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A Model-aided Optical Flow/Inertial Sensor Fusion Method for a Quadrotor

Published online by Cambridge University Press:  12 August 2016

Pin Lyu
(College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China) (Institute for Aerospace Studies, University of Toronto, Toronto, Canada)
Jizhou Lai*
(College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China)
Hugh H.T. Liu
(Institute for Aerospace Studies, University of Toronto, Toronto, Canada)
Jianye Liu
(College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China)
Wenjing Chen
(College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China)


In this paper, a fault-tolerant velocity estimation method is proposed for quadrotors in a GPS denied environment. A novel filter is developed in light of the quadrotor model and measurements from optical flow and inertial sensors. The proposed filter is capable of detecting and isolating the optical flow sensor faults, by which the velocity estimation accuracy and stability will be improved. It is also demonstrated that the wind velocity is observable in the proposed filter. Therefore, the new filter can also be implemented in a windy environment, which is a significant improvement to the previous model-aided inertial sensor estimator. At the end, some simulations are carried out to verify the advantages of our method.

Research Article
Copyright © The Royal Institute of Navigation 2016 

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