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State Estimation and Kalman Filtering

State Estimation and Kalman Filtering. Sensors and Uncertainty. Real world sensors are noisy and suffer from missing data (e.g., occlusions, GPS blackouts) Use sensor models to estimate ground truth, unobserved variables, make forecasts. How does this relate to motion?. A robot must:

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