Biomimetic Gaze Stabilization

Accurate oculomotor control is one of the essential pre-requisites for successful visuomotor coordination. In this paper, we suggest a biologically inspired control system for learning gaze stabilization with a biomimetic robotic oculomotor system. In a stepwise fashion, we develop a control circuit for the vestibulo-ocular re ex (VOR) and the opto-kinetic response (OKR), and add a nonlinear learning network to allow adaptivity. We discuss the parallels and di erences of our system with biological oculomotor control and suggest solutions how to deal with nonlinearities and time delays in the control system. In simulation and actual robot studies, we demonstrate that our system can learn gaze stabilization in real time in only a few seconds with high nal accuracy.

[1]  G. Jones,et al.  Frequency—response analysis of central vestibular unit activity resulting from rotational stimulation of the semicircular canals , 1971, The Journal of physiology.

[2]  P. Fells.  Basic Mechanisms of Ocular Motility and their Clinical Implications , 1976 .

[3]  L. Dell’Osso.  Basic Mechanisms of Ocular Motility and Their Clinical Implications , 1976 .

[4]  R. Carpenter,et al.  Movements of the Eyes , 1978 .

[5]  Lennart Ljung,et al.  Theory and Practice of Recursive Identification , 1983 .

[6]  Masao Ito.  The Cerebellum And Neural Control , 1984 .

[7]  Yiannis Aloimonos,et al.  Active vision , 2004, International Journal of Computer Vision.

[8]  Mitsuo Kawato,et al.  Feedback-Error-Learning Neural Network for Supervised Motor Learning , 1990 .

[9]  S. Lisberger,et al.  Visual responses of Purkinje cells in the cerebellar flocculus during smooth-pursuit eye movements in monkeys. II. Complex spikes. , 1990, Journal of neurophysiology.

[10]  S. Lisberger,et al.  Visual responses of Purkinje cells in the cerebellar flocculus during smooth-pursuit eye movements in monkeys. I. Simple spikes. , 1990, Journal of neurophysiology.

[11]  Weiping Li,et al.  Applied Nonlinear Control , 1991 .

[12]  Dana H. Ballard,et al.  Principles of animate vision , 1992, CVGIP Image Underst..

[13]  Michael Brady,et al.  Design of stereo heads , 1993 .

[14]  Atsuo Takanishi,et al.  Development of an anthropomorphic head-eye system for robot and human communication , 1995, Proceedings 4th IEEE International Workshop on Robot and Human Communication.

[15]  O. Hikosaka,et al.  Anticipatory saccades in sequential procedural learning in monkeys. , 1996, Journal of neurophysiology.

[16]  Giulio Sandini,et al.  Vergence and tracking fusing log-polar images , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[17]  Yasuo Kuniyoshi,et al.  Learning of oculo-motor control: a prelude to robotic imitation , 1996, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems. IROS '96.

[18]  A G Barto,et al.  Prediction of complex two-dimensional trajectories by a cerebellar model of smooth pursuit eye movement. , 1997, Journal of neurophysiology.

[19]  S. Lisberger,et al.  Neural Learning Rules for the Vestibulo-Ocular Reflex , 1998, The Journal of Neuroscience.

[20]  Giulio Sandini,et al.  Oculo-motor stabilization reflexes: integration of inertial and visual information , 1998, Neural Networks.

[21]  Christopher G. Atkeson,et al.  Constructive Incremental Learning from Only Local Information , 1998, Neural Computation.