Autonomous robots need to connect what they observe with what they know, what they want to achieve and what they can do next. Cognitive robotics studies the representations and reasoning processes that support these decisions.
Work in this theme includes reasoning about actions, task planning, knowledge representation and high-level robot programming. CSE’s earlier blackboard architectures used shared memory to connect cognitive processes. Cognitive hierarchies provided a framework for integrating symbolic and sub-symbolic representations, while action formalisms supported planning and reasoning about incomplete knowledge.
The aim is to make complex behaviour easier to specify, inspect and revise. This matters both for researchers developing autonomous systems and for people who need to understand how a robot reaches its decisions.
Explore rUNSWeep and the work of Michael Thielscher.