2 Dimensional LiDAR

Two-dimensional LiDAR, a cost-effective alternative to 3D LiDAR, is increasingly used in robotics and autonomous systems for tasks like navigation, mapping, and object detection. Current research focuses on improving the accuracy and robustness of 2D LiDAR-based solutions, often through sensor fusion with cameras or IMUs, and employing advanced algorithms like deep learning (including transformer networks and multi-head self-attention) and particle filters for tasks such as SLAM and localization. These advancements are enabling more reliable and efficient operation of mobile robots in diverse indoor and outdoor environments, particularly in applications where computational constraints are significant.