Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-24T17:16:02.607Z Has data issue: false hasContentIssue false
  • English
  • Français

Real-time full body motion imitation on the COMAN humanoid robot

Published online by Cambridge University Press:  20 June 2014

Andrej Gams ,
Jesse van den Kieboom ,
Florin Dzeladini ,
Aleš Ude  and
Auke Jan Ijspeert
Andrej Gams*
Affiliation:
Department of Automation, Biocybernetics and Robotics, Jožef Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia Biorobotics Laboratory, École Polytechnique Fédérale de Lausanne, Station 14, CH-1015 Lausanne, Switzerland
Jesse van den Kieboom
Affiliation:
Biorobotics Laboratory, École Polytechnique Fédérale de Lausanne, Station 14, CH-1015 Lausanne, Switzerland
Florin Dzeladini
Affiliation:
Biorobotics Laboratory, École Polytechnique Fédérale de Lausanne, Station 14, CH-1015 Lausanne, Switzerland
Aleš Ude
Affiliation:
Department of Automation, Biocybernetics and Robotics, Jožef Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia
Auke Jan Ijspeert
Affiliation:
Biorobotics Laboratory, École Polytechnique Fédérale de Lausanne, Station 14, CH-1015 Lausanne, Switzerland
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

On-line full body imitation with a humanoid robot standing on its own two feet requires simultaneously maintaining the balance and imitating the motion of the demonstrator. In this paper we present a method that allows real-time motion imitation while maintaining stability, based on prioritized task control. We also describe a method of modified prioritized kinematic control that constrains the imitated motion to preserve stability only when the robot would tip over, but does not alter the motions otherwise. To cope with the passive compliance of the robot, we show how to model the estimation of the center of mass of the robot using support vector machines. In the paper we give detailed description of all steps of the algorithm, essentially providing a tutorial on the implementation of kinematic stability control. We present the results on a child-sized humanoid robot called Compliant Humanoid Platform or COMAN. Our implementation shows reactive and stable on-line motion imitation of the humanoid robot.

Keywords

KinematicsMotion imitationStabilityCenter-of-massSVM
Type
Articles
Information
Robotica , Volume 33 , Special Issue 5: Robotics in the Alpe-Adria-Danube Region (RAAD 2013) , June 2015 , pp. 1049 - 1061
Copyright
Copyright © Cambridge University Press 2014 

