Aiming at the problems of unsmooth and low efficiency in path planning of the indoor mobile robot, a path planning obstacle avoidance system is proposed. First, the global path is generated in the environment grid map by A* algorithm. Second, as the pose constraint, the Reeds-Shepp path set can generate the executable control instructions by extracting the key points of the path. Third, the static/dynamic obstacle is recognized by a binocular camera and avoided by a decision-making method. The experimental result shows that the generated path can meet the actual motion constraints of the mobile robot, the relative error of the obstacle depth distance is 0.03%, which meets the requirements of the robot path planning.
This topic mainly studies the navigation parameters obtained by image processing technology to achieve omnidirectional mobile AGV autonomous navigation. The camera is mounted on the bottom of the body of the AGV and captures the black tape path on the ground. Image preprocessing is performed, including image graying, improved CANNY algorithm edge detection, morphological processing, and so on. Then the Hough transform is used to detect the path of the preprocessed image. Finally, a straight line is selected to obtain the effective edge line, and the navigation deviation parameters are extracted. Experimental results show that the effectiveness of the guidance techniques in this paper has achieved the expected results.
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