Agricultural Field Path Planning with End-of-Swath Row Detection
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Solution Overview
Problem
Existing path planning methods for agricultural fields face challenges in accurately defining paths with limited sensor range, especially when detecting rows that are partially or completely outside the sensor's range, leading to incomplete or inaccurate field path plans.
Innovation Solution
A method utilizing a sensor unit mounted on an agricultural vehicle to detect row ends, determine path segments, and adjust for missing segments by analyzing distances and orders of path segments, with the aid of machine learning or neuronal networks, to create a comprehensive field path plan that accounts for row orientations and obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a sensor unit with limited sensing range is used to detect rows in an agricultural field, then the device complexity is reduced, but the measurement precision and completeness of row detection deteriorates
Solution Approach 1:
The system performs preliminary detection of row ends by moving the sensor unit along the field boundaries before generating the complete path plan. This preliminary action allows the limited-range sensor to capture critical endpoint information that defines the paths, compensating for its inability to detect entire rows at once.
Solution Approach 2:
The detection process is segmented into detecting first ends of rows at a first edge and second ends of rows at a second edge. The control unit then segments the path planning into first path segments matching first ends and second path segments matching second ends, allowing the limited sensor to contribute to complete path definition through partial observations.
2Productivity
If the sensor unit moves along the field boundary to detect row ends, then the productivity of path planning is improved, but the risk of missing rows that are completely outside sensing range increases
Solution Approach 1:
The control unit uses feedback from detecting the number of first path segments and second path segments to identify and correct missing detections. When the numbers do not match, the system infers missing rows and generates additional path segments, ensuring reliable and complete path planning despite sensor limitations.
Solution Approach 2:
The system performs excessive detection actions by measuring distances between multiple path segments and comparing them against expected row spacing. This partial redundancy allows the system to infer missing rows through distance analysis, compensating for the sensor's limited range and ensuring complete path coverage.
3Reliability
If additional path segments are added to compensate for missing row detections, then the completeness of the field path plan is improved, but the device complexity and processing requirements increase
Solution Approach 1:
The control unit changes parameters by measuring distances between path segments and comparing them against expected row spacing parameters. This parameter-based approach allows the system to automatically infer missing rows through simple distance comparisons rather than complex image processing or additional sensing, maintaining relatively simple device architecture while improving path plan completeness.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables the creation of accurate and complete field path plans by detecting row ends and adjusting for missing segments, ensuring efficient navigation and minimizing disturbance to the agricultural field, even with limited sensor range.
Implementation Method 1
moving a sensor unit having a limited sensing range in the agricultural field for detecting rows
Implementation Method 2
The sensor unit may comprise a camera, a LIDAR, a radar or any other device capable to detect rows in an agricultural field
Implementation Method 3
The sensor unit may comprise a camera, a LIDAR, a radar or any other device capable to detect rows in an agricultural field
Data Source
AI summary
A method for path planning for an agricultural field having rows contains steps for moving a sensor unit having a limited sensing range in the agricultural field for detecting rows, detecting first ends of rows located at a first edge of the agricultural field, detecting second ends of rows located at a second edge of the agricultural field, determining first path segments each matching with a first end and determining second path segments each matching with a second end, and a vehicle with a control unit configured to carry out the method.