Cerebellar Control of Robot Arms

with other parts of the nervous system. Nevertheless, the application of computational cerebellar models to the control of robot dynamics remains in its infant state. To date, a few applications have been realized, but limited to the control of traditional robot structures which, strictly speaking, do not require adaptive control for the tasks that are performed since their dynamic structures are relatively simple. The currently emerging family of light-weight robots (Hirzinger, G. (1996) In Proceedings of the 2nd International Conference on Advanced Robotics, Intelligent Automation, and Active Systems, Vienna, Austria ) poses a new challenge to robot control: owing to their complex dynamics, traditional methods, depending on a full analysis of the dynamics of the system, are no

[1]  W T Thach,et al.  The cerebellum and the adaptive coordination of movement. , 1992, Annual review of neuroscience.

[2]  James S. Albus,et al.  I A New Approach to Manipulator Control: The I Cerebellar Model Articulation Controller , 1975 .

[3]  Patrick van der Smagt.  Minimisation methods for training feedforward neural networks , 1994, Neural Networks.

[4]  S. Grossberg,et al.  Neural dynamics of planned arm movements: emergent invariants and speed-accuracy properties during trajectory formation. , 1988, Psychological review.

[5]  T. Bliss,et al.  A synaptic model of memory: long-term potentiation in the hippocampus , 1993, Nature.

[6]  James C. Houk,et al.  Cerebellar learning for control of a two-link arm in muscle space , 1997, Proceedings of International Conference on Robotics and Automation.

[7]  Gerd Hirzinger,et al.  Solving the Ill-Conditioning in Neural Network Learning , 1996, Neural Networks: Tricks of the Trade.

[8]  V. Lovelace-Chandler.  The Cerebellum and the Adaptive Coordination of Movement. Thach WT, Goodkin HP, Keating JG. Ann Rev Neurosci 15:403-442, 1992. , 1993 .

[9]  J. Hore,et al.  Changes in motor cortex neural discharge associated with the development of cerebellar limb ataxia. , 1988, Journal of neurophysiology.

[10]  M. Paulin.  The role of the cerebellum in motor control and perception. , 1993, Brain, behavior and evolution.

[11]  K. Kreutz-Delgado,et al.  Inverse Kinematics of Dextrous Manipulators , 1997 .

[12]  W. Singer,et al.  Long-term depression of excitatory synaptic transmission and its relationship to long-term potentiation , 1993, Trends in Neurosciences.

[13]  E. De Schutter.  A new functional role for cerebellar long-term depression. , 1997, Progress in brain research.

[14]  Stephen Grossberg,et al.  Vector associative maps: Unsupervised real-time error-based learning and control of movement trajectories , 1991, Neural Networks.

[15]  Daniel Bullock,et al.  Can artificial cerebellar models compete to control robots , 1997 .

[16]  Masao Ito,et al.  Climbing fibre induced depression of both mossy fibre responsiveness and glutamate sensitivity of cerebellar Purkinje cells , 1982, The Journal of physiology.

[17]  Masazumi Katayama,et al.  Learning Trajectory and Force Control of an Artificial Muscle Arm , 1990, NIPS.

[18]  V. Braitenberg,et al.  Morphological observations on the cerebellar cortex , 1958, The Journal of comparative neurology.

[19]  James C. Houk,et al.  A Predictive Switching Model of Cerebellar Movement Control , 1995, NIPS.

[20]  A. Barto,et al.  Models of the cerebellum and motor learning , 1996 .

[21]  Blake Hannaford,et al.  Measurement and modeling of McKibben pneumatic artificial muscles , 1996, IEEE Trans. Robotics Autom..

[22]  J. Houk.  Cooperative Control of Limb Movements by the Motor Cortex, Brainstem and , 1989 .

[23]  Henk B. Verbruggen,et al.  Semi-mechanistic modeling of chemical processes with neural networks , 1998 .

[24]  P. Flourens.  Recherches expérimentales sur les propriétés et les fonctions du système nerveux dans les animaux vertébrés , 1842 .

[25]  N. Hogan.  An organizing principle for a class of voluntary movements , 1984, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[26]  E. Schutter.  A new functional role for cerebellar long-term depression. , 1997 .

[27]  M. Kawato,et al.  The cerebellum and VOR/OKR learning models , 1992, Trends in Neurosciences.

[28]  J. Lance.  Anatomy and physiology of the cerebellum. , 1963, Bulletin of the Post-Graduate Committee in Medicine, University of Sydney.

