For the mobile robot with dynamic uncertain modeling,modeling error and external disturbance,a computed torque control algorithm with RBF (radial basis function) neural network compensation was designed.The kinematic auxiliary speed control algorithm was designed based on the backstepping method.According to the dynamic ideal nominal model,a general torque controller was designed based on the computed torque method.On this basis,a dynamic model of the mobile robot with uncertain modeling,modeling error and external disturbance was established.The torque controller with RBF neural network compensation controller was designed based on the computed torque method.The weights of the neural network were given by the adaptive law.Finally,the stability of the system was proved by using Lyapunov theory.The simulation results show that neural network has good approximation performance for system uncertainty,compared with general computed torque control,the proposed computed torque control algorithm with RBF neural network compensation has better tracking performance,and the control system has better robustness.