Safe haptic teleoperations of admittance controlled robots with virtualization of the force feedback (2404.07672v1)
Abstract: Haptic teleoperations play a key role in extending human capabilities to perform complex tasks remotely, employing a robotic system. The impact of haptics is far-reaching and can improve the sensory awareness and motor accuracy of the operator. In this context, a key challenge is attaining a natural, stable and safe haptic human-robot interaction. Achieving these conflicting requirements is particularly crucial for complex procedures, e.g. medical ones. To address this challenge, in this work we develop a novel haptic bilateral teleoperation system (HBTS), featuring a virtualized force feedback, based on the motion error generated by an admittance controlled robot. This approach allows decoupling the force rendering system from the control of the interaction: the rendered force is assigned with the desired dynamics, while the admittance control parameters are separately tuned to maximize interaction performance. Furthermore, recognizing the necessity to limit the forces exerted by the robot on the environment, to ensure a safe interaction, we embed a saturation strategy of the motion references provided by the haptic device to admittance control. We validate the different aspects of the proposed HBTS, through a teleoperated blackboard writing experiment, against two other architectures. The results indicate that the proposed HBTS improves the naturalness of teleoperation, as well as safety and accuracy of the interaction.
- J. Yang and H. Li, “Accuracy assessment of robot-assisted implant surgery in dentistry: A systematic review and meta-analysis,” The Journal of Prosthetic Dentistry, Jan. 2024.
- S. L. Bolding and U. N. Reebye, “Accuracy of haptic robotic guidance of dental implant surgery for completely edentulous arches,” The Journal of Prosthetic Dentistry, vol. 128, pp. 639–647, Oct. 2022.
- G. Raju, G. Verghese, and T. Sheridan, “Design issues in 2-port network models of bilateral remote manipulation,” in 1989 International Conference on Robotics and Automation Proceedings, vol. 3, May 1989, pp. 1316–1321.
- I. El Rassi and J.-M. El Rassi, “A review of haptic feedback in tele-operated robotic surgery,” Journal of Medical Engineering & Technology, vol. 44, pp. 247–254, July 2020.
- S. Hirche and M. Buss, “Human Perceived Transparency with Time Delay,” in Advances in Telerobotics, ser. Springer Tracts in Advanced Robotics. Berlin, Heidelberg: Springer, 2007, pp. 191–209.
- N. Hogan, “Impedance control of industrial robots,” Robotics and Computer-Integrated Manufacturing, vol. 1, pp. 97–113, Jan. 1984.
- C. Vavra, “Tips for improving safety, ROI for collaborative robots,” Control Engineering, vol. 63, no. 3, pp. 26–30, Mar. 2016.
- M. Kitagawa, D. Dokko, A. M. Okamura, B. T. Bethea, and D. D. Yuh, “Effect of sensory substitution on suture manipulation forces for surgical teleoperation,” Studies in Health Technology and Informatics, vol. 98, pp. 157–163, 2004.
- V. Cesari, F. Melfi, A. Gemignani, and D. Menicucci, “Sensory substitution increases robotic surgical performance and sets the ground for a mediating role of the sense of embodiment: a systematic review,” Heliyon, vol. 9, p. e21665, Nov. 2023.
- C. E. Reiley, T. Akinbiyi, D. Burschka, D. C. Chang, A. M. Okamura, and D. D. Yuh, “Effects of Visual Force Feedback on Robot-Assisted Surgical Task Performance,” The Journal of thoracic and cardiovascular surgery, vol. 135, pp. 196–202, Jan. 2008.
- A. Abiri, J. Pensa, A. Tao, J. Ma, Y.-Y. Juo, S. J. Askari, J. Bisley, J. Rosen, E. P. Dutson, and W. S. Grundfest, “Multi-Modal Haptic Feedback for Grip Force Reduction in Robotic Surgery,” Scientific Reports, vol. 9, p. 5016, Mar. 2019.
