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On the integration of FBG sensing technology into robotic grippers

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Abstract

Modern industrial processes aim for the continuous production of small volumes tailored to the customer’s needs. Machines and robotic platforms have to be more and more adaptable, flexible, and able to cope with complex scenarios where sensing and manipulation capabilities are the key technology to succeed. The literature has plenty of capacitive, resistive, piezoelectric, and piezoresistive sensors used as tactile or force sensors. All of them present some drawbacks like non-linear behavior, sensitivity to temperature or electromagnetic noise, and hysteresis, among others. Other sensing systems are bulky and hard to integrate, sometimes jeopardizing the dexterity and manipulability of the gripper. In this context, the manuscript proposes fiber Bragg grating (FBG) optical fiber as a tactile sensing element to capture the interaction forces during material handling and object manipulation since it has numerous advantages compared with the other sensing devices. The work also offers a methodology to easily integrate the fiber in industrial grippers and introduces a set of tests useful to characterize the sensors. Custom gripper fingers have been realized in rapid prototyping to present a pictorial example of such an integration. Finally, the essay presents some experiments that assess the capability of a tactile sensor based on FBG optical fiber showing as it can correctly perceive the contact forces (NRMSE = 0.75%) and can recognize the material of the object that is being manipulated. The authors believe that the application of optical fiber sensor as tactile feedback can be useful in industrial scenarios to enable complex manipulation activities.

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References

  1. Acer M, Salerno M, Agbeviade K, Paik J (2015) Development and characterization of silicone embedded distributed piezoelectric sensors for contact detection. Smart Materials and Structures 24 7(075):030

    Google Scholar 

  2. Ascari L, Corradi P, Beccai L, Laschi C (2007) A miniaturized and flexible optoelectronic sensing system for tactile skin. J Micromech Microeng 17(11):2288

    Article  Google Scholar 

  3. Barone F, Signorini A, Ntibarikure L, Fiore T, Di Pasquale F, Oton CJ (2018) Fiber-optic liquid level sensing by temperature profiling with an fbg array. Sensors 18:8. https://doi.org/10.3390/s18082422. https://www.mdpi.com/1424-8220/18/8/2422

    Article  Google Scholar 

  4. Birglen L, Schlicht T (2018) A statistical review of industrial robotic grippers. Robotics and Computer-Integrated Manufacturing 49:88–97. https://doi.org/10.1016/j.rcim.2017.05.007. http://www.sciencedirect.com/science/article/pii/S0736584516304240

    Article  Google Scholar 

  5. Choi B, Choi HR, Kang S (2005) Development of tactile sensor for detecting contact force and slip. In: 2005 IEEE/RSJ International conference on intelligent robots and systems, pp. 2638–2643. IEEE

  6. Chossat JB, Shin HS, Park Y, Duchaine V (2015) Soft tactile skin using an embedded ionic liquid and tomographic imaging, journal of mechanisms and robotics,7, 2

  7. Culshaw B, Kersey A (2008) Fiber-optic sensing: a historical perspective. J Light Technol 26 (9):1064–1078. https://doi.org/10.1109/JLT.0082.921915https://doi.org/10.1109/JLT.0082.921915

    Article  Google Scholar 

  8. Cutkosky MR, Provancher W (2016) Force and tactile sensing. In: Springer handbook of robotics, pp. 717–736. Springer

  9. Cutkosky MR, Ulmen J (2014) Dynamic tactile sensing. In: The human hand as an inspiration for robot hand development, pp. 389–403. Springer

  10. Dahiya RS, Valle M (2013) Tactile sensing technologies. In: Robotic tactile sensing, pp. 79–136. Springer

  11. D’Avella S, Tripicchio P, Avizzano CA (2020) A study on picking objects in cluttered environments: exploiting depth features for a custom low-cost universal jamming gripper. http://www.sciencedirect.com/science/article/pii/S0736584519307276, vol 63, p 888, DOI https://doi.org/10.1016/j.rcim.2019.101888

