Laser radar based real-time ego-motion estimation for intelligent vehicles

Ego-motion estimation is a key issue in intelligent vehicles and important to moving objects tracking. In this paper, after a simple overview of existed method, we present a tangent based hybrid real-time ego-motion estimation algorithm based on laser radar, which is composed of iterative tangent weighted closest point (ITCP) and Hough transform based tangent angle histogram (HTAH) algorithms to overcome problems with past methods, such as local minimum, aperture-like, and high computation problem, etc. This algorithm has been tested on both synthetic data and real range data in outdoor environment. Experimental results demonstrate its high accuracy, low computation, wide applicability and high robustness to aperture-like problem, occlusion and noises.