Predictive Crop Map for Harvester Header Control
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Solution Overview
Problem
Agricultural harvesters face performance degradation when operating in areas with varying crop states, such as downed crops, due to the need for adjusted machine settings, which can lead to inefficiencies and grain loss if not managed effectively.
Innovation Solution
The use of in-situ sensors and predictive mapping technology to generate functional predictive maps that anticipate crop states, allowing for real-time adjustments in machine settings and operation, such as header height and direction, to optimize harvesting in diverse crop conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the agricultural harvester operates in areas with varying crop states, then the harvesting coverage is maintained, but the harvesting efficiency and grain loss reduction deteriorate due to the need for frequent machine setting adjustments
Solution Approach 1:
The system performs preliminary sensing of crop state conditions ahead of the harvester's path using forward-looking sensors. This advance detection allows the control system to pre-adjust machine settings (header height, reel speed, cutter bar position) before entering areas with downed or varying crop, eliminating the need for frequent manual adjustments and maintaining harvesting efficiency across diverse field conditions
Solution Approach 2:
The system continuously monitors crop state using in-situ sensors and feeds this information back to the control system. The feedback loop enables real-time automatic adjustment of harvesting parameters based on actual crop conditions, resolving the contradiction by making the system responsive to varying crop states without requiring operator intervention
2Loss of substance
If the agricultural harvester uses manual machine setting adjustments for downed crops, then the grain loss is reduced, but the productivity and harvesting speed deteriorate due to operational interruptions
Solution Approach 1:
The harvester system performs self-adjustment of its harvesting parameters through automated control based on sensor input. The system independently detects crop state variations and automatically modifies header height, reel speed, and other settings without operator intervention, thereby reducing grain loss while maintaining continuous operation and harvesting speed
Solution Approach 2:
The system replaces manual mechanical adjustment operations with automated sensor-based control. Electronic sensors detect crop conditions and trigger automatic mechanical adjustments via actuators, eliminating the need for operators to stop and manually adjust settings, thus preserving both grain recovery and harvesting productivity
3Adaptability or versatility
If the agricultural harvester operates without predictive mapping, then the device complexity is reduced, but the adaptability to varying crop states and path planning capability deteriorate
Solution Approach 1:
The system creates predictive maps of crop state conditions ahead of the harvester's current position using forward-looking sensors and historical data. This preliminary mapping allows the control system to plan the optimal harvesting path in advance, adapting to varying crop states without requiring complex real-time decision-making, thus balancing adaptability with manageable system complexity
Data Source
AI summary
One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.