Skip to main content

A Survey on Components of AR Interfaces to Aid Packing Operations

  • Conference paper
  • First Online:
Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future (SOHOMA 2021)

Abstract

Manual packing operations require a suitable interface to communicate the physical packing sequence (PPS) to the operators involved. The interfaces available in these applications are not much used because of their low effectiveness. Augmented Reality (AR) interfaces can help to improve the communication of the PPS but there is a lack of knowledge about its components and the performance in relation with the packing operation. This paper explores this relation with a method based on a documentary analysis that allows identifying articles and surveys concerning: (1) typologies of packing and its relationship with AR interfaces, (2) components of an AR system, and its relationship with packing operations and (3) tracking algorithms suitable to industrial packing environments. The survey is intended to review techniques in AR and packing operations, that allow the identification of current trends, and the formulation of a taxonomy in marker-less tracking algorithms suitable for packing applications. Authors expect that those formulations serve as guidance for the creation of new solutions in the area.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Araújo, L.J.P., Özcan, E., Atkin, J.A.D., Baumers, M.: Analysis of irregular three-dimensional packing problems in additive manufacturing: a new taxonomy and dataset. Int. J. Prod. Res. 57(18), 5920–5934 (2019)

    Article  Google Scholar 

  2. Berkemeier, L., Zobel, B., Werning, S., Ickerott, I., Thomas, O.: Engineering of augmented reality-based information systems: design and implementation for intralogistics services. Bus. Inf. Syst. Eng. 61(1), 67–89 (2019)

    Article  Google Scholar 

  3. Bimber, O., Raskar, R.: Spatial Augmented Reality Merging Real and Virtual Worlds (2005)

    Google Scholar 

  4. Bortfeldt, A., Wäscher, G.: Constraints in container loading - a state-of-the-art review. Eur. J. Oper. Res. 229(1), 1–20 (2013)

    Article  MathSciNet  Google Scholar 

  5. Byravan, A., Fox, D.: SE3-nets: learning rigid body motion using deep neural networks. In: Proceedings - IEEE International Conference on Robotics and Automation, no. 3, pp. 173–180 (2017)

    Google Scholar 

  6. Chatzopoulos, D., Bermejo, C., Huang, Z., Hui, P.: Mobile augmented reality survey: from where we are to where we go. IEEE Access 5, 6917–6950 (2017)

    Article  Google Scholar 

  7. de Souza Cardoso, L.F., Queiroz, F.C.M., Zorzal, E.R.: A survey of industrial augmented reality. Comput. Ind. Eng. 139, 106–159 (2019)

    Google Scholar 

  8. DeTone, D., Malisiewicz, T., Rabinovich, A.: Deep Image Homography Estimation (2016)

    Google Scholar 

  9. Duong, N.D., Kacete, A., Sodalie, C., Richard, P.Y., Royan, J.: XyzNet: towards machine learning camera relocalization by using a scene coordinate prediction network. In: Adjunct Proceedings - 2018 IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2018, pp. 258–263 (2018)

    Google Scholar 

  10. Dyckhoff, H.: A typology of cutting and packing problems. Eur. J. Oper. Res. 44(2), 145–159 (1990)

    Article  MathSciNet  Google Scholar 

  11. Easy Cargo. Easy Cargo (2016)

    Google Scholar 

  12. Garon, M., Lalonde, J.F.: Deep 6-DOF tracking. IEEE Trans. Visual Comput. Graphics 23(11), 2410–2418 (2017)

    Article  Google Scholar 

  13. Ghiani, G.: Intelligent software for logistics. In: Hanne, T., Dornberger, R. (eds.) Computational Intelligence in Logistics and Supply Chain Management, 1 edn, chap. 7, p. 472. Springer, Cham (2017)

    Google Scholar 

  14. Hansson, K., Hernvall, M.: Performance and Perceived Realism in Rasterized 3D Sound Propagation for Interactive Virtual Environments, June 2019

    Google Scholar 

  15. Kim, K., Lepetit, V., Woontack, W.: Scalable real-time planar targets tracking for digilog books. Visual Comput. 26(6–8), 1145–1154 (2010)

    Article  Google Scholar 

  16. Koulieris, G.A., Akşit, K., Stengel, M., Mantiuk, R.K., Mania, K., Richardt, C.: Near-eye display and tracking technologies for virtual and augmented reality. Comput. Graph. Forum 38(2), 493–519 (2019)

    Article  Google Scholar 

  17. Kretschmer, V., Plewan, T., Rinkenauer, G., Maettig, B.: Smart palletisation: cognitive ergonomics in augmented reality based palletising. Adv. Intell. Syst. Comput. 722, 355–360 (2018)

    Google Scholar 

  18. Maettig, B., Hering, F., Doeltgen, M.: Development of an intuitive, visual packaging assistant. In: Nunes, I.L. (ed.) AHFE 2018. AISC, vol. 781, pp. 19–25. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-94334-3_3

    Chapter  Google Scholar 

  19. Maettig, B., Kretschmer, V.: Smart packaging in intralogistics: an evaluation study of human-technology interaction in applying new collaboration technologies. In: Proceedings of the 52nd Hawaii International Conference on System Sciences, pp. 739–748 (2019)

