A Survey on Remote Assistance and Training in Mixed Reality Environments

被引:13
|
作者
Fidalgo, Catarina G. G. [1 ,2 ]
Yan, Yukang [2 ]
Cho, Hyunsung [2 ]
Sousa, Mauricio [3 ]
Lindlbauer, David [2 ]
Jorge, Joaquim [4 ,5 ]
机构
[1] Univ Lisbon, INESC ID, Inst Super Tecn, Lisbon, Portugal
[2] Carnegie Mellon Univ, Pittsburgh, PA USA
[3] Univ Toronto, Toronto, ON, Canada
[4] INESC ID, Lisbon, Portugal
[5] Univ Lisbon, Inst Super Tecn, Lisbon, Portugal
基金
美国安德鲁·梅隆基金会;
关键词
Training; Virtual reality; Collaboration; Mixed reality; Task analysis; Maintenance engineering; Visualization; Mixed Reality; Virtual Reality; Augmented Reality; Extended Reality; Remote; Assistance; AUGMENTED REALITY; COLLABORATION; DESIGN; SYSTEM; USER;
D O I
10.1109/TVCG.2023.3247081
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
The recent pandemic, war, and oil crises have caused many to reconsider their need to travel for education, training, and meetings. Providing assistance and training remotely has thus gained importance for many applications, from industrial maintenance to surgical telemonitoring. Current solutions such as video conferencing platforms lack essential communication cues such as spatial referencing, which negatively impacts both time completion and task performance. Mixed Reality (MR) offers opportunities to improve remote assistance and training, as it opens the way to increased spatial clarity and large interaction space. We contribute a survey of remote assistance and training in MR environments through a systematic literature review to provide a deeper understanding of current approaches, benefits and challenges. We analyze 62 articles and contextualize our findings along a taxonomy based on degree of collaboration, perspective sharing, MR space symmetry, time, input and output modality, visual display, and application domain. We identify the main gaps and opportunities in this research area, such as exploring collaboration scenarios beyond one-expert-to-one-trainee, enabling users to move across the reality-virtuality spectrum during a task, or exploring advanced interaction techniques that resort to hand or eye tracking. Our survey informs and helps researchers in different domains, including maintenance, medicine, engineering, or education, build and evaluate novel MR approaches to remote training and assistance. All supplemental materials are available at https://augmented-perception.org/publications/2023-training-survey.html.
引用
收藏
页码:2291 / 2303
页数:13
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