Habituation rules for a theory of the cerebellar cortex
Biological Cybernetics
On the adaptive control of robot manipulators
International Journal of Robotics Research
A dynamical system view of cerebellar function
CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Foundations of robotics: analysis and control
Foundations of robotics: analysis and control
An adaptive sensorimotor network inspired by the anatomy and physiology of the cerebellum
Neural networks for control
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
A comparison of five algorithms for the training of CMAC memories for learning control systems
Automatica (Journal of IFAC)
Neurofuzzy adaptive modelling and control
Neurofuzzy adaptive modelling and control
Multiple paired forward and inverse models for motor control
Neural Networks - Special issue on neural control and robotics: biology and technology
Neural network based control schemes for flexible-link manipulators: simulations and experiments
Neural Networks - Special issue on neural control and robotics: biology and technology
The handbook of brain theory and neural networks
A cerebellar model of timing and prediction in the control of reaching
Neural Computation
Robot Evolution: The Development of Anthrobotics
Robot Evolution: The Development of Anthrobotics
Towards a new Robot Generation
Proceedings of the 5th International Symposium on Experimental Robotics V
A Model of Cerebellar Learning for Control of Arm Movements Using Muscle Synergies
CIRA '97 Proceedings of the 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation
Dynamic Programming
A real-time implementation of a neural-network controller for industrial robotics
A real-time implementation of a neural-network controller for industrial robotics
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Decades of research into the structure and function of the cerebellum have led to a clear understanding of many of its cells, as well as how learning might take place. Furthermore, there are many theories on what signals the cerebellum operates on, and how it works in concert 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, few applications have been realized.The currently emerging family of light-weight robots (Hirzinger, in iProc. Second ecpd Int. Conference on Advanced Robotics, Intelligent Automation and Active Systems, 1996) poses a new challenge to robot control: due to their complex dynamics traditional methods, depending on a full analysis of the dynamics of the system, are no longer applicable since the joints influence each other dynamics during movement. Can artificial cerebellar models compete here?