Image-Based Harvester Control for Real-Time Yield Adjustment
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Solution Overview
Problem
Existing self-driving agricultural work machines struggle to help drivers, especially inexperienced ones, achieve optimal yield in new or unknown situations, as the current display of yield indicators does not provide sufficient guidance.
Innovation Solution
The implementation of a camera-based system that uses a setting device to determine the proportion of harvest culture in a digital image, allowing for the adjustment of employment units and driving speed of the self-driving agricultural machine to optimize yield.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a camera-based system with image analysis is implemented to determine crop proportion and automatically adjust working units and driving speed, then yield optimization and ease of operation are improved, but device complexity increases
Solution Approach 1:
The system enables the agricultural machine to automatically adjust its own working units and driving speed based on real-time image analysis of crop conditions. The control unit processes camera images to determine crop proportion and autonomously modifies operational parameters without requiring manual driver intervention, allowing the machine to serve itself in optimizing harvest operations
Solution Approach 2:
The patent replaces manual mechanical control by the driver with an automated optical-electronic control system. Instead of relying on human visual assessment and manual adjustments, the system uses a camera to capture images, a control unit to analyze crop proportion through image processing, and automated actuators to adjust working units and speed, substituting the mechanical driver-operated control system with an automated vision-based control system
2Productivity
If real-time image analysis and automatic adjustment systems are implemented, then productivity and yield optimization are improved, but device complexity and energy consumption increase
Solution Approach 1:
The system performs preliminary analysis of crop conditions using image capture and processing before the harvesting action occurs. The control unit determines crop proportion in advance based on captured images and pre-adjusts working units and driving speed to optimal settings before entering new field areas, enabling proactive optimization rather than reactive adjustments
Solution Approach 2:
The system establishes a closed-loop feedback mechanism where the camera continuously captures images of the crop, the control unit analyzes the images to determine current crop proportion, and based on this feedback information, automatically adjusts working units and driving speed. This continuous monitor-adjust cycle ensures the system responds to changing field conditions in real-time, maintaining optimal productivity
Data Source
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AI summary
The present invention relates to a self-propelled agricultural machine (1) with working units (8) for picking up, processing, and conveying harvested crops (3) from a crop stand (2) of an agricultural field (35), and with a drive motor (6) for driving the working units (8) and for propelling the self-propelled agricultural machine (1) at a travel speed along the agricultural field (35), and with a camera device (21) for capturing a digital image (21a) of the crop stand (2) of the agricultural field (35) in the vicinity of the self-propelled agricultural machine (1). The present invention is based on the general concept that the existing proportion of harvested crops (3) is determined in the digital image (21a) in order to optimally adjust the self-propelled agricultural machine (1) based on this.