Occupancy Grid

Occupancy grids are probabilistic representations of an environment, mapping space into cells indicating the likelihood of occupancy by obstacles. Current research focuses on enhancing these grids by incorporating semantic information, predicting unseen areas (like walls or occluded spaces) using techniques like deep learning and autoregressive models, and integrating them with control systems for safe robot navigation. This work is crucial for advancing autonomous systems, particularly in robotics and autonomous driving, by enabling more robust perception, planning, and decision-making in dynamic and uncertain environments.