Rigid Body Attitude Estimation- An Overview and Comparative Stud.pdf

Such operations require aerial vehicles with a

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c congestion and security applications. Such operations require aerial vehicles with a certain level of autonomy and manoeuvrability. Unmanned Aerial Vehicles (UAVs) have shown great potentials in many indoor and outdoor applications. These vehicles can either be very large or relatively small in size depending on the applications they are intended to. From the heavy weight military drones to small vertical take-o ff and landing (VTOL) UAVs, the control of all these flying vehicles relies on some crucial sensors that provide the necessary flight information. The UAV position, orientation and velocities are crucial states that need to be measured or estimated for the implementation of a successful motion control strategy. The position and linear velocity can be obtained using a Global Positioning System (GPS) for instance, while the angular velocity can be obtained using a body-attached gyroscope. As for the orientation (attitude), there is no sensor that measures it directly. However, the orientation is usually obtained using some attitude estimation algorithms relying on gyroscopic and 1
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C hapter 1. G eneral I ntroduction 2 body vector measurements. The earliest attempts to estimate the attitude of flying vehicles may go back to the time when mechanical gyroscopes, which provide measurements of angular velocity, were used in an integration process in which the knowledge of an initial attitude would be su ffi cient in finding the attitude in any other time. However, since these devices were primitive and usually had many problems with pressure, heat, etc., their ultimate performance was not satisfying and frequent restarting of the estimation process was required. With the advances in electronic devices, microelectromechanical systems (MEMS) have replaced those previous measurement devices. These components have provided low cost and light weight Inertial Measurement Units (IMUs) for both industrial and research applications. The use of body vector measurements sensors such as accelerometers and magnetometers have allowed researchers to design better attitude estimation algorithms. Probably one of the first and yet most influential works in the attitude estimation field was a mathematical problem proposed by Wahba in [Wahba, 1965]. The problem con- sists in finding the optimal attitude rotation matrix provided that a number of vectorial measurements are available. Several attempts to solve this problem resulted in the devel- opment of fast estimation methods, such as the Singular Value Decomposition (SVD) in [Markley, 1988], Quaternion Estimation (QUEST) in [Shuster and Oh, 1981], and Filter QUEST in [Shuster, 1989b], which were used in some of the NASA projects in 1980’s. Various solutions to the Wahba’s problem are categorized as a class of attitude estimators known as deterministic attitude estimators.
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