Abstract
Low-cost Unmanned Aerial Vehicles have large potential for applications in the civil sector. Cheap inertial sensors alone can not provide the degree of accuracy required for control and navigation of the UAVs. Additional sensors, and sensor fusion techniques are needed to reduce the state estimation error. In the context of this work, the possibility of using visual information to augment the inertial data is investigated. The projected image of the ground plane is processed by a homography constrained optical flow description and used as a measurement update for an EKF. A simulation environment is used, which models the UAV dynamics, the rate-gyro and accelerometer errors as well as a low resolution vision system.
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© 2008 Springer-Verlag Berlin Heidelberg
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Schwendner, J. (2008). Homography Based State Estimation for Aerial Robots. In: Dengel, A.R., Berns, K., Breuel, T.M., Bomarius, F., Roth-Berghofer, T.R. (eds) KI 2008: Advances in Artificial Intelligence. KI 2008. Lecture Notes in Computer Science(), vol 5243. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85845-4_41
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DOI: https://doi.org/10.1007/978-3-540-85845-4_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85844-7
Online ISBN: 978-3-540-85845-4
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