Collaborative Mapping

Collaborative mapping focuses on integrating data from multiple sources, such as robots or sensors, to create a more accurate and comprehensive map than any single source could provide. Current research emphasizes efficient algorithms for fusing data from diverse sources, including lightweight approaches for resource-constrained devices and distributed methods using neural networks (like NeRFs) or graph-based techniques for handling inconsistencies and improving global map consistency. This field is crucial for advancing robotics, autonomous driving, and environmental monitoring, enabling more robust and scalable solutions for mapping large-scale or dynamic environments.