In the current Leader-Follower AGVs cooperative operation, in addition to obtaining environmental information, the positioning and navigation of the following AGV also need to observe the position and attitude of the leading AGV for path tracking, which has higher requirements for accuracy and stability of navigation and location. In order to improve the navigation accuracy of following AGV, an integrated navigation method combining inertial navigation and multi-vision was proposed. Aiming at the problem of multi-sensor data fusion, an optimal pose estimation method based on adaptive unscented Kalman filter was proposed. The output signal of inertial navigation sensor was used to follow the AGV attitude prediction;the path tracking navigation and RGB-D navigation constituted the multi-vision navigation, which was used as the system observation to correct the accumulated offset of inertial navigation. The experimental results showed that the compound navigation scheme had faster convergence speed, more stable path tracking state and formation maintenance.This method improved the real-time performance and robustness of the two AGVs cooperative handling system.