Robust SLAM

Robust SLAM (Simultaneous Localization and Mapping) aims to create navigation systems for robots and autonomous vehicles that are reliable and accurate even in challenging environments. Current research focuses on improving resilience to various factors, including dynamic objects, weak textures, and poor lighting conditions, through techniques like incorporating multiple sensor modalities (LiDAR, radar, vision), advanced data association algorithms, and robust loop closure detection and verification methods. These advancements are crucial for enabling safe and reliable operation of autonomous systems in real-world scenarios, impacting fields such as robotics, autonomous driving, and augmented reality.