Control of Pneumatic Artificial Muscles with SNN-based Cerebellar-Like Model

Soft robotics technologies have gained growing interest in recent years, which allows various applications from manufacturing to human-robot interaction. Pneumatic artificial muscle (PAM), a typical soft actuator, has been widely applied robots. The compliance and resilience of actuators allow robots behave compliant when interacting with unstructured environments, while the utilization also introduces nonlinearity uncertainty. Inspired by Cerebellum’s vital functions control human’s physical movement, neural network model Cerebellum based on spiking neuron networks (SNNs) is designed. This used as feed-forward controller controlling 1-DOF robot arm driven PAMs. simulation results show that this Cerebellar-based system achieves good performance increases system’s response speed.