Research on Laser Radar Based Real-Time Pose Estimation for Mobile Robots
基于激光雷达的移动机器人实时位姿估计方法研究

Pose estimation is a key issue in mobile robots and important to moving objects tracking, robot navigation, map building, etc. A real-time pose estimation method using 2D range data from a laser radar is presented, which consists of iterative tangent weighted closest point and Hough transform bat ed tangent angle histogram algorithms to overcome problems with past methods, such as local minimum, aperture-like, high computation problem, etc. This method has been tested on both synthetic and real range data collected in outdoor environment. Experimental results demonstrate its high accuracy, low computation, wide applicability and high robustness to aperture-like problem, occlusion and noises.