The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Using Animated Augmented Reality to Cognitively Guide Assembly
Abstract
Assembly is the process in which two or more objects are joined together. An assembly manual is typically used to guide the tasks required to put together an artifact. As an emerging technology, augmented reality (AR) integrates three-dimensional (3D) images of virtual objects into a real-world workspace. The insertion of digitalized information into the real workspace using AR can provide workers with the means to implement correct assembly procedures with improved accuracy and reduce errors. A prototype animated AR system was configured for assembly tasks that are normally guided by reference to documentation and was tested using a series of experiments. A LEGO model was used as the assembly and experimental tester task. Experimentation was devised and conducted to validate the cognitive gains that can be derived from using AR to assemble a LEGO model. Two formal experiments with 50 participants were conducted to compare an animated AR system and the paper-based manual system. One experiment measured the cognitive workload of using the system for assembly, whereas the other measured the learning curves of novice assemblers. Findings from the experiments revealed that the animated AR system yielded shorter task completion times, less assembly errors, and lower total task load. The results also revealed that the learning curve of novice assemblers was reduced and task performance relevant to working memory was increased when using AR training. Future work will apply the knowledge gained from the controlled assembly experiments to the real-scale construction assembly scenario to measure the productivity improvements.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
(2001) · doi:10.1017/cbo9780511546396 · Cited by 4,482
NASA-Task Load Index (NASA-TLX); 20 Years Later
Hart, S. G. (2006) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/154193120605000909 · Cited by 4,297
Recent advances in augmented reality
Azuma, R., Baillot, Y., Behringer, R., Feiner, S., Julier, S., & MacIntyre, B. (2001) · IEEE Computer Graphics and Applications · doi:10.1109/38.963459 · Cited by 4,148
Unsworth, N., & Engle, R. W. (2007) · Psychological Review · doi:10.1037/0033-295x.114.1.104 · Cited by 1,307
Neuroimaging Studies of Mental Rotation: A Meta-analysis and Review
Zacks, J. M. (2008) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2008.20.1.1 · Cited by 792
Beatty, J. T., & Lucero-Wagoner, B. (2000) · Cited by 703
Comparative effectiveness of augmented reality in object assembly
Tang, A., Owen, C., Biocca, F., & Mou, W. (2003) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/642611.642626 · Cited by 603
Hoffman, R. R., Crandall, B., & Shadbolt, N. (1998) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872098779480442 · Cited by 403
MULHALL, J. P., CREECH, S. D., BOORJIAN, S. A., GHALY, S., KIM, E. D., MOTY, A., DAVIS, R., & HELLSTROM, W. (2004) · Journal of Urology · doi:10.1097/01.ju.0000127744.18878.f1 · Cited by 385
Training in virtual environments: transfer to real world tasks and equivalence to real task training
Rose, F. D., Attree, E. A., Brooks, B. M., Parslow, D. M., & Penn, P. R. (2000) · Ergonomics · doi:10.1080/001401300184378 · Cited by 372
Cited by
Eswaran, M., & Bahubalendruni, M. V. A. R. (2022) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2022.09.016 · Cited by 308
Mystakidis, S., Christopoulos, A., & Pellas, N. (2022) · Education and Information Technologies · doi:10.1007/s10639-021-10682-1 · Cited by 269
Comparing Video and Augmented Reality Assistance in Manual Assembly
Loch, F., Quint, F., & Brishtel, I. (2016) · 2016 12th International Conference on Intelligent Environments (IE) · doi:10.1109/ie.2016.31 · Cited by 110
Laviola, E., Gattullo, M., Manghisi, V. M., Fiorentino, M., & Uva, A. E. (2022) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-021-08449-6 · Cited by 79
Deep Learning-Based Applications for Safety Management in the AEC Industry: A Review
Hou, L., Chen, H., Zhang, G. (., & Wang, X. (2021) · Applied Sciences · doi:10.3390/app11020821 · Cited by 76
Self-citation
Metadata
- Authors
- Hou, L., Wang, X., Bernold, L., & Love, P. E. D.
- Venue
- Journal of Computing in Civil Engineering
- Published
- 2013-09
- Volume
- 27
- Issue
- 5
- Pages
- 439-451
- ISSN
- 0887-3801 (ISSN-L)
- 1943-5487
- OpenAlex
- W2038969306
- Cited by
- 261
- References
- 28
- FWCI
- 8.18
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Using Animated Augmented Reality to Cognitively Guide Assembly. https://app.cochat.ai/papers/10.1061/(asce)cp.1943-5487.0000184
- The paper
- Hou, L., Wang, X., Bernold, L., & Love, P. E. D. (2013). Using Animated Augmented Reality to Cognitively Guide Assembly. Journal of Computing in Civil Engineering. https://doi.org/10.1061/(asce)cp.1943-5487.0000184
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.