Collaborative SLAM

Collaborative Simultaneous Localization and Mapping (SLAM) focuses on enabling multiple robots to cooperatively build a map of an unknown environment while simultaneously determining their own locations within that map. Current research emphasizes efficient data sharing and distributed computation, employing techniques like centralized pose graph optimization, multi-level partitioning algorithms, and the use of high-level semantic information to reduce communication overhead and improve robustness. This field is crucial for advancing multi-robot systems in various applications, including autonomous exploration, search and rescue, and automated driving, by enabling more complex and reliable collaborative tasks in GPS-denied environments.