LiDAR Data

LiDAR data, representing three-dimensional point clouds of the environment, is crucial for applications like autonomous driving and robotics, primarily aiming to achieve accurate scene understanding and object detection. Current research focuses on improving data quality through denoising techniques and motion correction algorithms, often integrating LiDAR with other sensor modalities (e.g., cameras, radar, IMUs) and employing advanced architectures like transformers and neural radiance fields for processing and analysis. These advancements are driving significant improvements in the accuracy and robustness of 3D perception, with broad implications for various fields including autonomous navigation, mapping, and environmental monitoring.