Autonomous Robots

, Volume 36, Issue 4, pp 331–347 | Cite as

Walking in the resonance with the COMAN robot with trajectories based on human kinematic motion primitives (kMPs)

  • Federico L. Moro
  • Nikos G. Tsagarakis
  • Darwin G. Caldwell
Article

Abstract

Research in humanoid robotics aims to develop autonomous systems that are able to assist humans in the performance of everyday tasks. Part of the robotics community claims that the best solution to guarantee the maximum adaptability of robots to the majority of human tasks is mimicry. Based on this premise both the structure of the human body and human behavior have been the focus of studies, with the aim of imitating and reproducing on robotic systems the results of millennia of human evolution. The research presented in this paper aims (i) at transferring the features of human locomotion to the COmpliant huMANoid (COMAN) robot, by means of kinematic motion primitives (kMPs) extracted from human subjects, and (ii) at improving the energetic performance of the walk of COMAN by exploiting its intrinsic compliance: it will be shown that, when the robot is walking at a gait frequency that is close to one of the main resonance frequencies of the mechanism, the springs contribute to tracking the human-like kMPs-based trajectories imposed, providing at the right time about 15 % of the energy required for locomotion, and that was previously stored.

References

  1. Brooks, R., Breazeal, C., Marjanovic, M., Scassellati, B., & Williamson, M. (1998). The cog project: Building a humanoid robot. In C. Nehaniv (Ed.), Computation for metaphors, analogy and Agents. Lecture notes in artificial intelligence (Vol. 1562, pp. 52–87). Berlin: Springer.CrossRefGoogle Scholar
  2. Collins, S., Ruina, A., Tedrake, R., & Wisse, M. (2005). Efficient bipedal robots based on passive-dynamic walkers. Science, 307(5712), 1082–1085.CrossRefGoogle Scholar
  3. D’Avella, A., Saltiel, P., & Bizzi, E. (2003). Combinations of muscle synergies in the construction of a natural motor behavior. Nature Neuroscience, 6(3), 300–308.CrossRefGoogle Scholar
  4. Degallier, S., Righetti, L., Natale, L., Nori, F., Metta, G., & Ijspeert, A. (2008). A modular bio-inspired architecture for movement generation for the infant-like robot iCub. In 2nd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (pp. 795–800), Scottsdale, AZ, USA.Google Scholar
  5. Dégallier Rochat, S., & Ijspeert, A. (2010). Modeling discrete and rhythmic movements through motor primitives: A review. Biological Cybernetics, 103(4), 319–338.CrossRefGoogle Scholar
  6. Dégallier Rochat, S., Righetti, L., Gay, S., & Ijspeert, A. (2011). Towards simple control for complex, autonomous robotic applications: Combining discrete and rhythmic motor primitives. Autonomous Robots, 31(2), 155–181.CrossRefGoogle Scholar
  7. Edsinger-Gonzales, A., & Weber, J. (2004). Domo: A force sensing humanoid robot for manipulation research. In IEEE-RAS International Conference on Humanoid Robots (pp. 1–19), Santa Monica, CA, USA.Google Scholar
  8. Fujimoto, Y. (2004). Trajectory generation of biped running robot with minimum energy consumption. In IEEE International Conference on Robotics and Automation (pp. 3803–3808), Barcelona, Spain.Google Scholar
  9. Grebenstein, M., et al. (2011). The dlr hand arm system. In IEEE International Conference on Robotics and Automation (pp. 3175–3182), Shanghai, China.Google Scholar
  10. Hollands, K., Wing, A. M., & Daffertshofer, A. (2007). Principal component analysis of contemporary dance kinematics. In 3rd IEEE EMBSS UK & RI Postgraduate Conference in Biomedical Engineering & Medical Physics (pp. 3989–3994). Southampton, UK: University of Southampton.Google Scholar
