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Adaptive Robot Biped Locomotion with Dynamic Motion Primitives and Coupled Phase Oscillators

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Abstract

In order to properly function in real-world environments, the gait of a humanoid robot must be able to adapt to new situations as well as to deal with unexpected perturbations. A promising research direction is the modular generation of movements that results from the combination of a set of basic primitives. In this paper, we present a robot control framework that provides adaptive biped locomotion by combining the modulation of dynamic movement primitives (DMPs) with rhythm and phase coordination. The first objective is to explore the use of rhythmic movement primitives for generating biped locomotion from human demonstrations. The second objective is to evaluate how the proposed framework can be used to generalize and adapt the human demonstrations by adjusting a few open control parameters of the learned model. This paper contributes with a particular view into the problem of adaptive locomotion by addressing three aspects that, in the specific context of biped robots, have not received much attention. First, the demonstrations examples are extracted from human gaits in which the human stance foot will be constrained to remain in flat contact with the ground, forcing the “bent-knee” at all times in contrast with the typical straight-legged style. Second, this paper addresses the important concept of generalization from a single demonstration. Third, a clear departure is assumed from the classical control that forces the robot’s motion to follow a predefined fixed timing into a more event-based controller. The applicability of the proposed control architecture is demonstrated by numerical simulations, focusing on the adaptation of the robot’s gait pattern to irregularities on the ground surface, stepping over obstacles and, at the same time, on the tolerance to external disturbances.

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References

  1. Argall, B.D., Chernova, S., Veloso, M., Browning, B.: A survey of robot learning from demonstration. Rob. Auton. Syst. 57(5), 469–483 (2009)

    Article  Google Scholar 

  2. Billard, A., Calinon, S., Dillmann, R., Schaal, S.: Robot programming by demonstration. Handb. Robot., 1371–1394 (2008)

  3. Kormushev, P., Nenchev, D.N., Calinon, S., Caldwell, D.G.: Upper-body kinesthetic teaching of a free-standing humanoid robot. In: Proceeding - IEEE Int. Conf. Robot. Autom., pp 3970–3975 (2011)

  4. Kulic, D., Ott, C., Lee, D., Ishikawa, J., Nakamura, Y.: Incremental learning of full body motion primitives and their sequencing through human motion observation. Int. J. Rob. Res. 31(3), 330–345 (2012)

    Article  Google Scholar 

  5. Chalodhorn, R., Grimes, D.B., Grochow, K., Rao, R.P.N.: Learning to walk by imitation in low-dimensional subspaces. Adv. Robot. 24(1–2), 207–232 (2010)

    Article  Google Scholar 

  6. Nakanishi, J.N.J., Morimoto, J.M.J., Endo, G., Cheng, G., Schaal, S., Kawato, M.: A framework for learning biped locomotion with dynamical movement primitives. 4th IEEE/RAS Int. Conf. Humanoid Robot. 2004 2, 925–940 (2004)

    Article  Google Scholar 

  7. Lee, D., Ott, C., Nakamura, Y.: Mimetic communication model with compliant physical contact in human–humanoid interaction. Int. J. Rob. Res. 29(13), 1684–1704 (2010)

    Article  Google Scholar 

  8. Asfour, T., Azad, P., Gyarfas, F., Dillmann, R.: Imitation learning of dual-arm manipulation tasks in humanoid robots. Int. J. Humanoid Robot. 5(2), 289–308 (2008)

    Article  Google Scholar 

  9. Calinon, S., D’Halluin, F., Sauser, E.L., Caldwell, D.G., Billard, A.G.: Learning and reproduction of gestures by imitation. IEEE Robot. Autom. Mag. 17(2), 44–54 (2010)

    Article  Google Scholar 

  10. Calinon, S., Guenter, F., Billard, A.: On Learning, representing, and generalizing a task in a humanoid robot. IEEE Trans. Syst. Man Cybern. Part B 37(2), 286–298 (2007)

