TactorBots: A Haptic Design Toolkit for Out-of-lab Exploration of Emotional Robotic Touch

Zhou, Ran; Schwemler, Zachary; Baweja, Akshay; Sareen, Harpreet; Hunt, Casey Lee; Leithinger, Daniel

doi:10.1145/3544548.3580799

Cited by 10 publications

(1 citation statement)

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“…The "otherness" approach differs phenomenologically and experientially and adopts a contrasting viewpoint. Recently, there has been a growing appreciation for the notion of "otherness", an aesthetic categorization that values the differences between social robotic objects and humans [16][17][18][19].…”

Section: Robotic Duality and Animacymentioning

confidence: 99%

Neural Correlates of Perceiving Animacy in Robotic Objects

Yizhar,

Maimon,

Tal

et al. 2024

Preprint

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The prevalence of robots in modern society calls for gaining a fundamental understanding of the underlying principles of human-robot interaction. In particular, we need to understand how people perceive robots and how different physical and social characteristics affect this perception. Here, we examined the neural correlates of observing simple gestures performed by a non-humanoid social robot, focusing on the role of the Ventral Occipitotemporal (VOT) cortex in processing perceived animacy. Our results reveal that a broad bilateral cortical network is activated, comprising areas related to action observation, the social brain, and the visual cortex, including the VOT. We also found a correlation between the level of neural responses in the VOT, especially in the left hemisphere, and individual animacy ratings of the robotic object. This correlation provides a physical basis for such subjective ratings. These results suggest a complex representation of perceived animacy across the lateral-medial axis of the VOT, explained by spatial cortical location and the amplitude of neural responses. Furthermore, we discuss the implications of these findings for understanding how people perceive robots, their behaviors and intentions, which are crucial for developing social robots that can interact with humans more naturally.

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Section: Robotic Duality and Animacymentioning

confidence: 99%