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Consistent, Convergent, and Constant-Time SLAM.

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 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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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author

Contributors

Role:
Editor
Role:
Editor


Publisher:
Morgan Kaufmann
Host title:
IJCAI
Pages:
1143-1150
Publication date:
2003-01-01
ISSN:
1045-0823


Pubs id:
pubs:392150
UUID:
uuid:f11ed738-ecb3-4c08-b52a-f24fc1f83337
Local pid:
pubs:392150
Source identifiers:
392150
Deposit date:
2013-11-17
ARK identifier:

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