The positioning accuracy of robots has an important influence on the stability and accuracy of robotic motion, which is one of the important indexes to measure the performance of robots. High-precision parameters help to improve the working efficiency of the robot. In practical engineering, some parameter ranges are difficult to obtain. This study firstly uses the Neural Networks model to describe the uncertain parameters of robots. Secondly, the uncertain parameters are considered to construct the kinematic equation of industrial robots. Thirdly, an analysis model of robots base on Neural Networks model is established. Finally, inversely find the interval of uncertain parameters. Compared with the traditional method, this method can narrow the interval of inverse parameters, making the results accurate and more practical. In the example, the effectiveness of the proposed method is verified by a six degrees of freedom robot.