Variable Impedance Learning Control for Robotic Arms from GMR-Encoded Behavior Priors
https://doi.org/10.17586/0021-3454-2024-67-10-893-898
Abstract
This study presents a control approach, where Cartesian variable impedance control parameters are tuned online as the result of quadratic programming optimization dynamically modulating stiffness and damping coefficients based on desired sensory-motor skill encoded by Gaussian mixture regression behavior prior model.
About the Authors
Ali Waddah
ITMO University
Russian Federation
Russian Federation
Waddah Ali — Post-Graduate Student; Faculty of Control Systems and Robotics, International Laboratory of Biomechatronics and EnergyEfficient Robotics; Engineer
St. Petersburg
S. A. Kolyubin
ITMO University
Russian Federation
Russian Federation
Sergey A. Kolyubin — Dr. Faculty of Control Systems and Robotics, International Laboratory of Biomechatronics and Energy-Efficient Robotics; Professor; Chief Researcher
St. Petersburg
References
1. Ali Waddah, Kolyubin S.А. Journal of Instrument Engineering, 2024, no. 6(67), pp. 500–510.
2. Hussein A., Gaber M.M., Elyan E., and Jayne C. ACM Computing Surveys, 2017, no. 2(50), art. 21, https://doi.org/10.1145/3071073.
3. Ravichandar H., Polydoros A.S., Chernova S., and Billard A. Annual review of control, robotics, and autonomous systems, 2020, no. 1(3), pp. 297–330, DOI:10.1146/annurev-control-100819-063206.
4. Abu-Dakka F.J. and Kyrki V. IEEE International Conference on Robotics and Automation, Paris, France, 2020, pp. 4421–4426.
5. Wang Y.Q., Hu Y.D., El Zaatari S., Li W.D., Zhou Y. Robotics and Computer-Integrated Manufacturing, 2021, no. 9(71), pp. 102169, DOI:10.1016/j.rcim.2021.102169
6. Kronander K. and Billard A. IEEE Transactions on Haptics, 2014, vol. 7, pp. 367–380.
7. Saveriano M. and Lee D. IEEE International Conference on Ubiquitous Robots and Ambient Intelligence, Kuala Lumpur, Malaysia, 2014, pp. 368–373.
8. Khansari-Zadeh S.M. and Billard A. IEEE Transaction on Robotics, 2011, vol. 27, pp. 943–957.
9. Li M., Yin H., Tahara K., and Billard A. IEEE International Conference on Robotics and Automation, Hong Kong, China, 2014, pp. 6784–6791.
10. Suomalainen M., Calinon S., Pignat E., and Kyrki V. IEEE International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada, 2019, pp. 8676–8682.
11. Byrd R.H., Lu P., and Nocedal J. SIAM Journal on Scientific and Statistical Computing, 1995, no. 5(16), pp. 1190– 1208.
Review
For citations:
Waddah A., Kolyubin S.A. Variable Impedance Learning Control for Robotic Arms from GMR-Encoded Behavior Priors. Journal of Instrument Engineering. 2024;67(10):893-898. https://doi.org/10.17586/0021-3454-2024-67-10-893-898
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