Learning to Recognize Novel Objects in One Shot through Human-Robot Interactions in Natural Language Dialogues

Evan Krause and Michael Zillich and Tom Williams and Matthias Scheutz

28th AAAI Conference on Artificial Intelligence

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.