Hostname: page-component-586b7cd67f-dlnhk Total loading time: 0 Render date: 2024-11-22T04:49:45.444Z Has data issue: false hasContentIssue false
  • English
  • Français

Delayed Bilateral Teleoperation of the Speed and Turn Angle of a Bipedal Robot

Published online by Cambridge University Press:  14 July 2020

Viviana Moya Open the ORCID record for Viviana Moya [Opens in a new window] ,
Emanuel Slawiñski  and
Vicente Mut
Viviana Moya*
Affiliation:
Instituto de Automática (INAUT), Universidad Nacional de San Juan, San Juan, Argentina Emails: [email protected]; [email protected]
Emanuel Slawiñski
Affiliation:
Instituto de Automática (INAUT), Universidad Nacional de San Juan, San Juan, Argentina Emails: [email protected]; [email protected]
Vicente Mut
Affiliation:
Instituto de Automática (INAUT), Universidad Nacional de San Juan, San Juan, Argentina Emails: [email protected]; [email protected]
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

This paper proposes a shared control scheme which aims to achieve a stable control of the speed and turn of a bipedal robot during a delayed bilateral teleoperation. The strategy allows to get a delay-dependent damping value that must be injected to assure a bounded response of the hybrid system, while simultaneously, the human operator receives a force feedback that help him to decrease the synchronism error. Furthermore, a test where a human operator handles the walking of a simulated bipedal robot, to follow a curve path in front of varying time delay, is performed and analyzed.

