Three new Iterative Closest Point variant-methods that improve scan matching for surface mining terrain

Donoso, F. A., Austin, K. J. and McAree, P. R. (2017) Three new Iterative Closest Point variant-methods that improve scan matching for surface mining terrain. Robotics and Autonomous Systems, 95 117-128. doi:10.1016/j.robot.2017.05.003


Author Donoso, F. A.
Austin, K. J.
McAree, P. R.
Title Three new Iterative Closest Point variant-methods that improve scan matching for surface mining terrain
Journal name Robotics and Autonomous Systems   Check publisher's open access policy
ISSN 0921-8890
1872-793X
Publication date 2017-09-01
Sub-type Article (original research)
DOI 10.1016/j.robot.2017.05.003
Open Access Status Not yet assessed
Volume 95
Start page 117
End page 128
Total pages 12
Place of publication Amsterdam, Netherlands
Publisher Elsevier BV * North-Holland
Language eng
Keyword Eigentropy
Entropy measures
Iterative Closest Point
Point cloud registration algorithms
Terrain mapping
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Mechanical & Mining Engineering Publications
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Created: Fri, 15 Sep 2017, 09:09:29 EST by Professor Ross Mcaree on behalf of School of Mechanical and Mining Engineering