  12. Denei S, Maiolino P, Baglini E, Cannata G (2015) On the development of a tactile sensor for fabric manipulation and classification for industrial applications. In: 2015 IEEE/RSJ International conference on intelligent robots and systems (IROS), pp. 5081–5086. IEEE

  13. Di Francesca D, Toccafondo I, Li Vecchi G, Calderini S, Girard S, Alessi A, Ferraro R, Danzeca S, Kadi Y, Brugger M (2018) Distributed optical fiber radiation sensing in the proton synchrotron booster at CERN. IEEE Transactions on Nuclear Science PP 65:1–1. https://doi.org/10.1109/TNS.2018.2818760

    Article  Google Scholar 

  14. Dragiev S, Toussaint M, Gienger M (2013) Uncertainty aware grasping and tactile exploration. In: 2013 IEEE International conference on robotics and automation, pp. 113–119. IEEE

  15. Edsinger-Gonzales A (2005) Design of a compliant and force sensing hand for a humanoid robot. tech. rep. massachusetts inst of tech cambridge artificial intelligence lab

  16. Engeberg ED, Meek SG (2013) Adaptive sliding mode control for prosthetic hands to simultaneously prevent slip and minimize deformation of grasped objects. IEEE/ASME Transactions on Mechatronics 18 (1):376–385

    Article  Google Scholar 

  17. Eum S, Kageyama K, Murayama H, Uzawa K, Ohsawa I, Kanai M, Igawa H (2008) Process/health monitoring for wind turbine blade by using FBG sensors with multiplexing techniques Proceedings of SPIE - The International Society for Optical Engineering

  18. Felip J, Morales A (2009) Robust sensor-based grasp primitive for a three-finger robot hand. In: 2009 IEEE/RSJ International conference on intelligent robots and systems, pp. 1811–1816

  19. Girão P.S., Ramos PMP, Postolache O, Pereira JMD (2013) Tactile sensors for robotic applications. Measurement 46(3):1257–1271. https://doi.org/10.1016/j.measurement.2012.11.015. http://www.sciencedirect.com/science/article/pii/S0263224112004368

    Article  Google Scholar 

  20. Jamali N, Sammut C (2011) Majority voting: material classification by tactile sensing using surface texture. IEEE Trans Robot 27(3):508–521

    Article  Google Scholar 

  21. Jara CA, Pomares J, Candelas FA, Torres F (2014) Control framework for dexterous manipulation using dynamic visual servoing and tactile sensors’ feedback. Sensors 14(1):1787–1804

    Article  Google Scholar 

  22. Kappassov Z, Corrales JA, Perdereau V (2015) Tactile sensing in dexterous robot hands. Robot Auton Syst 74:195–220

    Article  Google Scholar 

  23. Kerrouche A, Leighton J, Boyle WJO, Gebremichael YM, Sun T, Grattan KTV, Taljsten B (2008) Strain measurement on a rail bridge loaded to failure using a fiber Bragg grating-based distributed sensor system. IEEE Sensors J 8(12):2059–2065. https://doi.org/10.1109/JSEN.2008.2006704

    Article  Google Scholar 

  24. Kim MS, Ahn HR, Lee S, Kim C, Kim YJ (2014) A dome-shaped piezoelectric tactile sensor arrays fabricated by an air inflation technique. Sensors and Actuators A: Physical 212:151–158. https://doi.org/10.1016/j.sna.2014.02.023. http://www.sciencedirect.com/science/article/pii/S0924424714000879

    Article  Google Scholar 

  25. collab=Leo Jiang, Low, K., Costa, J., Black, R.J., Park, Y. (2015) Fiber optically sensorized multi-fingered robotic hand. In: 2015 IEEE/RSJ International conference on intelligent robots and systems (IROS), pp. 1763–1768