- M. Panzirsch, A. Pereira, H. Singh, B. Weber, E. Ferreira, A. Gherghescu, L. Hann, E. den Exter, F. van der Hulst, L. Gerdes, L. Cencetti, K. Wormnes, J. Grenouilleau, W. Carey, R. Balachandran, T. Hulin, C. Ott, D. Leidner, A. Albu-Schäffer, N. Y. Lii, and T. Krüger, “Exploring planet geology through force-feedback telemanipulation from orbit,” Science Robotics, vol. 7, Apr. 2022.
- X. Gong, L. Wang, Y. Mou, H. Wang, X. Wei, W. Zheng, and L. Yin, “Improved Four-channel PBTDPA Control Strategy Using Force Feedback Bilateral Teleoperation System,” International Journal of Control, Automation and Systems, vol. 20, pp. 1002–1017, Mar. 2022.
- I. Dekker, K. Kellens, and E. Demeester, “Design and Evaluation of an Intuitive Haptic Teleoperation Control System for 6-DoF Industrial Manipulators,” Robotics, vol. 12, p. 54, Apr. 2023.
- H. Ji, S. Li, J. Wang, and Z. Ruan, “Improving Teleoperation Through Human-Aware Haptic Feedback: A Distinguishable and Interpretable Physical Interaction Based on the Contact State,” IEEE Transactions on Human-Machine Systems, vol. 53, pp. 24–34, Feb. 2023.
- J.-H. Ryu, J. Artigas, and C. Preusche, “A passive bilateral control scheme for a teleoperator with time-varying communication delay,” Mechatronics, vol. 20, pp. 812–823, Oct. 2010.
- J. Lachner, F. Allmendinger, E. Hobert, N. Hogan, and S. Stramigioli, “Energy budgets for coordinate invariant robot control in physical human–robot interaction,” The International Journal of Robotics Research, vol. 40, pp. 968–985, Aug. 2021.
- H. Gao, X. Zhang, C. Ma, and C. Zhou, “Combined active and passive adaptive variable admittance compliant control for space robotic manipulators,” in 2023 IEEE International Conference on Robotics and Biomimetics (ROBIO), Dec. 2023, pp. 1–8.
- M. Radi, “Workspace Scaling and Haptic Feedback for Industrial Telepresence and Teleaction Systems with Heavy-duty Teleoperators,” ser. Forschungsberichte IWB. Herbert Utz Verlag, 2012.
- F. L. Markley, Y. Cheng, J. L. Crassidis, and Y. Oshman, “Averaging Quaternions,” Journal of Guidance, Control, and Dynamics, vol. 30, pp. 1193–1197, July 2007.
- Z. Li, H. Huang, X. Song, W. Xu, and B. Li, “A fuzzy adaptive admittance controller for force tracking in an uncertain contact environment,” IET Control Theory & Applications, vol. 15, pp. 2158–2170, 2021.
- L. Roveda, A. A. Shahid, N. Iannacci, and D. Piga, “Sensorless Optimal Interaction Control Exploiting Environment Stiffness Estimation,” IEEE Transactions on Control Systems Technology, vol. 30, pp. 218–233, Jan. 2022.
- B. L. Somberg, “Character aspect ratio and design tradeoffs,” Proceedings of the Human Factors Society Annual Meeting, vol. 34, no. 19, pp. 1461–1464, 1990.
- L. Sheng, U. Ahmad, Y. Ye, and Y.-J. Pan, “A time domain passivity control scheme for bilateral teleoperation,” Electronics, vol. 8, p. 325, Mar. 2019.
- X. Zhang, L. Sun, Z. Kuang, and M. Tomizuka, “Learning variable impedance control via inverse reinforcement learning for force-related tasks,” IEEE Robotics and Automation Letters, vol. 6, Apr. 2021.
- Lorenzo Pagliara (3 papers)
- Enrico Ferrentino (12 papers)
- Andrea Chiacchio (2 papers)
- Giovanni Russo (113 papers)