DocumentCode :
25518
Title :
Globally Asymptotically Stable Sensor-Based Simultaneous Localization and Mapping
Author :
Guerreiro, Bruno J. N. ; Batista, Pedro ; Silvestre, Carlos ; Oliveira, P.
Author_Institution :
Inst. for Syst. & Robot., Tech. Univ. of Lisbon, Lisbon, Portugal
Volume :
29
Issue :
6
fYear :
2013
fDate :
Dec. 2013
Firstpage :
1380
Lastpage :
1395
Abstract :
This paper presents the design, analysis, and experimental validation of a globally asymptotically stable (GAS) filter for simultaneous localization and mapping (SLAM), with application to unmanned aerial vehicles. The SLAM problem is formulated in a sensor-based framework and modified in such a way that the underlying system structure can be regarded as linear time varying for observability analysis and filter design purposes, from which a linear Kalman filter with GAS error dynamics follows naturally. The performance and consistency validation of the proposed sensor-based SLAM filter are successfully assessed with real data, acquired indoors, using an instrumented quadrotor.
Keywords :
Kalman filters; SLAM (robots); asymptotic stability; autonomous aerial vehicles; linear systems; observability; sensors; time-varying systems; GAS error dynamics; GAS filter; SLAM; globally asymptotically stable filter; globally asymptotically stable sensor-based simultaneous localization and mapping; instrumented quadrotor; linear Kalman filter design; linear time varying system; observability analysis; sensor-based SLAM filter; unmanned aerial vehicles; Nonlinear systems; Observability; Sensor fusion; Simultaneous localization and mapping; Unmanned aerial vehicles; Vehicle dynamics; Aerial robotics; globally asymptotically stable (GAS); mapping; sensor fusion; simultaneous localization and mapping (SLAM);
fLanguage :
English
Journal_Title :
Robotics, IEEE Transactions on
Publisher :
ieee
ISSN :
1552-3098
Type :
jour
DOI :
10.1109/TRO.2013.2273838
Filename :
6609095
Link To Document :
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