Lippiello, Vincenzo and Loianno, Giuseppe and Siciliano, Bruno (2011) MAV indoor navigation based on a closed-form solution for absolute scale velocity estimation using Optical Flow and inertial data. In: 2011 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC) Orlando, FL, USA, December 12-15, 2011. IEEE, pp. 3566-3571. ISBN 978-1-61284-800-6
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| Tipologia del documento: | Capitolo di libro |
|---|---|
| Lingua: | English |
| Titolo: | MAV indoor navigation based on a closed-form solution for absolute scale velocity estimation using Optical Flow and inertial data |
| Autori: | Autore Email Lippiello, Vincenzo [non definito] Loianno, Giuseppe [non definito] Siciliano, Bruno [non definito] |
| Data: | 2011 |
| Numero di pagine: | 6 |
| Istituzione: | Università degli Studi di Napoli Federico II |
| Dipartimento: | Ingegneria elettrica e delle Tecnologie dell'Informazione |
| Titolo dell'opera che contiene il documento: | 2011 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC) Orlando, FL, USA, December 12-15, 2011 |
| Editore: | IEEE |
| Data: | 2011 |
| ISBN: | 978-1-61284-800-6 |
| Intervallo di pagine: | pp. 3566-3571 |
| Numero di pagine: | 6 |
| Diritti di accesso: | Accesso aperto |
| Informazioni aggiuntive: | AIRobots |
| Depositato il: | 23 Giu 2014 11:00 |
| Ultima modifica: | 17 Mag 2017 17:28 |
| URI: | http://www.fedoa.unina.it/id/eprint/9589 |
Abstract
A new vision-based obstacle avoidance technique for indoor navigation of Micro Aerial Vehicles (MAVs) is presented in this paper. The vehicle trajectory is modified according to the obstacles detected through the Depth Map of the surrounding environment, which is computed online using the Optical Flow provided by a single onboard omnidirectional camera. An existing closed-form solution for the absolute-scale velocity estimation based on visual correspondences and inertial measurements is generalized and here employed for the Depth Map estimation. Moreover, a dynamic region-of-interest for image features extraction and a self-limitation control for the navigation velocity are proposed to improve safety in view of the estimated vehicle velocity. The proposed solutions are validated by means of simulations.
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