GEN 078

State Estimation and Filtering for Robotic Perception

Stanford University · UGRD · Fall 2026

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Kalman filtering, recursive Bayesian filtering, and nonlinear filter architectures including the extended Kalman filter, particle filter, and unscented Kalman filter. Observer-based state estimation for linear and non-linear systems. Examples from aerospace, including state estimation for fixed-wing aircraft, rotorcraft, spacecraft, and planetary rovers, with applications to control, navigation, and autonomy.

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Class #stanford-0078Fall 2026UGRD3 credits
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