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Core lab DecisionS


When machines and vehicles become more complex, their control systems will follow. Sensors make sure that the status of machines and vehicles can be monitored at all times, just as their environment. These so-called big data that are captured by these sensors must then be interpreted in order to be able to take correct decisions. Decisions that the system can take autonomously or not.

In the Flanders Make core lab DecisionS, we perform research into technologies for

  • Sensors: object identification, sensor fusion for determination of speed, acceleration or slip angle, environment models.
  • Condition monitoring: condition monitoring of machines based on, among others, vibration analysis
  • Control: avoiding obstacles, hybrid energy flow management
  • Decision-making: development of algorithms for artificial intelligence and machine learning

This leads, among others, to interesting learning control applications. Machines are equipped with sensors. The data that they collect from the machine and its environment are used as input for controller algorithms. For this, the controller not only uses models but also what the machine learned from previous executions of the task. In this way, machine performances improve whenever it performs a similar task.

We make use of high-tech test and validation infrastructure to take our research to the next level. This includes, for instance:

  • An indoor ultra-wide band-based localisation system
  • An outdoor GPS-based localisation system
  • A set-up for the accelerated ageing of bearings and for conducting vibration analyses
  • A hardware-in-the-loop platform for laser path planning in 3D-printing
  • Drones, Automated Guided Vehicles and mobile robots

Some realisations of our core lab

Our core lab DecisionS works together with European research centres in the vehicle industry such as the University of Surrey, the Université de Technologie de Compiègne and Virtual Vehicle in Graz on issues such as online estimation of tire forces, slip angle and the centre of gravity of vehicles based on (1) data from sensors that have already been integrated in the vehicles and (2) condition estimation algorithms.

For more information, feel free to contact our core lab manager Wouter De Nijs on