Agricultural Vehicle Path Planning for Fewer Passes and Less Compaction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing agricultural path planning systems fail to provide a comprehensive solution for optimizing operational paths in terms of efficiency, distance, and environmental impact, lacking a systematic approach to determine optimal paths based on performance metrics.
Innovation Solution
A control system that determines a boundary for the working environment, segments it into candidate paths, evaluates performance metrics such as number of rows, overlap, and soil compaction, and selects a primary path based on these metrics to optimize agricultural operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual path planning is performed by the operator, then flexibility and adaptability to field conditions are maintained, but operational efficiency and time consumption are reduced
Solution Approach 1:
The system enables self-service by allowing the agricultural machine to automatically determine and follow optimized paths without continuous operator intervention. The control system autonomously processes field boundary data, calculates optimal paths using performance metrics, and guides the machine, thereby improving productivity while maintaining operational flexibility through automated decision-making.
2Productivity
If existing path planning systems are used, then some path suggestions are provided, but comprehensive optimization considering multiple performance metrics is not achieved
Solution Approach 1:
The system segments the field boundary into multiple boundary segments and evaluates each segment independently with respect to multiple performance metrics. This segmentation approach allows comprehensive optimization by considering different path options for each segment, enabling the system to select the optimal overall path that balances productivity improvement with manageable system complexity.
Solution Approach 2:
The system employs parameter changes by evaluating multiple performance metrics (such as path length, number of turns, overlap, and soil compaction) to determine the optimal path. By changing and comparing different metric parameters, the system achieves comprehensive path optimization that considers various operational factors simultaneously, resolving the contradiction between optimization completeness and system complexity.
3Reliability
If the number of passes is increased to cover the entire working environment, then complete coverage is achieved, but time consumption and soil compaction increase
Solution Approach 1:
The system performs preliminary action by pre-calculating the optimal path before the agricultural operation begins. By determining the boundary segments and evaluating multiple path options in advance using performance metrics, the system identifies the most efficient route that achieves complete coverage with minimal passes. This preliminary optimization reduces both operational time and soil compaction while ensuring reliability of coverage.
Solution Approach 2:
The system uses feedback mechanisms by evaluating performance metrics for each candidate path and selecting the optimal one based on comprehensive analysis. The feedback loop considers coverage completeness, time consumption, and soil compaction impacts, allowing the system to adjust and optimize the path selection to achieve complete coverage while minimizing time loss and environmental impact.
Data Source
Figure 1~2
Figure 3
Figure 4(a)~4(b)
AI summary
Systems and methods are provided for planning an agricultural operation for an agricultural machine in a working environment. This Includes determining a boundary for the working environment; determining a plurality of boundary segments for the boundary; and determining, for each of the boundary segments, a candidate operational path. A performance metric associated with the determined operational path for the boundary segment is used to select a primary boundary segment which is optimized for a given metric of the operation. Operational components associated with the agricultural machine can then be controlled based on the determined operational path, e.g. to guide the machine along the path or present the path to an operator.