    Google Scholar 

  20. Majewski, M., Kacalak, W.: Human-machine speech-based interfaces with augmented reality and interactive systems for controlling mobile cranes. IEEE Commun. Mag. 54(3), 63–68 (2016)

    Google Scholar 

  21. Marchand, E., Uchiyama, H., Spindler, F.: Pose estimation for augmented reality: a hands-on survey. IEEE Trans. Visual Comput. Graphics 22(12), 2633–2651 (2016)

    Article  Google Scholar 

  22. Masood, T., Egger, J.: Augmented reality in support of industry 4.0-implementation challenges and success factors. Robot. Comput.-Integrated Manuf. 58(March), 181–195 (2019)

    Article  Google Scholar 

  23. Murauer, N., Panz, N., von Hassel, C.: Comparison of scan mechanisms in augmented reality supported order picking processes. In: CEUR Workshop Proceedings, vol. 2082, pp. 69–76 (2018)

    Google Scholar 

  24. Payet, N., Todorovic, S.: From contours to 3D object detection and pose estimation. In: 2011 International Conference on Computer Vision, (ICCV), pp. 983–990 (2011)

    Google Scholar 

  25. Popple, R.: The science of Palletizing - Vol. 3. Technical report, Columbia Machine (2009)

    Google Scholar 

  26. Pressigout, M., Marchand, E.: Model-free augmented reality by virtual visual servoing. In: Proceedings - International Conference on Pattern Recognition, pp. 887–890 (2004)

    Google Scholar 

  27. Ramos, A.G., Oliveira, J.F., Lopes, M.P.: A physical packing sequence algorithm for the container loading problem with static mechanical equilibrium conditions. Int. Trans. Oper. Res. 23(1–2), 215–238 (2016)

    Article  MathSciNet  Google Scholar 

  28. Rusinkiewicz, S., Levoy, M.: Efficient variants of the ICP algorithm. In: Proceedings of International Conference on 3-D Digital Imaging and Modeling, 3DIM, pp. 145–152 (2001)

    Google Scholar 

  29. Saputra, M.R.U., Markham, A., Trigoni, N.: Visual SLAM and structure from motion in dynamic environments-a survey. ACM Comput. Surv. 51(2), 1–36 (2018)

    Article  Google Scholar 

  30. Schmalstieg, D., Hollerer, T.: Augmented Reality: Principles and Practice. Pearson Education (2016)

    Google Scholar 

  31. Tan, D.J., Navab, N., Tombari, F.: 6D Object Pose Estimation with Depth Images: A Seamless Approach for Robotic Interaction and Augmented Reality. arXiv, pp. 1–4 (2017)

    Google Scholar 

  32. Tareen, S.A.K., Saleem, Z.: A comparative analysis of SIFT, SURF, KAZE, AKAZE, ORB, and BRISK. In: 2018 International Conference on Computing, Mathematics and Engineering Technologies: Invent, Innovate and Integrate for Socioeconomic Development, pp. 1–10 (2018)

    Google Scholar 

  33. Uchiyama, H., Marchand, E.: Object detection and pose tracking for augmented reality: recent approaches. In: Foundation in Computer Vision, pp. 1–8 (2012)

    Google Scholar 

  34. Wang, F., Hauser, K.: Robot packing with known items and nondeterministic arrival order. In: Proceedings of RSS, pp. 1–9 (2019)

    Google Scholar 

  35. Wang, X., Ong, S.K., Nee, A.Y.C.: A comprehensive survey of augmented reality assembly research. Adv. Manuf. 4(1), 1–22 (2016). https://doi.org/10.1007/s40436-015-0131-4

    Article  Google Scholar 

  36. Wang, Y., Zhang, S., Yang, S., He, W., Bai, X.: Mechanical assembly assistance using marker-less augmented reality system. Assembly Autom. 38(1), 77–87 (2018)

    Article  Google Scholar 

  37. Wäscher, G., Haußner, H., Schumann, H.: An improved typology of cutting and packing problems. Eur. J. Oper. Res. 183(3), 1109–1130 (2007)

    Article  Google Scholar 

  38. Wurll, C.: Mixed case palletizing with industrial robots summary/abstract state of the art. In: Proceedings of ISR 2016: 47st International Symposium on Robotics, pp. 682–687 (2016)

    Google Scholar 

  39. Zou, D., Cao, Q., Zhuang, Z., Huang, H., Gao, R., Qin, W.: An improved method for model-based training, detection and pose estimation of texture-less 3D objects in occlusion scenes. In: 11th CIRP Conference on Industrial Product-Service Systems, pp. 541–546 (2019)

    Google Scholar 

  40. Zou, Z., Shi, Z., Guo, Y., Ye, J.: Object Detection in 20 Years: A Survey, pp. 1–39 (2019)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Guillermo Camacho-Muñoz .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Camacho-Muñoz, G., Loaiza-Correa, H., Nope, S.E., Álvarez-Martínez, D. (2021). A Survey on Components of AR Interfaces to Aid Packing Operations. In: Trentesaux, D., Borangiu, T., Leitão, P., Jimenez, JF., Montoya-Torres, J.R. (eds) Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future. SOHOMA 2021. Studies in Computational Intelligence, vol 987. Springer, Cham. https://doi.org/10.1007/978-3-030-80906-5_7

Download citation

Publish with us

Policies and ethics