Object Learning with Natural Language in a Distributed Intelligent System: A Case Study of Human-Robot Interaction
The development of humanoid robots for helping humans as well as for understanding the human cognitive system is of significant interest in science and technology. How to bridge the large gap between the needs of a natural human-robot interaction and the capabilities of recent humanoid platforms is an important but open question. In this paper we describe a system to teach a robot, based on a dialogue in natural language about its real environment in real time. For this, we integrate a fast object recognition method for the NAO humanoid robot and a hybrid ensemble learning mechanism. With a qualitative analysis we show the effectiveness of our system.
KeywordsEnsemble learning Human-robot interaction Language
The authors would like to thank Sven Magg and Nils Meins for very inspiring as well as very helpful discussions. This work has been partially supported by the KSERA project funded by the European Commission under n\(^\circ \) 2010-248085 and by the RobotDoC project funded by Marie Curie ITN under 235065.
- 1.Bauer J, Weber C, Wermter S (2012) A som-based model for multi-sensory integration in the superior colliculus. In: Proceedings of the 2012 international joint conference on neural networks (IJCNN), IEEE, Brisbane, Australia, June 2012, pp 1–8Google Scholar
- 2.Bay H, Tuytelaars T, Gool LV (2006) Surf: speeded up robust features. Comput Vis Image Und 110(3):404–417Google Scholar
- 3.Du KL, Swamy MNS (2006) Neural networks in a softcomputing framework. Springer, New YorkGoogle Scholar
- 5.Heinrich S, Wermter S (2011) Towards robust speech recognition for human-robot interaction. In: Proceedings of the IROS2011 workshop on cognitive neuroscience robotics (CNR), San Francisco, CA, USA, Sept 2011, pp 29–34Google Scholar
- 7.Pfeifer R, Bongard J, Berry D (2011) Designing intelligence: why brains aren’t enough. GRIN Verlag, MunichGoogle Scholar
- 8.Spranger M, Loetzsch M, Steels L (2012) A perceptual system for language game experiments. In: Language grounding in robots, Springer, NY, pp 89–110Google Scholar
- 9.Suzuki S, Abe K (1985) Topological structural analysis of digitized binary images by border following. Comput Vis Graph Image Process 30(1):32–46Google Scholar
- 10.Vernon D, von Hofsten C, Fadiga L (2011) A roadmap for cognitive development in Humanoid robots. Springer, HeidelbergGoogle Scholar