Abstract
Controlling the teleoperation of snake-like robots is challenging due to complex nonlinear dynamics and communication delays. This research proposes an online bilateral predictive control architecture to address these issues. This control structure is established by predicting environment force and the user’s future motion. The former uses a model-mediated approach by creating a virtual environment on the master side and the latter adopts an artificial neural network (ANN) for online operator’s motion prediction. The slave controller utilizes transmitted data from ANN to generate required backbone lengths, which are then transformed into the slave's local bending and torsional degrees of freedom through the inverse kinematics of the robot. Motion prediction is examined in two scenarios: when the ANN predicts the trained motions, and when it predicts a different motion. Simulation studies demonstrate that the proposed online bilateral predictive teleoperation structure successfully achieves real-time position synchronization and force feedback, by effectively bypassing communication delays.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Code or Data Availability
The codes and datasets analyzed during the current study are not publicly available due to the university’s policies but are available from the corresponding author upon reasonable request.
References
Kadkhodazade, M., Pourmokhtari, M., Yazdankhoo, B., Beigzadeh, B.: The Influence of Sex Factor on the Modeling of the Human Hand/Arm Interacting with a Teleoperation System. J. Mech. Med. Biol. (2023). https://doi.org/10.1142/S0219519423501063.p.2350106
Ghasemi, A., Yousefi, K., Yazdankhoo, B., Beigzadeh, B.: Cost-effective Haptic Teleoperation Framework: Design and Implementation. In 2023 11th RSI International Conference on Robotics and Mechatronics (ICRoM). IEEE, pp. 253–258 (2023)
Kaviri, M., Fesharaki, A.J., Sadeghnejad, S.: Soft robotics in medical applications: State of the art, challenges, and recent advances. Medical and Healthcare Robotics. pp. 25–61 (2023). https://doi.org/10.1016/B978-0-443-18460-4.00009-3
Chang, A.H., Vela, P.A.: Evaluation of bio-inspired scales on locomotion performance of snake-like robots. Robotica 37(8), 1302–1319 (2019)
Della Santina, C., Katzschmann, R.K., Bicchi, A., Rus, D.: Model-based dynamic feedback control of a planar soft robot: trajectory tracking and interaction with the environment. Int. J. Robotics Res. 39(4), 490–513 (2020)
Liang, X., He, G., Su, T., Wang, W., Huang, C., Zhao, Q., Hou, Z.-G.: Finite-time observer-based variable impedance control of cable-driven continuum manipulators. IEEE Trans. Hum. Mach. Syst. 52(1), 26–40 (2021)
Sadati, S.H., Naghibi, S.E., Walker, I.D., Althoefer, K., Nanayakkara, T.: Control space reduction and real-time accurate modeling of continuum manipulators using ritz and ritz–galerkin methods. IEEE Robot. Autom. Lett. 3(1), 328–335 (2017)
Samadi Khoshkho, M., Samadikhoshkho, Z., Lipsett, M.G.: Distilled neural state-dependent Riccati equation feedback controller for dynamic control of a cable-driven continuum robot. Int J Adv Robot Syst 20(3), 17298806231174736 (2023)
Yazdankhoo, B., Ha’iri Yazdi, M.R., Najafi, F., Beigzadeh, B.: L1 impedance control for bilateral teleoperation containing model uncertainty. Transactions of the Institute of Measurement and Control, vol. 44, no. 16, pp. 3154–3164 (2022). https://doi.org/10.1177/01423312221099382
Yazdankhoo, B., Najafi, F., Ha’iriYazdi, M.R., Beigzadeh, B.: Position synchronization for an uncertain teleoperation system with time delays using L1 theory. Scientia Iranica 30(1), 16–29 (2023)
Kolbari, H., Sadeghnejad, S., Bahrami, M., Ali, K.E.: Adaptive control of a robot-assisted tele-surgery in interaction with hybrid tissues. J. Dyn. Syst. Meas. Contr. 140(12), 121012 (2018)
Raeisi Sarkhooni, M., Yazdankhoo, B., Hairi Yazdi, M.R., Najafi, F.: Fuzzy logic-based variable impedance control for a bilateral teleoperation system under time delay. J. Comput. Appl. Mech. (2024). https://doi.org/10.22059/JCAMECH.2024.369060.914
Uddin, R., Ryu, J.: Predictive control approaches for bilateral teleoperation. Annu. Rev. Control. 42, 82–99 (2016)
Choi, H., Jung, S.: Teleoperation control of a position-based impedance force controlled mobile robot by neural network learning: experimental studies. Asian J. Control 22(1), 92–103 (2020)
Yazdankhoo, B., Beigzadeh, B.: Increasing stability in model-mediated teleoperation approach by reducing model jump effect. Scientia Iranica 26(Special Issue on: Socio-Cognitive Engineering), 3–14 (2019)
