Journal article
A Combination of Machine Learning and Cerebellar-like Neural Networks for the Motor Control and Motor Learning of the Fable Modular Robot
Department of Electrical Engineering, Technical University of Denmark1
Automation and Control, Department of Electrical Engineering, Technical University of Denmark2
Centre for Playware, Centers, Technical University of Denmark3
Copenhagen Center for Health Technology, Centers, Technical University of Denmark4
We scaled up a bio-inspired control architecture for the motor control and motor learning of a real modular robot. In our approach, the Locally Weighted Projection Regression algorithm (LWPR) and a cerebellar microcircuit coexist, in the form of a Unit Learning Machine. The LWPR algorithm optimizes the input space and learns the internal model of a single robot module to command the robot to follow a desired trajectory with its end-effector.
The cerebellar-like microcircuit refines the LWPR output delivering corrective commands. We contrasted distinct cerebellar-like circuits including analytical models and spiking models implemented on the SpiNNaker platform, showing promising performance and robustness results.
Language: | English |
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Year: | 2017 |
Pages: | 62-66 |
ISSN: | 23526386 and 24059021 |
Types: | Journal article |
ORCIDs: | Baira Ojeda, Ismael , Tolu, Silvia , Christensen, David Johan and Lund, Henrik Hautop |