View-based imitation with rotation invariant pan-tilt stereo cameras

In our previous work (2000), we have developed a method for visual imitation by recovering the demonstrator's view based on the stereo epipolar constraint. The method is applied to the stationary pair of the stereo cameras, therefore, the visual fields to observe the motions of both the demonstrator and the learner are limited. This paper presents a method to extend our previous work by adopting a pair of rotation invariant stereo cameras that has pan and tilt motions without changing the optical center, therefore, the stereo epipolar equation does not change. The spherical projection is used to represent the constraint. The experimental results obtained are shown.

[1]  H. C. Longuet-Higgins,et al.  A computer algorithm for reconstructing a scene from two projections , 1981, Nature.

[2]  Minoru Asada,et al.  Cognitive developmental robotics as a new paradigm for the design of humanoid robots , 2001, Robotics Auton. Syst..

[3]  Stefan Schaal,et al.  Is imitation learning the route to humanoid robots? , 1999, Trends in Cognitive Sciences.

[4]  Gillian M. Hayes,et al.  Imitative Learning Mechanisms in Robots and Humans , 1996 .

[5]  Minoru Asada,et al.  Versatile visual servoing without knowledge of true Jacobian , 1994, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94).

[6]  Yasuharu Koike,et al.  PII: S0893-6080(96)00043-3 , 1997 .

[7]  Yoshihiko Nakamura,et al.  Imitation and primitive symbol acquisition of humanoids by the integrated mimesis loop , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[8]  Minoru Asada,et al.  View-based imitation learning by conflict resolution with epipolar geometry , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

[9]  Jun Nakanishi,et al.  Trajectory formation for imitation with nonlinear dynamical systems , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

[10]  Masayuki Inaba,et al.  Learning by watching: extracting reusable task knowledge from visual observation of human performance , 1994, IEEE Trans. Robotics Autom..

[11]  Aude Billard,et al.  Learning human arm movements by imitation: : Evaluation of a biologically inspired connectionist architecture , 2000, Robotics Auton. Syst..