The aim of this paper is solving the problem of an autonomous mobile robot indoor trajectory tracking based on Simultaneous Location And Mapping (SLAM) technique. Faced with the high-cost experiment equipment, this paper introduces a solution via lower-cost hardware. In addition, the system improves mobile robot tracking rate of accuracy by an adaptive controller. Therefore, it can help to rapid development for self-driving industry regarding cost-effectiveness. Similar with a human driver, the adaptive controller optimizes the mobile robot movement based on Lyapunov direct method. In addition, the controller implementation task was finished on a practical low-cost mobile robot, Turtlebot2. In future, the research will focus on a path-planning algorithm when the mobile robot moving on the way and facing with coming obstacles. This technology can be applied to the self-driving car in industry, and improves the feasibility of outdoor automatic logistics.