Combining dynamical systems control and programmingby demonstration for teaching discrete bimanual coordination tasks to a humanoid robot

ABSTRACT

We present a generic framework that combines Dynamical Systems movement control with Programming by Demonstration (PbD) to teach a robot bimanual coordination task. The model consists of two systems: a learning system that processes data collected during the demonstration of the task to extract coordination constraints and a motor system that reproduces the movements dynamically, while satisfying the coordination constraints learned by the first system. We validate the model through a series of experiments in which a robot is taught bimanual manipulatory tasks with the help of a human.

REFERENCES

• 1: J. Bezdek and N. Pal. Some new indexes of cluster validity. IEEE Transaction on System, Man, and Cybernetics, 28:301--315, 1998.
• 2: D. Bullock and S. Grossberg. Neural dynamics of planned arm movements: Emergent invariants and speed-accuracy properties during trajectory formation. Psychological Review, 95(1):49-90, 1988.
• 3: S. Calinon and A. Billard. Stochastic gesture production and recognition model for a humanoid robot. In Proceedings of IROS, pages 2769--2774, September 2004.
• 4: Sylvain Calinon , Aude Billard, Incremental learning of gestures by imitation in a humanoid robot, Proceedings of the ACM/IEEE international conference on Human-robot interaction, March 10-12, 2007, Arlington, Virginia, USA [doi>10.1145/1228716.1228751]
• 5: Y. Demiris and B.Khadhouri. Hierarchical attentive multiple models for execution and recognition of actions. Robotics and Autonomous Systems, 54:361--369, 2006.
• 6: J. Desai, M. Zefran, and V.Kumar. Two-arm manipulation tasks with friction assisted grasping. Proceedings of the IROS, 1:189--195, 1997.
• 7: A. Edsinger and C. Kemp. Manipulation in human environments. Proceedings of the 6th IEEE-RAS International Conference on Humanoid Robots, pages 102--109, 2006.
• 8: P. M. Fitts. The information capacity of the human motor system in controlling the amplitude of movement. Journal of Experimental Psychology, 47:381--391, 1954.
• 9: H. Haken, J. Kelso, and H. Bunz. A theoretical model of phase transitions in human hand movements. Biological Cybernetics, 51:347--356, 1985.
• 10: M. Hersch and A. Billard. A biologically-inspired model of reaching movements. In Proceedings of the International Conference on Biomedical Robotics and Biomechatronics, pages 1067--1072, 2006.
• 11: N. Hodges and I. Franks. Modelling coaching practice: the role of instruction and demonstration. Journal of Sport Sciences, 20:793--811, 2002.
• 12: L. Hubert and P. Arabie. Comparing partitions. Journal of Classification, 2:193--218, 1985.
• 13: J. Kelso, D. Southard, and D. Goodman. On the coordination of two-handed movements. Journal of Experimental Psychological Human Perception, 5(2):229--238, 1979.
• 14: J. Lieberman and C. Breazeal. Improvements on action parsing and action interpolation for learning through demonstration. In Proceedings of International Conference on Humanoid Robots, 1:342-365, 2004.
• 15: J. B. MacQueen. Some methods for classification and analysis of multivariate observations. In Proceedings of 5-th Berkeley Symposium on Mathematical Statistics and Probability, 1967.
• 16: L. Rabiner. A tutorial on hidden markov models and selected applications in speech recognition. Proceedings of IEEE, 77:257--286, 1989.
• 17: H. Sakoe and S. Chiba. Dynamic programming algorithm optimization for spoken word recognition. IEEE Transactions on Acoustic, Speech, and Signal Processing, pages 43--49, 1978.
• 18: G. Schoner. A dynamic theory of coordination of discrete movement. Biological Cybernetics, 63:257--270, 1990.
• 19: A. Ude, C. Atkeson, and M.Riley. Programming full-body movements for humanoid robots by observation. Robotics and Autonomous Systems, 47:93--108, 2004.
• 20: J. Desai , E. Henis, Two-arm manipulation: what can we learn by studying humans?, Proceedings of the International Conference on Intelligent Robots and Systems-Volume 1, p.70, August 05-09, 1995
• 21: R. Zollner, T. Afour, and R. Dillman. Programming by demonstration: Dual-arm manipulation tasks for humanoid robots. In Proceedings of the IROS, 2004.

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.6 Learning

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.9 Robotics

General Terms:
Algorithms, Performance

Keywords:
bimanual coordination, dynamical systems, human-robot interaction(hri), humanoid robot, learning by imitation, programming by demonstration (pbd)