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Hashimoto, Shuji; Narita, Shin; Kasahara, Hironori; Shirai, K.; Kobayashi, Tetsuo; Takanishi, Atsuo; Sugano, Shigeki; Yamaguchi, J.; Sawada, Hideyuki; Takanobu, Hideaki; Shibuya, Kazuo; Morita, Takeshi; Kurata, Takeshi; Onoe, Naouyki; Ouchi, Kethilen Y.; Noguchi, T.; Niwa, Yasumasa; Nagayama, Satoshi; Tabayashi, H.; Matsui, Itsuo; Obata, Masayoshi; Matsuzaki, Hiroyuki; Murasugi, A.; Haruyama, S.; Okada, Tokuji; Hidaki, Y.; Taguchi, Yuichi; Hoashi, Keiichiro; Morikawa, E.; Iwano, Y.; Araki, Daichi; Suzuki, Junya; Yokoyama, M.; Dawa, I.; Nishino, Daisuke; Inoue, Shunsuke; Hirano, Tôru; Soga, Eiji; Gen, Shu; Yanada, Toru; Kato, Kensuke; Sakamoto, Shin; Ishii, Yoshinaga; Matsuo, S.; Yamamoto, Y.; Sato, Kosuke; Hagiwara, Takao; Ueda, Taro; Honda, Nakaji; Hashimoto, Kazuaki; Hanamoto, Tsuyoshi; Kayaba, Shintaro; Kojima, Tetsuhito; Iwata, Hiroyasu; Kubodera, H.; Matsuki, R.; Nakajima, T.; Nitto, Kaito; Yamamoto, Daisuke; Kamizaki, Y.; Nagaike, S.; Kunitake, Yutaka; Morita, Satoru

doi:10.1023/a:1013202723953

Cited by 76 publications

(5 citation statements)

References 12 publications

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“…The interaction with the robot is multimodal through several channels (vision, auditory, gestural, and physiological). Hashimoto et al [150] describe that for a robot to realize informed interactions with humans, it should be integrating different data that allows it to recognize the environment, such as vision, voice, and gestures. Thus, different input sources in social robots are required.…”

Section: Discussionmentioning

confidence: 99%

Affective Communication for Socially Assistive Robots (SARs) for Children with Autism Spectrum Disorder: A Systematic Review

Cano

González

Gil

et al. 2021

Sensors

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Research on affective communication for socially assistive robots has been conducted to enable physical robots to perceive, express, and respond emotionally. However, the use of affective computing in social robots has been limited, especially when social robots are designed for children, and especially those with autism spectrum disorder (ASD). Social robots are based on cognitive-affective models, which allow them to communicate with people following social behaviors and rules. However, interactions between a child and a robot may change or be different compared to those with an adult or when the child has an emotional deficit. In this study, we systematically reviewed studies related to computational models of emotions for children with ASD. We used the Scopus, WoS, Springer, and IEEE-Xplore databases to answer different research questions related to the definition, interaction, and design of computational models supported by theoretical psychology approaches from 1997 to 2021. Our review found 46 articles; not all the studies considered children or those with ASD.

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Section: Discussionmentioning

confidence: 99%

Affective Communication for Socially Assistive Robots (SARs) for Children with Autism Spectrum Disorder: A Systematic Review

Cano

González

Gil

et al. 2021

Sensors

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“…A distinctive characteristic of bipedal robots is their anthropomorphic geometry (humanoid robots 42 ). They can only be statically stable to some extent.…”

Section: Locomotionmentioning

confidence: 99%

A review of mobile robots: Concepts, methods, theoretical framework, and applications

Rubio

Chuliá

Llopis-Albert

2019

International Journal of Advanced Robotic Systems

507

178

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Humanoid robots, unmanned rovers, entertainment pets, drones, and so on are great examples of mobile robots. They can be distinguished from other robots by their ability to move autonomously, with enough intelligence to react and make decisions based on the perception they receive from the environment. Mobile robots must have some source of input data, some way of decoding that input, and a way of taking actions (including its own motion) to respond to a changing world. The need to sense and adapt to an unknown environment requires a powerful cognition system. Nowadays, there are mobile robots that can walk, run, jump, and so on like their biological counterparts. Several fields of robotics have arisen, such as wheeled mobile robots, legged robots, flying robots, robot vision, artificial intelligence, and so on, which involve different technological areas such as mechanics, electronics, and computer science. In this article, the world of mobile robots is explored including the new trends. These new trends are led by artificial intelligence, autonomous driving, network communication, cooperative work, nanorobotics, friendly human-robot interfaces, safe human-robot interaction, and emotion expression and perception. Furthermore, these news trends are applied to different fields such as medicine, health care, sports, ergonomics, industry, distribution of goods, and service robotics. These tendencies will keep going their evolution in the coming years.

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“…The WABIAN humanoid robot (Hashimoto et al, 2002) was also equipped with an active vision system that directed its gaze toward people, based on images and sound. The work of Wolfe (1994), studying how to determine relevant areas in images, inspired these approaches.…”

Section: State Of the Artmentioning

confidence: 99%

Client-Server Approach for Managing Visual Attention, Integrated in a Cognitive Architecture for a Social Robot

et al. 2021

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This paper proposes a novel system for managing visual attention in social robots. This system is based on a client/server approach that allows integration with a cognitive architecture controlling the robot. The core of this architecture is a distributed knowledge graph, in which the perceptual needs are expressed by the presence of arcs to stimuli that need to be perceived. The attention server sends motion commands to the actuators of the robot, while the attention clients send requests through the common knowledge representation. The common knowledge graph is shared by all levels of the architecture. This system has been implemented on ROS and tested on a social robot to verify the validity of the approach and was used to solve the tests proposed in RoboCup @ Home and SciROc robotic competitions. The tests have been used to quantitatively compare the proposal to traditional visual attention mechanisms.

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Untitled

Cited by 76 publications

References 12 publications

Affective Communication for Socially Assistive Robots (SARs) for Children with Autism Spectrum Disorder: A Systematic Review

Affective Communication for Socially Assistive Robots (SARs) for Children with Autism Spectrum Disorder: A Systematic Review

A review of mobile robots: Concepts, methods, theoretical framework, and applications

Client-Server Approach for Managing Visual Attention, Integrated in a Cognitive Architecture for a Social Robot

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