A robust solution to the stereo-vision-based simultaneous localization and mapping problem with steady and moving landmarks

Pathirana, Pubudu N., Savkin, Andrey V., Ekanayake, Samitha W. and Bauer, Nicholas J. 2011, A robust solution to the stereo-vision-based simultaneous localization and mapping problem with steady and moving landmarks, Advanced robotics, vol. 25, no. 6-7, pp. 765-788.

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Title A robust solution to the stereo-vision-based simultaneous localization and mapping problem with steady and moving landmarks
Author(s) Pathirana, Pubudu N.
Savkin, Andrey V.
Ekanayake, Samitha W.
Bauer, Nicholas J.
Journal name Advanced robotics
Volume number 25
Issue number 6-7
Start page 765
End page 788
Publisher VSP
Place of publication Leiden, Netherlands
Publication date 2011
ISSN 0169-1864
1568-5535
Keyword(s) robust filtering
robust state estimation
stable SLAM
visual SLAM
Summary The problem of visual simultaneous localization and mapping (SLAM) is examined in this paper using recently developed ideas and algorithms from modern robust control and estimation theory. A nonlinear model for a stereo-vision-based sensor is derived that leads to nonlinear measurements of the landmark coordinates along with optical flow-based measurements of the relative robot-landmark velocity. Using a novel analytical measurement transformation, the nonlinear SLAM problem is converted into the linear domain and solved using a robust linear filter. Actually, the linear filter is guaranteed stable and the SLAM state estimation error is bounded within an ellipsoidal set. A mathematically rigorous stability proof is given that holds true even when the landmarks move in accordance with an unknown control input. No similar results are available for the commonly employed extended Kalman filter, which is known to exhibit divergence and inconsistency characteristics in practice. A number of illustrative examples are given using both simulated and real vision data that further validate the proposed method.
Language eng
Field of Research 090602 Control Systems, Robotics and Automation
Socio Economic Objective 861604 Integrated Systems
HERDC Research category C1 Refereed article in a scholarly journal
HERDC collection year 2011
Copyright notice ©2011, Koninklijke Brill NV, Leiden and The Robotics Society of Japan
Persistent URL http://hdl.handle.net/10536/DRO/DU:30040638

Document type: Journal Article
Collection: School of Engineering
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