A sliding window approach to exploration for 3D map building using a biologically inspired bridge inspection robot

Paul, G; Quin, P; To, AWK; Liu, D

A sliding window approach to exploration for 3D map building using a biologically inspired bridge inspection robot

Paul, G

Quin, P

To, AWK Liu, D

Permalink

Publication Type:: Conference Proceeding
Citation:: 2015 IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, IEEE-CYBER 2015, 2015, pp. 1097 - 1102
Issue Date:: 2015-10-02

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download full textAdobe PDF (1.46 MB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Paul, G https://orcid.org/0000-0002-3478-0020	en_US
dc.contributor.author	Quin, P https://orcid.org/0000-0001-6542-3459	en_US
dc.contributor.author	To, AWK	en_US
dc.contributor.author	Liu, D https://orcid.org/0000-0002-1581-5582	en_US
dc.date.available	2015-03-10	en_US
dc.date.issued	2015-10-02	en_US
dc.identifier.citation	2015 IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, IEEE-CYBER 2015, 2015, pp. 1097 - 1102	en_US
dc.identifier.isbn	9781479987290	en_US
dc.identifier.uri	http://hdl.handle.net/10453/36649
dc.description.abstract	© 2015 IEEE. This paper presents a Sliding Window approach to viewpoint selection when exploring an environment using a RGB-D sensor mounted to the end-effector of an inchworm climbing robot for inspecting areas inside steel bridge archways which cannot be easily accessed by workers. The proposed exploration approach uses a kinematic chain robot model and information theory-based next best view calculations to predict poses which are safe and are able to reduce the information remaining in an environment. At each exploration step, a viewpoint is selected by analysing the Pareto efficiency of the predicted information gain and the required movement for a set of candidate poses. In contrast to previous approaches, a sliding window is used to determine candidate poses so as to avoid the costly operation of assessing the set of candidates in its entirety. Experimental results in simulation and on a prototype climbing robot platform show the approach requires fewer gain calculations and less robot movement, and therefore is more efficient than other approaches when exploring a complex 3D steel bridge structure.	en_US
dc.relation	http://purl.org/au-research/grants/arc/LP100200750
dc.relation.ispartof	2015 IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, IEEE-CYBER 2015	en_US
dc.relation.isbasedon	10.1109/CYBER.2015.7288098	en_US
dc.title	A sliding window approach to exploration for 3D map building using a biologically inspired bridge inspection robot	en_US
dc.type	Conference Proceeding
utslib.for	0913 Mechanical Engineering	en_US
dc.location.activity	Shenyang, China
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:

© 2015 IEEE. This paper presents a Sliding Window approach to viewpoint selection when exploring an environment using a RGB-D sensor mounted to the end-effector of an inchworm climbing robot for inspecting areas inside steel bridge archways which cannot be easily accessed by workers. The proposed exploration approach uses a kinematic chain robot model and information theory-based next best view calculations to predict poses which are safe and are able to reduce the information remaining in an environment. At each exploration step, a viewpoint is selected by analysing the Pareto efficiency of the predicted information gain and the required movement for a set of candidate poses. In contrast to previous approaches, a sliding window is used to determine candidate poses so as to avoid the costly operation of assessing the set of candidates in its entirety. Experimental results in simulation and on a prototype climbing robot platform show the approach requires fewer gain calculations and less robot movement, and therefore is more efficient than other approaches when exploring a complex 3D steel bridge structure.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/36649