A cut-edge detection method based on machine vision was developed for obtaining the navigation path of a combine harvester. First, the Cr component in the YCbCr color model was selected as the grayscale feature factor. Then, by detecting the end of the crop row, judging the target demarcation and getting the feature points, the region of interest (ROI) was automatically gained. Subsequently, the vertical projection was applied to reduce the noise. All the points in the ROI were calculated, and a dividing point was found in each row. The hierarchical clustering method was used to extract the outliers. At last, the polynomial fitting method was used to acquire the straight or curved cut-edge. The results gained from the samples showed that the average error for locating the cut-edge was 2.84 cm. The method was capable of providing support for the automatic navigation of a combine harvester.

An automatic navigation system was developed to realize automatic driving for combine harvester, including the mechanical design, control method and software design. First of all, for the harvester modified with the automatic navigation system, a dynamic calibration method of the rear wheel center position was proposed. The control part included the navigation controller and the steering controller. A variable universe fuzzy controller was designed to the navigation controller, which used fuzzy control to change the fuzzy universe of input and output dynamically, that means, under the condition that the fuzzy rules remain unchanged, the fuzzy universe changes with the change of input, which is an adaptive fuzzy control method and can modify the control strategy in time. To realize the automatic navigation of the harvester, the decision result of the navigation controller based on the variable universe fuzzy control was input into the steering controller, and then the electric steering wheel was controlled to rotate. To test the performance of the designed automatic navigation system, the experiments were carried out. When the combine harvester was navigating linearly at a speed of 0.8 m/s, the overall root mean square error (RMSE) of the lateral deviation was 5.87 cm. The test results showed that the system was designed could make the combine track the preset path smoothly and stably, and the tracking accuracy was at the centimeter level. Keywords: automatic navigation system, combine harvester, GNSS, development, dynamic calibration, variable universe adaptive fuzzy control DOI: 10.25165/j.ijabe.20211405.6596 Citation: Li S C, Zhang M, Cao R Y, Ji Y H, Zhang Z Q, Li H, et al. Development of the automatic navigation system for combine harvester based on GNSS. Int J Agric & Biol Eng, 2021; 14(5): 163–171.