Title :
Fast Iterative Closest Point framework for 3D LIDAR data in intelligent vehicle
Author :
Choi, Won-Seok ; Kim, Yang-Shin ; Oh, Se-young ; Lee, Jeihun
Author_Institution :
Dept. of Electr. Eng., Pohang Univ. of Sci. & Technol. (POSTECH), Pohang, South Korea
Abstract :
The Iterative Closest Point (ICP) algorithm is one of the most popular methods for geometric alignment of 3-dimensional data points. We focus on how to make it faster for 3D range scanner in intelligent vehicle. The ICP algorithm mainly consists of two parts: nearest neighbor search and estimation of transformation between two data sets. The former is the most time consuming process. Many variants of the k-d trees have been introduced to accelerate the search. This paper presents a remarkably efficient search procedure, exploiting two concepts of approximate nearest neighbor and local search. Consequently, the proposed algorithm is about 24 times faster than the standard k-d tree.
Keywords :
intelligent robots; iterative methods; mobile robots; optical radar; road vehicle radar; search problems; telerobotics; trees (mathematics); 3-dimensional data points geometric alignment; 3D LIDAR data; 3D range scanner; ICP algorithm; intelligent vehicle; iterative closest point algorithm; nearest neighbor search; search acceleration; search procedure; standard k-d tree; time consuming process; transformation estimation; Algorithm design and analysis; Approximation algorithms; Iterative closest point algorithm; Nearest neighbor searches; Sensors; Standards; Vehicles;
Conference_Titel :
Intelligent Vehicles Symposium (IV), 2012 IEEE
Conference_Location :
Alcala de Henares
Print_ISBN :
978-1-4673-2119-8
DOI :
10.1109/IVS.2012.6232293
