This study focuses on the development and implementation of a shape-mimetics wireless monitoring system. A 3D printer is used to monitoring device, which mimics these shapes, is referred to as a shape-mimetics wireless monitoring robot. The effectiveness of this system depends on the complexity of both the shape and the environment. When both factors are relatively simple, trajectory estimation can be performed using mathematical modeling. This was validated through experiments involving the motion of a ball on a horizontal plane using grasp-less handling. In contrast, when both factors are complex, vibrations and external forces can be directly monitored as raw data in a straightforward manner. This was demonstrated during the egg washing and inspection process, which served as a complex, real-world application. These results show that the shape-mimetics wireless monitoring system can achieve continuous trajectory estimation and monitor vibrations and external forces at a higher sampling frequency compared to conventional vision-based monitoring systems. The findings suggest that the proposed system could be beneficial in a wide range of industries, including manufacturing and food processing.

1. [1] A. G. Frank, L. S. Dalenogare, and N. F. Ayala, “Industry 4.0 technologies: Implementation patterns in manufacturing companies,” Int. J. Prod. Econ., Vol.210, pp. 15-26, 2019. https://doi.org/10.1016/j.ijpe.2019.01.004
2. [2] J. Vachálek, L. Bartalský, O. Rovný, D. Šišmišová, M. Morháč, and M. Lokšík, “The digital twin of an industrial production line within the industry 4.0 concept,” 2017 21st Int. Conf. Proc. Control (PC), pp. 258-262, 2017. https://doi.org/10.1109/PC.2017.7976223
3. [3] M. Liu, S. Fang, H. Dong, and C. Xu, “Review of digital twin about concepts, technologies, and industrial applications,” J. Manuf. Syst., Vol.58, Part B, pp. 346-361, 2021. https://doi.org/10.1016/j.jmsy.2020.06.017
4. [4] D. Jones, C. Snider, A. Nassehi, J. Yon, and B. Hicks, “Characterising the digital twin: A systematic literature review,” CIRP J. Manuf. Sci. Technol., Vol.29, Part A, pp. 36-52, 2020. https://doi.org/10.1016/j.cirpj.2020.02.002
5. [5] M. Singh, E. Fuenmayor, E. P. Hinchy, Y. Qiao, N. Murray, and D. Devine, “Digital twin: origin to future,” Appl. Syst. Innov., Vol.4, Article No.36, 2021. https://doi.org/10.3390/asi4020036
6. [6] S. Boschert and R. Rosen, “Digital twin—the simulation aspect,” P. Hehenberger and D. Bradley, (Eds), “Mechatronic Futures,” Springer, pp. 59-74, 2016. https://doi.org/10.1007/978-3-319-32156-1_5
7. [7] L. U. Khan, Z. Han, W. Saad, E. Hossain, M. Guizani, and C. S. Hong, “Digital twin of wireless systems: Overview, taxonomy, challenges, and opportunities,” IEEE Commun. Surv. Tutor., Vol.24, No.4, pp. 2230-2254, 2022. https://doi.org/10.1109/COMST.2022.3198273
8. [8] B. Sheen, J. Yang, X. Feng, and M. M. U. Chowdhury, “A digital twin for reconfigurable intelligent surface assisted wireless communication,” Netw. Internet Archit., 2020. https://doi.org/10.48550/arXiv.2009.00454
9. [9] D. Kandris, C. Nakas, D. Vomvas, and G. Koulouras, “Applications of wireless sensor networks: an up-to-date survey,” Appl. Syst. Innov., Vol.3, No.1, Article No.14, 2020. https://doi.org/10.3390/asi3010014
