Evidence map›Paper›PMID 34071352›Full record

ArticleSensors (Basel, Switzerland)2021

Metrological Evaluation of Human-Robot Collaborative Environments Based on Optical Motion Capture Systems.

Leticia González, Juan C Álvarez, Antonio M López, Diego Álvarez

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Accuracy validation of a wearable IMU-based gait analysis in healthy female.BMC sports science, medicine & rehabilitation · 2024
    Article
  2. 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

4 authors.

Leticia GonzálezMultisensor Systems and Robotics Group (SiMuR), Department of Electrical, Electronic, Computer and Systems Engineering, University of Oviedo, C/Pedro Puig Adam, 33203 Gijón, Spain.ORCID 0000-0002-1605-7998
Juan C ÁlvarezMultisensor Systems and Robotics Group (SiMuR), Department of Electrical, Electronic, Computer and Systems Engineering, University of Oviedo, C/Pedro Puig Adam, 33203 Gijón, Spain.ORCID 0000-0002-8910-4855
Antonio M LópezMultisensor Systems and Robotics Group (SiMuR), Department of Electrical, Electronic, Computer and Systems Engineering, University of Oviedo, C/Pedro Puig Adam, 33203 Gijón, Spain.ORCID 0000-0002-5589-6954
Diego ÁlvarezMultisensor Systems and Robotics Group (SiMuR), Department of Electrical, Electronic, Computer and Systems Engineering, University of Oviedo, C/Pedro Puig Adam, 33203 Gijón, Spain.ORCID 0000-0003-0395-2712

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the context of human-robot collaborative shared environments, there has been an increase in the use of optical motion capture (OMC) systems for human motion tracking. The accuracy and precision of OMC technology need to be assessed in order to ensure safe human-robot interactions, but the accuracy specifications provided by manufacturers are easily influenced by various factors affecting the measurements. This article describes a new methodology for the metrological evaluation of a human-robot collaborative environment based on optical motion capture (OMC) systems. Inspired by the ASTM E3064 test guide, and taking advantage of an existing industrial robot in the production cell, the system is evaluated for mean error, error spread, and repeatability. A detailed statistical study of the error distribution across the capture area is carried out, supported by a Mann-Whitney U-test for median comparisons. Based on the results, optimal capture areas for the use of the capture system are suggested. The results of the proposed method show that the metrological characteristics obtained are compatible and comparable in quality to other methods that do not require the intervention of an industrial robot.

Indexed as

calibrationgroupwarehuman–robot interactionindustrial robotsoptical tracking

Identifiers

PMID34071352
PMCPMC8198618

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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.