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An Ackerman mobile robot based on the open-source Robot Operating System (ROS) was developed in this research, which can be controlled by the self-designed upper computer and achieve automated handling in specific situations. The robot can use the gmapping algorithm to build a map, use LIDAR and IMU sensors to obtain information about the external environment, and locate the position and attitude of itself in real-time. When the robot receives the target point sent by the upper computer, The robot will autonomously path plan and avoid surrounding obstacles according to the target point sent by the upper computer and the external environment, complete the required tasks through deep learning, and reach the known target point. And, this paper makes improvements to the pure pursuit algorithm in the path tracking method for self-driving car. For the traditional pure pursuit algorithm, the tracking accuracy is limited by the look-ahead distance and the inability to achieve a good tracking effect, this paper proposes the dynamic look-ahead distance selection and the improved pure pursuit algorithm.
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