Calibration of a Rotating Laser Range Finder using Intensity Features

Katuwandeniya, K; Ranasinghe, R; Dantanarayana, L; Dissanayake, G; Liu, D

Calibration of a Rotating Laser Range Finder using Intensity Features

Katuwandeniya, K Ranasinghe, R

Dantanarayana, L

Dissanayake, G

Liu, D

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Publication Type:: Conference Proceeding
Citation:: 2018 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018, 2018, pp. 228 - 234
Issue Date:: 2018-12-18

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Field	Value	Language
dc.contributor.author	Katuwandeniya, K	en_US
dc.contributor.author	Ranasinghe, R https://orcid.org/0000-0002-3785-3723	en_US
dc.contributor.author	Dantanarayana, L https://orcid.org/0000-0002-8887-329X	en_US
dc.contributor.author	Dissanayake, G https://orcid.org/0000-0002-7992-0680	en_US
dc.contributor.author	Liu, D https://orcid.org/0000-0002-1581-5582	en_US
dc.date.available	2020-12-20T18:03:09Z
dc.date.issued	2018-12-18	en_US
dc.identifier.citation	2018 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018, 2018, pp. 228 - 234	en_US
dc.identifier.isbn	9781538695821	en_US
dc.identifier.uri	http://hdl.handle.net/10453/132847
dc.description.abstract	© 2018 IEEE. This paper presents an algorithm for calibrating a '3D range sensor' constructed using a two-dimensional laser range finder (LRF), that is rotated about an axis using a motor to obtain a three-dimensional point cloud. The sensor assembly is modelled as a two degree of freedom open kinematic chain, with one joint corresponding to the axis of the internal mirror in the LRF and the other joint set along the axis of the motor used to rotate the body of the LRF. In the application described in this paper, the sensor unit is mounted on a robot arm used for infrastructure inspection. The objective of the calibration process is to obtain the coordinate transform required to compute the locations of the 3D points with respect to the robot coordinate frame. Proposed strategy uses observations of a set of markers arbitrarily placed in the environment. Distances between these markers are measured and a metric multidimensional scaling is used to obtain the coordinates of the markers with respect to a local coordinate frame. Intensity associated with each beam point of a laser scan is used to locate the reflective markers in the 3D point cloud and a least squares problem is formulated to compute the relationship between the robot coordinate frame, LRF coordinate frame and the marker coordinate frame. Results from experiments using the robot, LRF combination to map a cavity inside a steel bridge structure are presented to demonstrate the effectiveness of the calibration process.	en_US
dc.relation.ispartof	2018 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018	en_US
dc.relation.isbasedon	10.1109/ICARCV.2018.8581350	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Calibration of a Rotating Laser Range Finder using Intensity Features	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
utslib.copyright.status	open_access	*
pubs.publication-status	Published	en_US

Abstract:

© 2018 IEEE. This paper presents an algorithm for calibrating a '3D range sensor' constructed using a two-dimensional laser range finder (LRF), that is rotated about an axis using a motor to obtain a three-dimensional point cloud. The sensor assembly is modelled as a two degree of freedom open kinematic chain, with one joint corresponding to the axis of the internal mirror in the LRF and the other joint set along the axis of the motor used to rotate the body of the LRF. In the application described in this paper, the sensor unit is mounted on a robot arm used for infrastructure inspection. The objective of the calibration process is to obtain the coordinate transform required to compute the locations of the 3D points with respect to the robot coordinate frame. Proposed strategy uses observations of a set of markers arbitrarily placed in the environment. Distances between these markers are measured and a metric multidimensional scaling is used to obtain the coordinates of the markers with respect to a local coordinate frame. Intensity associated with each beam point of a laser scan is used to locate the reflective markers in the 3D point cloud and a least squares problem is formulated to compute the relationship between the robot coordinate frame, LRF coordinate frame and the marker coordinate frame. Results from experiments using the robot, LRF combination to map a cavity inside a steel bridge structure are presented to demonstrate the effectiveness of the calibration process.

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http://hdl.handle.net/10453/132847