Sensor AI Lab

AI for Sensor Networks

Sensors are everywhere – measuring, processing and inferring from the environment. We also carry sensors with us personally, wherever we go. These sensors are present in smartphones and activity trackers, and provide information about where we are, how we are moving and what we are doing. Technological advances have made sensors more available and more accurate over recent years, opening up many exciting applications.

The field of sensor fusion focuses on combining data from different types of sensors in order to extract more information than that available from each sensor alone. Physical knowledge can used, for instance about how a system can move over time or about sensor properties. AI can also be used: new models can be established using data from sensors and sensor networks. Sensor AI unites the fields of sensor fusion and AI, bringing physical knowledge into AI to enable the extraction of more information from available sensor data. 

The Sensor AI Lab focuses on developing novel algorithms, and on applying these tools in different fields. Examples include human motion estimation; distributed learning in sensor networks; and navigation of swarms of multiagent systems such as robots, ships, drones and satellites. 

The Sensor AI Lab is part of the TU Delft AI Labs programme.

The Team