A Grain Harvester Unmanned Operation System and Operation Method

Abstract

The invention provides an unmanned operation system and operation method for a grain harvester, which relate to the fields of agricultural equipment and navigation. For the reentry operation path scheme, the three-dimensional depth sensors are installed symmetrically on both sides of the harvester body, and for the circle operation path scheme, the three-dimensional depth sensors are only installed on one side of the harvester body. The three-dimensional depth sensor simultaneously obtains the information of a certain length of the stubble surface and the nearby area of ​​the stubble, and automatically advances along the stubble surface for grain harvesting operations. By calculating the height of the ear head area and the change value of the grain height in the near area of ​​stubble cutting, the judgment of the feeding amount and lodging can be realized, and the forward speed of the grain harvester and the height of the header can be automatically adjusted to realize the adaptive feeding amount and lodging unmanned harvesting operations. The system of the invention has simple structure, good stability and real-time performance, and has good adaptability to different fields, grains and the like.

Description

technical field [0001] The invention relates to the field of agricultural equipment and navigation, in particular to an unmanned operation system and operation method for a grain harvester based on three-dimensional depth vision. Background technique [0002] In recent years, agricultural machinery navigation and assisted driving technologies have developed rapidly. At the same time, in order to liberate the labor force and improve the quality of work, research on unmanned agricultural machinery has also begun to receive attention; grain harvesters are one of the most important agricultural machinery, and their autonomous driving has become the focus of research and development. The autonomous driving technology of grain harvesters still has the following deficiencies: [0003] (1) Satellite positioning based on Beidou and GPS often requires complex system components such as navigation base stations, rover stations, antennas, boards, etc., and only has the spatial coordinate...

AI Technical Summary

Problems solved by technology

[0003] (1) Satellite positioning based on Beidou and GPS often requires complex system components such as navigation base stations, rover stations, antennas, boards, etc., and only has the spatial coordinate information of the fuselage, which cannot meet the needs of unmanned autonomous operations, and Limited applicability and practical value for small and medium-sized fields;

[0004] (2) Visual navigation is mainly based on CCD cameras. In the field, the light changes greatly, there is a lot of redundant information, and the color difference between the target and the background is not prominent, and it is difficult to achieve effective extraction of crop stubble and field ridges;

[0005] (3) Lidar can only detect two-dimensional depth information, which is convenient for judging the presence or absence of obstacles in navigation, but it is difficult to judge crops, fields, etc.

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