Humans attribute emotions to a robot that shows simple behavioural patterns borrowed from dog behaviour

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.