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Globally Asymptotically Stable Sensor-Based Simultaneous Localization and Mapping

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4 Author(s)
Bruno J. N. Guerreiro ; Inst. for Syst. & Robot., Tech. Univ. of Lisbon, Lisbon, Portugal ; Pedro Batista ; Carlos Silvestre ; Paulo Oliveira

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.

Published in:

IEEE Transactions on Robotics  (Volume:29 ,  Issue: 6 )