Agricultural Machine Navigation With Row Detection and Mode Switching
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Solution Overview
Problem
Agricultural machines face challenges in navigating fields without defined crop rows or ridges, as existing technologies rely on manual steering when such features are absent, limiting automation and efficiency.
Innovation Solution
An agricultural machine equipped with an image recognition system to detect crop rows and ridges, a positioning system, and a controller that switches between automatic path travel and row-following travel based on the presence or absence of these features, allowing for precise navigation and automation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If automatic steering using positioning system is used, then automation level is improved, but it cannot operate when crop rows or ridges are absent
Solution Approach 1:
The agricultural machine is equipped with multiple travel control modes (automatic path travel and row-following travel) that can be selected based on field conditions. The image recognition system can detect both crop rows/ridges and generate paths when they are present, or rely on positioning system when they are absent, making the system universally applicable to different field types.
Solution Approach 2:
The system dynamically switches between different travel control modes based on the detection results. When crop rows or ridges are detected, row-following travel is activated; when they are not detected, automatic path travel is activated. This dynamic adaptation allows the system to maintain high automation level across various field conditions.
2Adaptability or versatility
If manual steering is used when crop rows or ridges are absent, then adaptability is improved, but automation level deteriorates
Solution Approach 1:
The image recognition system automatically determines whether crop rows or ridges are present in the field and selects the appropriate travel control mode without requiring manual intervention. The system serves itself by autonomously adapting to different field conditions, maintaining high automation level while preserving adaptability.
3Measurement precision
If image recognition system is added to detect crop rows and ridges, then row-following capability is improved, but device complexity increases
Solution Approach 1:
The image recognition system is integrated with the existing positioning system and travel control system. The controller unifiedly manages both automatic path travel and row-following travel modes, merging multiple functions into a coordinated system that achieves precise row detection while managing overall system complexity through integration.
4Adaptability or versatility
If dual travel control modes are implemented, then versatility is improved, but control system complexity increases
Solution Approach 1:
The control system dynamically selects between automatic path travel and row-following travel modes based on real-time image recognition results. This dynamic switching mechanism provides versatile travel options while managing control complexity through condition-based automation rather than parallel manual control systems.
Data Source
AI summary
An agricultural machine includes an image recognition system to detect, from an acquired image, a row region including at least one of a crop and a ridge on a ground surface of a field, a positioning system to acquire a position of the agricultural machine, traveling equipment including a wheel responsible for steering, and a controller configured or programmed to perform either one of automatic path travel in which the traveling equipment is caused to travel along a target path based on the position of the agricultural machine acquired by the positioning system, or row-following travel in which the traveling equipment is caused to travel along a row region that is detected by the image recognition system.