Abstract
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.
| Original language | English |
|---|---|
| Article number | 17107508 |
| Pages (from-to) | 203-212 |
| Number of pages | 10 |
| Journal | Industrial Robot |
| Volume | 41 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2014 Jan 1 |
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Keywords
- Hierarchical segmentation
- Plane extraction
- Plane registration
- Robust PCA
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
- Control and Systems Engineering
- Computer Science Applications
Cite this
Robust-PCA-based hierarchical plane extraction for application to geometric 3D indoor mapping. / Yeon, Suyong; Jun, Changhyun; Choi, Hyunga; Kang, Jaehyeon; Yun, Youngmok; Doh, Nakju.
In: Industrial Robot, Vol. 41, No. 2, 17107508, 01.01.2014, p. 203-212.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Robust-PCA-based hierarchical plane extraction for application to geometric 3D indoor mapping
AU - Yeon, Suyong
AU - Jun, Changhyun
AU - Choi, Hyunga
AU - Kang, Jaehyeon
AU - Yun, Youngmok
AU - Doh, Nakju
PY - 2014/1/1
Y1 - 2014/1/1
N2 - 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.
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.
KW - Hierarchical segmentation
KW - Plane extraction
KW - Plane registration
KW - Robust PCA
UR - http://www.scopus.com/inward/record.url?scp=84897401505&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84897401505&partnerID=8YFLogxK
U2 - 10.1108/IR-04-2013-347
DO - 10.1108/IR-04-2013-347
M3 - Article
AN - SCOPUS:84897401505
VL - 41
SP - 203
EP - 212
JO - Industrial Robot
JF - Industrial Robot
SN - 0143-991X
IS - 2
M1 - 17107508
ER -