The article discusses a method to improve the accuracy of simultaneous localization and mapping (SLAM) systems used in autonomous driving. By incorporating semantic information, the researchers enhanced the odometry method, reducing errors and improving registration accuracy. This approach helps in detecting loop closures and constructing maps more effectively. Testing on the KITTI dataset showed that this strategy significantly boosts the system's precision.