In this paper, an algorithm in which active function is improved is proposed through analyzing the conventional BP algorithm, and different learning rates are used to increase the learning speed in each layer. The multilayer forward neural networks are used to establish the inverse kinematics models for robot manipulator by this improved BP algorithm. The simulations demonstrate that the proposed method is effective, and improves the inverse kinematics solutions for robot manipulator as compared to the conventional BP algorithm.