Loughborough University Centre for Control and Autonomous Systems (LUCAS)

The Centre focuses on the development and application of autonomous system and control technologies particularly in the context of aerospace and automotive engineering.

Our research is of significant interdisciplinary nature, cross engineering, computer science, transport, agriculture, and environment. The Centre is internationally renowned for its work in unmanned aerial vehicles, intelligent vehicles, advanced control theory, and precision agriculture. 

Current research profile of the Centre falls into three core directions:

  1. Development of autonomous system and control technologies
    Development of advanced algorithms/methods for autonomous vehicles such as autopilot, situation awareness, path planning, and decision making. Focuses are on unmanned aerial vehicles, and intelligent ground vehicles.

  2. Ensuring the safety of autonomous system and control technologies
    Research in this direction includes developing contingence management to enable safe operation of autonomous vehicles,  understanding and mitigating safety risk when embedding AI algorithms on a product and system, or, more importantly, developing new techniques/procedures to support verification and validation of new autonomous functions/systems to provide assurance.

  3. Application of autonomous system and control technologies
    This is an ever-growing research direction, including the applications of artificial intelligence, data mining and autonomous system technologies in a wide range of sectors, from intelligent mobility and defense to agriculture and environment monitoring.

The Centre has strong links with industrial partners and attracts significant research funding from the UK government funding agencies and industry.

The mission of the Centre is to advance control and autonomous systems, increase the levels of automation, and safeguard a wider application of automation and artificial intelligence, driven by the global challenges and the UK priorities. Particularly it aims to integrate fundamental research with real-world challenges and tackle real world challenges to ensure safety of a future highly automated society.

Our research activities

Activities we address include but are not limited to:

  • Intelligent mobility
  • Cyber-physical systems
  • Human machine interface/systems
  • Active learning
  • Dual control for exploitation and exploration
  • Model predictive control
  • Disturbance observer-based control
  • Situational awareness
  • Robust decision making
  • Multiple moving object tracking
  • Bayesian inference and learning
  • Machine learning and data mining
  • UAV/Satellite remote sensing
  • Cognitive search and informative planning
  • Computer vision and pattern recognition
  • Personalisation and classification
  • Precision agriculture
  • Environment protection