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From human motion capture to humanoid locomotion imitation Application to the robots HRP-2 and HOAP-3

Published online by Cambridge University Press:  19 May 2010

Luc Boutin ,
Antoine Eon ,
Said Zeghloul  and
Patrick Lacouture
Luc Boutin*
Affiliation:
Département Génie Mécanique et Systèmes Complexes, Institut Pprime, CNRS - Université de Poitiers - ENSMA, SP2MI, BP30179, 86962 Futuroscope, France
Antoine Eon
Affiliation:
Département Génie Mécanique et Systèmes Complexes, Institut Pprime, CNRS - Université de Poitiers - ENSMA, SP2MI, BP30179, 86962 Futuroscope, France
Said Zeghloul
Affiliation:
Département Génie Mécanique et Systèmes Complexes, Institut Pprime, CNRS - Université de Poitiers - ENSMA, SP2MI, BP30179, 86962 Futuroscope, France
Patrick Lacouture
Affiliation:
Département Génie Mécanique et Systèmes Complexes, Institut Pprime, CNRS - Université de Poitiers - ENSMA, SP2MI, BP30179, 86962 Futuroscope, France
*
*Corresponding author. E-mail: boutin@lms.univ-poitiers.fr
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Summary

This paper presents a method to generate humanoid gaits from a human locomotion pattern recorded by a motion capture system. Thirty seven reflective markers were fixed on the human subject skin in order to get the subject whole body motion. To reproduce the human gait, especially the toes and heel contacts, the front and back edges of the robot's feet are used as support at the start and the end of the double support phase. The balance of the robot is respected using the zero moment point (ZMP) criterion and confirmed by the simulation software OPENHRP (General Robotics, Inc®). First, the feet trajectory as well as the ZMP reference trajectory are defined from the motion of the robot controlled as a marionette with the measured human joint angles. Then a specific inverse kinematic (IK) algorithm is proposed to find the humanoid robot's joint trajectories respecting the constraints of balance, floor contacts, and joint limits. The studied motion presented in this paper is a human walking trajectory containing a start, a movement in a straight line, a stop, and a quarter turn. The method was developed to be easily used for human-like robots of different sizes, masses, and structures and has been tested on the robot HRP-2 (AIST, Kawada Industries, Inc®) and on the small-sized humanoid robot HOAP-3 (Fujitsu Automation Ltd®).

Keywords

Humanoid robotsBiomimetic robotsBipedsHuman biomechanicsLegged robots
Type
Article
Information
Robotica , Volume 29 , Issue 2 , March 2011 , pp. 325 - 334
Copyright
Copyright © Cambridge University Press 2010

