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Aiming at the problem that the current robot motion control system can not achieve accurate control due to the small adjustment of motion data, which leads to large trajectory error and low efficiency of motion control, an intelligent detection robot motion control system based on big data clustering is designed. TMS320LF2407A main control chip and 650V power transistor are used to work in intermittent mode of inductor current to provide system driving energy, set optocoupler, process control signal emission and adjust internal current relationship of control circuit. The 6ES7214-1AG40-0XB0 controller and the signal and communication module are used to control the trajectory of the robot. Combined with the internal driving device, the motion data information is integrated for storage, and the hardware structure of the motion control system is designed. By adjusting the program start data, combined with the internal pulse data, the software platform management module is constructed to obtain the robot trajectory data. Using big data clustering technology, the control system big data distribution structure model is established to simulate nonlinear time-varying LFM control signal, feature extraction and clustering motion trajectory data to obtain accurate motion trajectory data, reduce the degree of motion trajectory deviation, and complete the motion control system software design. The experimental results show that the motion trajectory error of the motion control system based on big data clustering is small, which can effectively achieve accurate control and improve the efficiency of motion control.