Evidence map›Paper›PMID 36054107›Full record

ArticlePloS one2022

Effect of button layout on the exploration and learning of robot operation using an unfamiliar controller.

Tetsuyou Watanabe

Abstract read
In one paragraph

Article in PloS one, 2022. 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

1 author.

Tetsuyou WatanabeFaculty of Frontier Engineering, Kanazawa University, Kanazawa, Ichikawa, Japan.ORCID 0000-0003-2549-1435

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Robots are becoming increasingly accessible to both experts and non-experts. Therefore, establishing a method for learning robot operations that can be easily mastered by non-experts is important. With this in mind, we aimed to develop a method that facilitates skill acquisition for non-experts that operate robots. As a first step, this study examined the effects of button layout on the exploration and learning of robot operations. A humanoid robot was operated using an unfamiliar tablet-based user interface to achieve the task of shifting the robot's posture to the desired posture: single-foot-standing. The process in which participants found and repeated sequences of commands to achieve the shift task was observed. Four types of button layouts were prepared: normal, random, name appears after the first success (NAFS), and change to normal controller after the first success (CNFS). The normal layout roughly matched the position of the robot's joints, whereas the random layout was randomly assigned, and no information was displayed on each button. Before completing the shift task, a random layout was provided in the NAFS and CNFS layouts. After the first success, the corresponding joint information was displayed in the NAFS layout, whereas the layout was changed to a normal one in the CNFS layout. In total, 51 participants used the normal layout, 7 participants used the random layout, 25 participants used the NAFS layout, and 24 participants used the CNFS layout. The results indicate that providing a random layout during the exploration process (before the first success) is preferable for effective exploration and learning. However, during the learning process (after the first success), providing the relationship between joint movements and buttons in a visual manner is better without changing the button layout from that used in the exploration process.

Indexed as

RoboticsRobotic Surgical ProceduresFootHumansLearningMovement

Identifiers

PMID36054107
PMCPMC9439237

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.