    Article  Google Scholar 

  11. Gams, A., Ijspeert, A.J., Schaal, S., Lenarčič, J.: On-line learning and modulation of periodic movements with nonlinear dynamical systems. Auton. Robots 27(1), 3–23 (2009)

    Article  Google Scholar 

  12. Ijspeert, A.J., Nakanishi, J., Hoffmann, H., Pastor, P., Schaal, S.: Dynamical movement primitives: learning attractor models for motor behaviors. Neural Comput. 25(2), 328–73 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  13. Ijspeert, A., Nakanishi, J., Schaal, S.: Movement imitation with nonlinear dynamical systems in humanoid robots. In: International Conference on Robotics and Automation, pp 1398–1403 (2002)

  14. Kober, J., Peters, J.: Policy search for motor primitives in robotics. Mach. Learn. 84(1–2), 171–203 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  15. Vukobratovic, M., Juricic, D: Contribution to the synthesis of biped gait. Biomed. Eng. IEEE Trans. BME-16(1), 1–6 (1969)

    Article  Google Scholar 

  16. Sano, A., Furusho, J.: Realization of natural dynamic walking using the angular momentum information. Proceedings., IEEE Int. Conf. Robot. Autom., 1476–1481 (1990)

  17. Stephens, B.: Integral control of humanoid balance. IEEE Int. Conf. Intell. Robot. Syst., 4020–4027 (2007)

  18. Choi, Y., Kim, D., Oh, Y., You, B. J.: Posture/walking control for humanoid robot based on kinematic resolution of CoM Jacobian with embedded motion. IEEE Trans. Robot. 23(6), 1285–1293 (2007)

    Article  Google Scholar 

  19. Kajita, S., Kanehiro, F.: Resolved momentum control: Humanoid motion planning based on the linear and angular momentum. Robot. Syst. 2(October), 1644–1650 (2003)

    Google Scholar 

  20. Sugihar, T., Hiko Nakamur, Y., Inoue, H., Sugihara, T., Nakamura, Y., Inoue, H., Sugihar, T., Inoue, H., Hiko Nakamur, Y., Inoue, H.: Realtime humanoid motion generat ion through ZMP manipulation based on inverted pendulum control. In: IEEE International Conference on Robotics & Automation, 2002, no. May, pp. 1404–1409

  21. Muico, U., Lee, Y., Popović, J., Popović, Z.: Contact-aware nonlinear control of dynamic characters. ACM Trans. Graph. 28(3), 81:1–81:9 (2009)

    Article  Google Scholar 

  22. Zhou, C., Meng, Q.: Dynamic balance of a biped robot using fuzzy reinforcement learning agents. Fuzzy Sets Syst. 134(1), 169–187 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  23. Ibanez, A., Bidaud, P., Padois, V.: Automatic optimal biped walking as a mixed-integer quadratic program. In: Jadran Lenarčič, O.K. (ed.) Advances in Robot Kinematics, pp 505–516. Springer International Publishing (2014)

  24. Huang, Q., Nakamura, Y.: Sensory reflex control for humanoid walking. IEEE Trans. Robot. 21 (5), 977–984 (2005)

    Article  Google Scholar 

  25. Taga, G.: “A model of the neuro-musculo-skeletal system for human locomotion. I. Emergence of basic gait. Biol. Cybern. 73(2), 97–111 (1995)

    Article  MATH  Google Scholar 

  26. Taga, G.: A model of the neuro-musculo-skeletal system for human locomotion - II. Real-time adaptability under various constraints. Biol. Cybern. 73(2), 113–121 (1995)

    Article  MATH  Google Scholar 

  27. Ijspeert, A.J.: Central pattern generators for locomotion control in animals and robots: a review. Neural Netw. 21(4), 642–653 (2008)

    Article  Google Scholar 

  28. Matos, V., Santos, C.: Towards goal-directed biped locomotion: Combining CPGs and motion primitives. Rob. Auton. Syst. 62(12), 1669–1690 (2014)

