Field Boundary Mapping for Obstruction-Aware Farming Paths
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Solution Overview
Problem
Conventional farming machine operations rely on outdated images of fields, which may not accurately represent the current layout, leading to potential damage and delays due to unaccounted obstructions, and the tolerance stack-up of image-based path planning results in imprecise navigation.
Innovation Solution
A farming machine management system uses a data collection device to travel along a suggested route, collecting location data with GPS and labeling obstructions, which are used to update field boundaries, and a verification device confirms these boundaries for precise path planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If path planning is generated based on outdated satellite images, then path planning can be performed, but the path may not be accurate due to unaccounted obstructions and layout changes
Solution Approach 1:
The system performs preliminary field boundary identification and obstruction detection before generating the farming path. A data collection device traverses the field perimeter to collect location data and identify obstructions in advance, so that the path planning is based on current field conditions rather than outdated satellite images
Solution Approach 2:
The system collects feedback data from the actual field conditions by having a data collection device traverse the field and report back on obstructions and boundary conditions. This feedback loop allows the path planning system to update its understanding of the field layout and generate accurate paths based on real-time information
2Productivity
If farming machines operate without real-time field boundary information, then operations can proceed, but machines may collide with obstructions causing damage or delays
Solution Approach 1:
The system identifies field boundaries and obstructions before farming operations begin. A data collection device traverses the field perimeter to map the current layout, so that farming machines can operate with knowledge of safe zones and avoid collisions with obstructions
Solution Approach 2:
The system takes preliminary action to prevent harmful collisions by identifying obstructions and establishing safe operating boundaries before farming machines enter the field. The path planning system uses this information to generate paths that avoid potential collision zones
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
Ensures safe and efficient farming operations by accurately identifying current field boundaries, avoiding obstructions, and optimizing path planning based on real-time field conditions.
Implementation Method 1
The data collection device may collect location data that tracks the motion of the data collection device using the global positioning system (GPS).
Data Source
AI summary
A system and a method are disclosed for planning a path within a field for a farming machine. The system predicts boundaries of the field using a previously captured image of the field and generates a suggested route to be taken by a data collection device based on the predicted boundaries. As the data collection device travels along the suggested route, the data collection device collects location data associated with a current layout of the field. The location data may be labeled with obstructions encountered along the way. Based on the location data, the system identifies current boundaries of the field, which may be different from the predicted boundaries. The current boundaries are sent to a verification device to be verified. After the current boundaries have been verified, the path for the farming machine is planned.