Agricultural Row-Following Control Using Safe Image Recognition
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Solution Overview
Problem
Agricultural machines face challenges in accurately determining row regions for automatic steering to avoid damaging crops, as existing systems struggle to ensure high positional accuracy and prevent wheels from contacting crop rows or ridges during row-following travel.
Innovation Solution
The implementation of an image recognition system that detects crop rows or ridges on a field surface using an imaging device and a processing device, which determines the relative position of these features with high accuracy and controls the agricultural machine's wheels to travel along the detected row regions only if it is safe to do so, preventing damage by assessing the feasibility of row-following travel based on the detected positions and orientations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automatic steering using image recognition is implemented, then productivity and operational efficiency are improved, but the risk of wheel contact with crop rows or ridges increases due to insufficient positional accuracy
Solution Approach 1:
The patent introduces an intermediary assessment mechanism between image recognition detection and automatic steering execution. The controller evaluates multiple factors including detected row/ridge positions, agricultural machine posture, and terrain conditions before authorizing row-following travel. This intermediary layer ensures high positional accuracy by validating safety conditions before enabling automatic steering, thus resolving the contradiction between productivity improvement and reliability maintenance.
2Ease of operation
If row-following travel is enabled based on image recognition, then ease of operation is improved, but crop damage risk increases due to inaccurate detection of row regions
Solution Approach 1:
The patent implements preliminary action by requiring the controller to assess and validate row region detection accuracy, agricultural machine posture, and terrain conditions before enabling row-following travel. The system performs preliminary safety checks including verifying that wheels will not contact crop rows or ridges, and only then allows automatic steering to operate. This preliminary validation eliminates crop damage risk while maintaining ease of operation.
Solution Approach 2:
The system continuously monitors detected row/ridge positions, agricultural machine posture, and terrain conditions, providing real-time feedback to the controller. This feedback mechanism allows dynamic adjustment of automatic steering operation, ensuring crop protection while maintaining operational ease. The controller uses this feedback to determine whether row-following travel should be enabled or disabled at any given moment.
3Object-affected harmful factors
If the system restricts row-following travel to prevent wheel contact, then crop protection is improved, but ease of operation deteriorates due to limited automatic steering availability
Solution Approach 1:
The patent applies dynamics by making automatic steering availability conditional rather than fixed. The controller dynamically enables or disables row-following travel based on real-time assessment of detected row/ridge positions, agricultural machine posture, and terrain conditions. This dynamic approach maximizes automatic steering availability when conditions permit while ensuring crop protection when risks are present, thus resolving the contradiction between crop protection and operational ease.
Data Source
AI summary
An agricultural machine includes an image recognition system to detect a row region including at least one of a crop and a ridge on a ground surface of a field, traveling equipment including a wheel responsible for steering, a controller configured or programmed to control the traveling equipment, and a start switch to give a command to start row-following travel where the controller is configured or programmed to control the traveling equipment to travel along the row region as detected by the image recognition system.