In order to explore the adaptive control process of automated production line, this paper designs the machine adaptive visual guidance system. After that, the omnidirectional motion of the automated production line is controlled on the principle of AGV kinematics, and the position of the AGV is adjusted by the fuzzy adaptive PID control method, which ensures that the precise control of the automated production line can be realized in the dynamically changing environment. The simulation results show that the fuzzy adaptive PID controller performs better. The motion deviation of the automated production line motion control system in X and Y directions is between ±0.016mm-0.017mm. In addition, this paper found that the shape of the visual data points and the concave and convex curves can be perfectly visualized by the Akima curves, which can control the error between the fitted points and the theoretical points at the same X coordinates extremely well, and the maximum error and the average error can be controlled within 0.114mm and 0.0287mm. Even if the constraints of path length and motion speed are increased, the model can maintain the optimal feed speed in a shorter time, which makes the speed planning curve more perfect.