Autonomous Navigation





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Course Contents

Course introduction, basic definition, notion, guidance, navigation, and control loops. Review to linear algebra. Coordinated frames, kinematics and dynamics, trim conditions. Linear control and autopilot design. Introduction to probability and random processes. Accelerometer, rate gyros, pressure sensors, magnetometers, inertial measurement units (IMUs), global positioning systems (GPS). State estimation: Kalman filter (KF), Extended Kalman filter(EKF), Unscented Kalman filter (UKF), Cubature Kalman filter (CKF), Information filters, GPS aided navigation. Path planning and path following algorithms. Controllability, observability, vision guided navigation. Cooperative control. 


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