Implement Kalman Filters for World State Representation

Description: Implement Kalman filters to improve the accuracy and reliability of our world state representation. The Kalman filter will help us smooth noisy sensor data and make better predictions about the positions of the ball, bots, and other moving entities on the field.

Tasks:

• Make sure you know what Kalman filters are.
• Implement a Kalman filter for tracking bot positions using sensor inputs.
• Implement a Kalman filter for tracking the ball's position and velocity.
• Test the Kalman filters by comparing filtered data to raw sensor data to confirm improvements in state estimation.
• Fine-tune filter parameters to optimize performance on the soccer field.

Acceptance Criteria:

• Kalman filters are successfully integrated into the world state representation.
• The Kalman filters improve accuracy in tracking bot and ball positions by reducing noise from sensor data.
• Documented code and instructions on how to use the filters.