In view of the low positioning accuracy of a single sensor and the importance of the environment map in the mobile robot positioning system, this paper proposes a mobile robot localization method based on multi-sensor fusion. Firstly, in an unknown environment, this paper respectively uses a single odometer and fused odometer and inertial measurement unit (IMU) by extended Kalman filter (EKF) algorithm to estimate the position. Experiments show that they have cumulative errors. Then, in a known environment, adaptive Monte Carlo localization (AMCL) algorithm is used to integrate odometer, IMU and lidar for positioning. The experimental results show that the method can correct the cumulative errors. Compared with the single odometer positioning and fusion positioning based on the EKF algorithm in an unknown environment, the proposed method has the average positioning error reduced by 68% and 30% respectively, which proves the effectiveness of multi-sensor fusion positioning and the importance of environment maps.