Consistent, Convergent, and Constant-Time SLAM.

This paper presents a new efficient algorithm for simultaneous localization and mapping (SLAM), using multiple overlapping submaps, each built with respect to a local frame of reference defined by one of the features in the submap. The global position of each submap is estimated using information fr...

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Bibliographic Details
Main Authors: Leonard, J, Newman, P
Other Authors: Gottlob, G
Format: Conference item
Published: Morgan Kaufmann 2003
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author Leonard, J
Newman, P
author2 Gottlob, G
author_facet Gottlob, G
Leonard, J
Newman, P
author_sort Leonard, J
collection OXFORD
description This paper presents a new efficient algorithm for simultaneous localization and mapping (SLAM), using multiple overlapping submaps, each built with respect to a local frame of reference defined by one of the features in the submap. The global position of each submap is estimated using information from other submaps in an efficient, provably consistent manner. For situations where the mobile robot is able to make repeated visits to all regions of the environment, the method achieves convergence to a near-optimal result with O(1) time complexity while maintaining consistent error bounds. Simulation results demonstrate the ability of the technique to converge to errors that are only slightly greater than the full solution, while maintaining consistency.
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spelling oxford-uuid:f11ed738-ecb3-4c08-b52a-f24fc1f833372022-03-27T11:53:35ZConsistent, Convergent, and Constant-Time SLAM.Conference itemhttp://purl.org/coar/resource_type/c_5794uuid:f11ed738-ecb3-4c08-b52a-f24fc1f83337Symplectic Elements at OxfordMorgan Kaufmann2003Leonard, JNewman, PGottlob, GWalsh, TThis paper presents a new efficient algorithm for simultaneous localization and mapping (SLAM), using multiple overlapping submaps, each built with respect to a local frame of reference defined by one of the features in the submap. The global position of each submap is estimated using information from other submaps in an efficient, provably consistent manner. For situations where the mobile robot is able to make repeated visits to all regions of the environment, the method achieves convergence to a near-optimal result with O(1) time complexity while maintaining consistent error bounds. Simulation results demonstrate the ability of the technique to converge to errors that are only slightly greater than the full solution, while maintaining consistency.
spellingShingle Leonard, J
Newman, P
Consistent, Convergent, and Constant-Time SLAM.
title Consistent, Convergent, and Constant-Time SLAM.
title_full Consistent, Convergent, and Constant-Time SLAM.
title_fullStr Consistent, Convergent, and Constant-Time SLAM.
title_full_unstemmed Consistent, Convergent, and Constant-Time SLAM.
title_short Consistent, Convergent, and Constant-Time SLAM.
title_sort consistent convergent and constant time slam
work_keys_str_mv AT leonardj consistentconvergentandconstanttimeslam
AT newmanp consistentconvergentandconstanttimeslam