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

1. Ude, A., Atkeson, C. G. and Riley, M., “Planning of Joint Trajectories for Humanoid Robots Using B-Spline Wavelets,” Proceedings of the IEEE International Conference on Robotics and Automation (2000) pp. 2223–2228. doi:10.1109/ROBOT.2000.846358.Google Scholar
2. Gams, A., Ijspeert, A. J., Schaal, S. and Lenarčič, J., “On-line learning and modulation of periodic movements with nonlinear dynamical systems,” Auton. Robots 27 (1), 3–23 (2009).CrossRefGoogle Scholar
3. Petrič, T., Gams, A., Babič, J. and Žlajpah, L., “Reflexive stability control framework for humanoid robots,” Auton. Robots 34 (4), 347–361 (2013).Google Scholar
4. Vukobratovic, M. and Juricic, D., “Contribution to the synthesis of biped gait,” IEEE Trans. Biomed. Eng. BME–16 (1), 1–6 (Jan. 1969).Google Scholar
5. Vukobratovic, M. and Borovac, B., “Zero-moment point—thirty five years of its life,” Int. J. Humanoid Robot. 1 (1), 157–173 (2004).CrossRefGoogle Scholar
6. Sardain, P. and Bessonnet, G., “Forces acting on a biped robot. center of pressure-zero moment point,” IEEE Trans. Syst. Man Cybern. 34 (5), 630–637 (2004).Google Scholar
7. Harada, K., Kajita, S., Kaneko, K. and Hirukawa, H., “ZMP Analysis for Arm/Leg Coordination,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 1 (Oct. 2003) pp. 75–81.Google Scholar
8. Kajita, S., Kanehiro, F., Kaneko, K., Fujiwara, K., Harada, K., Yokoi, K. and Hirukawa, H., “Biped Walking Pattern Generation by Using Preview Control of Zero-Moment Point,” Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), vol. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) (Sep. 2003) pp. 1620–1626.Google Scholar
9. Hyon, S.-H., Hale, J. G. and Cheng, G., “Full-body compliant human–humanoid interaction: Balancing in the presence of unknown external forces,” Full-body compliant human–humanoid interaction: Balancing in the presence of unknown external forces 23 (5), 884–898 (Oct. 2007).Google Scholar
10. Sugihara, T., Nakamura, Y. and Inoue, H., “Real-Time Humanoid Motion Generation through ZMP Manipulation Based on Inverted Pendulum Control,” Proceedings of the IEEE International Conference on Robotics and Automation, vol. Proceedings of the IEEE International Conference on Robotics and Automation (2002) pp. 1404–1409. doi:10.1109/ROBOT.2002.1014740.Google Scholar
11. Suleiman, W., Kanehiro, F., Miura, K. and Yoshida, E., “Improving ZMP-Based Control Model Using System Identification Techniques,” Proceedings of the 9th IEEE-RAS International Conference on Humanoid Robots (Humanoids) (Dec. 2009) pp. 74 –80.CrossRefGoogle Scholar
12. Mansard, N. and Chaumette, F., “Task sequencing for high-level sensor-based control,” IEEE Tran. Robot. 23 (1), 60–72 (Feb. 2007).Google Scholar
13. Sentis, L., Park, J. and Khatib, O., “Compliant control of multicontact and center-of-mass behaviors in humanoid robots,” IEEE Trans. Robot. 26 (3), 483–501 (2010).Google Scholar
14. Mistry, M., Nakanishi, J. and Schaal, S., “Task Space Control with Prioritization for Balance and Locomotion,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (Oct. 2007) pp. 331–338.Google Scholar
15. Chang, C.-C. and Lin, C.-J., “LIBSVM: A library for support vector machines,” LIBSVM: A library for support vector machines 2, 27:1–27 (2011).Google Scholar
16. Cortes, C. and Vapnik, V., “Support-vector networks,” Mach. Learn. 20 (3), 273–297 (1995).Google Scholar
17. Lee, J., Dallali, H., Tsagarakis, N. and Caldwell, D., “Robust and Model-Free Link Position Tracking Control for Humanoid COMAN with Multiple Compliant Joints,” Proceedings of the 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids) (Oct. 2013) pp. 56–61.Google Scholar
18. Mosadeghzad, M., Li, Z., Tsagarakis, N., Medrano-Cerda, G. A., Dallali, H. and Caldwell, D. G., “Optimal Ankle Compliance Regulation for Humanoid Balancing Control,” Proceedings of the 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (Nov. 2013) pp. 4118–4123.CrossRefGoogle Scholar
19. Gay, S., van den Kieboom, J., Santor-Victor, J. and Ijspeert, A. J., “Model-Based and Model-Free Approaches for Postural Control of a Compliant Humanoid Robot using Optical Flow,” Proceedings of the 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids) (Oct. 2013) pp. 1–7.Google Scholar
20. Nguyen, V. V. and Lee, J.-H., “Full-body Imitation of Human Motions with Kinect and Heterogeneous Kinematic Structure of Humanoid Robot,” Proceedings of the 2012 IEEE/SICE International Symposium on System Integration (Dec. 2012) pp. 93–98.Google Scholar
21. Koenemann, J. and Bennewitz, M., “Whole-Body Imitation of Human Motions with a Nao Humanoid,” Proceedings of the 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI) (Mar. 2012) pp. 425–425.CrossRefGoogle Scholar
22. Ramos, O. E., Saab, L., Hak, S. and Mansard, N., “Dynamic Motion Capture and Edition Using a Stack of Tasks,” Proceedings of the 11th IEEE-RAS International Conference on Humanoid Robots (Humanoids) (Oct. 2011) pp. 224–230.Google Scholar
23. Zheng, Y. and Yamane, K., “Human Motion Tracking Control with Strict Contact Force Constraints for Floating-Base Humanoid Robots,” Proceedings of the 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids) (Oct. 2013) pp. 1–7.Google Scholar
24. Santis, A., Gironimo, G., Pelliccia, L., Siciliano, B. and Tarallo, A., “Multiple-point Kinematic Control of a Humanoid Robot,” In: Advances in Robot Kinematics: Motion in Man and Machine (Lenarcic, J. and Stanisic, M. M., eds.) (Springer, Netherlands, 2010) pp. 157–168.Google Scholar
25. Bajd, T., Mihelj, M., Lenarčič, J., Stanovnik, A. and Munih, M., “Robotics,” In: Intelligent Systems, Control and Automation: Science and Engineering, vol. 43 (Springer Science+Business Media B.V., 2010) pp. 23–32.Google Scholar
26. Kajita, S., Kanehiro, F., Kaneko, K., Yokoi, K. and Hirukawa, H., “The 3D Linear Inverted Pendulum Mode: A Simple Modeling for a Biped Walking Pattern Generation,” Proceedings of the 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. Proceedings of the 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems (2001) pp. 239–246. doi:10.1109/IROS.2001.973365.Google Scholar
27. Goswami, A., “Postural stability of biped robots and the foot-rotation indicator (FRI) point,” Int. J. Robot. Res. 18 (6), 523–533 (1999).CrossRefGoogle Scholar
28. Moro, F. L., Tsagarakis, N. G. and Caldwell, D. G., “A Human-Like Walking for the Compliant Humanoid Coman Based on Com Trajectory Reconstruction from Kinematic Motion Primitives,” Proceedings of the 11th IEEE-RAS International Conference on Humanoid Robots (Humanoids) (Oct. 2011) pp. 364–370.Google Scholar
29. Colasanto, L., Tsagarakis, N. G. and Caldwell, D. G., “A Compact Model for the Compliant Humanoid Robot COMAN,” Proceedings of the 4th IEEE RAS EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob) (Jun. 2012) pp. 688–694.Google Scholar
30. Michel, O., “Webots: Professional mobile robot simulation,” J. Adv. Robot. Syst. 1 (1), 39–42 (2004).Google Scholar
31. Pastor, P., Kalakrishnan, M., Binney, J., Kelly, J., Righetti, L., Sukhatme, G. and Schaal, S., “Learning Task Error Models for Manipulation,” Proceedings of the 2013 IEEE International Conference on Robotics and Automation (May 2013) pp. 2612–2618.CrossRefGoogle Scholar