Standalone IMU positioning determining system for UAVs using artificial intelligenece
Date
2021-05
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Abstract
Inertial Measurement Units (IMUs) are Micro-Electromechanical Systems (MEMS) that are able
to provide acceleration angular orientation rates information via inertial sensing. Unlike other
positioning devices like the Global positioning System (GPS), they do not require any form of
communication with an external device or technology in order to obtain this information. This
makes them the ideal positioning devices to serve as standalone systems. However, with certain
drawbacks associated with the IMU they are unable to effectively serve in this role. Existing
schemes employ the use of Kalman filters as a complementary approach to solve this issue but this
also presents complexity and drawbacks resulting in the failure of the Kalman estimator especially
when there is no GPS signal available. This paper proposes a technique by employing the use of
an Artificial neural Network (ANN) to model certain state variables in order to estimate the
position of an Unmanned Aerial Vehicle (UAV) quadrotor with the IMU serivng as a standalone
positionng determing device.
Description
Capstone Project submitted to the Department of Engineering, Ashesi University in partial fulfillment of the requirements for the award of Bachelor of Science degree in Electrical and Electronic Engineering, May 2021
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Capstone project
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Keywords
drones, Inertial Measurement Unit