  26. Liang Q, Zou K, Long J, Jin J, Zhang D, Coppola G, Sun W, Wang Y, Ge Y (2018) Multi-component FBG-based force sensing systems by comparison with other sensing technologies: a review. IEEE Sensors J 18(18):7345–7357

    Article  Google Scholar 

  27. Liu X, Iordachita II, He X, Taylor RH, Kang JU (2012) Miniature fiber-optic force sensor based on low-coherence Fabry-Pérot interferometry for vitreoretinal microsurgery. Biomed. Opt. Express 3(5):1062–1076. https://doi.org/10.1364/BOE.3.001062. http://www.osapublishing.org/boe/abstract.cfm?URI=boe-3-5-1062

    Article  Google Scholar 

  28. Lévesque F., Sauvet B, Cardou P, Gosselin C (2018) A model-based scooping grasp for the autonomous picking of unknown objects with a two-fingered gripper. Robotics and Autonomous Systems 106:14–25. https://doi.org/10.1016/j.robot.2018.04.003. http://www.sciencedirect.com/science/article/pii/S0921889017308898

    Article  Google Scholar 

  29. Ma CW, Hsu LS, Kuo JC, Yang YJ (2015) A flexible tactile and shear sensing array fabricated using a novel buckypaper patterning technique. Sensors and Actuators A:, Physical 231:21–27

    Article  Google Scholar 

  30. Mantriota G (2007) Optimal grasp of vacuum grippers with multiple suction cups. Mechanism and Machine Theory 42(1):18–33. https://doi.org/10.1016/j.mechmachtheory.2006.02.007. http://www.sciencedirect.com/science/article/pii/S0094114X06000541

    Article  MATH  Google Scholar 

  31. Marin YE, Nannipieri T, Oton CJ, Pasquale FD (2018) Current status and future trends of photonic-integrated FBG interrogators. J. Lightwave Technol. 36(4):946–953. http://jlt.osa.org/abstract.cfm?URI=jlt-36-4-946

    Article  Google Scholar 

  32. Massari L, Oddo CM, Sinibaldi E, Detry R, Bowkett J, Carpenter K (2019) Tactile sensing and control of robotic manipulator integrating fiber Bragg grating strain-sensor. Frontiers in neurorobotics 13:8

    Article  Google Scholar 

  33. Muanenda Y, Faralli S, Oton CJ, Pasquale FD (2018) Dynamic phase extraction in a modulated double-pulse ϕ-otdr sensor using a stable homodyne demodulation in direct detection. Opt. Express 26(2):687–701. https://doi.org/10.1364/OE.26.000687. http://www.opticsexpress.org/abstract.cfm?URI=oe-26-2-687

    Article  Google Scholar 

  34. Park Y, Ryu SC, Black RJ, Chau KK, Moslehi B, Cutkosky MR (2009) Exoskeletal force-sensing end-effectors with embedded optical fiber-Bragg-grating sensors. IEEE Trans Robot 25(6):1319–1331

    Article  Google Scholar 

  35. Pirozzi S (2012) Multi-point force sensor based on crossed optical fibers. Sensors and Actuators A: Physical 183:1–10. https://doi.org/10.1016/j.sna.2012.05.045. http://www.sciencedirect.com/science/article/pii/S0924424712003664

    Article  Google Scholar 

  36. Ramly R, Kuntjoro W, Rahman MKA (2012) Using embedded fiber Bragg grating (FBG) sensors in smart aircraft structure materials. In: Procedia Engineering 41, 600–606 (2012). http://www.sciencedirect.com/science/article/pii/S18777058120 26185 International Symposium on Robotics and Intelligent Sensors 2012 IRIS, DOI https://doi.org/10.1016/j.proeng.2012.07.218, (to appear in print)

