Clusters and Projects

There are now seven clusters, but more are under consideration since the second intake of PhD students is completed. Each cluster involves university, industrial, and affiliated PhD students. The clusters cover areas that are scientifically important, of high relevance, and which form a broad but well-connected research palette. On the software and computation side, one cluster will develop methodology for advanced industrial software development, and one cluster concerns the rapidly emerging area of autonomy in cloud infrastructures. Two clusters consider the key aspect of cooperation between autonomous systems and humans, where one cluster tackles perception and robotics, and the other deals with new concepts in human-machine interaction such as cognitive digital companions. One cluster deals with the fundamental questions of localization, and one deals with scalability, both developing new techniques that are expected to be essential in many autonomous systems. The remaining cluster is aiming at the future automated transport systems.

The program comprises a number of projects, such as industrial PhD projects. The projects are gathered in clusters in order to allow for cooperation between related projects and to create network.

The initial seven WASP clusters are described in more detail below.

Software Engineering for Smart Systems

Smart and autonomous systems are dependent on software to realize their functionality, but the functionality of these systems must be able to evolve much more rapidly than is possible with classical software engineering approaches. This cluster will study data-driven methods for continuously evolving the functionality and performance of smart systems.


  • Jan Bosch (cluster coordinator) Chalmers
  • Patrizio Pelliccione, Chalmers
  • Per Runeson, Lund University

Link to further information: Software Engineering for Smart Systems

Autonomous Cloud

This cluster will provide autonomy and predictability in the distributed cloud by developing dynamic, control-based resource management methods for deciding how much and what type of resources to allocate, and when and where to deploy them.


  • Karl-Erik Årzén (cluster coordinator)/Maria Kihl, Lund University
  • Erik Elmroth, Umeå University

Link to further information: The Autonomous Cloud

Integrating Perception, Learning and Verification in Interactive Autonomous Systems

The cluster will study perception methods based on fusion of multi-modal sensory information in combination with learning, and formal verification of autonomous systems.

  • Danica Kragic (cluster coordinator), KTH
  • Michael Felsberg, Linköping University
  • Alexandre Proutiere, KTH
  • Kalle Åström, Lund University

Link to further information: Integrating Perception

Interaction and Communication with Autonomous Agents in Sensor-Rich Environments

This cluster will develop the next generation of decision support systems, so called cognitive companions, designed to adaptively reduce the cognitive load caused by the large and rapid information flows while ensuring mission-critical decision timescales.


  • Anders Ynnerman (cluster coordinator), Linköping University
  • Patrick Doherty, Linköping University
  • Morten Fjeld, Chalmers
  • Görel Hedin, Lund University

Link to further information: Interaction and Communication

Smart Localization Systems

Accurate localization anywhere and anytime – of vehicles, robots, humans, and gadgets in both the absolute and relative sense – is a fundamental Component in achieving high level of autonomy. The research challenge is to provide scalable, available and reliable smart localization technology needed to enable future intelligent and autonomous systems.


  • Fredrik Gustafsson, (cluster coordinator), Linköping University
  • Henk Wymeersch, Chalmers
  • Peter Händel, KTH
  • Joakim Jaldén, KTH
  • Patric Jensfelt, KTH
  • Isaac Skog, KTH
  • Gustaf Hendeby, Linköping University
  • Bo Bernhardsson, Lund University
  • Fredrik Tufvesson, Lund University
  • Kalle Åström, Lund University

Link to further information: Smart Localization System

Large Scale Optimization and Control

The cluster will develop basic theory and methodology for distributed optimization, learning and decision-making in large scale dynamic systems. This is essential to efficiently and reliably operate infrastructure networks for transportation, communications, data, electricity, heat and water, as well as smart cities and health care. The main research challenges are in the intersection between optimization, control, statistics, machine learning and economics.


  • Anders Rantzer (cluster coordinator), Lund University
  • Anders Hansson, Linköping University
  • Mikael Johansson, KTH
  • Bengt Lennartsson, Chalmers

Link to further information: Large Scale Optimization

Automated Transport Systems

Automated transport systems will revolutionize the efficiency of transportation of people and goods, and at the same time dramatically reduce environmental impact. This cluster concerns optimization of the overall transport performance by taking advantage of new possibilities for efficient communication, accurate position estimation, and smart decision systems.


  • Bo Wahlberg (cluster coordinator), KTH
  • Karl Henrik Johansson, KTH
  • Lars Nielsen, Linköping University
  • Jonas Sjöberg, Chalmers
  • Fredrik Tufvesson, Lund University
  • Henk Wymeersch, Chalmers

Link to further information: Automated Transport Systems