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Licenciatura degree in Electrical Engineering from the Instituto Superior Tecnico (IST) of Lisbon, Portugal
- Publisher
- Springer Journals
- Copyright
- Copyright © 2015 by Springer Science+Business Media New York
- Subject
- Engineering; Robotics and Automation; Artificial Intelligence (incl. Robotics); Computer Imaging, Vision, Pattern Recognition and Graphics; Control, Robotics, Mechatronics
- ISSN
- 0929-5593
- eISSN
- 1573-7527
- DOI
- 10.1007/s10514-015-9499-z
- Publisher site
- See Article on Publisher Site
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 main contributions of this paper are the results of global convergence and stability for SLAM in tridimensional (3-D) environments. The SLAM problem is formulated in a sensor-based framework and modified in such a way that the structure may be regarded as linear time-varying for observability purposes, from which a Kalman filter with GAS error dynamics follows naturally. The proposed solution includes the estimation of both body-fixed linear velocity and rate gyro measurement biases. Experimental results from several runs, using an instrumented quadrotor equipped with a RGB-D camera, are included in the paper to illustrate the performance of the algorithm under realistic conditions.
Journal
Autonomous Robots – Springer Journals
Published: Sep 24, 2015