DocumentCode :
2059385
Title :
Prior-knowledge assisted fast 3D map building of structured environments for steel bridge maintenance
Author :
Sehestedt, Stephan ; Paul, Gay ; Rushton-Smith, David ; Dikai Liu
Author_Institution :
Fac. of Eng., Univ. of Technol., Sydney, NSW, Australia
fYear :
2013
fDate :
17-20 Aug. 2013
Firstpage :
1040
Lastpage :
1046
Abstract :
Practical application of a robot in a structured, yet unknown environment, such as in bridge maintenance, requires the robot to quickly generate an accurate map of the surfaces in the environment. A consistent and complete map is fundamental to achieving reliable and robust operation. In a real-world and field application, sensor noise and insufficient exploration oftentimes result in an incomplete map. This paper presents a robust environment mapping approach using prior knowledge in combination with a single depth camera mounted on the end-effector of a robotic manipulator. The approach has been successfully implemented in an industrial setting for the purpose of steel bridge maintenance. A prototype robot, which includes the presented map building approach in its software package, has recently been delivered to industry.
Keywords :
bridges (structures); end effectors; industrial manipulators; maintenance engineering; solid modelling; steel; structural engineering computing; end effectors; environment mapping approach; prior-knowledge assisted fast 3D map building; robotic manipulators; sensors; software package; steel bridge maintenance; Bridges; Iterative closest point algorithm; Maintenance engineering; Robot sensing systems; Service robots; Steel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation Science and Engineering (CASE), 2013 IEEE International Conference on
Conference_Location :
Madison, WI
ISSN :
2161-8070
Type :
conf
DOI :
10.1109/CoASE.2013.6653892
Filename :
6653892
Link To Document :
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