Delft Sensor AI Lab (Sensor AI Lab)

Themes: Distributed Autonomous Sensing Systems

Distributed AI for sensor networks

Sensors are everywhere - measuring, processing and inferring from the environment. We also personally carry sensors with us 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. Thanks to technological advances, the availability of these sensors as well as their accuracy has steadily increased over recent years, opening up for many exciting applications. 

The field of sensor fusion focuses on combining data from different types of sensors in order to extract more information than could be done using each sensor individually. To this end, physical knowledge is being used, for instance about how a system can move over time or about the properties of the sensors. Artificial Intelligence (AI) on the other hand, new models are learned from data from sensors and sensor networks. Sensor AI unites the fields of sensor fusion and AI, focusing on including physical knowledge in AI to open up for extracting more information from available sensor data. 

Within the Sensor AI Lab, we focus on developing novel algorithms and on applying these tools in different fields, for example in human motion estimation, distributed learning in sensor networks and navigation of swarms of multiagent systems such as robots, ships, drones and satellites.

There are 2 PhD positions (1 vacancy) within this project, on Relative navigation of swarms and on Distributed learning in multi-agent systems.

Project data

Researchers: Raj Thilak Rajan, Manon Kok, Kaiwen Zhang
Starting date: December 2021
Closing date: December 2026
Funding: 1000 kE; related to group 500 kE
Contact: Raj Thilak Rajan