For the robot trajectory planning problem, an improved Differential Evolution(DE) algorithm based on sliding mode control is proposed. The operation time and energy consumption is taken as the objective function. The direction of variation is guided by the difference between the best individuals and the average individuals in the population. Using the best individuals to replace the worst individuals in the population, the rate of convergence is accelerated. Removal of mutation factor and cross factor reduces manual intervention and enhances the stability of the model. Using piecewise Hermite interpolation of order 3 instead of spline interpolation of order 3 to prevent fitting overshoot and reduce chattering. Based on the system state space equation, a sliding mode control law was designed and stability is proved by using a Lyapunov function. Simulation experiments and the analysis of results are demonstrated that the improved algorithm not only has strong search ability but also accelerate the convergence rate and reduce the chattering effect in the trajectory planning of the system states.