COLLABORATIVE CONTROL IN A HUMANOID DYNAMIC TASK

Diego Pardo, Cecilio Angulo

2007

Abstract

This paper describes a collaborative control scheme that governs the dynamic behavior of an articulated mobile robot with several degrees of freedom (DOF) and redundancies. These types of robots need a high level of coordination between the motors performance to complete their motions. In the employed scheme, the actuators involved in a specific task share information, computing integrated control actions. The control functions are found using a stochastic reinforcement learning technique allowing the robot to automatically generate them based on experiences. This type of control is based on a modularization principle: complex overall behavior is the result of the interaction of individual simple components. Unlike the standard procedures, this approach is not meant to follow a trajectory generated by a planner, instead, the trajectory emerges as a consequence of the collaboration between joints movements while seeking the achievement of a goal. The learning of the sensorimotor coordination in a simulated humanoid is presented as a demonstration.

References

  1. Daley, S. and Liu, G. (1999). Optimal pid tuning using direct search algorithms. Computing and Control Engineering Journal, 10(2):251-56.
  2. Fujita, M. and Kitano, H. (1998). Development of an autonomous quadruped robot for robot entertainment. Autonomous Robots, 5(1):7-18.
  3. Hirai, K., Hirose, M., Haikawa, Y., and Takenaka, T. (1998). The development of honda humanoid robot. In Proceedings of the IEEE International Conference on Robotics and Automation, ICRA.
  4. Jabri, M. and Flower, B. (1992). Weight perturbation: An optimal architecture and learning technique for analog VLSI feedforward and recurrent multilayer networks.
  5. IEEE Transactions on Neural Networks, 3(1):154- 157.
  6. Kaneko, K., Kanehiro, F., Kajita, S., Hirukawa, H., Kawasaki, T., Hirata, M., Akachi, K., and Isozumi, T. (2004). Humanoid robot hrp-2. In Proceedings of the IEEE International Conference on Robotics and Automation, ICRA.
  7. Koszalka, L., Rudek, R., and Pozniak-Koszalka, I. (2006). An idea for using reinforcement learning in adaptive control systems. In Proceedings of the IEEE Int Conference on Networking, Systems and Mobile Communications and Learning Technologies, Kerkrade, Netherlands.
  8. Kuroki, Y., Blank, B., Mikami, T., Mayeux, P., Miyamoto, A., Playter, R., Nagasaya, K., Raibert, M., Nagano, M., and Yamaguchi, J. (2003). A motion creating system for a small biped entretainment robot. In Proceedings of the IEEE International Conference on Intelligent Robots and Systems, IROS.
  9. Michel, O. (2004). Webots: Professional mobile robot simulation. Journal of Advanced Robotics Systems, 1(1):39-42.
  10. Rosenstein, M. T. (2003). Learning to exploit dynamics for robot motor coordination. PhD thesis, University of Massachusetts, Amherst.
  11. Rosenstein, M. T. and Barto, A. G. (2001). Robot weightlifting by direct policy search. In Proceedings of the IEEE International Conference on Artificial Intelligence, IJCAI, pages 839-846.
  12. Sutton, R., McAllester, D., Singh, S., and Mansour, Y. (2000). Policy gradient methods for reinforcement learning with function approximation. Advances in Neural Information Processing Systems, 12:1057- 1063.
  13. Vukobratovic, M. and Stepanenko, J. (1972). On the stability of anthropomorphic systems. Mathematical Biosciences, 15:1-37.
  14. Williams, R. J. (1992). Simple statistical gradient-following algorithms for connectionist reinforcement learning. Machine Learning, 8:229-256.
Download


Paper Citation


in Harvard Style

Pardo D. and Angulo C. (2007). COLLABORATIVE CONTROL IN A HUMANOID DYNAMIC TASK . In Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-972-8865-83-2, pages 174-180. DOI: 10.5220/0001629001740180


in Bibtex Style

@conference{icinco07,
author={Diego Pardo and Cecilio Angulo},
title={COLLABORATIVE CONTROL IN A HUMANOID DYNAMIC TASK},
booktitle={Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2007},
pages={174-180},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001629001740180},
isbn={978-972-8865-83-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - COLLABORATIVE CONTROL IN A HUMANOID DYNAMIC TASK
SN - 978-972-8865-83-2
AU - Pardo D.
AU - Angulo C.
PY - 2007
SP - 174
EP - 180
DO - 10.5220/0001629001740180