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Uncalibrated Visual Compass from Omnidirectional Line Images with Application to Attitude MAV Estimation

Stefano Scheggi 1, * Fabio Morbidi 2, 3 Domenico Prattichizzo 1
* Corresponding author
2 NECS - Networked Controlled Systems
GIPSA-DA - Département Automatique, Inria Grenoble - Rhône-Alpes
Abstract : This paper presents a new algorithm based on previous results of the authors, for the estimation of the yaw angle of an omnidirectional camera robot undergoing a 6-DoF rigid motion. Our real-time algorithm is uncalibrated, robust to noisy data, and it only relies on the projection of 3-D parallel lines as image features. Numerical and real-world experiments conducted with an eye-in-hand robot manipulator, which we used to simulate the 3-D motion of a Micro unmanned Aerial Vehicle (MAV), show the accuracy and reliability of our estimation algorithm.
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Stefano Scheggi, Fabio Morbidi, Domenico Prattichizzo. Uncalibrated Visual Compass from Omnidirectional Line Images with Application to Attitude MAV Estimation. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2013), Nov 2013, Tokyo, Japan. pp.1602-1607. ⟨hal-00961584⟩

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