Active SLAM in 3D deformable environments

Xu, M; Zhao, L; Huang, S; Hao, Q

Active SLAM in 3D deformable environments

Xu, M Zhao, L Huang, S

Hao, Q

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: IEEE International Conference on Intelligent Robots and Systems, 2022, 2022-October, pp. 7952-7958
Issue Date:: 2022-01-01

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Field	Value	Language
dc.contributor.author	Xu, M
dc.contributor.author	Zhao, L
dc.contributor.author	Huang, S https://orcid.org/0000-0002-6124-4178
dc.contributor.author	Hao, Q
dc.date	2022-10-23
dc.date.accessioned	2023-03-09T05:26:05Z
dc.date.available	2023-03-09T05:26:05Z
dc.date.issued	2022-01-01
dc.identifier.citation	IEEE International Conference on Intelligent Robots and Systems, 2022, 2022-October, pp. 7952-7958
dc.identifier.isbn	9781665479271
dc.identifier.issn	2153-0858
dc.identifier.issn	2153-0866
dc.identifier.uri	http://hdl.handle.net/10453/166817
dc.description.abstract	This paper considers active SLAM problem for 3D deformable environments where the trajectory of the robot is planned to optimize the SLAM results. A planning strategy combining an efficient global planner with an accurate local planner is proposed to solve the problem. Simulation results under different scenarios have shown that the proposed active SLAM algorithm provides a good balance between accuracy and efficiency as compared to the local planner and the global planner. The MATLAB code of this first active SLAM algorithm for 3D deformable environments is made publicly available4.
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	IEEE International Conference on Intelligent Robots and Systems
dc.relation.ispartof	2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
dc.relation.isbasedon	10.1109/IROS47612.2022.9982224
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Active SLAM in 3D deformable environments
dc.type	Conference Proceeding
utslib.citation.volume	2022-October
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/Strength - RI - Robotics Institute
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
utslib.copyright.status	open_access	*
dc.date.updated	2023-03-09T05:26:03Z
pubs.finish-date	2022-10-27
pubs.publication-status	Published
pubs.start-date	2022-10-23
pubs.volume	2022-October

Abstract:

This paper considers active SLAM problem for 3D deformable environments where the trajectory of the robot is planned to optimize the SLAM results. A planning strategy combining an efficient global planner with an accurate local planner is proposed to solve the problem. Simulation results under different scenarios have shown that the proposed active SLAM algorithm provides a good balance between accuracy and efficiency as compared to the local planner and the global planner. The MATLAB code of this first active SLAM algorithm for 3D deformable environments is made publicly available4.

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http://hdl.handle.net/10453/166817