Abstract: Autonomous mobile robots often struggle to navigate dynamic environments where obstacles may appear, disappear, or move unpredictably. Traditional static mapping approaches fail to provide ...

Training deep learning models for semantic occupancy prediction is challenging due to factors such as a large number of occupancy cells, severe occlusion, limited visual cues, complicated driving ...

Abstract: Occupancy mapping is a fundamental component of robotic systems to reason about the unknown and known regions of the environment. This article presents an efficient occupancy mapping ...