@inproceedings{262ee6958ce34d44924d545b94620851,
title = "Real-Time terrain estimation based on multi-scale radial basis function for unmanned ground vehicle",
abstract = "Accurate terrain estimation is essential for unmanned ground vehicle (UGV) to achieve autonomous navigation. However, some existing approaches are difficult to reconstruct the 3D surface in real-Time because of serious amount of computation. A method of environmental terrain estimation based on multi-scale radial basis function with a 3D lidar mounted on a moving vehicle was proposed in this paper. By combining kernel template with terrain grid map, the approach is applicable to the non-uniform density distribution of laser point cloud with the increasing detection range and improves the efficiency of calculation. What's more,the estimation of culverts and trees will be more accurate if treat the point cloud in separate layers for suspended obstacles problem. All terrain estimation approaches were verified with good performance in an interactive system, which is set up with Virtual Robot Experimentation Platform (VREP) and actual vehicle.",
keywords = "3D lidar, Multi-scale radial basis function, Terrain estimation, UGV",
author = "Yi Yang and Zhili Wang and Xinghe Li and Mengyin Fu",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE International Conference on Information and Automation, IEEE ICIA 2016 ; Conference date: 01-08-2016 Through 03-08-2016",
year = "2017",
month = jan,
day = "24",
doi = "10.1109/ICInfA.2016.7831902",
language = "English",
series = "2016 IEEE International Conference on Information and Automation, IEEE ICIA 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "659--664",
booktitle = "2016 IEEE International Conference on Information and Automation, IEEE ICIA 2016",
address = "United States",
}