Human-Robot Interaction using Intention Recognition
Pages 299 - 302
Abstract
Recognition of human intention is an important issue in human-robot interaction research and allows a robot to respond adequately according to human's wish. In this paper, we discuss how robots can infer human intention by learning affordance, a concept used to represent the relation between an agent and its environment. Learning of the robot, to understand human and its interaction with environment, is achieved within the framework of action-perception cycle. The action-perception cycle explains how an intelligent agent learns and enhances its ability continuously by interacting with its surrounding. The proposed intention recognition and recommendation system includes several key functions such as joint attention, object recognition, affordance model, motion understanding module and so on. The experimental results show high successful recognition performance and the plausibility of the proposed system.
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Index Terms
- Human-Robot Interaction using Intention Recognition
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Information & Contributors
Information
Published In
October 2015
254 pages
ISBN:9781450335270
DOI:10.1145/2814940
- General Chairs:
- Minho Lee,
- Takashi Omori,
- Program Chairs:
- Hirotaka Osawa,
- Hyeyoung Park,
- James Young
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Sponsors
- BESK: Brain Engineering Society of Korea
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 21 October 2015
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- Research-article
Funding Sources
- Ministry of Trade Industry and Energy (MOTIE Korea)
- Ministry of Science ICT and future Planning
Conference
HAI 2015
Sponsor:
- BESK
HAI 2015: The Third International Conference on Human-Agent Interaction
October 21 - 24, 2015
Kyungpook, Daegu, Republic of Korea
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Overall Acceptance Rate 121 of 404 submissions, 30%
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