A Random Finite Set Approach for Dynamic Occupancy Grid Maps with Real-Time Application

Understand

Grid mapping is a well established approach for environment perception in robotic and automotive applications.

• Early work suggests estimating the occupancy state of each grid cell in a robot's environment using a Bayesian filter to recursively combine new measurements with the current posterior state estimate of each grid cell.
• This filter is often referred to as binary Bayes filter (BBF).
• A basic assumption of classical occupancy grid maps is a stationary environment.