Evidence map›Paper›PMID 38894462›Full record

ArticleSensors (Basel, Switzerland)2024

Creating Expressive Social Robots That Convey Symbolic and Spontaneous Communication.

Enrique Fernández-Rodicio, Álvaro Castro-González, Juan José Gamboa-Montero, Sara Carrasco-Martínez, Miguel A Salichs

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Enrique Fernández-RodicioRoboticsLab, Department of Systems Engineering and Automation, Universidad Carlos III de Madrid, Av. de la Universidad 30, 28911 Madrid, Spain.ORCID 0000-0001-5763-2015
Álvaro Castro-GonzálezRoboticsLab, Department of Systems Engineering and Automation, Universidad Carlos III de Madrid, Av. de la Universidad 30, 28911 Madrid, Spain.ORCID 0000-0002-5189-0002
Juan José Gamboa-MonteroRoboticsLab, Department of Systems Engineering and Automation, Universidad Carlos III de Madrid, Av. de la Universidad 30, 28911 Madrid, Spain.ORCID 0000-0001-7845-5812
Sara Carrasco-MartínezRoboticsLab, Department of Systems Engineering and Automation, Universidad Carlos III de Madrid, Av. de la Universidad 30, 28911 Madrid, Spain.ORCID 0000-0002-2148-2067
Miguel A SalichsRoboticsLab, Department of Systems Engineering and Automation, Universidad Carlos III de Madrid, Av. de la Universidad 30, 28911 Madrid, Spain.ORCID 0000-0002-0263-6606

Funding

Agencia Estatal de Investigación PID2021-123941OA-I00Ministerio de Ciencia, Innovación y Universidades RTI2018-096338-B-I00
6 · The paper itself

Abstract

Robots are becoming an increasingly important part of our society and have started to be used in tasks that require communicating with humans. Communication can be decoupled in two dimensions: symbolic (information aimed to achieve a particular goal) and spontaneous (displaying the speaker's emotional and motivational state) communication. Thus, to enhance human-robot interactions, the expressions that are used have to convey both dimensions. This paper presents a method for modelling a robot's expressiveness as a combination of these two dimensions, where each of them can be generated independently. This is the first contribution of our work. The second contribution is the development of an expressiveness architecture that uses predefined multimodal expressions to convey the symbolic dimension and integrates a series of modulation strategies for conveying the robot's mood and emotions. In order to validate the performance of the proposed architecture, the last contribution is a series of experiments that aim to study the effect that the addition of the spontaneous dimension of communication and its fusion with the symbolic dimension has on how people perceive a social robot. Our results show that the modulation strategies improve the users' perception and can convey a recognizable affective state.

Indexed as

affective state expressionexpressiveness managementhuman–robot interactionmultimodal interaction

Identifiers

PMID38894462
PMCPMC11175349

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.