LiDAR Perception

LiDAR perception focuses on using light detection and ranging (LiDAR) sensor data to understand 3D environments, primarily for autonomous vehicles. Current research emphasizes improving the robustness and efficiency of LiDAR perception systems, focusing on techniques like data augmentation (including generative models from text descriptions), novel evaluation metrics (e.g., perception entropy), and the development of efficient multi-task networks (often based on transformer architectures) that handle object detection, segmentation, and motion estimation simultaneously. These advancements are crucial for enhancing the reliability and safety of autonomous systems, particularly in challenging conditions like adverse weather or when dealing with limited sensor resources.