Design and Fabrication of Soft 3D Printed Sensors and Performance Analysis of the Soft Sensors in a C-leg as Sensing Element

Year 2022, Volume: 9 Issue: 3, 193 - 204, 28.09.2022

Doğa Özbek Talip Batuhan Yılmaz Mert Ali İhsan Kalın Onur Özcan

https://doi.org/10.17350/HJSE19030000271

Abstract

In soft robotics, a recent challenge is to decrease the number of rigid components used tocreate entirely soft robots. A common rigid component used in soft robots is the rigid encoder, which should be replaced with a soft counterpart if possible. In this work, we de-sign and manufacture a soft sensor, which is embedded into a C-shaped leg of a soft, legged, miniature robot. Our main goal is to show that we can embed a soft sensor into and receive contact feedback from a soft C-shaped leg of our soft miniature quadruped. We test various sensor parameters using custom test setups to analyze the soft sensor performance. Our soft sensor design is iterated by experimentally investigating several sensor shape options. For the C-leg of the soft miniature quadruped, optimal sensor geometry and position for the sensor implementation are found from a discrete design space as the outcome of this work. We received feedback from the soft sensor and compared commercial encoder data to the soft sensor embedded C-leg data. We managed to detect the rotation speed of the C-leg with the accuracy of 87.5% on a treadmill and with the accuracy of %86.7 under free rotation of the C-leg. However, if connection loss occurs in the miniature slipring mechanism, the error percentage in estimating the rotational speed increases significantly.

Keywords

soft robots, miniature robots, legged robots, soft sensors, soft robot materials and design

References

• S. Kim, C. Laschi and B. Trimmer. Soft robotics: A bioinspired evolution in robotics. Trends in Biotechnology 4, 5 (2013) 287-294.
• C. Laschi and B. Mazzolai. Lessons from animals and plants: The symbiosis of morphological computation and soft robotics. IEEE Robotics & Automation Magazine 23, 3 (2016) 107-114.
• M. S. Xavier, A. J. Fleming and Y. K. Yong. Experimental characterisation of hydraulic fiber-reinforced soft actuators for worm-like robots. Paper presented at 7th International Conference on Control, Mechatronics and Automation, TU Delft, Netherlands, 6-8 November. pp. 204-209, 2019.
• Jin, T., Sun, Z., Li, L. et al. Triboelectric nanogenerator sensors for soft robotics aiming at digital twin applications. Nature Communucations 11, 5381 (2020).
• P. Ferrentino, K. T. Seyedreza, J. Brancart, G. Van Assche, B. Vanderborght and S. Terryn. FEA-Based Inverse Kinematic Control: Hyperelastic Material Characterization of Self-Healing Soft Robots in IEEE Robotics & Automation Magazine (2021) 2-12.
• A. L. Gunderman, J. A. Collins, A. L. Myers, R. T. Threlfall and Y. Chen, Tendon-Driven Soft Robotic Gripper for Blackberry Harvesting. IEEE Robotics and Automation Letters 7, 2 (2022) 2652-2659.
• X. Huang, K. Kumar, M. Khalid Jawed, Z. Ye and C. Majidi. Soft Electrically Actuated Quadruped (SEAQ)—Integrating a Flex Circuit Board and Elastomeric Limbs for Versatile Mobility. IEEE Robotics and Automation Letters 4, 3 (2019) 2415-2422.
• M. A. İ. Kalın, C. Aygül, A. Türkmen, J. Kwiczak-Yiğitbaşı, B. Baytekin and O. Özcan. Design, Fabrication, and Locomotion Analysis of an Untethered Miniature Soft Quadruped, SQuad. IEEE Robotics and Automation Letters 5, 3 (2020) 3854-3860.
• D. Özbek, T. B. Yılmaz, M. A. İ. Kalın, K. Şentürk and O. Özcan. Detecting Scalable Obstacles Using Soft Sensors in the Body of a Compliant Quadruped. IEEE Robotics and Automation Letters 7, 2 (2022) 1745-1751.
• Wehner, M., Truby, R., Fitzgerald, D. et al. An integrated design and fabrication strategy for entirely soft, autonomous robots. Nature 536 (2016) 451–455.
• T. G. Thuruthel, B. Shih, C. Laschi and M. T. Tolley. Soft robot perception using embedded soft sensors and recurrent neural networks. Science Robotics 4, 26 (2019) eaav1488.
• B. Shih et al. Design considerations for 3D printed soft multimaterial resistive sensors for soft robotics. Frontiers in Robotics and AI 6 (2019).
• K. B. Justus et al. A biosensing soft robot: Autonomous parsing of chemical signals through integrated organic and inorganic interfaces. Science Robotics 4, 31 (2019) eaax0765.
• A. Atalay et al. Batch fabrication of customizable silicone-textile composite capacitive strain sensors for human motion tracking. Advance Materials Technologies 2, 9 (2017) 1700136.
• Y. Mengüç et al. Wearable soft sensing suit for human gait measurement. The International Journal of Robotics Research 33, 14 (2014) 1748-1764.
• GONG, Jun, et al. MetaSense: Integrating Sensing Capabilities into Mechanical Metamaterial. Paper presented at The 34th Annual ACM Symposium on User Interface Software and Technology, Virtual Event USA, 10-14 October. E-Publishing Inc., New York, pp. 1063–1073, 2021.
• W.-Y. Li, A. Takata, H. Nabae, G. Endo and K. Suzumori. Shape recognition of a tensegrity with soft sensor threads and artificial muscles using a recurrent neural network. IEEE Robotics and Automation Letters 6, 4 (2021) 6228-6234.
• TAWK, Charbel, et al. Soft pneumatic sensing chambers for generic and interactive human–machine interfaces. Advanced Intelligent Systems 1,1 (2019) 1900002.
• C. To, T. L. Hellebrekers and Y. -L. Park. Highly stretchable optical sensors for pressure, strain, and curvature measurement. Paper presented at IEEE/RSJ International Conference on Intelligent Robots and Systems, 28 September - 2 October. pp. 5898-5903, 2015.
• Jones, R.M. Mechanics of Composite Materials, second ed. CRC Press, Boca Raton, 1999.