TY - GEN
T1 - Water hazard detection based on 3D LIDAR
AU - Shao, Hai Yan
AU - Zhang, Zhen Hai
AU - Li, Ke Jie
AU - Wang, Jian
AU - Xu, Tao
AU - Hou, Shuai
AU - Zhang, Liang
N1 - Publisher Copyright:
© (2014) Trans Tech Publications, Switzerland.
PY - 2014
Y1 - 2014
N2 - Autonomous off-road navigation is a highly complicated task for a robot or unmanned ground vehicle (UGV) owing to the different kinds of obstacles it could encounter. In-particular, water hazards such as puddles and ponds are very common in outdoor environments and are hard to detect even with ranging devices due to the specular nature of reflection at the air water interface. In recent years, many researches to detect the water bodies have been done. But there still has been very little work on detecting bodies of water that could be navigation hazards, especially at night. In this paper, we used Velodyne HDL-64ES2 3D LIDAR to detect water hazard. The approach first analyzes the data format and transformation of 3D LIDAR, and then writes the data acquisition and visualizations algorithm, integrated data based on ICP algorithm. Finally according the intensity distribution identifies the water hazard. Experiments are carried out on the experimental car in campus, and results show the promising performance.
AB - Autonomous off-road navigation is a highly complicated task for a robot or unmanned ground vehicle (UGV) owing to the different kinds of obstacles it could encounter. In-particular, water hazards such as puddles and ponds are very common in outdoor environments and are hard to detect even with ranging devices due to the specular nature of reflection at the air water interface. In recent years, many researches to detect the water bodies have been done. But there still has been very little work on detecting bodies of water that could be navigation hazards, especially at night. In this paper, we used Velodyne HDL-64ES2 3D LIDAR to detect water hazard. The approach first analyzes the data format and transformation of 3D LIDAR, and then writes the data acquisition and visualizations algorithm, integrated data based on ICP algorithm. Finally according the intensity distribution identifies the water hazard. Experiments are carried out on the experimental car in campus, and results show the promising performance.
KW - 3D LIDAR
KW - ICP algorithm
KW - Unmanned ground vehicle (UGV)
KW - Water hazard detection
UR - http://www.scopus.com/inward/record.url?scp=84920770943&partnerID=8YFLogxK
U2 - 10.4028/www.scientific.net/AMM.668-669.1174
DO - 10.4028/www.scientific.net/AMM.668-669.1174
M3 - Conference contribution
AN - SCOPUS:84920770943
T3 - Applied Mechanics and Materials
SP - 1174
EP - 1177
BT - Mechanical Components and Control Engineering III
A2 - Ge, Weimin
PB - Trans Tech Publications Ltd.
T2 - 3rd Asian Pacific Conference on Mechanical Components and Control Engineering, ICMCCE 2014
Y2 - 20 September 2014 through 21 September 2014
ER -