A concept for a cognitive-oriented approach to build autonomous systems

This contribution proposes an architecture of an autonomous system based on a situation-operator-modeling technique to realize a cognitive-based control. The cognitive functions of the system are divided into the learning, testing, and exploration modules; and the planning and plan supervision modules. The proposed architecture of an autonomous learning system consists of different parts, e.g. filter modules, cognitive functions, knowledge base, and goal translation. The core of the approach is the representation of changes of the outside-world of the systems as a sequence of scenes and actions, which are modeled using a special modeling technique. The steps to realize the proposed architecture are illustrated and detailed for a mobile robot as an example.