Whelan, Thomas and Ma, L. and Bondarev, Egor and de With, Peter H.N. and McDonald, John (2015) Incremental and batch planar simplification of dense point cloud maps. Robotics and Autonomous Systems, 69. pp. 3-14. ISSN 0921-8890

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Abstract

Dense RGB-D SLAM techniques and high-fidelity LIDAR scanners are examples from an abundant set of systems capable of providing multi-million point datasets. These datasets quickly become difficult to process due to the sheer volume of data, typically containing significant redundant information, such as the representation of planar surfaces with millions of points. In order to exploit the richness of information provided by dense methods in real-time robotics, techniques are required to reduce the inherent redundancy of the data. In this paper we present a method for incremental planar segmentation of a gradually expanding point cloud map and a method for efficient triangulation and texturing of planar surface segments. Experimental results show that our incremental segmentation method is capable of running in real-time while producing a segmentation faithful to what would be achieved using a batch segmentation method. Our results also show that the proposed planar simplification and triangulation algorithm removes more than 90% of the input planar points, leading to a triangulation with only 10% of the original quantity of triangles per planar segment. Additionally, our texture generation algorithm preserves all colour information contained within planar segments, resulting in a visually appealing and geometrically accurate simplified representation.

Item Type:	Article
Additional Information:	This is a preprint of the published article, which is available at DOI: 10.1016/j.robot.2014.08.019
Keywords:	Planar simplification; Point clouds; Mapping; Plane segmentation; Triangulation; Incremental;
Academic Unit:	Faculty of Science and Engineering > Computer Science
Item ID:	8272
Identification Number:	https://doi.org/10.1016/j.robot.2014.08.019
Depositing User:	John McDonald
Date Deposited:	01 Jun 2017 16:06
Journal or Publication Title:	Robotics and Autonomous Systems
Publisher:	Elsevier
Refereed:	Yes
URI:	http://www.sciencedirect.com
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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