Increasingly, systems are required to accommodate changes while remaining continuously available. Led by Prof Greg Provan, this hub addresses run-time adaptation techniques that allow a system to react to potentially unforeseen changes in its environment. Adaptive systems offer the possibility of greater automation and utilisation of resources via the so-called “self-* properties” such as self-configuration, self-healing, self-optimisation and self-protection, and are increasingly important to deliver the Internet of Things concept.

Autonomous systems are currently the centre of intensive development, both from theoretical and application-specific perspectives. For example, autonomy is the main driver for the automobile industry, and represents a multi-trillion-euro market opportunity that will totally revolutionise this industry.

The Brookings Institute estimated that between 2014 and 2017 $80bn was invested in autonomous cars alone, and predicts an investment in 2018 in excess of $80bn. The advances in autonomy and adaptation will mostly take place in software, with hardware sensors and processors already offering data and processing that are only partially exploited. As such, Lero is well positioned to provide key software capabilities in this area.

Lero’s Autonomous and Adaptive Systems hub has traditionally focused on developing software for contextually-aware, self-managing and adaptive systems, with a focus on non-real-time aerospace applications. Since 2015, however, Lero has a renewed focus on the area of autonomy, with industrial impact, i.e., creating research that is company-focused and is based on active company engagement. Application domains include the automotive and agricultural sectors, that focus on software providing autonomous capabilities. 

Lero’s Autonomous and Adaptive Systems hub is currently focussed on two defined areas:

  • Modelling and Verification of Adaptive and Cyber-physical Systems (CPSs);
  • Machine Learning for Software Engineering.