Algorithm Overview
The Kalman Filter is a recursive estimation algorithm that provides a means of estimating the true state of a dynamic system, even in the presence of noise and uncertainty. In autonomous driving systems, the Kalman Filter is employed to fuse data from various sensors such as LIDAR, radar, and cameras to predict the position, velocity, and orientation of the vehicle, as well as those of surrounding objects. By continuously updating its estimates based on new measurements, the Kalman Filter enables the vehicle to navigate and control its motion more accurately, accounting for real-world uncertainties. This robust prediction and estimation capability is critical for ensuring the safety and reliability of autonomous vehicles.