We investigate robots that can understand their environment semantically and geometrically, in order to perform manipulation and other safety critical tasks in proximity to humans. This encompasses semantic understanding under open-set conditions, map representations of the environment, active perception and planning, as well as adaptation and continual self-supervised learning.
SNI-SLAM++: Tightly-Coupled Semantic Neural Implicit SLAM
IEEE Transactions on Pattern Analysis and Machine Intelligence 2025