Decision and control

This research program investigates how to reliably make autonomous decisions and control for robots in the presence of uncertainty. We are achieving this  by advancing model-based filtering, estimation, detection, decision and planning techniques for robotic systems.

Our research questions include how to:

  • design robotic systems capable of achieving specified performance outcomes in the presence of uncertainty
  • detect anomalous system conditions in weak measurement environments
  • characterise and manage network systems.

Projects

Team