LiDAR Frame

A LiDAR frame, a single snapshot of data from a Light Detection and Ranging (LiDAR) sensor, is a fundamental unit in various applications, particularly autonomous driving and robotics. Current research focuses on improving the accuracy and robustness of LiDAR-based systems by addressing challenges such as limited data availability, varying field-of-view, and noisy or sparse point clouds, often employing techniques like deep learning (e.g., neural radiance fields, 3D convolutional networks), Kalman filtering, and optimal transport. These advancements are crucial for enhancing the reliability and precision of 3D scene understanding, object detection, and localization, ultimately impacting the safety and efficiency of autonomous systems.