State Estimation

Learning Objectives

• Implement the standard Kalman Filter for linear systems
• Apply Extended Kalman Filters (EKF) to non-linear kinematics
• Develop Particle Filters for global localization
• Handle sensor asynchrony and latency in filtering

Core Topics

Practical Exercise

Combine noisy IMU acceleration data and delayed GPS position data using an EKF to estimate vehicle trajectory.

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