Active Mapping

Active mapping focuses on efficiently exploring unknown environments by strategically planning sensor movements to maximize information gain. Current research emphasizes using neural representations, such as Neural Radiance Fields (NeRFs) and Gaussian splatting, alongside advanced algorithms like Riemannian optimization and information-theoretic approaches (e.g., maximizing Shannon mutual information) to guide exploration and build high-quality maps. This field is crucial for advancing robotics, autonomous navigation, and environmental monitoring, enabling more robust and efficient operation in unstructured or hazardous settings.