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Manipulator inverse trajectory which means to solve the joint variable by the end of the mechanical arm position is mainly used in the accurate location and trajectory planning of the end executor. How to efficiently solve the inverse solution of kinematics of robotic is the difficulty. In view of the traditional algorithm of robot arm inverse kinematics is complex and there are multiple solutions, this paper proposes a mechanical arm inverse kinematics method based on BP neural network. With four degrees of freedom mechanical arm as the research object, analyses its kinematics principle, on the basis of improving the BP neural network algorithm, the mechanical arm are simulated and modeled by using MATLAB toolbox. The results show that using BP neural network model to solve inverse kinematics which avoids the disadvantages of traditional methods is simple in design and precision; it is a feasible manipulator inverse kinematics solution.