NDLI: Extracting Edge Voxels from 3D Volumetric Maps to Reduce Map Size and Accelerate Mapping Alignment

Content Provider	IEEE Xplore Digital Library
Author	Ryde, J. Delmerico, J.A.
Copyright Year	2012
Abstract	For effective mobile robots we need a concise yet adequately descriptive mechanism for representing their surroundings. Traditionally 2D occupancy grids have proven effective for task such as SLAM, path planning and obstacle avoidance. Applying this to 3D maps requires consideration due to the large memory requirements of the resulting dense arrays. Approaches to address this, such as octrees and occupied voxel lists, take advantage of the relative sparsity of occupied voxels. We enhance the occupied voxel list representation by filtering out those voxels that are on planar sections of the environment to leave edge-like voxels. To do this we apply a structure tensor operation to the voxel map followed by a classification of the eigen values to remove voxels that are part of flat regions such as floors, walls and ceilings. This leaves the voxels tracing the edges of the environment producing a wire-frame like model. Fewer edge voxels require less memory and enable faster alignment. We compare the performance of scan-to-map matching of extracted edge voxels with that of the corresponding full 3D scans. We show that alignment accuracy is preserved when using edge voxels, while achieving a five times speedup and reduced memory requirements, compared to matching with all occupied voxels. It is posited that these edge voxel maps could also be useful for appearance based localisation.
Starting Page	330
Ending Page	337
File Size	586569
Page Count	8
File Format	PDF
ISBN	9781467312714
DOI	10.1109/CRV.2012.50
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-05-28
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Tensile stress Simultaneous localization and mapping mapping SLAM Image edge detection Memory management localisation Feature extraction Eigenvalues and eigenfunctions edge detection Data mining voxels
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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