Assessing AR Visualizations during Non-Complex Assembly: Reporting Preliminary Results from a Crowdsourcing Rework Study

This study assesses the viability of using a simple assembly task as part of a crowdsourcing experiment to evaluate different visualizations in augmented reality (AR). We recruited 36 participants through a crowdsourcing platform to assess how visualization types (i.e., none, contour, and abstract) impact the performance of a gear-box assembly rework task. Our preliminary results suggest that the learning effect associated with manual assembly of a non-complex gearbox object plays a more significant role in improving performance than the type of visualization used. This pilot study also highlights requirements for crowdsourced task difficulty in order to offer potentially viable insights.

Authors

Institutions

Publication Details

Published
2024-10-21
DOI
https://doi.org/10.1109/ismar-adjunct64951.2024.00025
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing AR Visualizations during Non-Complex Assembly: Reporting Preliminary Results from a Crowdsourcing Rework Study

Alexander Albers, Sławomir Tadeja, Magdalena Igraś-Cybulska, Thomas Bohné
Manufacturing Process and Optimization
article

Assessing AR Visualizations during Non-Complex Assembly: Reporting Preliminary Results from a Crowdsourcing Rework Study

Alexander Albers, Sławomir Tadeja, Magdalena Igraś-Cybulska, Thomas Bohné
article en

Abstract

This study assesses the viability of using a simple assembly task as part of a crowdsourcing experiment to evaluate different visualizations in augmented reality (AR). We recruited 36 participants through a crowdsourcing platform to assess how visualization types (i.e., none, contour, and abstract) impact the performance of a gear-box assembly rework task. Our preliminary results suggest that the learning effect associated with manual assembly of a non-complex gearbox object plays a more significant role in improving performance than the type of visualization used. This pilot study also highlights requirements for crowdsourced task difficulty in order to offer potentially viable insights.

University of Cambridge (GB), Craft Engineering Associates (United States) (US)
Openalex Percentile: Top 69%
Manufacturing Process and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.