Name
Title | ||
|---|---|---|
Cerebellar-inspired adaptive control of a robot eye actuated by pneumatic artificial muscles. |
Abstract | ||
|---|---|---|
In this paper, a model of cerebellar function is implemented and evaluated in the control of a robot eye actuated by pneumatic artificial muscles. The investigated control problem is stabilization of the visual image in response to disturbances. This is analogous to the vestibuloocular reflex (VOR) in humans. The cerebellar model is structurally based on the adaptive filter, and the learning rule is computationally analogous to least-mean squares, where parameter adaptation at the parallel fiber/Purkinje cell synapse is driven by the correlation of the sensory error signal (carried by the climbing fiber) and the motor command signal. Convergence of the algorithm is first analyzed in simulation on a model of the robot and then tested online in both one and two degrees of freedom. The results show that this model of neural function successfully works on a real-world problem, providing empirical evidence for validating: 1) the generic cerebellar learning algorithm; 2) the function of the cerebellum in the VOR; and 3) the signal transmission between functional neural components of the VOR. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/TSMCB.2009.2018138 | IEEE Transactions on Systems, Man, and Cybernetics, Part B |
Keywords | Field | DocType |
motor command signal,cerebellar function,parallel fiber,cerebellar model,sensory error signal,functional neural component,control problem,cerebellar-inspired adaptive control,generic cerebellar,robot eye,signal transmission,neural function,pneumatic artificial muscle,vestibuloocular reflex,concurrent computing,arm,stability,biomimetics,empirical evidence,movements,plasticity,least mean square,adaptive control,adaptive filters,systems,least mean squares,muscle,neurorobotics,adaptive filter,convergence,neuroscience,pneumatic actuators,robot control | Neurorobotics,Robot control,Pneumatic actuator,Control theory,Computer science,Learning rule,Adaptive filter,Pneumatic artificial muscles,Parallel fiber,Adaptive control | Journal |
Volume | Issue | ISSN |
39 | 6 | 1941-0492 |
Citations | PageRank | References |
21 | 1.41 | 17 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alexander Lenz | 1 | 75 | 6.52 |
| Sean R. Anderson | 2 | 89 | 14.87 |
| A. G. Pipe | 3 | 90 | 6.73 |
| Chris Melhuish | 4 | 747 | 87.61 |
| Paul Dean | 5 | 93 | 10.90 |
| John Porrill | 6 | 352 | 85.11 |