Title :
Landmark Pair based Localization for Intelligent Vehicles using Laser Radar
Author :
Wu, Shun-Xi ; Yang, Ming
Author_Institution :
Shanghai Jiao Tong Univ., Shanghai
Abstract :
Localization, namely pose estimation is of great importance in the research of intelligent vehicles. In this paper, after a simple overview of existing methods, a method of laser radar localization based on landmark pairs (L3P) is presented, which is an improved algorithm of localization based on landmarks to overcome problems of traditional methods, such as low reliability and low robustness of landmark detection, etc. This algorithm has been verified on both synthetic data and real range data in the outdoor environment. Experimental results demonstrate its high accuracy, high robustness to noises and low computation.
Keywords :
Kalman filters; mobile robots; nonlinear filters; object detection; optical radar; path planning; pose estimation; extended Kalman filter; intelligent vehicle; landmark pair detection; laser radar localization; mobile robot; pose estimation; Intelligent vehicles; Laser radar; Motion estimation; Noise robustness; Radar detection; Radar tracking; Shape; State estimation; Vehicle detection; Wheels;
Conference_Titel :
Intelligent Vehicles Symposium, 2007 IEEE
Conference_Location :
Istanbul
Print_ISBN :
1-4244-1067-3
Electronic_ISBN :
1931-0587
DOI :
10.1109/IVS.2007.4290116