Weeding Vehicle Trajectory Planning for Targeted Weed Zones
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Solution Overview
Problem
Agricultural working vehicles inefficiently navigate crop fields with distinct weed areas, leading to excessive time, fuel consumption, and machinery wear due to indiscriminate coverage rather than optimized routing.
Innovation Solution
A support system comprising a mapping unit, capacity parameter unit, and trajectory calculating unit that determines an optimized trajectory for agricultural work vehicles based on field boundaries, weed area coordinates, and vehicle capabilities, using analytical or numerical calculations to minimize operational time, fuel consumption, and non-weed area travel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If farmers cover the entire field indiscriminately to ensure all weed areas are covered, then weed coverage completeness is improved, but operational time, fuel consumption, and machinery wear increase
Solution Approach 1:
The field is segmented into distinct weed areas based on coordinate data obtained from drone surveillance or field mapping. The trajectory calculating unit divides the overall field into multiple target zones that need weeding, allowing the vehicle to focus only on these specific segments rather than covering the entire field uniformly.
Solution Approach 2:
The system performs preliminary mapping and identification of weed areas before the actual weeding operation. Coordinates of all weed locations are obtained in advance through drone overflight or field walking, enabling the trajectory to be pre-calculated and optimized before the vehicle enters the field.
2Reliability
If farmers cover the entire field indiscriminately to ensure all weed areas are covered, then weed coverage completeness is improved, but fuel consumption increases
Solution Approach 1:
The field is segmented into distinct weed areas based on coordinate data obtained from drone surveillance or field mapping. The trajectory calculating unit divides the overall field into multiple target zones that need weeding, allowing the vehicle to focus only on these specific segments rather than covering the entire field uniformly.
Solution Approach 2:
The system applies partial action by treating only the specific weed-infested areas rather than the entire field. The trajectory is optimized to pass through only those coordinate points where weeds are located, reducing unnecessary travel through clean crop areas and thereby reducing fuel consumption.
3Reliability
If farmers cover the entire field indiscriminately to ensure all weed areas are covered, then weed coverage completeness is improved, but machinery wear increases
Solution Approach 1:
The field is segmented into distinct weed areas based on coordinate data obtained from drone surveillance or field mapping. The trajectory calculating unit divides the overall field into multiple target zones that need weeding, allowing the vehicle to focus only on these specific segments rather than covering the entire field uniformly.
Solution Approach 2:
The system applies partial action by treating only the specific weed-infested areas rather than the entire field. The trajectory is optimized to pass through only those coordinate points where weeds are located, reducing unnecessary travel through clean crop areas and thereby reducing machinery wear.
4Productivity
If farmers follow an optimized trajectory through distinct weed areas, then operational efficiency is improved, but risk of missing some weed areas increases
Solution Approach 1:
The system incorporates feedback mechanisms where the actual trajectory followed by the vehicle is monitored and compared against the optimized trajectory. If deviations occur or if weed areas are missed, the system can adjust subsequent path planning to ensure complete coverage while maintaining efficiency.
Solution Approach 2:
The system performs preliminary mapping and identification of weed areas before the actual weeding operation. Coordinates of all weed locations are obtained in advance through drone overflight or field walking, enabling the trajectory to be pre-calculated and optimized before the vehicle enters the field.
Data Source
AI summary
The present disclosure relates to a support system for determining a trajectory to be followed by an agricultural work vehicle when weeding distinct areas of weed within a field of crops, the system comprising: a mapping unit configured for receiving: i) coordinates relating to the boundaries of a field to be worked; and ii) coordinates relating to the boundaries of distinct areas of weed being located within the boundary of the field of crops; a capacity parameter unit configured for receiving one or more capacity parameters relating to the working vehicle; a trajectory calculating unit configured for calculating an optimized trajectory to be followed by the work vehicle upon weeding the distinct areas of weed; wherein the optimized trajectory is being calculated on the basis of the coordinates received by the mapping unit; and one or more of the one or more capacity parameters received by the capacity parameter unit.