Evidence map›Paper›PMID 39632895›Full record

ArticleScientific reports2024

Teleoperation system for multiple robots with intuitive hand recognition interface.

Lucas Alexandre Zick, Dieisson Martinelli, André Schneider de Oliveira, Vivian Cremer Kalempa

Abstract read
In one paragraph

Article in Scientific reports, 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

4 authors.

Lucas Alexandre ZickGraduate Program in Electrical and Computer Engineering, Universidade Tecnolágica Federal do Paraná (UTFPR), Curitiba, 80230-901, Brazil. zick@alunos.utfpr.edu.br.
Dieisson Martinelli *Department of Information Systems, Universidade do Estado de Santa Catarina (UDESC), São Bento do Sul, 89283-081, Brazil.
André Schneider de Oliveira *Graduate Program in Electrical and Computer Engineering, Universidade Tecnolágica Federal do Paraná (UTFPR), Curitiba, 80230-901, Brazil.
Vivian Cremer Kalempa *Department of Information Systems, Universidade do Estado de Santa Catarina (UDESC), São Bento do Sul, 89283-081, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Robotic teleoperation is essential for hazardous environments where human safety is at risk. However, efficient and intuitive human-machine interaction for multi-robot systems remains challenging. This article aims to demonstrate a robotic teleoperation system, denominated AutoNav, centered around autonomous navigation and gesture commands interpreted through computer vision. The central focus is on recognizing the palm of the hand as a control interface to facilitate human-machine interaction in the context of multi-robots. The MediaPipe framework was integrated to implement gesture recognition from a USB camera. The system was developed using the Robot Operating System, employing a simulated environment that includes the Gazebo and RViz applications with multiple TurtleBot 3 robots. The main results show a reduction of approximately 50% in the execution time, coupled with an increase in free time during teleoperation, reaching up to 94% of the total execution time. Furthermore, there is a decrease in collisions. These results demonstrate the effectiveness and practicality of the robotic control algorithm, showcasing its promise in managing teleoperations across multi-robots. This study fills a knowledge gap by developing a hand gesture-based control interface for more efficient and safer multi-robot teleoperation. These findings enhance human-machine interaction in complex robotic operations. A video showing the system working is available at https://youtu.be/94S4nJ3IwUw .

Indexed as

Autonomous navigationHuman–robotMulti-robotsROSTeleoperation

Identifiers

PMID39632895
PMCPMC11618356

What OpenQuestion holds

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LicenceCC BY
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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.