Consistent, Convergent, and Constant-Time SLAM
Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence. Pages 1143-1149.
Abstract
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 0(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.
@inproceedings{ijcai2003p163,
title = {Consistent, Convergent, and Constant-Time SLAM},
author = {Leonard, John J. and Newman, Paul M.},
booktitle = {Proceedings of the Eighteenth International Joint Conference on
Artificial Intelligence, {IJCAI-03}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Georg Gottlob},
pages = {1143--1149},
year = {2003},
url = {https://ijcai.org/proceedings/2003/163},
}
TY - CPAPER TI - Consistent, Convergent, and Constant-Time SLAM AU - Leonard, John J. AU - Newman, Paul M. T2 - Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, IJCAI-03 PB - International Joint Conferences on Artificial Intelligence PY - 2003 SP - 1143 EP - 1149 UR - https://ijcai.org/proceedings/2003/163 ER -Copied
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