Harvester Unload Conveyor Alignment Using Camera-Based Vehicle Detection
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Solution Overview
Problem
The challenge of synchronizing the operation of combine and forage harvesters with receiving vehicles during grain unloading is laborious and challenging due to limited visibility, environmental conditions, and the need for precise alignment, especially with large or elongated grain bins, which can lead to inefficiencies and grain spillage.
Innovation Solution
A system utilizing a camera and machine learning algorithms to identify and determine the location of receiving vehicles relative to the harvester, combined with automated guidance systems to align the unload conveyor with the grain bin, either manually assisted or fully automated, using GNSS, LiDAR, or RADAR for precise positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual alignment is used to position the receiving vehicle with the unload conveyor, then the operator can control the positioning, but the operation becomes laborious and challenging due to limited visibility and environmental conditions
Solution Approach 1:
The patent replaces manual mechanical alignment operations with an automated optical guidance system. Cameras mounted on the harvester capture images of the receiving vehicle, and a processing system generates graphical representations that guide the operator or automate the alignment process, eliminating the need for manual visual alignment under difficult conditions
Solution Approach 2:
The patent introduces a graphical representation as an intermediary between the harvester and receiving vehicle. This visual interface displays the relative positions and alignment status, enabling the operator to achieve precise alignment without directly observing the physical gap between vehicles under challenging environmental conditions
2Volume of stationary object
If the receiving vehicle has a large or elongated grain bin, then the storage capacity increases, but it becomes difficult to align and requires shifting position during unloading to evenly fill the bin
Solution Approach 1:
The patent enables dynamic adjustment of the receiving vehicle's position during the unloading process. The guidance system continuously updates the graphical representation, allowing the operator to shift the vehicle's position to evenly fill different sections of the elongated grain bin while maintaining alignment with the moving unload conveyor
Solution Approach 2:
The system provides continuous visual feedback through the graphical representation showing the relative positions of the unload conveyor and grain bin. This real-time information allows the operator to make precise positional adjustments during unloading to achieve even grain distribution throughout the large grain bin
3Productivity
If the harvester and receiving vehicle move at different speeds, then each vehicle can operate at its optimal speed, but maintaining alignment becomes challenging
Solution Approach 1:
The patent employs a feedback mechanism where cameras continuously capture the relative positions of the harvester and receiving vehicle, and the processing system updates the graphical representation in real-time. This allows the operator to monitor and adjust positions to maintain alignment even when vehicles operate at different speeds
Solution Approach 2:
The system establishes the desired alignment relationship between the unload conveyor and grain bin before unloading begins. The graphical representation provides preliminary guidance on positioning, enabling the operator to maintain proper alignment throughout the unloading process despite speed variations
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
Enables accurate and efficient alignment of receiving vehicles with the harvester's unload conveyor, reducing operator effort and minimizing grain spillage, even in challenging environmental conditions, through real-time position data and automated guidance.
Implementation Method 1
a camera to capture images of an area proximate the agricultural harvester and generate image data from the captured images
Implementation Method 2
an electromagnetic detecting and ranging module to emit electromagnetic waves and generate a digital representation of objects within a field of view of the electromagnetic detecting and ranging module
Implementation Method 3
a light detecting and ranging (LiDAR) module to emit light and generate a digital representation of an area within a field of view of the light detecting and ranging module
Data Source
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AI summary
An agricultural harvester includes an unload conveyor for transferring a stream of processed crop out of the agricultural harvester and a camera for capturing images of an area proximate the agricultural harvester and generating image data. A computing device is configured to receive the image data from the camera during a harvest operation; apply a machine learning model to identify, using only image data from the camera, a receiving vehicle from among a plurality of possible different receiving vehicles; determine dimensions associated with the identified receiving vehicle; determine, using the dimensions and the image data, a location of the receiving vehicle relative to the agricultural harvester; and generate automated navigation data based on the location of the receiving vehicle, the automated navigation data to automatically control operation of at least one of the agricultural harvester and the receiving vehicle to align an unloading conveyor with the receiving vehicle.