NDLI: 3D mapping with multi-resolution occupied voxel lists

Content Provider	Springer Nature Link
Author	Ryde, Julian Hu, Huosheng
Copyright Year	2009
Abstract	Most current navigation algorithms in mobile robotics produce 2D maps from data provided by 2D sensors. In large part this is due to the availability of suitable 3D sensors and difficulties of managing the large amount of data supplied by 3D sensors. This paper presents a novel, multi-resolution algorithm that aligns 3D range data stored in occupied voxel lists so as to facilitate the construction of 3D maps. Multi-resolution occupied voxel lists (MROL) are voxel based data structures that efficiently represent 3D scan and map information. The process described in this research can align a sequence of scans to produce maps and localise a range sensor within a prior global map. An office environment (200 square metres) is mapped in 3D at 0.02 m resolution, resulting in a 200,000 voxel occupied voxel list. Global localisation within this map, with no prior pose estimate, is completed in 5 seconds on a 2 GHz processor. The MROL based sequential scan matching is compared to a standard iterative closest point (ICP) implementation with an error in the initial pose estimate of plus or minus 1 m and 90 degrees. MROL correctly scan matches 94% of scans to within 0.1 m as opposed to ICP with 30% within 0.1 m.
Starting Page	169
Ending Page	185
Page Count	17
File Format	PDF
ISSN	09295593
Journal	Autonomous Robots
Volume Number	28
Issue Number	2
e-ISSN	15737527
Language	English
Publisher	Springer US
Publisher Date	2009-09-30
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Mobile robotics Localisation 3D mapping 3D laser scanner SLAM Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence (incl. Robotics) Control , Robotics, Mechatronics Robotics and Automation
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence

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