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.