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Event-Triggered Adaptive Hybrid Position-Force Control for Robot-Assisted Ultrasonic Examination System

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Abstract

In this paper, an adaptive motion-force control scheme is presented for a networked ultrasound robotic manipulator to perform a transversal abdomen scan. An adaptive backstepping position controller is designed to ensure the stability of the ultrasound robot in the presence of parametric uncertainties and external disturbances. A proportional-integral-derivative force controller is proposed to maintain a constant interaction force during the scan process. Rather than periodic time-triggered implementation, the Lyapunov-based triggering condition is derived to update the control inputs in an aperiodic manner, reduce the communication burden, and preserve the stability of the robotic system during the task. The effectiveness of the proposed control strategy is investigated based on a comparison study with different time-triggered adaptive control schemes. Moreover, the proposed event-triggered mechanism is compared with the most common triggering conditions in literature, i.e., fixed and relative thresholds. These schemes are devoted to carry out the transversal ultrasound scan in the simulation environment. Additional validation of the proposed control scheme is performed in the virtual robot experimentation platform (V-REP). From the results of simulation and experimental runs, the proposed event-triggered control scheme is found to be more promising and efficient in robot-assisted ultrasound imaging.

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References

  1. Beasley, R.A.: Medical robots: current systems and research directions. J. Robotics. 2012, 1–14 (2012)

    Article  Google Scholar 

  2. Hockstein, N.G., Nolan, J.P., O'Malley Jr., B.W., Woo, Y.J.: Robotic microlaryngeal surgery: a technical feasibility study using the daVinci surgical robot and an airway mannequin. Laryngoscope. 115(5), 780–785 (2005)

    Article  Google Scholar 

  3. Ju, M.-S., Lin, C.-C., Lin, D.-H., Hwang, I.-S., Chen, S.-M.: A rehabilitation robot with force-position hybrid fuzzy controller: hybrid fuzzy control of rehabilitation robot. IEEE Trans. Neural Syst. Rehabil. Eng. 13(3), 349–358 (2005)

    Article  Google Scholar 

  4. Erol, D., Sarkar, N.: Intelligent control for robotic rehabilitation after stroke. J. Intell. Robot. Syst. 50(4), 341–360 (2007)

    Article  Google Scholar 

  5. Evans, K., Roll, S., Baker, J.: Work-related musculoskeletal disorders (WRMSD) among registered diagnostic medical sonographers and vascular technologists: a representative sample. J. Diagn. Med. Sonogr. 25(6), 287–299 (2009)

    Article  Google Scholar 

  6. Klimstra, M., Dowling, J., Durkin, J.L., MacDonald, M.: The effect of ultrasound probe orientation on muscle architecture measurement. J. Electromyogr. Kinesiol. 17(4), 504–514 (2007)

    Article  Google Scholar 

  7. Sasaki, Y., Eura, F., Kobayashi, K., Kondo, R., Tomita, K., Nishiyama, Y., Tsukihara, H., Matumoto, N., Koizumi, N.: Development of compact portable ultrasound robot for home healthcare. J. Eng. 2019(14), 495–499 (2019)

    Article  Google Scholar 

  8. Priester, A.M., Natarajan, S., Culjat, M.O.: Robotic ultrasound systems in medicine. IEEE Trans. Ultrason. Ferroelectr. Freq. Control. 60(3), 507–523 (2013)

    Article  Google Scholar 

  9. Fang, T.-Y., Zhang, H.K., Finocchi, R., Taylor, R.H., Boctor, E.M.: Force-assisted ultrasound imaging system through dual force sensing and admittance robot control. Int. J. Comput. Assist. Radiol. Surg. 12(6), 983–991 (2017)

    Article  Google Scholar 

  10. Gonçalves, P.J.S., Torres, P.M., Santos, F., António, R., Catarino, N., Martins, J.: A vision system for robotic ultrasound guided orthopaedic surgery. J.Intell. Robot. Syst. 77(2), 327–339 (2015)