10. [10] O. I. Khalaf and B. M. Sabbar, “An overview on wireless sensor networks and finding optimal location of nodes,” Period. Eng. Nat. Sci., Vol.7, No.3, pp. 1096-1101, 2019. https://doi.org/10.21533/pen.v7i3.645
11. [11] B. Shakmak and A. Al-Habaibeh, “Detection of water leakage in buried pipes using infrared technology; A comparative study of using high and low resolution infrared cameras for evaluating distant remote detection,” 2015 IEEE Jordan Conf. on Applied Electrical Engineering and Computing Technologies (AEECT), 2015. https://doi.org/10.1109/AEECT.2015.7360563
12. [12] Y. Horikawa, A. Mizutani, T. Noda, and H. Kikuta, “Stereo Camera System with Digital Image Correlation Method for Accurate Measurement of Position and Orientation of Positioning Stage,” Int. J. Automation Technol., Vol.9, No.4, pp. 436-443, 2015. https://doi.org/10.20965/ijat.2015.p0436
13. [13] N. Kochi, T. Tanabata, A. Hayashi, and S. Isobe, “A 3D Shape-Measuring System for Assessing Strawberry Fruits,” Int. J. Automation Technol., Vol.12, No.3, pp. 395-404, 2018. https://doi.org/10.20965/ijat.2018.p0395
14. [14] N. Kochi, S. Isobe, A. Hayashi, K. Kodama, and T. Tanabata, “Introduction of All-Around 3D Modeling Methods for Investigation of Plants,” Int. J. Automation Technol., Vol.15, No.3, pp. 301-312, 2021. https://doi.org/10.20965/ijat.2021.p0301
15. [15] K. Ohno, H. Date, and S. Kanai, “Study on Real-Time Point Cloud Superimposition on Camera Image to Assist Environmental Three-Dimensional Laser Scanning,” Int. J. Automation Technol., Vol.15, No.3, pp. 324-333, 2021. https://doi.org/10.20965/ijat.2021.p0324
16. [16] K. Endo, T. Ishiwata, and T. Yamazaki, “Development of Ultralow-Cost Machine Vision System,” Int. J. Automation Technol., Vol.11, No.4, pp. 629-637, 2017. https://doi.org/10.20965/ijat.2017.p0629
17. [17] F. Bleicher, P. Schörghofer, and C. Habersohn, “In-process control with a sensory tool holder to avoid chatter,” J. of Machine Engineering, Vol.18, No.3, pp. 16-17, 2018. https://doi.org/10.5604/01.3001.0012.4604
18. [18] F. Bleicher, D. Biermann, W.-G. Drossel, H.-C. Moehring, and Y. Altintas, “Sensor and actuator integrated tooling systems,” CIRP Annals, Vol.72, No.2, pp. 673-696, 2023. https://doi.org/10.1016/j.cirp.2023.05.009
19. [19] T. Yamamoto, R. Matsuda, M. Shindou, T. Hirogaki, and E. Aoyama, “Monitoring of Vibrations in Free-Form Surface Processing Using Ball Nose End Mill Tools with Wireless Tool Holder Systems,” Int. J. Automation Technol., Vol.15, No.3, pp. 335-342, 2021. https://doi.org/10.20965/ijat.2021.p0335
20. [20] R. Matsuda, M. Shindou, T. Hirogaki, and E. Aoyama, “Monitoring of Rotational Vibration in Tap and Endmill Processes with a Wireless Multifunctional Tool Holder System,” Int. J. Automation Technol., Vol.12, No.6, pp. 876-882, 2018. https://doi.org/10.20965/ijat.2018.p0876
21. [21] T. Stone, N. Stone, N. Roy, W. Melton, J. B. Jackson, and S. Nelakuditi, “On Smart Soccer Ball as a Head Impact Sensor,” IEEE Trans. on Instrumentation and Measurement, Vol.68, No.8, pp. 2979-2987, 2019. https://doi.org/10.1109/TIM.2018.2872307
