SLAM System

Simultaneous Localization and Mapping (SLAM) systems aim to build a map of an unknown environment while simultaneously tracking the robot's location within that map. Current research emphasizes improving robustness and efficiency across diverse sensor modalities (LiDAR, cameras, event cameras, WiFi), often integrating deep learning for feature extraction, loop closure detection, and dynamic object handling. This active field is crucial for advancing autonomous navigation in robotics, augmented reality, and autonomous driving, with ongoing efforts focused on real-time performance, accuracy in challenging conditions, and efficient map representations.