    Article  Google Scholar 

  29. Degallier, S., Righetti, L., Gay, S., Ijspeert, A.: Toward simple control for complex, autonomous robotic applications: Combining discrete and rhythmic motor primitives. Auton. Robots 31(2–3), 155–181 (2011)

    Article  Google Scholar 

  30. Kober, J., Peters, J.: Learning Motor Skills: From Algorithms to Robot Experiments (2013)

  31. Morimoto, J., Endo, G., Nakanishi, J., Cheng, G.: A biologically inspired biped locomotion strategy for humanoid robots: modulation of sinusoidal patterns by a coupled oscillator model. IEEE Trans. Robot. 24(1), 185–191 (2008)

    Article  Google Scholar 

  32. Pastor, P., Hoffmann, H., Asfour, T., Schaal, S.: Learning and generalization of motor skills by learning from demonstration, IEEE Int. Conf. Robot. Autom. 2009. ICRA ’09, pp. 763–768 (2009)

  33. Ude, A., Gams, A., Asfour, T., Morimoto, J.: Task-specific generalization of discrete and periodic dynamic movement primitives. IEEE Trans. Robot. 26(5), 800–815 (2010)

    Article  Google Scholar 

  34. Hoffmann, M., Marques, H., Arieta, A., Sumioka, H., Lungarella, M., Pfeifer, R.: Body schema in robotics: a review. IEEE Trans. Auton. Ment. Dev. 2(4), 304–324 (2010)

    Article  Google Scholar 

  35. Aoi, S.A.S., Tsuchiya, K.: Stability analysis of a simple walking model driven by an oscillator with a phase reset using sensory feedback. IEEE Trans. Robot. 22(2), 391–397 (2006)

    Article  Google Scholar 

  36. Righetti, L., Ijspeert, A.J.: Programmable central pattern generators: an application to biped locomotion control. In: Proceeding 2006 IEEE Int. Conf., Robot. Autom. 2006. ICRA 2006. no. May, pp 1585–1590 (2006)

  37. Righetti, L., Ijspeert, A.J.: Pattern generators with sensory feedback for the control of quadruped locomotion. In: Proceeding - IEEE Int. Conf. Robot. Autom. no. July 2015, pp 819–824 (2008)

  38. Maufroy, C., Kimura, H., Takase, K.: Integration of posture and rhythmic motion controls in quadrupedal dynamic walking using phase modulations based on leg loading/unloading. Auton. Robots 28(3), 331–353 (2010)

    Article  Google Scholar 

  39. Perry, J.: Gait Analysis: Normal and Pathological Function, vol. 12 (1992)

  40. Bauby, C.E., Kuo, A.D.: Active control of lateral balance in human walking. J. Biomech. 33(11), 1433–1440 (2000)

    Article  Google Scholar 

  41. Rohmer, E., Singh, S.P.N., Freese, M.: V-REP: A versatile and scalable robot simulation framework. IEEE Int. Conf. Intell. Robot. Syst., 1321–1326 (2013)

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Authors and Affiliations

  1. Department of Computer Engineering and Systems, Instituto Superior de Engenharia de Coimbra - IPC, Coimbra, Portugal

    José Rosado

  2. IEETA, Department of Electronics Telecommunications and Informatics, University of Aveiro, Aveiro, Portugal

    Filipe Silva & Vítor Santos

  3. ESSUA, University of Aveiro, Aveiro, Portugal

    António Amaro

Authors
  1. José Rosado
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  2. Filipe Silva
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  3. Vítor Santos
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  4. António Amaro
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Correspondence to José Rosado.

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Rosado, J., Silva, F., Santos, V. et al. Adaptive Robot Biped Locomotion with Dynamic Motion Primitives and Coupled Phase Oscillators. J Intell Robot Syst 83, 375–391 (2016). https://doi.org/10.1007/s10846-016-0336-1

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  • DOI: https://doi.org/10.1007/s10846-016-0336-1

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