22. [22] H. Hanai, A. Miura, T. Hirogaki, and E. Aoyama, “Advanced musical saw manipulation by an industrial cooperative humanoid robot with passive sound feedback,” J. Robot. Mechatron., Vol.35, No.3, pp. 711-722, 2023. https://doi.org/10.20965/jrm.2023.p0711
23. [23] H. Hanai, M. Ozawa, T. Hirogaki, and E. Aoyama, “Consideration of autonomous decentralized coordination of electric balancer and robotic arm with inertia compensation for larger payload manipulation,” ASME 2023 Int. Des. Eng. Tech. Conf. Comput. Inf. Eng. Conf., 2023. https://doi.org/10.1115/DETC2023-115166
24. [24] H. Hanai, A. Miura, T. Hirogaki, and E. Aoyama, “Tuning motion of musical saw with a humanoid robot for industrial automation based on a sound feed-back process,” ASME 2021 Int. Des. Eng. Tech. Conf. Comput. Inf. Eng. Conf., 2021. https://doi.org/10.1115/DETC2021-68287
25. [25] H. Hanai, T. Hirogaki, M. Ozawa, and E. Aoyama, “Investigation of autonomous cooperation between industrial cooperative humanoid robot and passive balancer,” Int. J. Mech. Eng. Robot. Res., Vol.11, No.12, pp. 884-890, 2022. https://doi.org/10.18178/ijmerr.11.12.884-890
26. [26] M. Shariatee, A. Akbarzadeh, A. Mousavi, and S. Alimardani, “Design of an economical SCARA robot for industrial applications,” 2014 Second RSI/ISM Int. Conf. Robot. Mechatron. (ICRoM), 2014. https://doi.org/10.1109/ICRoM.2014.6990957
27. [27] M. T. Das and L. C. Dülger, “Mathematical modelling, simulation and experimental verification of a scara robot,” Simul. Model. Pract. Theory, Vol.13, No.3, pp. 257-271, 2005. https://doi.org/10.1016/j.simpat.2004.11.004
28. [28] N. Wang, J. Liu, S. Wei, Z. Xu, and X. Zhang, “The control system design of a SCARA robot,” X. Zhang, H. Liu, Z. Chen, and N. Wang (Eds.), “Intelligent Robotics and Applications,” Springer, pp. 136-145, 2014. https://doi.org/10.1007/978-3-319-13963-0_14
29. [29] H. Hanai, M. Yuma, Y. Wada, M. Nakagawa, T. Hirogaki, and E. Aoyama, “Nonlinear Modeling of Ball Rolling Motion on a Horizontal Surface for Improving Grasp-Less Handling by Applying Rolling Friction Torque,” 2024 Int. Symp. on Flexible Automation, Article No.ISFA2024-140998, 2024. https://doi.org/10.1115/ISFA2024-140998
30. [30] F. Narváez, F. Árbito, and R. Proaño, “A quaternion-based method to IMU-to-body alignment for gait analysis,” Int. Conf. Dig. Hum. Model. Appl. Health Saf. Ergon. Risk Manag., pp. 217-231, 2018.
31. [31] R. Brard, L. Bellanger, L. Chevreuil, F. Doistau, P. Drouin, and A. Stamm, “A novel walking activity recognition model for rotation time series collected by a wearable sensor in a free-living environment,” Sensors, Vol.22, No.9, 2022. https://doi.org/org10.3390/s22093555
32. [32] X. Kong, “INS algorithm using quaternion model for low cost IMU Sensors,” Robot. Auton. Syst., Vol.46, No.4, pp. 221-246, 2004. https://doi.org/10.1016/j.robot.2004.02.001
33. [33] K. Wen, K. Yu, S. Zhang, and W. Zhang, “A new quaternion Kalman filter based foot-mounted IMU and UWB tightly-coupled method for indoor pedestrian navigation,” IEEE Trans. Veh. Technol., Vol.69, No.4, pp. 4340-4352, 2020. https://doi.org/10.1109/TVT.2020.2974667
34. [34] H. Hanai, Y. Mita, T. Hirogaki, and E. Aoyama, “Monitoring Method of Ball Rolling Motion with Quaternion-Based Signal Processing,” Advances in Science and Technology, Vol.143, pp. 55-60, 2024. https://doi.org/10.4028/p-psCvO9