Keywords

Bilateral teleoperationBipedal robotTime-varying delayTurnStable walk.
Type
Articles
Information
Robotica , Volume 39 , Issue 4 , April 2021 , pp. 633 - 651
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Westervelt, E. R., Grizzle, J. W., Chevallereau, C., Choi, J. H. and Morris, B., Feedback Control of Dynamic Bipedal Robot Locomotion (CRC Press, Boca Raton, FL, 2007).Google Scholar
Shih, C.-L., Grizzle, J. W. and Chevallereau, C., “From stable walking to steering of a 3D bipedal robot with passive point feet,” Robotica 30(7), 1119–1130 (2012).CrossRefGoogle Scholar
Plestan, F., Grizzle, J. W., Westervelt, E. R. and Abba, G., “Stable walking of a 7-DOF biped robot,” IEEE Trans. Robot. Autom. 19(4), 653–668 (2003).CrossRefGoogle Scholar
Ames, A. D., “Human-inspired control of bipedal walking robots,” IEEE Trans. Autom. Contr. 59(5), 1115–1130 (2014).CrossRefGoogle Scholar
Ferreira, J. P., Amaral, T. G., Pires, V. F., Crisostomo, M. M. and Coimbra, P., “A Neural-Fuzzy Walking Control of an Autonomous Biped Robot,” Proceedings World Automation Congress, Seville, Spain (2004) pp. 253–258.Google Scholar
Park, J. H., “Fuzzy-logic zero-moment-point trajectory generation for reduced trunk motions of biped robots,” Fuzzy Sets Syst. 134(1), 189–203 (2003).CrossRefGoogle Scholar
Chevallereau, C., Grizzle, J. W. and Shih, C.-L., “Asymptotically stable walking of a five-link underactuated 3-D bipedal robot,” IEEE Trans. Robot. 25(1), 37–50 (2009).CrossRefGoogle Scholar
Gregg, R. D. and Spong, M. W., “Bringing the Compass-Gait Bipedal Walker to Three Dimensions,” Proceedings of the International Conference on Intelligent Robots and Systems, St. Louis, MO, USA (2009) pp. 4469–4474.Google Scholar
Gregg, R. D. and Spong, M. W., “Reduction-Based Control with Application to Three-Dimensional Bipedal Walking Robots,” Proceedings of the 2008 American Control Conference, Seattle, WA, USA (2008) pp. 880–887.Google Scholar
Miura, K., Nakaoka, S., Morisawa, M., Kanehiro, F., Harada, K. and Kajita, S., “Analysis on a Friction Based “Twirl” for Biped Robots,” Proceedings of the IEEE International Conference on Robotics and Automation, Anchorage, AK, USA (2010) pp. 4249–4255.Google Scholar
Shahbazi, H., Jamshidi, K. and Monadjemi, A. H., “Curvilinear bipedal walk learning in nao humanoid robot using a CPG based policy gradient method,” Appl. Mech. Mater. 110–116, 5161–5166 (2012).Google Scholar
Slawiñski, E., Mut, V. A., Fiorini, P. and Salinas, L. R., “Quantitative absolute transparency for bilateral teleoperation of mobile robots,” IEEE Trans. Syst. Man Cybern. A Syst. Hum. 42(2), 430–442 (2012).CrossRefGoogle Scholar
Peternel, L. and Babic, J., “Learning of compliant human-robot interaction using full-body haptic interface,” Adv. Robot. 27(13), 1003–1012 (2013).Google Scholar
Brygo, A., Sarakoglou, I., Garcia-Hernandez, N., and Tsagarakis, N., “Humanoid Robot Teleoperation with Vibrotactile Based Balancing Feedback,” In: Haptics: Neuroscience, Devices, Modeling, and Applications (Auvray, M. and Duriez, C., eds.), LNCS, vol. 8619 (Springer, Berlin, Heidelberg, 2014) pp. 266–275.Google Scholar
Ramos, J. and Kim, S., “Humanoid dynamic synchronization through whole-body bilateral feedback teleoperation,” IEEE Trans. Robot. 34(4), 953–965 (2018).CrossRefGoogle Scholar
B. Wang and C. Yang and Q. Xie, “Human-Machine Interfaces Based on EMG and Kinect Applied to Teleoperation of a Mobile Humanoid Robot,” Proceedings of the 10th World Congress on Intelligent Control and Automation, Beijing, China (2012) pp. 3903–3908.Google Scholar
Mukherjee, S., Paramkusam, D. and Dwivedy, S. K., “Inverse Kinematics of a NAO Humanoid Robot Using Kinect to Track and Imitate Human Motion,” Proceedings of the International Conference on Robotics, Automation, Control and Embedded Systems (RACE), Chennai, India (2015) pp. 1–7.Google Scholar
Hua, C. and Liu, X. P., “Delay-dependent stability criteria of teleoperation systems with asymmetric time-varying delays,” IEEE Trans. Robot. 26(5), 925–932 (2010).CrossRefGoogle Scholar
Ames, A., Galloway, K., Sreenath, K. and Grizzle, J. W., “Rapidly exponentially stabilizing control Lyapunov functions and hybrid zero dynamics,” IEEE Trans. Autom. Contr. 59(4), 876–891 (2014).CrossRefGoogle Scholar
Karbasizadeh, N., Zarei, M., Aflakian, A., Tale Masouleh, M. and Kalhor, A., “Experimental dynamic identification and model feed-forward control of Novint Falcon haptic device,” Mechatronics 51, 19–30 (2018).CrossRefGoogle Scholar
Nuño, E., Ortega, R., Barabanov, N. and Basañez, L., “A globally stable PD ccontroller for bilateral teleoperators,” IEEE Trans. Robot. 24(3), 753–758 (2008).CrossRefGoogle Scholar
Li, H., Zhang, L. and Kawashima, K., “Operator dynamics for stability condition in haptic and teleoperation system: A survey,” Int. J. Med. Robot. Comput. Assist. Surg. 14(2), 1–10 (2018).CrossRefGoogle ScholarPubMed
Nuño, E., Basañez, L. and Ortega, R.,“Passivity-based control for bilateral teleoperation: A tutorial,” Automatica 47(3), 485–495 (2011).CrossRefGoogle Scholar
Slawiñski, E., Mut, V. and Santiago, D.,“PD-like controller for delayed bilateral teleoperation of wheeled robots,” Int. J. Contr. 89(8), 1622–1631 (2016).CrossRefGoogle Scholar
Dongjun Lee, O. Martinez-Palafox and M. W. Spong, “Bilateral Teleoperation of a Wheeled Mobile Robot Over Delayed Communication Network,” Proceedings 2006 IEEE International Conference on Robotics and Automation, Orlando, FL, USA (2006) pp. 3298–3303.Google Scholar
Salinas, L., Santiago, D., Slawiñski, E., Mut, V. A., Chavez, D., Leica, P. and Camacho, O.,“P+d plus sliding mode control for bilateral teleoperation of a mobile robot,” Int. J. Contr. Autom. Syst. 16(4), 1927–1937 (2018).CrossRefGoogle Scholar
Vaughan, C., Davis, B. and O’Connor, J., Dynamics of Human Gait (Human Kinetics Publishers, Champaign, IL, 1992).Google Scholar
Ivanenko, Y., Grasso, R., Macellari, V. and Lacquaniti, F., “Control of foot trajectory in human locomotion: Role of ground contact forces in simulated reduced gravity,” J. Neurophysiol. 87(6), 3070–3089 (2002).CrossRefGoogle ScholarPubMed
Spong, M. W., Hutchinson, S. and Vidyasagar, M., Robot Modeling and Control (John Wiley & Sons, Inc., Hoboken, NJ, 2005).Google Scholar