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References

1.Bell, A., Pedersen, D. and Brand, R., “A comparison of the accuracy of several hip center location prediction methods,” J. Biomech. 23 (6), 617–621 (1990). [Online]. Available at: http://www.scopus.com/scopus/inward/record.url?eid=2-s2.0-0025353537&partnerID=40CrossRefGoogle ScholarPubMed
2.Cappozzo, A., Catani, F., Croce, U. D. and Leardini, A., “Position and orientation in space of bones during movement: Anatomical frame definition and determination,” Clin. Biomech. 10 (4), 171–178, 1995. [Online]. Available at: http://www.sciencedirect.com/science/article/B6T59-3XY2J45-10/2/4140cd43d860aeb4c92f098589cfc242CrossRefGoogle ScholarPubMed
3.De Leva, P., “Adjustments to zatsiorsky-seluyanov's segment inertia parameters,” J. Biomech. 29 (9), 1223–1230 (1996). [Online]. Available: http://www.scopus.com/scopus/inward/record.url?eid=2-s2.0-0030245739&partnerID=40CrossRefGoogle ScholarPubMed
4.Desailly, E., Daniel, Y., Sardain, P. and Lacouture, P., “Foot contact event detection using kinematic data in cerebral palsy children and normal adults gait,” Gait Posture 29 (1), 76–80 (2009). [Online]. Available at: http://www.scopus.com/scopus/inward/record.url?eid=2-s2.0-57649216012&partnerID=40CrossRefGoogle ScholarPubMed
5.Gleicher, M., “Retargetting Motion to New Characters,” Proceedings of the ACM SIGGRAPH Conference on Computer Graphics (1998), pp. 33–42. [Online]. Available at: http://www.scopus.com/scopus/inward/record.url?eid=2-s2.0-0031639121&partnerID=40Google Scholar
6.Kajita, S., Kanehiro, F., Kaneko, K., Fujiwara, K., Harada, K., Yokoi, K. and Hirukawa, H., “Biped Walking Pattern Generation by Using Preview Control of Zero-Moment Point,” Proceedings of IEEE International Conference on Robotics and Automation ICRA '03, Vol. 2 (2003) pp. 1620–1626.Google Scholar
7.Liegeois, A., “Automatic supervisory control of the configuration and behavior of multibody mechanisms,” IEEE Trans. Syst. Man Cybern. 7 (12), 868–871 (1977).Google Scholar
8.Monnet, T., Desailly, E., Begon, M., Vall'ee, C. and Lacouture, P., “Comparison of the score and ha methods for locating in vivo the glenohumeral joint centre,” J. Biomech. 40 (15), 3487–3492 (2007). [Online]. Available at: http://www.scopus.com/scopus/inward/record.url?eid=2-s2.0-35448929927&partnerID=40CrossRefGoogle ScholarPubMed
9.Nakaoka, S., Nakazawa, A., Kanehiro, F., Kaneko, K., Morisawa, M., Hirukawa, H. and Ikeuchi, K., “Learning from observation paradigm: Leg task models for enabling a biped humanoid robot to imitate human dances,” Int. J. Robot. Res. 26 (8), 829–844 (2007). [Online]. Available at: http://www.scopus.com/scopus/inward/record.url?eid=2-s2.0-34547162912&partnerID=40CrossRefGoogle Scholar
10.Rose, G. J., Human Walking (Williams and Wilkins, 1994). [Online]. Available at: http://www.lww.com/product/?978-0-7817-5954-0Google Scholar
11.Sardain, P. and Bessonnet, G., “Forces acting on a biped robot. Center of pressure – zero moment point,” IEEE Trans. Syst. Man Cybern. 34 (5), 630–637 (2004).CrossRefGoogle Scholar
12.Sellaouti, R., Stasse, O., Kajita, S., Yokoi, K. and Kheddar, A., “Faster and Smoother Walking of Humanoid hrp-2 with Passive Toe Joints,” Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (2006) pp. 4909–4914.Google Scholar
13.Vukobratovic, M. and Stepanenko, J., “Mathematical models of general anthropomorphic systems,” Math. Biosci. 17 (3–4), 191–242 (1973). [Online]. Available at: http://www.scopus.com/scopus/inward/record.url?eid=2-s2.0-0015784223&partnerID=40CrossRefGoogle Scholar
14.Wampler, C. W., “Manipulator inverse kinematic solutions based on vector formulations and damped least-squares methods,” IEEE Trans. Syst. Man Cybern. 16 (1), 93–101 (1986).CrossRefGoogle Scholar
15.Wu, G., Cavanagh, P. and Brand, R., “Isb recommendations for standardization in the reporting of kinematic data,” J. Biomech. 28 (10), 1257–1261 (1995).CrossRefGoogle ScholarPubMed
16.Yamane, K., Hodgins, J. K. and Brown, H. B., “Controlling a Marionette with Human Motion Capture Data,” Proceedings of IEEE International Conference on Robotics and Automation ICRA '03, Vol. 3 (2003) pp. 3834–3841.Google Scholar
17.Yang, W., Chong, N., Kim, C. and You, B., “Locomotion Imitation of Humanoid Using Goal-Directed Self-Adjusting Adaptor,” IEEE International Conference on Intelligent Robots and Systems (2006) pp. 5650–5656. [Online]. Available at: http://www.scopus.com/inward/record.url?eid=2-s2.0-34250659377&partnerID=40Google Scholar