Humans attribute emotions to a robot that shows simple behavioural patterns borrowed from dog behaviour. (June 2016)
- Record Type:
- Journal Article
- Title:
- Humans attribute emotions to a robot that shows simple behavioural patterns borrowed from dog behaviour. (June 2016)
- Main Title:
- Humans attribute emotions to a robot that shows simple behavioural patterns borrowed from dog behaviour
- Authors:
- Gácsi, Márta
Kis, Anna
Faragó, Tamás
Janiak, Mariusz
Muszyński, Robert
Miklósi, Ádám - Abstract:
- Abstract: In social robotics it has been a crucial issue to determine the minimal set of relevant behaviour actions that humans interpret as social competencies. As a potential alternative of mimicking human abilities, it has been proposed to use a non-human animal, the dog as a natural model for developing simple, non-linguistic emotional expressions for non-humanoid social robots. In the present study human participants were presented with short video sequences in which a PeopleBot robot and a dog displayed behaviours that corresponded to five emotional states (joy, fear, anger, sadness, and neutral) in a neutral environment. The actions of the robot were developed on the basis of dog expressive behaviours that had been described in previous studies of dog–human interactions. In their answers to open-ended questions, participants spontaneously attributed emotional states to both the robot and the dog. They could also successfully match all dog videos and all robot videos with the correct emotional state. We conclude that our bottom up approach (starting from a simpler animal signalling system, rather than decomposing complex human signalling systems) can be used as a promising model for developing believable and easily recognisable emotional displays for non-humanoid social robots. Highlights: Humans spontaneously attribute emotions to an ethologically inspired robot. Dog emotional videos prime the attribution of emotions to robot videos. Participants were able to matchAbstract: In social robotics it has been a crucial issue to determine the minimal set of relevant behaviour actions that humans interpret as social competencies. As a potential alternative of mimicking human abilities, it has been proposed to use a non-human animal, the dog as a natural model for developing simple, non-linguistic emotional expressions for non-humanoid social robots. In the present study human participants were presented with short video sequences in which a PeopleBot robot and a dog displayed behaviours that corresponded to five emotional states (joy, fear, anger, sadness, and neutral) in a neutral environment. The actions of the robot were developed on the basis of dog expressive behaviours that had been described in previous studies of dog–human interactions. In their answers to open-ended questions, participants spontaneously attributed emotional states to both the robot and the dog. They could also successfully match all dog videos and all robot videos with the correct emotional state. We conclude that our bottom up approach (starting from a simpler animal signalling system, rather than decomposing complex human signalling systems) can be used as a promising model for developing believable and easily recognisable emotional displays for non-humanoid social robots. Highlights: Humans spontaneously attribute emotions to an ethologically inspired robot. Dog emotional videos prime the attribution of emotions to robot videos. Participants were able to match both dog and robot videos to the corresponding emotions. Experience with dogs does not help identify dog and robot emotions. … (more)
- Is Part Of:
- Computers in human behavior. Volume 59(2016)
- Journal:
- Computers in human behavior
- Issue:
- Volume 59(2016)
- Issue Display:
- Volume 59, Issue 2016 (2016)
- Year:
- 2016
- Volume:
- 59
- Issue:
- 2016
- Issue Sort Value:
- 2016-0059-2016-0000
- Page Start:
- 411
- Page End:
- 419
- Publication Date:
- 2016-06
- Subjects:
- Robot emotions -- Ethological approach -- Dog model -- Expressive behaviour
Interactive computer systems -- Periodicals
Man-machine systems -- Periodicals
004.019 - Journal URLs:
- http://www.sciencedirect.com/science/journal/07475632 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.chb.2016.02.043 ↗
- Languages:
- English
- ISSNs:
- 0747-5632
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.921600
British Library DSC - BLDSS-3PM
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