Agricultural Vehicle Route Planning Using Tramline Center Lines
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Solution Overview
Problem
Existing agricultural route planning techniques fail to efficiently utilize tramline information for optimizing vehicle paths, leading to inefficiencies in fuel consumption and soil compaction, and lack adaptive mechanisms to correct deviations during agricultural processes.
Innovation Solution
A computer-implemented method generates a recommended route for agricultural vehicles using boundary and tramline information, including center lines and connecting segments, and updates the route in real-time to adapt to deviations, utilizing machine learning and position monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If traditional route planning techniques are used, then route generation is simple, but fuel consumption increases and soil compaction worsens
Solution Approach 1:
The system performs preliminary actions by obtaining tramline information from previous agricultural operations and generating center lines in advance. This pre-processing of spatial data enables optimized route planning that minimizes fuel consumption and soil compaction without requiring complex real-time calculations during vehicle operation.
Solution Approach 2:
The system creates a digital copy of the physical field structure by generating center lines that represent the optimal paths through the field. These center lines are derived from tramline information, creating an abstract geometric model that guides the agricultural vehicle along fuel-efficient routes while avoiding soil compaction issues.
2Object-affected harmful factors
If traditional route planning techniques are used, then route generation is simple, but soil compaction increases
Solution Approach 1:
The system performs preliminary actions by obtaining tramline information from previous agricultural operations and generating center lines in advance. This pre-processing of spatial data enables optimized route planning that minimizes fuel consumption and soil compaction without requiring complex real-time calculations during vehicle operation.
Solution Approach 2:
The system creates a digital copy of the physical field structure by generating center lines that represent the optimal paths through the field. These center lines are derived from tramline information, creating an abstract geometric model that guides the agricultural vehicle along fuel-efficient routes while avoiding soil compaction issues.
3Measurement precision
If real-time route updating is implemented, then route adherence precision improves, but system complexity increases
Solution Approach 1:
The system implements feedback by continuously monitoring the agricultural vehicle's actual position and comparing it to the recommended center line route. When deviations are detected, the system provides guidance corrections to steer the vehicle back onto the optimal path, ensuring precise route adherence while maintaining manageable system complexity through incremental adjustments.
Data Source
Figure 1
Figure 2A~2B
Figure 2C~2D
AI summary
A mechanism for generating a recommended route for an agricultural vehicle in advance of performing an agricultural process. The mechanism further includes tracking adherence of the agricultural vehicle to the recommended route and/or controlling the vehicle to follow the recommended route. The recommended route is generated responsive to at least boundary information and a plurality of center lines generated based on identified pairs of parallel tramlines.