Agricultural Vehicle Route Planning by Boundary Segment Classification
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Solution Overview
Problem
Existing route planning for agricultural vehicles does not adequately consider the classification of boundary segments and their effects on the agricultural process, leading to potential damage to the vehicle or the environment, and inefficiencies in fuel consumption and soil compaction.
Innovation Solution
A computer-implemented method generates a recommended route for agricultural vehicles by classifying boundary segments based on their proximity to objects or areas outside the region, using sensor data and machine-learning algorithms to update the route in real-time, ensuring adherence to permissible proximities and vehicle characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the agricultural vehicle follows a traditional route planning approach without considering boundary segment classification, then the route generation is simple and quick, but the vehicle may approach dangerous boundary segments too closely causing potential damage to the vehicle or environment
Solution Approach 1:
The boundary of the agricultural region is divided into multiple segments, each classified with specific characteristics (e.g., dangerous, safe, restricted). This segmentation allows the route planning system to treat different boundary portions differently, enabling the vehicle to maintain appropriate distances from dangerous segments while optimizing the overall route efficiency.
Solution Approach 2:
Different boundary segments are assigned different quality classifications based on their characteristics. The route planning algorithm adjusts the permissible proximity dynamically according to the local quality of each segment, allowing the vehicle to approach safe segments closely while maintaining distance from dangerous ones, thus resolving the contradiction between safety and route efficiency.
2Reliability
If the route avoids all boundary segments to prevent damage, then vehicle safety is improved, but the cultivable area is reduced and fuel consumption increases
Solution Approach 1:
The system applies different safety margins and proximity constraints to different boundary segments based on their classification. Safe segments allow closer approach maximizing cultivable area, while dangerous segments enforce larger safety margins. This local differentiation resolves the contradiction by protecting the vehicle without unnecessarily reducing the cultivable area.
Solution Approach 2:
The permissible proximity parameter is dynamically adjusted based on the classification of the current boundary segment. The route planning algorithm modifies safety distance parameters locally rather than applying a uniform safety margin, enabling optimal balance between vehicle protection and area coverage.
3Adaptability or versatility
If the route is updated in real-time based on vehicle position monitoring, then route accuracy and adaptability are improved, but the system complexity and computational requirements increase
Solution Approach 1:
The system continuously monitors the vehicle's actual position and compares it with the recommended route. Based on this feedback, the system detects deviations and updates the route in real-time. This feedback mechanism enables the system to adapt to actual operating conditions while maintaining manageable complexity through established control algorithms.
Solution Approach 2:
The route is pre-calculated based on boundary segment classifications before the agricultural operation begins. This preliminary route planning provides a solid foundation that reduces the computational burden during real-time operation, where only minor adjustments based on actual position monitoring are needed, thus balancing adaptability with system complexity.
4Reliability
If the system defines permissible proximity for each boundary segment based on classification, then vehicle damage prevention is improved, but the route planning computation time increases
Solution Approach 1:
The system performs boundary segment classification and defines permissible proximity for each segment before the agricultural operation begins. This preliminary processing creates a ready-to-use framework that guides real-time route planning, reducing the computational time required during actual operations while maintaining comprehensive damage prevention coverage.
Solution Approach 2:
By dividing the boundary into classified segments with pre-defined proximity rules, the system transforms a complex continuous optimization problem into a series of simpler discrete decisions. This segmentation approach enables faster route calculation while ensuring appropriate safety distances are maintained for each segment type.
Data Source
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 the classification(s) of one or more segments of a boundary of a predetermined region in which the agricultural process is to be performed.