Implementing anthropomorphic features to robots is a frequently used approach to create positive perceptions in human-robot interaction. However, anthropomorphism does not always lead to positive consequences and might trigger a more gendered perception of robots. More precisely, anthropomorphic features of robots seem to evoke a male-robot bias. Yet, it is unclear if this bias is induced via a male appearance of higher anthropomorphic robots, a general male-technology bias, or even due to language aspects. As the word robot is differently grammatically gendered in different languages, this might be associated with the representation of robot gender. To target these open questions, we investigated how the degree of anthropomorphism and the way the word robot is gendered in different languages, as well as within one language influence the perceived gender of the robot. We therefore conducted two online-studies in which participants were presented with pictures of differently anthropomorphic robots. The first study investigated two different samples from which one was conducted in German, as grammatically-gendered language, and one in English as natural gender language. We did not find significant differences between both languages. Robots with a higher degree of anthropomorphism were perceived as significantly more male than neutral or female. The second study investigated the effect of grammatically-gendered descriptions (feminine, masculine, neuter) on the perception of robots. This study revealed that masculine grammatical gender tends to reinforce a male ascription of gender-neutral robots. The results suggest that the male-robot bias found in previous studies seems to be associated with appearance of most anthropomorphic robots, and the grammatical gender the robot is referenced by.
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http://dx.doi.org/10.1007/s12369-023-00975-5 | DOI Listing |
Front Robot AI
December 2024
CREATE-Lab, Department of Mechanical Engineering, Swiss Federal Technology Institute of Lausanne (EPFL), Lausanne, Switzerland.
Creativity and style in music playing originates from constraints and imperfect interactions between instruments and players. Digital and robotic systems have so far been unable to capture this naturalistic playing. Whether as an additional tool for musicians, function restoration with prosthetics, or artificial intelligence-powered systems, the physical embodiment and interactions generated are critical for expression and connection with an audience.
View Article and Find Full Text PDFISA Trans
December 2024
Amity Centre for Artificial Intelligence, Amity University, Noida, UP, India. Electronic address:
Inverse kinematics, crucial in robotics, involves computing joint configurations to achieve specific end-effector positions and orientations. This task is particularly complex for six-degree-of-freedom (six-DoF) anthropomorphic robots due to complicated mathematical equations, nonlinear behaviours, multiple valid solutions, physical constraints, non-generalizability and computational demands. The primary contribution of this work is to address the complex inverse kinematics problem for six-DoF anthropomorphic robots through the systematic exploration of AI models.
View Article and Find Full Text PDFHeliyon
March 2024
Department of Electrical Engineering, Bahria University, H-11, Islamabad, 47000, Pakistan.
Physiologically relevant optimal controllers better represent the decision-making process of the central nervous system (CNS) with proper neural inputs and proprioceptor feedback. A biomechanical mathematical framework in the human palm reference frame was simulated using physiological dynamics to explore the biomechanics of movement coordination of fingers in a human hand. Physiological state space models include multiple zero eigenvalues, representing a redundant system.
View Article and Find Full Text PDFPeerJ Comput Sci
October 2024
Industrial Organization and Management Engineering Dept., University of the Basque Country UPV/EHU, Vitoria, Araba, Spain.
The article addresses the identification and prediction of research topics in human-robot interaction (HRI), fundamental in Industry 4.0 (I4.0) and future Industry 5.
View Article and Find Full Text PDFSci Rep
November 2024
Center for Interventional Oncology, National Institutes of Health, Bethesda, MD, USA.
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