Motor Control of a Limb Segment Actuated by Artificial Muscles

In this article we present a biologically inspired motor control scheme based on sensory-motor interaction modalities within the Central Nervous System, and its application to the control of a single joint limb segment actuated by two pneumatic McKibben muscles. The embedded Artificial Neural Network (ANN) module's architecture, whose functioning is regulated by reinforcement learning, is similar to the connectivity of cerebellar cortex. Various biologically plausible learning schemes, which enable functional plasticity in the cerebellar cortex, are discussed. The simulation and experimental results are then reported.