Cognitive Neuroscience Robotics A

Kasaki, Masashi; Ishiguro, Hiroshi; Asada, Minoru; Osaka, Mariko; Fujikado, Takashi

doi:10.1007/978-4-431-54595-8

Cited by 5 publications

(1 citation statement)

References 112 publications

(140 reference statements)

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“…Humanoid robots are easily recognized as robots by their overall mechanical look, even though they usually possess a head, torso, arms, and sometimes legs. In contrast, android robots are intended to mimic human appearance as realistically as possible, emphasized for example, by silicone skin, clothing, wigs, or highly realistic details such as eyelashes (see Ishiguro, 2016).…”

Section: Human-like Robotsmentioning

confidence: 99%

Human-Like Robots and the Uncanny Valley

Mara

Appel

Gnambs

2022

Zeitschrift für Psychologie

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Abstract. In the field of human-robot interaction, the well-known uncanny valley hypothesis proposes a curvilinear relationship between a robot’s degree of human likeness and the observers’ responses to the robot. While low to medium human likeness should be associated with increased positive responses, a shift to negative responses is expected for highly anthropomorphic robots. As empirical findings on the uncanny valley hypothesis are inconclusive, we conducted a random-effects meta-analysis of 49 studies (total N = 3,556) that reported 131 evaluations of robots based on the Godspeed scales for anthropomorphism (i.e., human likeness) and likeability. Our results confirm more positive responses for more human-like robots at low to medium anthropomorphism, with moving robots rated as more human-like but not necessarily more likable than static ones. However, because highly anthropomorphic robots were sparsely utilized in previous studies, no conclusions regarding proposed adverse effects at higher levels of human likeness can be made at this stage.

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Section: Human-like Robotsmentioning

confidence: 99%

Human-Like Robots and the Uncanny Valley

Mara

Appel

Gnambs

2022

Zeitschrift für Psychologie

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A Computational Model for Distance Perception Based on Visual Attention Redeployment in Locomotor Infants

Jaramillo–Henao

Vélez–Aristizábal

Arango–Castro

2019

Applications of Computational Intelligence

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Optimal Muscular Arrangement Using Genetic Algorithm for Musculoskeletal Potential Method with Muscle Viscosity

Kino

Ochi

Tahara³

2021

JRM

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Muscle contractions (or equivalent mechanical elements) are responsible for joint movement in systems with musculoskeletal structure. Because muscles can only transmit force in the tensile direction in such systems, the internal force exists between the muscles. By utilizing the potential field generated by the internal force, the musculoskeletal potential method makes it possible to control the position without complex real-time calculations or sensory feedback by entering step-inputs of the balanced internal force at the target posture. However, the conditions of convergence to the target posture strongly depend on muscular arrangement. Previous studies have elucidated the mathematical conditions of the muscular arrangement; however, they provide sufficient conditions that must be satisfied by the muscular arrangement to converge to the target posture, which do not necessarily lead to optimal muscular arrangement conditions. This study proposes a method to determine the optimal muscular arrangement of a two-joint six-muscle system, wherein muscle viscosity is considered, that uses a genetic algorithm and an evaluation function considering the motion response time. The effect of the obtained muscular arrangement is verified in a simulation.

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Cognitive Neuroscience Robotics A

Cited by 5 publications

References 112 publications

Human-Like Robots and the Uncanny Valley

Human-Like Robots and the Uncanny Valley

A Computational Model for Distance Perception Based on Visual Attention Redeployment in Locomotor Infants

Optimal Muscular Arrangement Using Genetic Algorithm for Musculoskeletal Potential Method with Muscle Viscosity

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