SAR Remote Collaboration Platform Supporting ATI for Training Tasks

Abstract Global events, including pandemics and geopolitical conflicts, have catalyzed a fundamental reevaluation of remote collaboration paradigms across training, technical assistance, maintenance, and educational domains. While conventional video conferencing technologies have achieved widespread adoption, significant potential remains for advancing augmented reality (AR)-based remote collaboration methodologies. Though hand-drawn AR annotations (AAS) remain prevalent for visual instruction delivery, their inherent informality often proves insufficient for conveying precise operational directives in industrial contexts. Consequently, multimodal verbal communication emerges as a critical compensatory mechanism to resolve ambiguities and mitigate linguistic barriers. This research introduces a novel Spatial AR (SAR) remote collaboration platform designed to bridge this communication gap through an Adaptive Transformation of Instructions (ATI) methodology. The proposed system enables dynamic conversion of freehand annotations into standardized symbolic representations, thereby enhancing instructional clarity and fostering universal comprehension. A rigorous formative user study was conducted to evaluate the platform’s efficacy across multiple dimensions: task completion time, annotation complexity, subjective collaborative experience, system usability (via standardized rankings), and user preference metrics. Results demonstrate statistically significant improvements in user experience when ATI-based cues are integrated into remote collaborative training scenarios. Beyond practical implications, this work provides actionable insights for future investigations into AR-mediated remote collaboration within technical training environments.

Authors

Institutions

Publication Details

Journal
PRESENCE Virtual and Augmented Reality
Published
2026-02-03
DOI
https://doi.org/10.1162/pres.a.421
Primary Topic
Augmented Reality Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

SAR Remote Collaboration Platform Supporting ATI for Training Tasks

Huan Yang, Fusheng Li, Xiuling Li, Peng Wang
PRESENCE Virtual and Augmented Reality
Augmented Reality Applications
article

SAR Remote Collaboration Platform Supporting ATI for Training Tasks

Huan Yang, Fusheng Li, Xiuling Li, Peng Wang
article en

Abstract

Abstract Global events, including pandemics and geopolitical conflicts, have catalyzed a fundamental reevaluation of remote collaboration paradigms across training, technical assistance, maintenance, and educational domains. While conventional video conferencing technologies have achieved widespread adoption, significant potential remains for advancing augmented reality (AR)-based remote collaboration methodologies. Though hand-drawn AR annotations (AAS) remain prevalent for visual instruction delivery, their inherent informality often proves insufficient for conveying precise operational directives in industrial contexts. Consequently, multimodal verbal communication emerges as a critical compensatory mechanism to resolve ambiguities and mitigate linguistic barriers. This research introduces a novel Spatial AR (SAR) remote collaboration platform designed to bridge this communication gap through an Adaptive Transformation of Instructions (ATI) methodology. The proposed system enables dynamic conversion of freehand annotations into standardized symbolic representations, thereby enhancing instructional clarity and fostering universal comprehension. A rigorous formative user study was conducted to evaluate the platform’s efficacy across multiple dimensions: task completion time, annotation complexity, subjective collaborative experience, system usability (via standardized rankings), and user preference metrics. Results demonstrate statistically significant improvements in user experience when ATI-based cues are integrated into remote collaborative training scenarios. Beyond practical implications, this work provides actionable insights for future investigations into AR-mediated remote collaboration within technical training environments.

PRESENCE Virtual and Augmented Reality
Chongqing University of Posts and Telecommunications (CN), Baoshan University (CN), Zhengzhou Railway Vocational & Technical College (CN)
Openalex Percentile: Top 70%
Augmented Reality Applications
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.