Autonomous Crop Pickup Using Drone Swath Mapping
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Solution Overview
Problem
Agricultural machines face challenges in autonomous operation due to distortions in sensor measurements caused by dust and flying particles, which hinder accurate field and crop data acquisition necessary for efficient crop material pickup.
Innovation Solution
A system comprising a vehicle and a controller that acquires field data, determines control instructions for machine operation, including steering and speed control, using sensors and aerial vehicles to map crop material locations and properties, enabling the machine to follow optimized routes for efficient crop pickup.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If sensors are mounted on the tractor to measure swath in front of the machine, then real-time crop material location data is available for autonomous operation, but measurement precision deteriorates due to dust and flying particles causing signal distortions
Solution Approach 1:
An unmanned aerial vehicle (drone) is introduced as an intermediary carrier for the swath measurement system. The drone flies over the field and captures images of the swath from above, transmitting the data to the tractor's controller. This separates the measurement function from the tractor itself, eliminating the problem of dust and particles interfering with sensors mounted on the moving tractor.
2Ease of operation
If the machine follows a predetermined fixed route through the field, then navigation is simplified and autonomous operation is easier to implement, but productivity decreases because the machine cannot adapt to actual crop material distribution
Solution Approach 1:
The system uses real-time feedback by continuously monitoring the actual swath location and dimensions captured by the drone, comparing it with the planned route, and dynamically adjusting the machine's path. The controller receives updated swath data and modifies navigation commands to optimize the route based on actual crop material distribution, combining automated control with adaptive decision-making.
3Productivity
If the machine operates at high speed to increase productivity, then more crop material is processed per unit time, but measurement precision and control accuracy deteriorate due to motion blur and sensor disturbances
Solution Approach 1:
The measurement system transitions from a ground-based perspective (collected from the tractor moving along the ground) to an aerial perspective (captured from above by the drone). This dimensional change allows the swath to be imaged from a stable platform overhead, eliminating motion blur and particle interference that occur when sensors are mounted on the moving tractor, thereby maintaining high measurement precision even during high-speed operation.
Data Source
AI summary
A system includes a vehicle configured to acquire field-data representative of a field having crop material that is to be picked up from the field; and a controller configured to determine control-instructions for a machine to pick up the crop material, based on the field-data. The control-instructions include machine-steering-instructions for automatically controlling the direction of travel of the machine, such that the machine follows a specific route through the field.