    Article  Google Scholar 

  11. Nakadate, R., Tokunaga, Y., Solis, J., Takanishi, A., Minagawa, E., Sugawara, M., Niki, K., Saito, A.: Development of robot assisted measurement system for abdominal ultrasound diagnosis. In: 2010 3rd IEEE RAS & EMBS international conference on biomedical robotics and biomechatronics, pp. 367-372. IEEE (2010)

  12. Conti, F., Park, J., Khatib, O.: Interface design and control strategies for a robot assisted ultrasonic examination system. In: experimental robotics, pp. 97-113. Springer (2014)

  13. Geng, C., Xie, Q., Chen, L., Li, A., Qin, B.: Study and analysis of a remote robot-assisted ultrasound imaging system. In: 2020 IEEE 4th information technology, networking, electronic and automation control conference (ITNEC), pp. 389-393. IEEE (2020)

  14. Salcudean, S.E., Zhu, W.H., Abolmaesumi, P., Bachmann, S., Lawrence, P.D.: A robot system for medical ultrasound. In: Robotics Research. pp. 195–202. Springer, (2000)

  15. Seitz, P.K., Baumann, B., Johnen, W., Lissek, C., Seidel, J., Bendl, R.: Development of a robot-assisted ultrasound-guided radiation therapy (USgRT). Int. J. Comput. Assist. Radiol. Surg. 15(3), 491–501 (2020)

    Article  Google Scholar 

  16. Janvier, M.-A., Durand, L.-G., Cardinal, M.-H.R., Renaud, I., Chayer, B., Bigras, P., De Guise, J., Soulez, G., Cloutier, G.: Performance evaluation of a medical robotic 3D-ultrasound imaging system. Med. Image Anal. 12(3), 275–290 (2008)

    Article  Google Scholar 

  17. Sage, H., De Mathelin, M., Ostertag, E.: Robust control of robot manipulators: a survey. Int. J. Control. 72(16), 1498–1522 (1999)

    Article  MathSciNet  Google Scholar 

  18. Fiala, J., Wavering, A.J.: Experimental evaluation of Cartesian stiffness control on a seven degree-of-freedom robot arm. J. Intell. Robot. Syst. 5(1), 5–24 (1992)

    Article  Google Scholar 

  19. Brahmi, B., Saad, M., Lam, J.T.A.T., Luna, C.O., Archambault, P.S., Rahman, M.H.: Adaptive control of a 7-DOF exoskeleton robot with uncertainties on kinematics and dynamics. Eur. J. Control. 42, 77–87 (2018)

    Article  MathSciNet  Google Scholar 

  20. Aboutalebian, B., Talebi, H.A., Etedali, S., Suratgar, A.A.: Adaptive control of teleoperation system based on nonlinear disturbance observer. Eur. J. Control. 53, 109–116 (2020)

    Article  MathSciNet  Google Scholar 

  21. Shi, D., Zhang, J., Sun, Z., Shen, G., Xia, Y.: Composite trajectory tracking control for robot manipulator with active disturbance rejection. Control Eng. Pract. 106, 104670

  22. Zhu, W.-H., Salcudean, S., Bachmann, S., Abolmaesumi, P.: Motion/force/image control of a diagnostic ultrasound robot. In: proceedings 2000 ICRA. Millennium conference. IEEE international conference on robotics and automation. Symposia proceedings (cat. No. 00CH37065), pp. 1580-1585. IEEE (2000)

  23. Mathiassen, K., Fjellin, J.E., Glette, K., Hol, P.K., Elle, O.J.: An ultrasound robotic system using the commercial robot UR5. Front. Robot. AI. 3, 1 (2016)

    Article  Google Scholar 

  24. Siciliano, B., Sciavicco, L., Villani, L., Oriolo, G.: Robotics: Modelling, Planning and Control. Springer Science & Business Media, (2010)

  25. Mustafa, A.S.B., Ishii, T., Matsunaga, Y., Nakadate, R., Ishii, H., Ogawa, K., Saito, A., Sugawara, M., Niki, K., Takanishi, A.: Development of robotic system for autonomous liver screening using ultrasound scanning device. In: 2013 IEEE international conference on robotics and Biomimetics (ROBIO), pp. 804-809. IEEE (2013)