  11. Ivanenko, Y. P., Cappellini, G., Dominici, N., Poppele, R. E., & Lacquaniti, F. (2005). Coordination of locomotion with voluntary movements in humans. The Journal of Neuroscience, 25(31), 7238–7253.CrossRefGoogle Scholar
  12. Ivanenko, Y. P., Poppele, R. E., & Lacquaniti, F. (2004). Five basic muscle activation patterns account for muscle activity during human locomotion. The Journal of Physiology, 556(1), 267–282.CrossRefGoogle Scholar
  13. Iwata, H., & Sugano, S. (2009). Design of human symbiotic robot twendy-one. In IEEE International Conference on Robotics and Automation (pp. 580–586), Kobe, Japan.Google Scholar
  14. Jafari, A., Tsagarakis, N., & Caldwell, D. G. (2011). Exploiting natural dynamic for energy minimization using an actuator with adjustable stiffness (awas). In IEEE International Conference on Robotics and Automation (pp. 4632–4637), Shanghai, China.Google Scholar
  15. Kagami, S., Kitagawa, T., Nishiwaki, K., Sugihara, T., Inaba, M., & Inoue, H. (2002). A fast dynamically equilibrated walking trajectory generation method of humanoid robot. Autonomous Robots, 12(1), 71–82.CrossRefMATHGoogle Scholar
  16. Kajita, S., Kanehiro, F., Kaneko, K., Fujiwara, K., Harada, K., Yokoi, K., et al. (2003). Biped walking pattern generation by using preview control of zero-moment point. In IEEE International Conference on Robotics and Automation (pp. 1620–1626), Taipei, Taiwan.Google Scholar
  17. Kaynov, D., Soueres, P., Pierro, P., & Balaguer, C. (2009). A practical decoupled stabilizer for joint-position controlled humanoid robots. In IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 3392–3397), St. Louis, MO, USA.Google Scholar
  18. Kormushev, P., Ugurlu, B., Calinon, S., Tsagarakis, N. G., & Caldwell, D. G. (2011). Bipedal walking energy minimization by reinforcement learning with evolving policy parameterization. In IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 318–324), San Francisco, CA, USA.Google Scholar
  19. Kuo, A. D. (2002). Energetics of actively powered locomotion using the simplest walking model. Journal of Biomechanical Engineering, 124, 113–120.CrossRefGoogle Scholar
  20. Kurazame, R., Tanaka, S., Yamashita, M., Hasegawa, T., & Yoneda, K. (2005). Straight legged walking of a biped robot. In IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 337–343), Edmonton, CanadaGoogle Scholar
  21. Mitobe, K., Capi, G., & Nasu, Y. (2000). Control of walking robots based on manipulation of the zero moment point. Robotica, 18(06), 651–657.CrossRefGoogle Scholar
  22. Morisawa, M., Harada, K., Kajita, S., Nakaoka, S., Fujiwara, K., Kanehiro, F., et al. (2007). Experimentation of humanoid walking allowing immediate modification of foot place based on analytical solution. In IEEE International Conference on Robotics and Automation (pp. 3989–3994), Rome, Italy.Google Scholar
  23. Moro, F., Gini, G., Zefran, M., & Rodic, A. (2010). Simulation for the optimal design of a biped robot: Analysis of energy consumption. In International Conference on Simulation, Modeling, and Programming for Autonomous Robots, Darmstadt, Germany.Google Scholar
  24. Moro, F. L., Spröwitz, A., Tuleu, A., Vespignani, M., Tsagarakis, N. G., Ijspeert, A. J., et al. (2013). Horse-like walking, trotting and galloping derived from kinematic motion primitives (kmps) and their application to walk/trot transitions in a compliant quadruped robot. Biological Cybernetics, 107, 309–320.CrossRefMathSciNetGoogle Scholar
  25. Moro, F. L., Tsagarakis, N. G., & Caldwell, D. G. (2011). A human-like walking for the compliant humanoid coman based on com trajectory reconstruction from kinematic motion primitives. In IEEE-RAS International Conference on Humanoid Robots (pp. 364–370), Bled, Slovenia.Google Scholar
