Autonomous Robotic Map Refinement for Targeted Resolution and Local Accuracy

Smith, W; Qin, Y; Furukawa, T; Dissanayake, G

Autonomous Robotic Map Refinement for Targeted Resolution and Local Accuracy

Smith, W Qin, Y Furukawa, T Dissanayake, G

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Publisher:: Institute of Electrical and Electronics Engineers (IEEE)
Publication Type:: Conference Proceeding
Citation:: SSRR 2022 - IEEE International Symposium on Safety, Security, and Rescue Robotics, 2023, 00, pp. 130-137
Issue Date:: 2023-11-10

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Field	Value	Language
dc.contributor.author	Smith, W
dc.contributor.author	Qin, Y
dc.contributor.author	Furukawa, T
dc.contributor.author	Dissanayake, G https://orcid.org/0000-0002-7992-0680
dc.date	2022-12-08
dc.date.accessioned	2023-11-06T06:02:56Z
dc.date.available	2023-11-06T06:02:56Z
dc.date.issued	2023-11-10
dc.identifier.citation	SSRR 2022 - IEEE International Symposium on Safety, Security, and Rescue Robotics, 2023, 00, pp. 130-137
dc.identifier.isbn	978-1-6654-5680-7
dc.identifier.issn	2374-3247
dc.identifier.issn	2475-8426
dc.identifier.uri	http://hdl.handle.net/10453/173064
dc.description.abstract	This paper presents a multistage approach to refining the map of an environment and satisfying the targeted resolution and local accuracy by an autonomous mobile robot. The proposed approach consists of two steps. Having a globally accurate coarse map of the environment developed using a conventional technique such as SLAM or SfM with bundle adjustment, the proposed first step plans a path for the robot to revisit the environment while maintaining a desired distance to all occupied regions of interest since the resolution and the local accuracy of the map typically depends on the distance from which objects in the environment are observed. An Unoccupancy Distance Map (UDM) and a reduced-order Travelling Salesman Problem (TSP) techniques are newly proposed to solve this class of problems. In the final step, an online path replanning and map refinement technique is proposed to achieve the targeted resolution and local accuracy of the map. Parametric studies have firstly validated the effectiveness of the proposed two steps. The autonomous capability of the proposed approach has then been demonstrated successfully in its use for a practical mission.
dc.language	en
dc.publisher	Institute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartof	SSRR 2022 - IEEE International Symposium on Safety, Security, and Rescue Robotics
dc.relation.ispartof	IEEE International Symposium on Safety, Security, and Rescue Robotics
dc.relation.isbasedon	10.1109/ssrr56537.2022.10018686
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Autonomous Robotic Map Refinement for Targeted Resolution and Local Accuracy
dc.type	Conference Proceeding
utslib.citation.volume	00
utslib.location.activity	Sevilla, Spain
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
utslib.copyright.status	closed_access	*
pubs.consider-herdc	true
dc.date.updated	2023-11-06T06:02:55Z
pubs.finish-date	2022-12-10
pubs.place-of-publication	Piscataway, USA
pubs.publication-status	Published
pubs.start-date	2022-12-08
pubs.volume	00
dc.location	Piscataway, USA

Abstract:

This paper presents a multistage approach to refining the map of an environment and satisfying the targeted resolution and local accuracy by an autonomous mobile robot. The proposed approach consists of two steps. Having a globally accurate coarse map of the environment developed using a conventional technique such as SLAM or SfM with bundle adjustment, the proposed first step plans a path for the robot to revisit the environment while maintaining a desired distance to all occupied regions of interest since the resolution and the local accuracy of the map typically depends on the distance from which objects in the environment are observed. An Unoccupancy Distance Map (UDM) and a reduced-order Travelling Salesman Problem (TSP) techniques are newly proposed to solve this class of problems. In the final step, an online path replanning and map refinement technique is proposed to achieve the targeted resolution and local accuracy of the map. Parametric studies have firstly validated the effectiveness of the proposed two steps. The autonomous capability of the proposed approach has then been demonstrated successfully in its use for a practical mission.

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http://hdl.handle.net/10453/173064