TY - GEN
T1 - Lane recognition self-learning scheme of mobile robot based on integrated perception system
AU - Yi, Yang
AU - Hao, Zhu
AU - Meng-Yin, Fu
AU - Mei-Ling, Wang
PY - 2013
Y1 - 2013
N2 - In this paper, a kind of integrated perception system for mobile robot is presented, which consists of 3D Lidar, 2D camera and their spatial registration. Based on the system and support vector machine (SVM), a self-supervised learning scheme between 3D point cloud data and 2D image data has been established, which can identify the traversable lane in driving environments through data association and parameters training. With this approach, vision-based autonomous navigation can be achieved and its effectiveness has been verified by extensive robot experiments.
AB - In this paper, a kind of integrated perception system for mobile robot is presented, which consists of 3D Lidar, 2D camera and their spatial registration. Based on the system and support vector machine (SVM), a self-supervised learning scheme between 3D point cloud data and 2D image data has been established, which can identify the traversable lane in driving environments through data association and parameters training. With this approach, vision-based autonomous navigation can be achieved and its effectiveness has been verified by extensive robot experiments.
UR - http://www.scopus.com/inward/record.url?scp=84892429586&partnerID=8YFLogxK
U2 - 10.1109/IVS.2013.6629604
DO - 10.1109/IVS.2013.6629604
M3 - Conference contribution
AN - SCOPUS:84892429586
SN - 9781467327558
T3 - IEEE Intelligent Vehicles Symposium, Proceedings
SP - 1046
EP - 1051
BT - 2013 IEEE Intelligent Vehicles Symposium, IEEE IV 2013
T2 - 2013 IEEE Intelligent Vehicles Symposium, IEEE IV 2013
Y2 - 23 June 2013 through 26 June 2013
ER -