Sensor-Guided Weed Removal Paths Around Crop Rows
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Solution Overview
Problem
Conventional mechanical weeding systems disrupt soil and crop plants, are inefficient, and fail to adapt to natural variations in crop plant sizes and spacings, leading to potential damage and high energy consumption.
Innovation Solution
An automated agricultural weed removal system that uses oscillating and linear travel paths for weed removal tools, adjusted by sensors and AI/ML, to minimize soil disturbance and adapt to crop plant variations, reducing mechanical stress and energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional mechanical weeding systems use rapid side to side movement to remove weeds, then weed removal effectiveness is improved, but soil disturbance increases and crop plants may be damaged
Solution Approach 1:
The system dynamically adjusts the implement tool trajectory in real-time based on detected crop plant positions and sizes. The trajectory is not fixed but adapts continuously to the actual field conditions, allowing the implement to follow an optimized path that removes weeds while avoiding crop plants and minimizing soil disturbance.
Solution Approach 2:
The system uses sensors to detect crop plant positions and sizes, processes this information through image processing or machine learning algorithms, and uses the results to adjust the implement tool trajectory. This closed-loop feedback system ensures that the weeding operation adapts to natural variations in crop plants while maintaining effectiveness.
2Device complexity
If fixed configuration weed removing implements are used, then device simplicity is improved, but adaptability to natural variations in crop plant sizes and spacings deteriorates
Solution Approach 1:
The system transforms the fixed configuration into a dynamic one by continuously adjusting the implement tool trajectory based on real-time detection of crop plant positions, sizes, and spacings. This allows a relatively simple implement structure to achieve high adaptability through intelligent control.
Solution Approach 2:
The system changes the trajectory parameters (position, orientation, speed) of the implement tool dynamically based on detected crop plant characteristics. By adjusting these parameters in real-time, the system adapts to natural variations without requiring complex mechanical reconfiguration of the implement itself.
3Productivity
If rapid side to side movement is used for weed removal, then weed removal speed is improved, but energy consumption increases and mechanical components experience high stress
Solution Approach 1:
The system uses dynamic trajectory optimization to smooth out rapid side-to-side movements, reducing acceleration and deceleration cycles. The implement follows a more continuous path that maintains weed removal effectiveness while reducing mechanical stress and energy consumption.
Solution Approach 2:
The system performs preliminary detection and trajectory planning before the weeding operation begins. By pre-calculating the optimized path based on detected crop plant positions, the system avoids last-minute rapid movements, reducing energy consumption and mechanical stress on components.
Data Source
AI summary
An agricultural weed removal method for a planted crop plant row that can include operating a weed removing implement tool on an optimized travel path for the implement tool, wherein the implement tool traverses the travel path at least partially around one or more crop plants planted in a row. The method can further include adjusting a trajectory of the travel path for the implement tool based on at least one variable. In addition, the step of adjusting the trajectory of the travel path for the implement tool may be further based on detecting the at least one variable in the travel path. Also, the detected variable may be based on least one or more sensors or cameras secured to a host vehicle. Further, the travel path may include an oscillating type pattern having a crest and a trough.