Humans no longer have exclusive control over training social robots to interact effectively, thanks to a new study. The study introduces a new simulation method that lets researchers test their social robots without needing human participants, making research faster and scalable.
Humans no longer have exclusive control over training social robots to interact effectively, thanks to a new study from the University of Surrey and the University of Hamburg.
Using a humanoid robot, the research team developed a dynamic scanpath prediction model to help the robot predict where a person would look in a social setting. The model was tested using two publicly available datasets, and the researchers demonstrated that humanoid robots were capable of mimicking human-like eye movements."Our method allows us to test whether a robot is paying attention to the right things -- just as a human would -- without needing real-time human supervision.
The research team matched how their model worked in the real world to that of a simulated one, projecting human gaze priority maps onto a screen to compare the robot's predicted attention focus with real-world data. This allowed for direct evaluation of social attention models in realistic conditions, reducing the need for large-scale human-robot interaction studies in the early phases of research.
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