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Research Article
Aug 14, 2018

Auto Takeoff and Precision Terminal-Phase Landing Using an Experimental Optical Flow Model for Global Positioning System/Inertial Navigation System Enhancement

Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
Volume 5, Issue 1

Abstract

The high estimated position error in current commercial-off-the-shelf (GPS/INS) impedes achieving precise autonomous takeoff and landing (TOL) flight operations. To overcome this problem, in this paper, we propose an integrated global positioning system (GPS)/inertial navigation system (INS)/optical flow (OF) solution in which the OF provides an accurate augmentation to the GPS/INS. To ensure accurate and robust OF augmentation, we have used a robust modeling method to estimate OF based on a set of real-time experiments conducted under various simulated helicopter-landing scenarios. Knowing that the accuracy of the OF measurements is dependent on the accuracy of the height measurements, we have developed a real-time testing environment to model and validate the obtained dynamic OF model at various heights. The performance of the obtained OF model matches the real OF sensor with 87.70% fitting accuracy. An accuracy of 0.006 m/s mean error between the real OF sensor velocity and the velocity of the OF model is also achieved. The velocity measurements of the obtained OF model and the position of the GPS/INS are used in performing a dynamic model-based sensor fusion algorithm. In the proposed solution, the OF sensor is engaged when the vehicle approaches a landing spot that is equipped with a predefined landing pattern. The proposed solution has succeeded in performing a helicopter auto TOL with a maximum position error of 27 cm. This article is available in the ASME Digital Collection at https://doi.org/10.1115/1.4039943.

Information & Authors

Information

Published In

Go to ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
Volume 5Issue 1March 2019

History

Received: Feb 11, 2017
Revision received: Apr 8, 2018
Published online: Aug 14, 2018
Published in print: Mar 1, 2019

Authors

Affiliations

Mohammad K. Al-Sharman [email protected]
Robotics Institute, Khalifa University of Science and Technology, P.O. Box 127788, Abu Dhabi, United Arab Emirates e-mail: [email protected]
Mohammad Amin Al-Jarrah [email protected]
Professor Department of Aeronautical Engineering, Higher Colleges of Technology, P.O. Box 15825, Dubai, United Arab Emirates e-mail: [email protected]
Mamoun Abdel-Hafez [email protected]
Professor Department of Mechanical Engineering, American University of Sharjah, P.O. Box 26666, Sharjah, United Arab Emirates e-mail: [email protected]

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