TY  - JOUR
AB  - Purpose– The authors aim to propose a novel plane extraction algorithm for geometric 3D indoor mapping with range scan data. Design/methodology/approach– The proposed method utilizes a divide-and-conquer step to efficiently handle huge amounts of point clouds not in a whole group, but in forms of separate sub-groups with similar plane parameters. This method adopts robust principal component analysis to enhance estimation accuracy. Findings– Experimental results verify that the method not only shows enhanced performance in the plane extraction, but also broadens the domain of interest of the plane registration to an information-poor environment (such as simple indoor corridors), while the previous method only adequately works in an information-rich environment (such as a space with many features). Originality/value– The proposed algorithm has three advantages over the current state-of-the-art method in that it is fast, utilizes more inlier sensor data that does not become contaminated by severe sensor noise and extracts more accurate plane parameters.
VL  - 41
IS  - 2
SN  - 0143-991X
DO  - 10.1108/IR-04-2013-347
UR  - https://doi.org/10.1108/IR-04-2013-347
AU  - Yeon Suyong
AU  - Jun ChangHyun
AU  - Choi Hyunga
AU  - Kang Jaehyeon
AU  - Yun Youngmok
AU  - Lett Doh Nakju
PY  - 2014
Y1  - 2014/01/01
TI  - Robust-PCA-based hierarchical plane extraction for application to geometric 3D indoor mapping
T2  - Industrial Robot: An International Journal
PB  - Emerald Group Publishing Limited
SP  - 203
EP  - 212
Y2  - 2024/04/23
ER  -