Toward Physics-Aware Deep Learning Architectures for LiDAR Intensity Simulation

arXiv:2404.15774v1 Announce Type: new
Abstract: Autonomous vehicles (AVs) heavily rely on LiDAR perception for environment understanding and navigation. LiDAR intensity provides valuable information about the reflected laser signals and plays a crucial role in enhancing the perception capabilities of AVs. However, accurately simulating LiDAR intensity remains a challenge due to the unavailability of material properties of the objects in the environment, and complex interactions between the laser beam and the environment. The proposed method aims to improve the accuracy of …

abstract architectures arxiv autonomous autonomous vehicles avs capabilities challenge cs.ai cs.cv deep learning eess.iv environment however information intensity lidar navigation perception physics role simulation type understanding vehicles