Robots intended for social contexts are often designed with explicit humanlike attributes in order to facilitate their reception by (and communication with) people. However, observation of an "uncanny valley"-a phenomenon in which highly humanlike entities provoke in human observers-has lead some to caution against this practice. Both of these contrasting perspectives on the anthropomorphic design of social robots find some support in empirical investigations to date. Yet, owing to outstanding empirical limitations and theoretical disputes, the uncanny valley and its implications for human-robot interaction remains poorly understood. We thus explored the relationship between and people's aversion toward humanlike robots via manipulation of the agents' appearances. To that end, we employed a picture-viewing task ( = 60) to conduct an experimental test ( = 72) of the uncanny valley's existence and the visual features that cause certain humanlike robots to be unnerving. Across the levels of human similarity, we further manipulated agent appearance on two dimensions, (prototypic, atypical, and ambiguous) and (robot, person), and measured participants' aversion using both subjective and behavioral indices. Our findings were as follows: (1) Further substantiating its existence, the data show a clear and consistent uncanny valley in the current design space of humanoid robots. (2) Both category ambiguity, and more so, atypicalities provoke aversive responding, thus shedding light on the visual factors that drive people's discomfort. (3) Use of the Negative Attitudes toward Robots Scale did not reveal any significant relationships between people's pre-existing attitudes toward humanlike robots and their aversive responding-suggesting positive exposure and/or additional experience with robots is unlikely to affect the occurrence of an uncanny valley effect in humanoid robotics. This work furthers our understanding of both the uncanny valley, as well as the visual factors that contribute to an agent's uncanniness.
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http://dx.doi.org/10.3389/fpsyg.2017.01366 | DOI Listing |
ACS Appl Mater Interfaces
January 2025
Department of Materials Science, National Engineering Lab for TFT-LCD Materials and Technologies, Fudan University, Shanghai 200433, China.
Tactile sensation and recognition in the human brain are indispensable for interaction between the human body and the surrounding environment. It is quite significant for intelligent robots to simulate human perception and decision-making functions in a more human-like way to perform complex tasks. A combination of tactile piezoelectric sensors with neuromorphic transistors provides an alternative way to achieve perception and cognition functions for intelligent robots in human-machine interaction scenarios.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Information Convergence Engineering, Pusan National University, Busan 46241, Republic of Korea.
Dialogue systems must understand children's utterance intentions by considering their unique linguistic characteristics, such as syntactic incompleteness, pronunciation inaccuracies, and creative expressions, to enable natural conversational engagement in child-robot interactions. Even state-of-the-art large language models (LLMs) for language understanding and contextual awareness cannot comprehend children's intent as accurately as humans because of their distinctive features. An LLM-based dialogue system should acquire the manner by which humans understand children's speech to enhance its intention reasoning performance in verbal interactions with children.
View Article and Find Full Text PDFCogn Res Princ Implic
December 2024
Vanderbilt University, Nashville, USA.
As a wide variety of intelligent technologies become part of everyday life, researchers have explored how people conceptualize agents that in some ways act and think like living things but are clearly machines. Much of this work draws upon the idea that people readily default to generalizing human-like properties to such agents, and only pare back on these generalizations with added thought. However, recent findings have also documented that people are sometimes initially hesitant to attribute minds to a machine but are more willing to do so with additional thought.
View Article and Find Full Text PDFFront Hum Neurosci
November 2024
Professorship for Social Brain Sciences, ETH Zurich, Zurich, Switzerland.
Introduction: Artificial intelligence (AI) and robots are increasingly shaping the aesthetic preferences of art consumers, influencing how they perceive and engage with artistic works. This development raises various questions: do cues to the humanness of the origin of an artwork or artist influence our aesthetic preferences?.
Methods: Across two experiments, we investigated how the perception and appreciation of dance is influenced by cues to human animacy.
Bioinspir Biomim
December 2024
Changsha University of Science and Technology, No. 960, Section 2, Wanjiali South Road, Muyun Street, Tianxin District, Changsha, China, Changsha, 410114, CHINA.
This paper presents the design of an underactuated adaptive humanoid Manipulator (UAHM) featuring a link-spring telescopic rod-slide mechanism, which is capable of basic human-like grasping functions. Initially, the mechanical structure of the UAHM is introduced, with a detailed exposition of its transmission mode, finger architecture, and overall configuration. Subsequently, the kinematic and static models of the UAHM are delineated, elucidating the relationship between the phalangeal contact forces, contact positions, and bending angles during both fingertip and envelope grasping.
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