Pin Slam

Pin-SLAM (Point-based Implicit Neural SLAM) focuses on creating accurate and globally consistent 3D maps using point cloud data, primarily from LiDAR but also applicable to other sensors like RGB-D cameras. Current research emphasizes efficient map representations, often employing implicit neural networks or novel data structures like Gaussian splatting and hierarchical grids, alongside advancements in robust pose estimation and loop closure detection algorithms. These improvements in SLAM technology are crucial for advancing autonomous navigation, robotics, and applications like augmented reality in surgery and 3D modeling of complex environments.