C Slam

Collaborative Simultaneous Localization and Mapping (C-SLAM) aims to enable multiple robots to concurrently build a map of their environment while simultaneously determining their own locations within that map. Current research focuses on developing robust and scalable algorithms, such as distributed optimization methods and neural network approaches, to handle the computational and communication challenges inherent in multi-robot systems, often incorporating diverse sensor modalities (visual, inertial, LiDAR). Improvements in C-SLAM accuracy and efficiency have significant implications for applications like autonomous drone surveying in challenging environments (e.g., forestry) and improved navigation in unstructured spaces, ultimately advancing robotics and automation.