TY - GEN
T1 - An accurate and efficient pile driver positioning system using laser range finder
AU - Huang, Xiangqi
AU - Sasaki, Takeshi
AU - Hashimoto, Hideki
AU - Inoue, Fumihiro
AU - Zheng, Bo
AU - Masuda, Takeshi
AU - Ikeuchi, Katsushi
PY - 2013
Y1 - 2013
N2 - Real-time positioning a pile for accurate pile driving is desirable for modern construction foundation work, but it suffers from the deficiency of the traditional systems because surveying instruments are manually used to mark the pile positions in which the accuracy heavily depends on the worker's experience. The paper confronts this problem by proposing a highly efficient positioning system using a Laser Range Finder (LRF). Over the traditional systems ours is superior to automatically detect the position of the pile or pile driver in real time with high accuracy. To this end, we first develop LRF based surveying system to scan the construction site in real time and gather the 2D laser point data. Then we detect target object such as pile or pile driver by fast fitting a circle-like geometric model to the data based on Maximum Likelihood Estimation (MLE) inference. The performance of the algorithm is validated by both synthesized and real data set. The results demonstrate the potentials on feasibility of our method in future construction field.
AB - Real-time positioning a pile for accurate pile driving is desirable for modern construction foundation work, but it suffers from the deficiency of the traditional systems because surveying instruments are manually used to mark the pile positions in which the accuracy heavily depends on the worker's experience. The paper confronts this problem by proposing a highly efficient positioning system using a Laser Range Finder (LRF). Over the traditional systems ours is superior to automatically detect the position of the pile or pile driver in real time with high accuracy. To this end, we first develop LRF based surveying system to scan the construction site in real time and gather the 2D laser point data. Then we detect target object such as pile or pile driver by fast fitting a circle-like geometric model to the data based on Maximum Likelihood Estimation (MLE) inference. The performance of the algorithm is validated by both synthesized and real data set. The results demonstrate the potentials on feasibility of our method in future construction field.
UR - http://www.scopus.com/inward/record.url?scp=84883286607&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84883286607&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-40303-3_17
DO - 10.1007/978-3-642-40303-3_17
M3 - Conference contribution
AN - SCOPUS:84883286607
SN - 9783642403026
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 158
EP - 167
BT - Advances in Depth Image Analysis and Applications - International Workshop, WDIA 2012, Selected and Invited Papers
T2 - International Workshop on Advances in Depth Image Analysis and Applications, WDIA 2012
Y2 - 11 November 2012 through 11 November 2012
ER -