Hypermaps improves how robots manage data about the environment they inhabit. The most common way for robots to handle environmental information is by using maps. At present, each different kind of data is hosted on a separate map. Similarly to how our use of maps have evolved from single-purpose maps (geographical, political, road map, etc.) to multi-layer maps (like Google Maps) which present us task-relevant information automatically, we propose a multi-layer mapping framework for robots. Hypermaps simplifies the way robots access maps and helps them correlate information from different maps. This enables robots to increase their ability to understand the world around them, perform more advanced tasks than what they can today, better understand user requests, and autonomously correct their knowledge about the environment. The research will be conducted in Aalto University, in collaboration with University of Bonn, Technical University of Munich, KONE ltd, and GIM Robotics.

2023

2027