Object Learning with Natural Language in a Distributed Intelligent System - A Case Study of Human-Robot Interaction

Stefan Heinrich, Pascal Folleher, Peer Springstübe, Erik Strahl, Johannes Twiefel, Cornelius Weber, Stefan Wermter

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

Abstract

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.
Original languageEnglish
Title of host publicationProceedings of the 2012 IEEE First International Conference on Cognitive Systems and Information Processing (CSIP2012)
EditorsFuchun Sun, Dewen Hu, Huaping Liu
Number of pages9
Volume215
PublisherSpringer
Publication date1 Dec 2012
Pages811-819
DOIs
Publication statusPublished - 1 Dec 2012
Externally publishedYes
SeriesAdvances in Intelligent Systems and Computing

Keywords

  • Human-Robot Interaction
  • Ensemble Learning
  • Language

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