  26. Karar, M.E.: A simulation study of adaptive force controller for medical robotic liver ultrasound guidance. Arab. J. Sci. Eng. 43(8), 4229–4238 (2018)

    Article  Google Scholar 

  27. Victorova, M., Navarro-Alarcon, D., Zheng, Y.-P.: 3D ultrasound imaging of scoliosis with force-sensitive robotic scanning. In: 2019 third IEEE international conference on robotic computing (IRC), pp. 262-265. IEEE (2019)

  28. Raibert, M.H., Craig, J.J.: Hybrid position/force control of manipulators. (1981)

  29. Arimoto, S., Liu, Y.H., Naniwa, T.: Principle of orthogonalization for hybrid control of robot arms. IFAC Proc. Vol. 26(2), 335–340 (1993)

    Article  Google Scholar 

  30. Pliego-Jiménez, J., Arteaga-Pérez, M.A.: Adaptive position/force control for robot manipulators in contact with a rigid surface with uncertain parameters. Eur. J. Control. 22, 1–12 (2015)

    Article  MathSciNet  Google Scholar 

  31. Gutiérrez-Giles, A., Arteaga-érez, M.: Output feedback hybrid force/motion control for robotic manipulators interacting with unknown rigid surfaces. Robotica. 38(1), 136–158 (2020)

    Article  Google Scholar 

  32. Yoshikawa, T., Sudou, A.: Dynamic hybrid position/force control of robot manipulators-on-line estimation of unknown constraint. IEEE Trans Rob Autom. 9(2), 220–226 (1993)

    Article  Google Scholar 

  33. Chaudhary, H., Panwar, V., Prasad, R., Sukavanam, N.: Adaptive neuro fuzzy based hybrid force/position control for an industrial robot manipulator. J. Intell. Manuf. 27(6), 1299–1308 (2016)

    Article  Google Scholar 

  34. Heck, D., Saccon, A., Van de Wouw, N., Nijmeijer, H.: Guaranteeing stable tracking of hybrid position–force trajectories for a robot manipulator interacting with a stiff environment. Automatica. 63, 235–247 (2016)

    Article  MathSciNet  Google Scholar 

  35. Cao, H., He, Y., Chen, X., Zhao, X.: Smooth adaptive hybrid impedance control for robotic contact force tracking in dynamic environments. Indust. Robot: Int. J. Robotics Res. Appl. 47, 231–242 (2020)

    Article  Google Scholar 

  36. Tabuada, P.: Event-triggered real-time scheduling of stabilizing control tasks. IEEE Trans. Automat. Contr. 52(9), 1680–1685 (2007)

    Article  MathSciNet  Google Scholar 

  37. Xing, L., Wen, C., Liu, Z., Su, H., Cai, J.: Event-triggered adaptive control for a class of uncertain nonlinear systems. IEEE Trans. Automat. Contr. 62(4), 2071–2076 (2016)

    Article  MathSciNet  Google Scholar 

  38. Al Issa, S., Chakravarty, A., Kar, I.: Improved event-triggered adaptive control of non-linear uncertain networked systems. IET Control Theory Appl. 13(13), 2146–2152 (2019)

    Article  Google Scholar 

  39. Tripathy, N.S., Kar, I., Paul, K.: An event-triggered based robust control of robot manipulator. In: 2014 13th international conference on Control Automation Robotics & Vision (ICARCV), pp. 425-430. IEEE (2014)

  40. Kumar, N., Porwal, A., Singh, A.R., Naskar, R., Purwar, S.: Event triggered control of robot manipulator. In: 2019 6th international conference on signal processing and integrated networks (SPIN), pp. 362-366. IEEE (2019)

  41. Al Issa, S., Sharma, M., Kar, I.: Event-triggered Backstepping Control Scheme for Networked Mobile Robots. In: Proceedings of the Advances in Robotics 2019. pp. 1–5. (2019)

