Autonomous Robotic Row-following Navigation Method for Ratoon-emerged Sugarcane Seedling Fields

Abstract:

It is very important to research the autonomous robotic row-following navigation method of ratoon-emerged sugarcane field robots at the seedling stage to promote the intelligent upgrading of management and protection in the seedling stage of ratoon-emerged sugarcane fields. On the basis of the research on the extraction of row-following navigation lines at the early stage of sugarcane seedlings, a row-following navigation path planning strategy was proposed based on spatio-temporal memory compensation, a light robot system was built, and an autonomous row-following navigation method for perennial sugarcane field robots at the seedling stage was established. At the optimal travel speed of 0. 2 m/s, when the set path fitting interval was 2/3 of the effective field of view, the accuracy of rowfollowing navigation was high, and the root mean square error was 4. 41 cm, indicating that the robot system exhibited robustness in image noise and seedling absence in sugarcane fields. The average frame rate of the robot system was 17.3 f/s, and the average time of logical decision-making and control was only 4. 7 ms, indicating that the vision model, navigation line extraction algorithm and autonomous "capability stack" constructed at the edge can meet the timeliness requirements of robots to quickly and autonomously row following in an unstructured sugarcane field environment.