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ISSN: 2168-9792

Journal of Aeronautics & Aerospace Engineering
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Research Article

A Low-cost Vision Based Navigation System for Small Size Unmanned Aerial Vehicle Applications

Roberto Sabatini R1*, Richardson M2, Bartel C1, Shaid T1 and Ramasamy S1
1Department of Aerospace Engineering, Cranfield University, Bedford MK43 0AL, UK
2UK Defence Academy, Cranfield University, Shrivenham, Swindon,Wiltshire, SN6 8LA, UK
*Corresponding Author : Roberto Sabatini
Lecturer, Department of Aerospace Engineering
Cranfield University, Bedford MK43 0AL, UK
Tel: +44 (0)1234 758290
E-mail: [email protected]
Received December 08, 2012; Accepted April 26, 2013; Published May 04, 2013
Citation: Roberto Sabatini R, Richardson M, Bartel C, Shaid T, Ramasamy S (2013) A Low-cost Vision Based Navigation System for Small Size Unmanned Aerial Vehicle Applications. J Aeronaut Aerospace Eng 2:110. doi: 10.4172/2168-9792.1000110
Copyright: © 2013 Roberto Sabatini R, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

A low cost navigation system based on Vision Based Navigation (VBN) and other avionics sensors is presented, which is designed for small size Unmanned Aerial Vehicle (UAV) applications. The main objective of our research is to design a compact, lightweight and relatively inexpensive system capable of providing the required navigation performance in all phases of flight of a small UAV, with a special focus on precision approach and landing, where Vision Based Navigation (VBN) techniques can be fully exploited in a multisensory integrated architecture. Various existing techniques for VBN are compared and the Appearance-based Navigation (ABN) approach is selected for implementation. Feature extraction and optical flow techniques are employed to estimate flight parameters such as roll angle, pitch angle, deviation from the runway and body rates. Additionally, we address the possible synergies between VBN, Global Navigation Satellite System (GNSS) and MEMS-IMU (Micro-Electromechanical System Inertial Measurement Unit) sensors and also the use of Aircraft Dynamics Models (ADMs) to provide additional information suitable to compensate for the shortcomings of VBN and MEMS-IMU sensors in high-dynamics attitude determination tasks. An Extended Kalman Filter (EKF) is developed to fuse the information provided by the different sensors and to provide estimates of position, velocity and attitude of the UAV platform in real-time. Two different integrated navigation system architectures are implemented. The first uses VBN at 20 Hz and GPS at 1 Hz to augment the MEMS-IMU running at 100 Hz. The second mode also includes the ADM (computations performed at 100 Hz) to provide augmentation of the attitude channel. Simulation of these two modes is performed in a significant portion of the AEROSONDE UAV operational flight envelope and performing a variety of representative manoeuvres (i.e., straight climb, level turning, turning descent and climb, straight descent, etc.). Simulation of the first integrated navigation system architecture (VBN/IMU/GPS) shows that the integrated system can reach position, velocity and attitude accuracies compatible with CAT-II precision approach requirements. Simulation of the second system architecture (VBN/IMU/GPS/ADM) also shows promising results since the achieved attitude accuracy is higher using the ADM/VBS/IMU than using VBS/IMU only. However, due to rapid divergence of the ADM virtual sensor, there is a need for frequent re-initialisation of the ADM data module, which is strongly dependent on the UAV flight dynamics and the specific manoeuvring transitions performed.

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