Abstract
Exploring the full potential of humanoid robots requires their ability to learn, generalize and reproduce complex tasks that will be faced in dynamic environments. In recent years, significant attention has been devoted to recovering kinematic information from the human motion using a motion capture system. This paper demonstrates the use of a VICON system to capture human locomotion that is used to train a set of Dynamic Movement Primitives. These DMP can then be used to directly control a humanoid robot on the task space. The main objectives of this paper are: (1) to study the main characteristics of human natural locomotion and human “robot-like” locomotion; (2) to use the captured motion to train a DMP; (3) to use the DMP to directly control a humanoid robot in task space. Numerical simulations performed on V-REP demonstrate the effectiveness of the proposed solution.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Billard, A., Callinon, S., Dillmann, R., Schaal, S.: Robot programming by demonstration. In: Siciliano, B., Khatib, O. (eds.) Handbook of Robotics. Springer, New York (2008)
Argall, B.D., Chernova, S., Veloso, M., Browning, B.: A Survey of Robot Learning from Demonstration. Robotics and Autonomous Systems 57(5), 469–483 (2009)
Dasgupta, A., Nakamura, Y.: Making feasible walking motion of humanoid robots from human motion capture data. In: IEEE International Conference on Robotics and Automation, pp. 1044–1049 (1999)
Elgammal, A., Lee, C.-S.: Tracking People on a Torus. IEEE Transactions on Pattern Analysis and Machine Intelligence 31(3), 520–538 (2009)
Inamura, T., Toshima, I., Tanie, H., Nakamura, Y.: Embodied Symbol Emergence Based on Mimesis Theory. International Journal of Robotics Research 23(4–5), 363–377 (2004)
Kulic, D., Takano, J.W., Nakamura, Y.: I”ncremental Learning, Clustering and Hierarchy Formation of Whole Body Motion Patterns using Adaptive Hidden Markov Chains. International Journal of Robotics Research 27(7), 761–784 (2008)
Shon, A.P., Grochow, K., Hertzmann, A., Rao, R.P.: Learning Shared Latent Structure for Image Synthesis and Robotic Imitation. In: Weiss, Y., Schlkopf, B., Platt, J.C. (eds.) Advances in Neural Information Processing Systems. MIT Press, Cambridge (2005)
Rohmer, E., Singh, S., Freese, M.: V-REP: a versatile and scalable robot simulation framework. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1321–1326 (2013)
Argall, B., Chernova, S., Veloso, M., Browning, B.: A survey of robot learning from demonstration. Robotics and Autonomous Systems 57(5), 469–483 (2009)
Billard, A., Callinon, S., Dillmann, R., Schaal, S.: Robot programming by demonstration. In: Siciliano, B., Khatib, O. (eds.) Handbook of robotics. Springer, New York (2008)
Schaal, S., Ijspeert, A., Billard, A.: Computational approaches to motor learning by imitation. Philosophical Transaction of the Royal Society of London: Series B, Biological Sciences 358, 537–547 (2003)
Breazeal, C., Scassellati, B.: Robots that imitate humans. Trends in Cognitive Science 6(11), 481–487 (2002)
Kober, J., Peters, J.,: Policy search for motor primitives in robotics. Machine Learning (2010)
Ijspeert, A., Nakanishi, J., Schaal, S.: Movement imitation with nonlinear dynamical systems in humanoid robots. In: Proceedings of the 2002 IEEE International Conference on Robotics and Automation, pp. 1398–1403 (2002)
Gams, A., Ijspeert, A.J., Schaal, S., Lenarcic, J.: On-line learning and modulation of periodic movements with nonlinear dynamical systems. Autonomous Robots 27(1), 3–23 (2009)
Ijspeert, A., Nakanishi, J., Hoffmann, H., Pastor, P., Schaal, S.: Dynamical movement primitives: learning attractor models for motor behaviors. Neural Computation 25, 328–373 (2013)
Pastor, P., Hoffmann, H., Asfour, T., Schaal, S.: Learning and generalization of motor skills by learning from demonstration. In: Proceedings of the IEEE International Conference on Robotics and Automation (2009)
Bitzer, S., Havoutis, I., Vijayakumar, S.: Synthesising Novel Movements through Space Modulation of Scalable Control Policies. From Animals to Animats. Springer (2008)
Umberger, B.R.: Stance and Swing Phase Costs in Human Walking. Journal of the Royal Society Interface 7(50), 1329–1340 (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Rosado, J., Silva, F., Santos, V. (2016). Biped Walking Learning from Imitation Using Dynamic Movement Primitives. In: Reis, L., Moreira, A., Lima, P., Montano, L., Muñoz-Martinez, V. (eds) Robot 2015: Second Iberian Robotics Conference. Advances in Intelligent Systems and Computing, vol 418. Springer, Cham. https://doi.org/10.1007/978-3-319-27149-1_15
Download citation
DOI: https://doi.org/10.1007/978-3-319-27149-1_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-27148-4
Online ISBN: 978-3-319-27149-1
eBook Packages: Computer ScienceComputer Science (R0)