Li, S., Bowman, M., Nobarani, H., Zhang, X.: Inference of manipulation intent in teleoperation for robotic assistance. J. Intell. Rob. Syst. 99(1), 29–43 (2020)
Jarrassé, N., Paik, J., Pasqui, V., Morel, G.: How can human motion prediction increase transparency? in 2008 IEEE International Conference on Robotics and Automation. IEEE, pp. 2134–2139 (2008)
Uddin, R., Park, S., Ryu, J.: A predictive energy-bounding approach for Haptic teleoperation. Mechatronics 35, 148–161 (2016)
Smith, C., Jensfelt, P.: A predictor for operator input for time-delayed teleoperation. Mechatronics 20(7), 778–786 (2010)
Feth, D., Peer, A., Buss, M.: Enhancement of multi-user teleoperation systems by prediction of dyadic haptic interaction. In: Experimental Robotics, vol. 79, pp. 855–869. Springer, Berlin, Heidelberg (2014). https://doi.org/10.1007/978-3-642-28572-1_59
Stakem, F., AlRegib, G.: An adaptive approach to exponential smoothing for CVE state prediction. in Proceedings of the 2Nd International Conference on Immersive Telecommunications. pp. 1–6 (2009)
Pourmokhtari, M., Beigzadeh, B.: Simple recognition of hand gestures using single-channel EMG signals. Proc. Inst. Mech. Eng. H J. Eng. Med. 238(3), 372–380 (2024). https://doi.org/10.1177/09544119231225528
Nikpour, M., Yazdankhoo, B., Beigzadeh, B., Meghdari, A.: Adaptive online prediction of operator position in teleoperation with unknown time-varying delay: simulation and experiments. Neural Comput. Appl. 33(13), 7575–7592 (2021)
Yazdankhoo, B., Nikpour, M., Beigzadeh, B., Meghdari, A.: Improvement of operator position prediction in teleoperation systems with time delay: simulation and experimental studies on Phantom Omni devices. JJMIE 13(3), 7575–7592 (2019)
Transeth, A.A., Pettersen, K.Y., Liljebäck, P.: A survey on snake robot modeling and locomotion. Robotica 27(7), 999–1015 (2009)
Simaan, N.: Snake-like units using flexible backbones and actuation redundancy for enhanced miniaturization. in Proceedings of the 2005 IEEE international conference on robotics and automation. IEEE, pp. 3012–3017 (2005)
Zhang, D., Li, Y., Wang, H., Cong, W.: Ultrasonic vibration-assisted laser directed energy deposition in-situ synthesis of NiTi alloys: Effects on microstructure and mechanical properties. J. Manuf. Process. 60, 328–339 (2020)
Simaan, N., Taylor, R., Flint, P.: A dexterous system for laryngeal surgery. in IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA'04. 2004. IEEE, pp. 351–357 (2004)
Gravagne, I.A., Walker, I.D.: Kinematic transformations for remotely-actuated planar continuum robots. in Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No. 00CH37065). IEEE, pp. 19–26 (2000)
Hirose, S., Ma, S.: Coupled tendon-driven multijoint manipulator. in Proceedings. 1991 IEEE International Conference on Robotics and Automation. IEEE Computer Society, pp. 1268–1275 (1991)
Mason, M.T., Salisbury Jr, J.K.: Robot hands and the mechanics of manipulation, pp. 59–59. MIT Press, Cambridge (1985)
Funding
The authors declare there is no financial support for this study.
Author information
Authors and Affiliations
Contributions
Mahdi Ebrahimian did the main research, particularly the literature review, dynamical modeling, and control. He also wrote the paper.
Mina Pourmokhtari contributed mainly to the AI-related sections and human motion prediction. She also revised the final draft of the paper.
Morteza Ghiyasi made a contribution to simulating the robot according to theoretical frameworks and aided in refining the article based on the feedback provided by the reviewers.
Behnam Yazdankhoo was the advisor of this research and contributed to the final draft revision.
Borhan Beigzadeh supervised the research.
Corresponding author
Ethics declarations
Ethical Approval
This paper does not report research that requires ethical approval. Consent to participate or consent to publish statements are accordingly also not required.
Consent to Participate
All authors have read and agreed to publish this work.
Consent for Publication
All authors have read and agreed to publish this work.
Conflicts of Interest
The authors declare there is no conflict of interest regarding this research work.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Supplementary file1 (MP4 21101 KB)
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Ebrahimian, M., Pourmokhtari, M., Ghiyasi, M. et al. Online Bilateral Predictive Control for Time-Delayed Teleoperation of Snake-like Robots. J Intell Robot Syst 110, 80 (2024). https://doi.org/10.1007/s10846-024-02113-3
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10846-024-02113-3