  42. Al Issa, S., Kar, I.: Event-triggered adaptive control of uncertain non-linear systems under input delay and limited resources. Int. J. Dyn. Control, 1–8 (2021)

  43. Guerrero-Castellanos, J.-F., Téllez-Guzmán, J.J., Durand, S., Marchand, N., Alvarez-Muñoz, J., Gonzalez-Diaz, V.R.: Attitude stabilization of a quadrotor by means of event-triggered nonlinear control. J.Intell. Robot. Syst. 73(1–4), 123–135 (2014)

    Article  Google Scholar 

  44. Lynch, K.M., Park, F.C.: Modern Robotics. Cambridge University Press, (2017)

  45. Quynh, N.X., Nan, W.Y., Yen, V.T.: A novel robust adaptive control using RFWNNs and backstepping for industrial robot manipulators with dead-zone. J .Intell. Robot. Syst., 1–14 (2019)

  46. Krstic, M., Kokotovic, P.V., Kanellakopoulos, I.: Nonlinear and Adaptive Control Design. John Wiley & Sons, Inc., (1995)

  47. Gilbarg, D., Trudinger, N.S.: Elliptic partial differential equations of second order. springer, (2015)

  48. Gritli, H., Belghith, S.: LMI-based synthesis of a robust saturated controller for an underactuated mechanical system subject to motion constraints. Eur. J. Control. 57, 179–193 (2021)

    Article  MathSciNet  Google Scholar 

  49. Craig, J., Hsu, P., Sastry, S.: Adaptive control of mechanical manipulators. In: proceedings. 1986 IEEE international conference on robotics and automation, pp. 190-195. IEEE (1986)

  50. Pan, H., Sun, W., Zhang, J., Yan, S., Lin, W.: Adaptive event-triggered control for vehicle active suspension systems with state constraints. IFAC-PapersOnLine. 51(31), 955–960 (2018)

    Article  Google Scholar 

  51. Freese, M., Singh, S., Ozaki, F., Matsuhira, N.: Virtual robot experimentation platform v-rep: a versatile 3d robot simulator. In: international conference on simulation, modeling, and programming for autonomous robots, pp. 51-62. Springer (2010)

  52. Abbas, M., Narayan, J., Banerjee, S., Dwivedy, S.K.: AlexNet based real-time detection and segregation of household objects using Scorbot. In: 2020 4th international conference on computational intelligence and networks (CINE), pp. 1-6. IEEE (2020)

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Acknowledgements

The first author would like to thank Al-Baath University, Ministry of Higher Education, Syrian Arab Republic for their financial supports.

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Authors and Affiliations

  1. Mechanical Engineering Department, Indian Institute of Technology Guwahati, Guwahati, 781039, India

    Mohamed Abbas & Santosha K. Dwivedy

  2. Department of Design and Production, Al-Baath University, Homs, Syria

    Mohamed Abbas

  3. Electronics and Electrical Engineering Department, Indian Institute of Technology Guwahati, Guwahati, 781039, India

    Sami Al Issa

  4. Department of Computer Engineering and Automation, Damascus University, Damascus, Syria

    Sami Al Issa

Authors
  1. Mohamed Abbas
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  2. Sami Al Issa
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  3. Santosha K. Dwivedy
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Contributions

MA formulated the dynamic analysis, hybrid position force control strategy and conducted simulation runs and experimental validation in V-REP environment. SA designed the event-triggered mechanism, stability analysis, and contributed significantly in writing the manuscript. SKD added the comparative study between the event-triggered and time triggered control schemes; thereafter organized the complete paper work. At last, all authors read and approved the final manuscript.

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Correspondence to Mohamed Abbas.

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Abbas, M., Al Issa, S. & Dwivedy, S.K. Event-Triggered Adaptive Hybrid Position-Force Control for Robot-Assisted Ultrasonic Examination System. J Intell Robot Syst 102, 84 (2021). https://doi.org/10.1007/s10846-021-01428-9

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