In order to carry out underwater detection, an underwater robotic fish with two caudal fins is designed. Due to the uncertainties of model parameters and the disturbances of complex water waves, a dynamic model with uncertain parameter factors is established to obtain a better control effect. A radial basis function (RBF) neural network sliding mode controller is designed according to the dynamic model. The stability of the system is proved by using the Lyapunov function. The simulation results show that the designed controller is insensitive to the changes of the parameters of the dual-fin underwater robotic fish and has higher control accuracy and stronger robustness than the traditional PID controller. This method provides a reference for the design and application of fin-actuated underwater robot in the future.