Occupancy grid map-based extended object tracking

Robust tracking of extended objects plays a major role in research on highly automated driving applications and advanced driver assistance systems. This paper proposes a new approach to estimate the extension of dynamic objects based on object-local occupancy grid maps. This enables estimating free-formed object shapes while being robust against errors coming from, e.g., incorrect segmentation or association. Its benefit is shown based on 4-layer laser scanner sensor data and is evaluated against a ground truth based on a D-GPS system fused with a highly accurate IMU.