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In order to achieve efficient autonomous operation for soil parameter detection in the wide-row planting environment of fruits and vegetables, the structure and control circuit of the soil drilling module and the detection sensor movement module for the multi-parameter soil detection robot were designed according to the requirements of automated soil testing tasks, and it was equipped with a visual navigation module. The visual navigation control module used the lightweight segmentation model DS-U2Net for path recognition, extracted the region of interest from the segmented path, acquired the left and right boundary points to calculate the middle navigation point, and then fit the navigation line by using the least squares method. Combined with the real-time acquisition of the robot’s heading angle, the PID algorithm was applied for accurate walking navigation control. Experiments showed that the DS-U2Net model had only 6.5×10 5 parameters, with a recognition frame rate of 63.17 frames per second, an average accuracy of 94.68% , and an F1 score of 89.87% , demonstrating good real-time performance and accuracy. With no initial position deviation, the average error at different speeds was no more than 0.074 m, with a standard error of no more than 0.044 m. With initial position deviation, the average error was no more than 0.085 m, with a standard error of no more than 0.088 m. The soil drilling and detection sensor movement module operated stably, which was capable of drilling and loosening soil at different depths and detecting parameters. The research results can provide a technical solution for autonomous soil detection in the planting environment of fruits and vegetables.