Learning to Recognize Novel Objects in One Shot through Human-Robot Interactions in Natural Language Dialogues
Evan Krause, Michael Zillich, Thomas Williams, Matthias J. Scheutz · Proceedings of the AAAI Conference on Artificial Intelligence · 2014
Being able to quickly and naturally teach robots new knowledge is critical for many future open-world human-robot interaction scenarios. In this paper we present a novel approach to using natural language context for one-shot learning of visual objects, where the robot is immediately able to recognize the described object. We describe the architectural components and demonstrate the proposed approach on a robotic platform in a proof-of-concept evaluation.