NDLI: A Cost Effective Motion Platform for Performance Testing of MEMS-Based Attitude and Heading Reference Systems

Content Provider	Springer Nature Link
Author	Wachter, Zachary
Copyright Year	2012
Abstract	An accurate attitude and heading reference system (AHRS) is a key component to ensuring safe and reliable flight of unmanned aerial vehicles (UAVs). Recently, much attention has been given to developing AHRS using inertial sensors based on microelectromechanical sytems (MEMS). These MEMS-based AHRS are low-cost, lightweight, and consume little power. However, the advantages of inexpensive MEMS sensors are coupled with the drawback of having greater potential error in reported roll, pitch, and yaw angles due to increased sensor noise and drift. To minimize this error, advanced sensor fusion techniques such as Kalman Filtering are commonly implemented. Testing these techniques, and the AHRS as a whole, is therefore a crucial part of the performance optimization process. This paper outlines the development of an inexpensive 3-axis motion platform for AHRS calibration and testing that replicates aircraft motions from actual UAV flights, or from a flight simulator. To accomplish this, custom LabVIEW control software was developed to process time-stamped aircraft orientation data. Commands were then sent through a microcontroller to the motion platform, which reconstructs the flights with high precision (R$^{2}$ = .994). By using this method, AHRS testing can be performed under more realistic conditions, providing an alternative to costly field testing. This technique is especially useful for simulations of autonomous vehicle technologies such as collision avoidance, where an increased risk of damage to the UAV is present.
Starting Page	411
Ending Page	419
Page Count	9
File Format	PDF
ISSN	09210296
Journal	Journal of Intelligent & Robotic Systems
Volume Number	70
Issue Number	1-4
e-ISSN	15730409
Language	English
Publisher	Springer Netherlands
Publisher Date	2012-08-23
Publisher Place	Dordrecht
Access Restriction	Subscribed
Subject Keyword	Attitude and heading reference systems Inertial measurement MEMS Unmanned aerial vehicles Control, Robotics, Mechatronics Electrical Engineering Artificial Intelligence (incl. Robotics) Mechanical Engineering
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Artificial Intelligence Control and Systems Engineering Mechanical Engineering Electrical and Electronic Engineering Software

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