Evidence map›Paper›PMID 39076841›Full record

ArticleFrontiers in robotics and AI2024

Enhancing emotional expression in cat-like robots: strategies for utilizing tail movements with human-like gazes.

Xinxiang Wang, Zihan Li, Songyang Wang, Yiming Yang, Yibo Peng, Changzeng Fu

Abstract read
In one paragraph

Article in Frontiers in robotics and AI, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Xinxiang Wang *HACI, Sydney Smart Technology College, Northeastern University, Shenyang, China.
Zihan Li *HACI, Sydney Smart Technology College, Northeastern University, Shenyang, China.
Songyang WangHACI, Sydney Smart Technology College, Northeastern University, Shenyang, China.
Yiming YangHACI, Sydney Smart Technology College, Northeastern University, Shenyang, China.
Yibo PengHACI, Sydney Smart Technology College, Northeastern University, Shenyang, China.
Changzeng Fu *HACI, Sydney Smart Technology College, Northeastern University, Shenyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, there has been a significant growth in research on emotion expression in the field of human-robot interaction. In the process of human-robot interaction, the effect of the robot's emotional expression determines the user's experience and acceptance. Gaze is widely accepted as an important media to express emotions in human-human interaction. But it has been found that users have difficulty in effectively recognizing emotions such as happiness and anger expressed by animaloid robots that use eye contact individually. In addition, in real interaction, effective nonverbal expression includes not only eye contact but also physical expression. However, current animaloid social robots consider human-like eyes as the main emotion expression pathway, which results in a dysfunctional robot appearance and behavioral approach, affecting the quality of emotional expression. Based on retaining the effectiveness of eyes for emotional communication, we added a mechanical tail as a physical expression to enhance the robot's emotional expression in concert with the eyes. The results show that the collaboration between the mechanical tail and the bionic eye enhances emotional expression in all four emotions. Further more, we found that the mechanical tail can enhance the expression of specific emotions with different parameters. The above study is conducive to enhancing the robot's emotional expression ability in human-robot interaction and improving the user's interaction experience.

Indexed as

bionic eyecat-like robotemotional expressionemotion recognitionhuman-robot interactionmechanical tailnonverbal communicationuser experience

Identifiers

PMID39076841
PMCPMC11284330

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.