In the simultaneous localization and mapping (SLAM) problem, the solution accuracy of the odometry part plays a vital role in the subsequent mapping. The inertial measurement unit ( IMU) can provide valuable assistance for odometry in SLAM. Based on the consideration of the movement characteristics of the planar mobile robot and the indoor environment characteristics, proposes a laser odometry solution method based on IMU loose coupling to realize the precise positioning of the odometry part. In the first stage, the point cloud information is processed in real time during the robot movement. The ground points are segmented and key points are extracted. In the second stage, the IMU information is introduced into the Kalman filter to provide the pose prior for the inter-frame matching. In the third stage, after the filter outputs the pose estimation value, the non-linear optimization method is used to match the point cloud frames to realize the solution of the odometer movement. Experimental results show that the proposed method has good stability and accuracy in laser point cloud processing and motion solving. The offset error can be controlled within 0. 4% . This method provides powerful data guarantee for subsequent mapping.