Automotive LiDAR

Automotive LiDAR research focuses on improving the accuracy, efficiency, and robustness of 3D point cloud data acquisition and processing for autonomous driving. Current efforts concentrate on developing efficient algorithms for scene flow estimation (using kernel methods and neural networks), LiDAR data completion and generation (leveraging compact representations and generative models), and robust sensor fusion techniques that handle noisy or misaligned data from multiple sensors. These advancements are crucial for enhancing the reliability and safety of autonomous vehicles by providing more accurate and complete environmental perception, even under challenging conditions.