An Ontology-based Multi-level Robot Architecture for Learning from Experiences

Rockel, Sebastian (University of Hamburg) | Neumann, Bernd (University of Hamburg) | Zhang, Jianwei (University of Hamburg) | Dubba, Sandeep Krishna Reddy (University of Leeds) | Cohn, Anthony G. (University of Leeds) | Konecny, Stefan (Örebro University) | Mansouri, Masoumeh (Örebro University) | Pecora, Federico (Örebro University) | Saffiotti, Alessandro (Örebro University) | Günther, Martin (University of Osnabrück) | Stock, Sebastian (University of Osnabrück) | Hertzberg, Joachim (University of Osnabrück) | Tome, Ana Maria (University of Aveiro ) | Pinho, Armando (University of Aveiro) | Lopes, Luis Seabra (University of Aveiro ) | Riegen, Stephanie von (HITeC e.V. ) | Hotz, Lothar (HITeC e.V.)

AAAI Conferences 

One way to improve the robustness and flexibility of robot performance is to let the robot learn from its experiences. In this paper, we describe the architecture and knowledge-representation framework for a service robot being developed in the EU project RACE, and present examples illustrating how learning from experiences will be achieved. As a unique innovative feature, the framework combines memory records of low-level robot activities with ontology-based high-level semantic descriptions.