Abstract
Technology advancement is changing the way industrial factories have to face an increasingly complex and competitive market. The fourth industrial revolution (known as industry 4.0) is also changing how human workers have to carry out tasks and actions. In fact, it is no longer impossible to think of a scenario in which human operators and industrial robots work side-by-side, sharing the same environment and tools. To realize a safe work environment, workers should trust robots as well as they trust human operators. Such goal is indeed complex to achieve, especially when workers are under stress conditions, such as when a fault occurs and the human operators are no longer able to understand what is happening in the industrial manipulator. Indeed, Augmented Reality (AR) can help workers to visualize in real-time robots’ faults. This paper proposes an augmented system that assists human workers to recognize and visualize errors, improving their awareness of the system. The system has been tested using both an AR see-through device and a smartphone.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Bauer, A., Wollherr, D., Buss, M.: Human-robot collaboration: a survey. Int. J. Humanoid Robot. 5(01), 47–66 (2008)
Morato, C., Kaipa, K.N., Zhao, B., Gupta, S.K.: Toward safe human robot collaboration by using multiple kinects based real-time human tracking. J. Comput. Inf. Sci. Eng. 14(1), 011006 (2014)
Coovert, M.D., Lee, T., Shindev, I., Sun, Y.: Spatial augmented reality as a method for a mobile robot to communicate intended movement. Comput. Hum. Behav. 34, 241–248 (2014)
Chen, J., Patton, R.J.: Robust Model-based Fault Diagnosis for Dynamic Systems, vol. 3. Springer, Boston (2012). https://doi.org/10.1007/978-1-4615-5149-2
Miseikis, J., Knobelreiter, P., Brijacak, I., Yahyanejad, S., Glette, K., Elle, O.J., Torresen, J.: Robot Localisation and 3D Position Estimation Using a Free-Moving Camera and Cascaded Convolutional Neural Networks (2018). arXiv preprint arXiv:1801.02025
Nikolaidis, S., Lasota, P., Rossano, G., Martinez, C., Fuhlbrigge, T., Shah, J.: Human-robot collaboration in manufacturing: quantitative evaluation of predictable, convergent joint action. In: 2013 44th International Symposium on Robotics (ISR), pp. 1–6. IEEE (2013)
Chadalavada, R.T., Andreasson, H., Krug, R., Lilienthal, A.J.: That’s on my mind! robot to human intention communication through on-board projection on shared floor space. In: 2015 European Conference on Mobile Robots (ECMR), pp. 1–6. IEEE (2015)
Matsumaru, T.: Mobile robot with preliminary-announcement and display function of forthcoming motion using projection equipment. In: The 15th IEEE International Symposium on Robot and Human Interactive Communication, 2006, ROMAN 2006, pp. 443–450. IEEE (2006)
Akan, B., Çürüklü, B.: Augmented reality meets industry: Interactive robot programming. In: Proceedings of SIGRAD 2010: Content Aggregation and Visualization, 25–26 November 2010, Västerås, Sweden, no. 052, pp. 55–58. Linköping University Electronic Press (2010)
Michalos, G., Karagiannis, P., Makris, S., Tokçalar, Ö., Chryssolouris, G.: Augmented reality (AR) applications for supporting human-robot interactive cooperation. Procedia CIRP 41, 370–375 (2016)
Mateo, C., Brunete, A., Gambao, E., Hernando, M.: Hammer: an android based application for end-user industrial robot programming. In: 2014 IEEE/ASME 10th International Conference on Mechatronic and Embedded Systems and Applications (MESA), pp. 1–6. IEEE (2014)
Fantuzzi, C., Secchi, C., Visioli, A.: On the fault detection and isolation of industrial robot manipulators. IFAC Proc. Vol. 36(17), 399–404 (2003)
Singh, V. D., Banga, V. K.: Overloading failures in robot manipulators. In: International Conference on Trends in Electrical, Electronics and Power Engineering (ICTEEP’2012)/Planetary Scientific Research Centre, pp. 15–16 (2012)
Michieletto, S., Chessa, N., Menegatti, E.: Learning how to approach industrial robot tasks from natural demonstrations. In: 2013 IEEE Workshop on Advanced Robotics and Its Social Impacts (ARSO), pp. 255–260. IEEE (2013)
Meta 2 ar headset. Accessed 2018
Eski, I., Erkaya, S., Savas, S., Yildirim, S.: Fault detection on robot manipulators using artificial neural networks. Robot. Comput.-Integr. Manuf. 27(1), 115–123 (2011)
Vemuri, A.T., Polycarpou, M.M.: Neural-network-based robust fault diagnosis in robotic systems. IEEE Trans. Neural Netw. 8(6), 1410–1420 (1997)
Ghrieb, A.O., Kourd, Y., Guersi, N.: Supervision of industrial manipulators using ANFIS system. In: 2017 17th International Conference on Control, Automation and Systems (ICCAS), pp. 161–166. IEEE, October 2017
https://www.epson.it/products/see-through-mobile-viewer/moverio-bt-200
Milgram, P., Kishino, F.: A taxonomy of mixed reality visual displays. IEICE Trans. Inf. Syst. 77, 1321–1329 (1994)
Hulin, T., Hertkorn, K., Preusche, C.: Interactive features for robot viewers. In: Su, C.-Y., Rakheja, S., Liu, H. (eds.) ICIRA 2012. LNCS (LNAI), vol. 7508, pp. 181–193. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-33503-7_19
Sutherland, I.E.: A head-mounted three dimensional display. In: Proceedings of the AFIPS, pp. 757–764. ACM, San Francisco (1968)
De Pace, F., Manuri, F., Sanna, A.: Augmented reality in industry 4.0. Am. J. Comput. Sci. Inf. Technol. 6(1), 1–7 (2018)
Sanna, A., Manuri, F.: A survey on applications of augmented reality. Adv. Comput. Sci. Int. J. 5(1), 18–27 (2016)
Acknowledgements
This work is co-funded by the regional project HuManS (Human Centered Manufacturing Systems).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
De Pace, F., Manuri, F., Sanna, A., Zappia, D. (2018). An Augmented Interface to Display Industrial Robot Faults. In: De Paolis, L., Bourdot, P. (eds) Augmented Reality, Virtual Reality, and Computer Graphics. AVR 2018. Lecture Notes in Computer Science(), vol 10851. Springer, Cham. https://doi.org/10.1007/978-3-319-95282-6_30
Download citation
DOI: https://doi.org/10.1007/978-3-319-95282-6_30
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-95281-9
Online ISBN: 978-3-319-95282-6
eBook Packages: Computer ScienceComputer Science (R0)