an intelligent humanoid robot imitation by image recognition

Sithara Gopinath,

Published in International Journal of Advanced Research in Robotics and Development

ISSN: 2348-2338          Impact Factor:1.678         Volume:1         Issue:1         Year: 08 December,2013         Pages:17-23

International Journal of Advanced Research in Robotics and Development

Abstract

In this paper, we present a system for the imitation of human motion on a humanoid robot by means of image recognition. For achieving this imitation, three main processes are to be considered. They are human imitation data acquisition; the data modification; and the ankle angle adjustment on the supporting foot of robot. In the first process that is human imitation data acquisition first we are pasting 13 color marks on a human body at different locations. For acquiring the motion imitation we have to make use of a Logitech webcam C905 to identify these color marks and then the relative positions of the marks for each motion is recorded and calculated into the motion database. In data modification stage, these data are modified with the help of computer simulation to make sure that the zero moment point of the humanoid robot is within the stable region. At last stage that is in ankle angle adjustment stage the ankle angles are adjusted. Thus, in real time the humanoid robot can imitate almost all the human motions with stability

Kewords

For achieving this imitation, three main processes are to be considered. They are human imitation data acquisition; the data modification

Reference

[1] Karlsson.N, Karlsson.B, and P. Wide, ―A glove equipped with finger flexion sensors as a command generator used in a fuzzy control system,‖ IEEE Trans. Instrum. Meas., vol. 47, no. 5 Oct. 1998. [2] X. He and Y. Chen, ―Six-degree-of-freedom haptic rendering in virtual teleoperation,‖ IEEE Trans. Instrum. Meas., vol. 57, no. 9, pp. 1866–1875, Sep. 2008. [3] G. Sen Gupta, S. C. Mukhopadhyay, C. H. Messom, and S. Demidenko, ―Master–slave control of a teleoperated anthropomorphic robotic arm with gripping force sensing,‖ IEEE Trans. Instrum. Meas., vol.55, no. 6, pp. 2136–2145, Dec. 2006.motion for a biped humanoid robot to imitate human dances?‖ in Proc. Int. Conf. Intell. Robot. Syst., 2005. [4] X. J. Zhao, O. Huang, Z. Peng, and K. Li, ―Kinematics mapping and sim- ilarity evaluation of humanoid motion based on human motion capture,‖ in Proc. Int. Conf. Intell. Robot. Syst., 2004, vol. 1, pp. 840–845. [5] S. Kim, C. Kim, and B.-J. You, ―Whole-body motion imitation using human modeling,‖ in Proc. IEEE Int. Conf. Robot. Biomimetics, 2009, pp. 596–601. [6] L. Tanco, J. P. Bandera, R. Marfil, and F. Sandoval, ―Real-time human motion analysis for human-robot interaction,‖in Proc. Int. Conf. Intell. Robot. Syst., 2005,. [7] K. Erbatur, A. Okazaki, K. Obiya, T. Takahashi, and A. Kawamura, ―A study on the zero moment point measurement for biped walking robots,‖ in Proc. 7th Int. Workshop Adv. Motion Control, 2002, pp. 431–436. [8] J. H. Park and H. Chung, ―ZMP compensation by online trajectory gen- eration for biped robots,‖ in Proc. IEEEInt. Conf. Syst., Man, Cybern.,1999, vol. 4 [9] J. P. Ferreira, M. M. Crisostomo, and A. P. Coimbra, ―Human gait acqui- sition and characterization,‖ IEEE Trans. Instrum. Meas., vol. 58, no. 9, , Sep. 2009.