Embedded Flex Sensor for Posture Estimation and Control of a Soft Robotic Neck
DOI:
https://doi.org/10.17979/ja-cea.2025.46.12225Keywords:
Soft robotics, Posture estimation, Fractional-order controlAbstract
This work presents a soft robotic neck with embedded sensing for posture estimation and control. A piezoresistive strain sensor, 3D-printed using TPU and carbon black, is integrated into the soft link to measure bending directly. The sensor’s resistance is mapped to pitch angle through third-order polynomial models, fitted separately for loading and unloading phases to capture hysteresis. A switching strategy based on signal slope dynamically selects between models for real-time estimation. For control, a fractional-order PI (FOPI) controller is implemented, operating on the estimated pitch from the sensor. Despite a low sampling rate (2 Hz) and nonlinear sensor response, the system demonstrates stable closed-loop tracking of a sinusoidal reference trajectory. Experimental results confirm that embedded sensing allows autonomous neck movement without relying on external IMUs. The approach offers a low-cost, compact solution for integrating sensing and control in soft robots. This work supports the development of self-contained, bioinspired robotic systems with enhanced autonomy and adaptability.
References
Ahmed, F., Waqas, M., Jawed, B., Soomro, A. M., Kumar, S., Hina, A., Khan, U., Kim, K. H., Choi, K. H., Jun. 2022. Decade of bio-inspired soft robots: a review. Smart Materials and Structures 31 (7), 073002, publisher: IOP Publishing. URL: https://dx.doi.org/10.1088/1361-665X/ac6e15 DOI: 10.1088/1361-665X/ac6e15
Cianchetti, M., Laschi, C., Menciassi, A., Dario, P., Jun. 2018. Biomedical applications of soft robotics. Nature Reviews Materials 3 (6), 143–153, publisher: Nature Publishing Group. URL: https://www.nature.com/articles/s41578-018-0022-y DOI: 10.1038/s41578-018-0022-y
Elgeneidy, K., Lohse, N., Jackson, M., Apr. 2018. Bending angle prediction and control of soft pneumatic actuators with embedded flex sensors – A data-driven approach. Mechatronics 50, 234–247. URL: https://www.sciencedirect.com/science/article/pii/S0957415817301496 DOI: 10.1016/j.mechatronics.2017.10.005
Gerboni, G., Diodato, A., Ciuti, G., Cianchetti, M., Menciassi, A., Aug. 2017. Feedback Control of Soft Robot Actuators via Commercial Flex Bend Sensors. IEEE/ASME Transactions on Mechatronics 22 (4), 1881–1888, conference Name: IEEE/ASME Transactions on Mechatronics. URL: https://ieeexplore.ieee.org/abstract/document/7914755?casa_token=xIwKRUIv4q4AAAAA:y1oDGWemog5V4adzwNQmzErkklnBav9flfGR7VtTwxOaHUE_PTgao1Y2ZhtnZ88KEkA6M9vpy0M DOI: 10.1109/TMECH.2017.2699677
Iida, F., Laschi, C., Jan. 2011. Soft Robotics: Challenges and Perspectives. Procedia Computer Science 7, 99–102. URL: https://www.sciencedirect.com/science/article/pii/S1877050911006958 DOI: 10.1016/j.procs.2011.12.030
Ji, Q., Jansson, J., Sj¨oberg, M., Wang, X. V., Wang, L., Feng, L., Jun. 2023. Design and calibration of 3D printed soft deformation sensors for soft actuator control. Mechatronics 92, 102980. URL: https://www.sciencedirect.com/science/article/pii/S0957415823000363 DOI: 10.1016/j.mechatronics.2023.102980
Mena, L., Monje, C. A., Nagua, L., Mu˜noz, J., Balaguer, C., Mar. 2020. Test Bench for Evaluation of a Soft Robotic Link. Frontiers in Robotics and AI 7, publisher: Frontiers Media S.A. DOI: 10.3389/frobt.2020.00027
Muñoz, J., Copaci, D. S., Monje, C. A., Blanco, D., Balaguer, C., 2020. Iso-m Based Adaptive Fractional Order Control With Application to a Soft Robotic Neck. IEEE Access 8, 198964–198976, conference Name: IEEE Access. URL: https://ieeexplore.ieee.org/abstract/document/9247181 DOI: 10.1109/ACCESS.2020.3035450
Muñoz, J., de Santos-Rico, R., Mena, L., Monje, C. A., Apr. 2024. Humanoid Head Camera Stabilization Using a Soft Robotic Neck and a Robust Fractional Order Controller. Biomimetics 9 (4), publisher: Multidisciplinary Digital Publishing Institute (MDPI). DOI: 10.3390/biomimetics9040219
Polygerinos, P., Correll, N., Morin, S. A., Mosadegh, B., Onal, C. D., Petersen, K., Cianchetti, M., Tolley, M. T., Shepherd, R. F., 2017. Soft Robotics: Review of Fluid-Driven Intrinsically Soft Devices; Manufacturing, Sensing, Control, and Applications in Human-Robot Interaction. Advanced Engineering Materials 19 (12), 1700016, eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/adem.201700016. URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/adem.201700016 DOI: 10.1002/adem.201700016
Roche, E. T., Wohlfarth, R., Overvelde, J. T. B., Vasilyev, N. V., Pigula, F. A., Mooney, D. J., Bertoldi, K., Walsh, C. J., Feb. 2014. A Bioinspired Soft Actuated Material. Advanced Materials 26 (8), 1200–1206. URL: https://onlinelibrary.wiley.com/doi/10.1002/adma. 201304018 DOI: 10.1002/adma.201304018
Sanchez, C., Rodrıguez, D., Otero, S., Monje, C. A., Jan. 2025. A Piezoresistive Printable Strain Sensor for Monitoring and Control of Soft Robotic Links. In: 2025 IEEE International Conference on Robotics and Automation (ICRA). DOI: Accepted for publication
Shintake, J., Cacucciolo, V., Floreano, D., Shea, H., 2018. Soft Robotic Grippers. Advanced Materials 30 (29), 1707035, eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/adma.201707035. URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/adma.201707035 DOI: 10.1002/adma.201707035
Yasa, O., Toshimitsu, Y., Michelis, M. Y., Jones, L. S., Filippi, M., Buchner, T., Katzschmann, R. K., May 2023. An Overview of Soft Robotics. Annual Review of Control, Robotics, and Autonomous Systems 6 (Volume 6, 2023), 1–29, publisher: Annual Reviews. URL: https://www.annualreviews.org/content/journals/10.1146/annurev-control-062322-100607 DOI: 10.1146/annurev-control-062322-100607
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Gianluca Miglietta, Claudia Sánchez Hernández, Jorge Muñoz, Santiago Martínez , Concepción A. Monje
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
