space. Field experiments were conducted to evaluate the accuracy of our proposal. As the result of the experiment, it was confirmed that a localization precision of 0.2 m (RMS) is possible using our proposal.
Publisher
Fuji Technology Press Ltd.
Subject
Electrical and Electronic Engineering,General Computer Science
Reference19 articles.
1. S. Thrun, W. Burgard, and D. Fox, “Probabilistic Robotics,” The MIT Press, 2005.
2. F. Dellaert et al., “Monte Carlo Localization for Mobile Robots,” In Proc. of IEEE ICRA, pp. 1322-1328, 1999.
3. F. Lu and E. Milios, “Robot Pose Estimation in Unknown Environments by Matching 2D Range Scans,” J. of Intelligent and Robotic Systems, Vol.18 No.3, pp. 249-275, 1997.
4. D. Fox et al., “Monte Carlo Localization: Efficient Position Estimation for Mobile Robots,” In Proc. of AAAI, pp. 343-349, 1999.
5. J. Meguro, R. Hirokawa, J. Takiguchi, and T. Hashizume, “Autonomous Mobile Surveillance System based on RTK-GPS in Urban Canyons,” J. of Robotics and Mech. (JRM) No.17, Vol.2, pp. 218-225, 2005.
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献