  26. Moro, F. L., Tsagarakis, N. G., & Caldwell, D. G. (2012a). Efficient human-like walking for the compliant humanoid coman based on kinematic motion primitives (kmps). In IEEE International Conference on Robotics and Automation, Saint Paul, MN, USA.Google Scholar
  27. Moro, F. L., Tsagarakis, N. G., & Caldwell, D. G. (2012b). The kinematic motion primitives (kmps) of periodic motions, discrete motions, and motions that are a combination of discrete and periodic movements. In Cognitive Neuroscience Robotics (CNR) Workshop at the IEEE/RSJ International Conference on Intelligent Robots and Systems, Vilamoura, Portugal.Google Scholar
  28. Moro, F. L., Tsagarakis, N. G., & Caldwell, D. G. (2012c). On the kinematic motion primitives (kmps)—Theory and application. Frontiers in Neurorobotics, 6(10), 1–18.Google Scholar
  29. Nagasaka, K., Kuroki, Y., Suzuki, S., Itoh, Y., & Yamaguchi, J. (2004). Integrated motion control for walking, jumping and running on a small bipedal entertainment robot. In IEEE International Conference on Robotics and Automation (pp. 3189–3194), Barcelona, Spain.Google Scholar
  30. Sheridan, T. (1966). Three models of preview control. IEEE Transactions on Human Factors in Electronics, 2, 91–102.CrossRefGoogle Scholar
  31. Silva, F. M., & Machado, J. A. T. (1999). Energy analysis during biped walking. In IEEE International Conference on Robotics and Automation (pp. 59–64), Detroit, MI, USA.Google Scholar
  32. Sugihara, T. (2009). Standing stabilizability and stepping maneuver in planar bipedalism based on the best com-zmp regulator. In IEEE International Conference on Robotics and Automation (pp. 1966–1971), Kobe, Japan.Google Scholar
  33. Torres-Jara, E. (2005). Obrero: A platform for sensitive manipulation. In IEEE-RAS International Conference on Humanoid Robots (pp. 327–332), Tsukuba, Japan.Google Scholar
  34. Tsagarakis, N. G., Becchi, F., Singlair, M., Metta, G., Caldwell, D. G., & Sandini, G. (2007a). Lower body realization of the baby humanoid ’icub’. In IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 3616–3622), San Diego, CA, USA.Google Scholar
  35. Tsagarakis, N. G., Laffranchi, M., Vanderborght, B., & Caldwell, D. G. (2009). A compact soft actuator unit for small scale human friendly robots. In IEEE International Conference on Robotics and Automation (pp. 4356–4362), Kobe, Japan.Google Scholar
  36. Tsagarakis, N. G., Li, Z., Saglia, J. A., & Caldwell, D. G. (2011). The design of the lower body of the compliant humanoid robot ccub. In IEEE International Conference on Robotics and Automation (pp. 2035–2040), Shanghai, China.Google Scholar
  37. Tsagarakis, N. G., Metta, G., Sandini, G., Vernon, D., Beira, R., Becchi, F., et al. (2007b). icub: The design and realization of an open humanoid platform for cognitive and neuroscience research. Advanced Robotics, 21(10), 1151–1175.CrossRefGoogle Scholar
  38. Ugurlu, B., Saglia, J. A., Tsagarakis, N. G., & Caldwell, Darwin G. (2012). Hopping at the resonance frequency: A trajectory generation technique for bipedal robots with elastic joints. In: IEEE International Conference on Robotics and Automation, Saint Paul, MN, USA.Google Scholar
  39. Vanderborght, B., Verrelst, B., Van Ham, R., Van Damme, M., Lefeber, D., Duran, B. M. Y., et al. (2006). Exploiting natural dynamics to reduce energy consumption by controlling the compliance of soft actuators. International Journal of Robotics Research, 25(4), 343–358.Google Scholar
  40. Yamasaki, F., Hosoda, K., & Asada, M. (2002). An energy consumption based control for humanoid walking. In IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 2473–2477), Lausanne, Switzerland.Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Federico L. Moro
    • 1
  • Nikos G. Tsagarakis
    • 1
  • Darwin G. Caldwell
    • 1
  1. 1.Department of Advanced RoboticsIstituto Italiano di Tecnologia (IIT)GenovaItaly

Personalised recommendations