Robust Autonomy and Decisions Group


Our work focusses on building autonomous robots and other cyber-physical systems systems, capable of working robustly in application domains such as the following:

  • Human-robot collaborative work in customisable manufacturing, personal robotics, etc.
  • Active sensing, predictive modelling and decision making in energy and environmental systems.

This motivates us to develop new models and algorithms to address conceptial issues such as:

  • Compositional and incremental methods for model learning and learning to act in multi-scale, dynamic environments.
  • Mechanisms of extended interaction for model selection, structure learning and coordinated action in the face of unknown unknowns.

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