  37. Saudabayev A, Varol HA (2015) Sensors for robotic hands: a survey of state of the art. IEEE Access 3:1765–1782

    Article  Google Scholar 

  38. Soto MA, Bolognini G, Pasquale FD, Thévenaz L. (2010) Simplex-coded BOTDA fiber sensor with 1 m spatial resolution over a 50 km range. Opt. Lett. 35(2):259–261. https://doi.org/10.1364/OL.35.000259. http://ol.osa.org/abstract.cfm?URI=ol-35-2-259

    Article  Google Scholar 

  39. Soto MA, Nannipieri T, Signorini A, Lazzeri A, Baronti F, Roncella R, Bolognini G, Pasquale FD (2011) Raman-based distributed temperature sensor with 1 m spatial resolution over 26 km SMF using low-repetition-rate cyclic pulse coding. Opt. Lett. 36(13):2557–2559. https://doi.org/10.1364/OL.36.002557. http://ol.osa.org/abstract.cfm?URI=ol-36-13-2557

    Article  Google Scholar 

  40. Suresh R, Tjin SC, Bhalla S (2009) Multi-component force measurement using embedded fiber Bragg grating. Optics & Laser Technology 41(4):431–440. https://doi.org/10.1016/j.optlastec.2008.08.004 . http://www.sciencedirect.com/science/article/pii/S0030399208001643

    Article  Google Scholar 

  41. Tai K, El-Sayed AR, Shahriari M, Biglarbegian M, Mahmud S (2016) State of the art robotic grippers and applications. Robotics 5(2):11

    Article  Google Scholar 

  42. Urhal P, Weightman A, Diver C, Bartolo P (2019) Robot assisted additive manufacturing: a review. Robotics and Computer-Integrated Manufacturing 59:335–345. https://doi.org/10.1016/j.rcim.2019.05.005. http://www.sciencedirect.com/science/article/pii/S0736584518303636

    Article  Google Scholar 

  43. Velha P, Nannipieri T, Signorini A, Morosi M, Solazzi M, Barone F, Frisoli A, Ricciardi L, Eusepi R, Icardi M, Recchia G, Lupi M, Arcoleo G, Firmi P, Di Pasquale F (2019) Monitoring large railways infrastructures using hybrid optical fibers sensor systems, ieee trans intell transp syst, 1–12

  44. Vogt DM, Park Y, Wood RJ (2013) Design and characterization of a soft multi-axis force sensor using embedded microfluidic channels. IEEE Sensors J 13(10):4056–4064. https://doi.org/10.1109/JSEN.2013.2272320

    Article  Google Scholar 

  45. Wang XD, Wolfbeis OS (2013) Fiber-optic chemical sensors and biosensors (2008–2012). Analytical chemistry 85(2):487–508

    Article  Google Scholar 

  46. Wong RDP, Posner JD, Santos VJ (2012) Flexible microfluidic normal force sensor skin for tactile feedback. Sensors and Actuators A: Physical 179:62–69. https://doi.org/10.1016/j.sna.2012.03.023. http://www.sciencedirect.com/science/article/pii/S0924424712001872

    Article  Google Scholar 

  47. Yamaguchi A, Atkeson CG (2016) Combining finger vision and optical tactile sensing: reducing and handling errors while cutting vegetables. In: 2016 IEEE-RAS 16Th international conference on humanoid robots (humanoids), pp. 1045–1051. IEEE

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Authors and Affiliations

  1. Department of Excellence in Robotics & AI, TeCIP Institute, Scuola Superiore Sant’Anna, Pisa, Italy

    Paolo Tripicchio, Salvatore D’Avella, Carlo Alberto Avizzano, Fabrizio Di Pasquale & Philippe Velha

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  1. Paolo Tripicchio
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  2. Salvatore D’Avella
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Correspondence to Paolo Tripicchio.

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Tripicchio, P., D’Avella, S., Avizzano, C.A. et al. On the integration of FBG sensing technology into robotic grippers. Int J Adv Manuf Technol 111, 1173–1185 (2020). https://doi.org/10.1007/s00170-020-06142-8

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