The Lab

The Autonomous Systems Laboratory is a research group within the Center for Integrated Emergency Management at the University of Agder, Norway. Its main objective is to advance the research front in the area of autonomous systems by developing algorithms and methodologies that enable decision-making in (possibly aerial) robotic, cyberphysical, and embedded systems without human supervision.

Our group conducts both theoretical and applied research. On the one hand, we pursue fundamental contributions in the following areas:

  • machine learning
  • artificial intelligence
  • wireless communications
  • signal processing
  • control theory
  • robotics

On the application side, we target specific goals in the context of mobile communications and information processing for emergency response. Specifically, note that emergency response operations are often impaired by lack of visibility, extreme temperatures or weather, remoteness of the operation site, and other conditions that increase the risk for emergency responders and compromise the success of the mission. In this context, our group is concerned with the application and development of information and communication technologies that alleviate the impact of the aforementioned challenges through enhanced communication and situational awareness capabilities.

To achieve the first of these objectives, the focus is on devising artificial intelligence and optimization algorithms as well as hardware architectures that enable the utilization of autonomous mobile communication infrastructure, such as fleets of unmanned aerial vehicles (UAVs) with on-board base stations. The latter can be swiftly deployed on-site, even before responders arrive, and can provide high-throughput data links to the control center, which can be used to exchange video feeds and sensing information.

The second objective comprises a set of artificial intelligence and signal processing techniques for collecting on-field sensor data, communicate it to the control center, and fuse the available heterogeneous sources of information to achieve seamless scene understanding with minimum human intervention. The aforementioned mobile infrastructure will also be leveraged to this end, both for data collection and communication purposes.