Agricultural Machine Row Alignment Using Position Error Rectification
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Solution Overview
Problem
Agricultural machines face sub-optimal performance due to position errors in field data, leading to incorrect targeting of crop rows during operations like spraying and harvesting, resulting in inefficiencies and misalignment.
Innovation Solution
A computer-implemented method that obtains prior field data, collects in situ plant detection data, determines position errors, and generates control signals to correct these errors, ensuring accurate alignment and operation of agricultural machines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If prior field data is used for agricultural operations, then operational efficiency is improved, but position errors cause misalignment and sub-optimal performance
Solution Approach 1:
The system uses plant detection sensors to obtain in situ plant location data and compares it with prior field data to determine position errors. This feedback loop allows the system to identify and correct alignment deviations in real-time, ensuring that the agricultural machine operates with accurate positioning information while maintaining operational efficiency.
Solution Approach 2:
The system performs preliminary correction of field data by determining position errors using in situ plant detection data before the agricultural operation begins. This preliminary action ensures that corrected, accurate field data is available for guiding the agricultural machine, preventing misalignment issues before they occur.
2Measurement precision
If in situ plant detection is performed to correct position errors, then position accuracy is improved, but system complexity increases
Solution Approach 1:
The agricultural machine performs its own field data correction by using its onboard plant detection sensors to obtain in situ plant location data. The system self-corrects position errors by comparing detected plant locations with prior field data, eliminating the need for external correction systems and reducing overall system complexity.
Solution Approach 2:
The plant detection sensors serve multiple functions: they detect plant locations for operational guidance, provide in situ data for position error determination, and enable field data correction. This multi-functionality reduces the need for separate correction systems, thereby managing system complexity while improving position accuracy.
3Measurement precision
If real-time position error correction is implemented, then operational accuracy is improved, but data processing requirements increase
Solution Approach 1:
The system extracts only the essential information needed for correction by comparing in situ plant detection data with prior field data to determine position errors. By focusing on extracting only the relevant position error information rather than processing all raw sensor data, the system reduces data processing requirements while maintaining operational accuracy.
Data Source
AI summary
A computer-implemented method of controlling a mobile agricultural machine includes obtaining prior field data representing a position of plants in a field, obtaining in situ plant detection data from operation of the mobile agricultural machine in the field, determining a position error in the prior field data based on the in situ plant detection data, and generating a control signal that controls the mobile agricultural machine based on the determined position error.