Agricultural Field Planning System with Edge Detection
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Solution Overview
Problem
Existing agricultural working machine route planning systems do not allow operators to directly influence the configuration of route plans based on field-specific data, limiting the ability to generate optimized processing routes and headland areas.
Innovation Solution
A planning system with a data processing unit that generates and processes field-specific data using an edge detection algorithm to derive reference objects, which can be selected by operators for creating processing plans, allowing for more precise and efficient route planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated algorithms generate route plans without operator input, then planning speed is improved, but the ability to incorporate field-specific data and operator expertise deteriorates
Solution Approach 1:
The system dynamically adjusts the level of automation based on operator needs, allowing switching between fully automated algorithmic planning and interactive planning where operators can select and modify reference objects. This dynamic adaptability resolves the contradiction by making the system flexible enough to handle both speed-critical and precision-critical scenarios.
Solution Approach 2:
The system incorporates feedback loops where operators can review, select, and modify reference objects generated by algorithms. This feedback mechanism allows operator expertise to correct and refine automated outputs, ensuring field-specific data is properly incorporated while maintaining the speed benefits of automated initial planning.
2Measurement precision
If operators manually select all input parameters, then planning accuracy is improved, but the complexity and time required for data processing increases
Solution Approach 1:
The system performs preliminary automated generation of reference objects (such as potential route lines and headland areas) before operator selection. This preliminary action reduces the complexity of manual data processing by pre-processing the field data into manageable reference objects that operators can easily review and select from, rather than requiring operators to process raw field data from scratch.
Solution Approach 2:
The system segments the complex field data into discrete reference objects (individual route lines, headland areas, etc.) that can be independently selected and evaluated by operators. This segmentation simplifies the operator's task by breaking down complex data processing into manageable discrete decisions, maintaining accuracy while reducing overall complexity.
3Productivity
If comprehensive field data is processed automatically, then route optimization is improved, but the time and computational resources required increase
Solution Approach 1:
The system implements partial automated processing by generating a limited set of high-quality reference objects that are most likely to be useful, rather than exhaustively processing all possible route combinations. This partial action approach achieves sufficient route optimization quality while significantly reducing the computational time and resources required compared to complete automated analysis.
Solution Approach 2:
The system allows dynamic adjustment of processing parameters such as the number of reference objects generated, the level of detail in field data analysis, and the optimization criteria. By changing these parameters, the system can balance route optimization quality against processing time requirements based on specific operational needs, resolving the contradiction between comprehensive optimization and time efficiency.
Data Source
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AI summary
A planning system for the, in particular interactive, planning of field cultivation for an agricultural machine comprises, in addition to a display unit, a data processing unit for processing field-specific data. According to the invention, the planning system is configured and designed to generate field-specific data and/or import predefined field-specific data into the data processing unit, to derive at least one reference object from the field-specific data using an algorithm stored in the data processing unit, to display at least one reference object on a display unit, wherein at least one reference object can be selected as input information for planning the field cultivation by an operator of the planning system, and based on the at least one selected reference object, a cultivation plan for the agricultural machine is generated.This enables a simplified generation of input information for creating a processing plan for a field based on field-specific data.