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Learning Socially Appropriate Robot Approaching Behavior Toward Groups using Deep Reinforcement Learning
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- Gao, Alex Yuan (author)
- Uppsala universitet,Avdelningen för visuell information och interaktion
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- Yang, Fangkai (author)
- KTH,Beräkningsvetenskap och beräkningsteknik (CST),KTH Royal Inst Technol, Dept Computat Sci & Technol, Stockholm, Sweden.
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- Frisk, Martin (author)
- Uppsala universitet,Avdelningen för visuell information och interaktion
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- IEEE, 2019
- 2019
- English.
- In: 2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN. - : IEEE. - 9781728126227
- Conference paper (peer-reviewed)
Abstract
Subject headings
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- Deep reinforcement learning has recently been widely applied in robotics to study tasks such as locomotion and grasping, but its application to social human-robot interaction (HRI) remains a challenge. In this paper, we present a deep learning scheme that acquires a prior model of robot approaching behavior in simulation and applies it to real-world interaction with a physical robot approaching groups of humans. The scheme, which we refer to as Staged Social Behavior Learning (SSBL), considers different stages of learning in social scenarios. We learn robot approaching behaviors towards small groups in simulation and evaluate the performance of the model using objective and subjective measures in a perceptual study and a HRI user study with human participants. Results show that our model generates more socially appropriate behavior compared to a state-of-the-art model.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Robotteknik och automation (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Robotics (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
Keyword
- Deep learning
- Machine learning
- Reinforcement learning
- Different stages
- ITS applications
- Learning schemes
- Objective and subjective measures
- Social behavior
- Social human-robot interactions
- Social scenarios
- State of the art
- Human robot interaction
Publication and Content Type
- ref (subject category)
- kon (subject category)
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- Gao, Alex Yuan
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- About the subject
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- ENGINEERING AND TECHNOLOGY
- ENGINEERING AND ...
- and Electrical Engin ...
- and Robotics
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- NATURAL SCIENCES
- NATURAL SCIENCES
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- Royal Institute of Technology
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