[29]  C. Atkeson,et al.  Kinematic features of unrestrained vertical arm movements , 1985, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[30]  Douglas R. Wylie,et al.  More on climbing fiber signals and their consequence(s) , 1996 .

[31]  S. Lisberger,et al.  Neural basis for motor learning in the vestibuloocular reflex of primates. I. Changes in the responses of brain stem neurons. , 1994, Journal of neurophysiology.

[32]  Norman Desmarais.  Experiments and Observations on Electricity , 1999 .

[33]  W. Thomas Miller,et al.  Real-time application of neural networks for sensor-based control of robots with vision , 1989, IEEE Trans. Syst. Man Cybern..

[34]  Chuan Wang,et al.  On-Line Stochastic Functional Smoothing Optimization for Neural Network Training , 1998 .

[35]  M. Kawato,et al.  Multiple internal models in the cerebellum: A functional MRI study , 1998, Neuroscience Research.

[36]  Satinder Singh,et al.  Distributed Representation of Limb Motor Programs in Arrays of Adjustable Pattern Generators , 1993, Journal of Cognitive Neuroscience.

[37]  D. Marr.  A theory of cerebellar cortex , 1969, The Journal of physiology.

[38]  D. Wolpert,et al.  Is the cerebellum a smith predictor? , 1993, Journal of motor behavior.

[39]  David Willshaw,et al.  The cerebellum as a neuronal machine , 1999 .

[40]  Stephen Grossberg,et al.  Neuromuscular realization of planned arm movement trajectories , 1988, Neural Networks.

[41]  Frank H. Guenther,et al.  The Neural Dynamics Approach to Sensory-Motor Control , 1997 .

[42]  S. Tonegawa,et al.  Deficient cerebellar long-term depression and impaired motor learning in mGluR1 mutant mice , 1994, Cell.

[43]  S. Grossberg,et al.  A neural model of cerebellar learning for arm movement control: cortico-spino-cerebellar dynamics. , 1997, Learning & memory.

[44]  P. van der Smagt,et al.  The locally linear nested network for robot manipulation , 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

[45]  M. Glickstein,et al.  Cerebellar agenesis. , 1994, Brain : a journal of neurology.

[46]  James S. Albus,et al.  New Approach to Manipulator Control: The Cerebellar Model Articulation Controller (CMAC)1 , 1975 .

[47]  Andrew H. Fagg.  Using Crude Corrective Movements to Learn Accurate Motor Programs for Reaching , 1997 .

[48]  G. Hirzinger.  Towards a new robot generation for space, terrestrial and medical applications , 1996 .

[49]  W. T. Miller,et al.  CMAC: an associative neural network alternative to backpropagation , 1990, Proc. IEEE.

[50]  Erik De Schutter.  One cannot build theories of cerebellar function on shaky foundations: Induction properties of long-term depression have to be taken into account , 1996 .

[51]  Patrick van der Smagt,et al.  Analysis and control of a rubbertuator arm , 1996, Biological Cybernetics.

[52]  M. Kano,et al.  Long-lasting potentiation of GABAergic inhibitory synaptic transmission in cerebellar purkinje cells : Its properties and possible mechanisms , 1996 .

[53]  J. Albus.  A Theory of Cerebellar Function , 1971 .

[54]  S. Lisberger.  Neural basis for motor learning in the vestibuloocular reflex of primates. III. Computational and behavioral analysis of the sites of learning. , 1994, Journal of neurophysiology.

[55]  S. Lisberger,et al.  Neural basis for motor learning in the vestibuloocular reflex of primates. II. Changes in the responses of horizontal gaze velocity Purkinje cells in the cerebellar flocculus and ventral paraflocculus. , 1994, Journal of neurophysiology.

[56]  Dean V. Buonomano,et al.  Neural Network Model of the Cerebellum: Temporal Discrimination and the Timing of Motor Responses , 1999, Neural Computation.

[57]  Daniel Bullock,et al.  Chapter 11 Vite and Flete: Neural Modules for Trajectory Formation and Postural Control , 1989 .

[58]  W. Thomas Miller,et al.  Dynamic Balance of a Biped Walking Robot , 1997 .

[59]  Michael Lang,et al.  A real-time implementation of a neural-network controller for industrial robotics , 1998 .

[60]  V. Braitenberg.  Functional Interpretation of Cerebellar Histology , 1961, Nature.

[61]  Michael G. Paulin,et al.  A Kalman filter theory of the cerebellum , 1988 .

[62]  José L. Contreras-Vidal,et al.  Navite: A Neural Network System For Sensory-Based Robot Navigation , 1993 .

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