Self-Balance Control of Two-Wheeled Robot Based on Skinner´s Operant Conditioning

Aiming at the movement balance problem of the two-wheeled robot, the operant conditioning theory of artificial cerebellar sensorimotor systems is used, and the theory adopts a learning mechanisms of Skinner´s operation conditioned based on the learning algorithm of recurrent neural network, through learning and training, the two-wheeled robot can obtain the skills of movement balance control like a robot or animal in the process of gradually forming, developing and improving by self-organization. The simulation results show that the Skinner´s operation conditioning has such a virtue of stronger self-learning ability and higher robustness.