Laser Crop Row Recognition Using Bird's-Eye Distance Mapping
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Solution Overview
Problem
Existing crop row recognition systems using camera images struggle with accuracy due to varying lighting conditions and seasonal changes in crop branches and leaves, making it difficult to stably recognize crop rows.
Innovation Solution
A work vehicle equipped with a distance sensor that uses laser light to acquire distance information and generate a bird's eye image, combined with a crop row recognition program that identifies straight lines corresponding to crop rows using detection points within row candidate regions, reducing the influence of non-crop objects and environmental factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a camera is used to photograph field images for crop row recognition, then the system can capture visual information, but the recognition accuracy deteriorates under varying lighting conditions and seasonal changes
Solution Approach 1:
The patent replaces the optical camera-based recognition system with a laser-based distance measurement system. Instead of using light to capture images that are affected by lighting conditions, the system uses laser ranging to directly measure distances to crop rows, converting an optical problem into a geometric measurement problem that is immune to lighting and seasonal variations.
Solution Approach 2:
The patent introduces laser distance measurements as an intermediary to indirectly determine crop row positions. Rather than directly imaging the crops, the system measures distances to multiple points and reconstructs the crop row geometry through coordinate calculation, using distance information as a mediator that is not affected by visual appearance changes.
2Reliability
If camera images are used for crop row recognition, then the system can identify crop rows, but stability deteriorates when crop branches and leaves change with seasons
Solution Approach 1:
The system replaces image-based visual recognition with laser-based geometric measurement. By measuring actual distances to crop rows and calculating positions through coordinate geometry, the system obtains physical measurement data that remains consistent regardless of how the visual appearance of crops changes with seasons.
Solution Approach 2:
The patent changes the measurement parameter from visual appearance (image intensity, color, texture) to physical distance (range measurement). This parameter transformation makes the measurement invariant to seasonal changes in crop morphology, as distance measurements remain consistent even when branches and leaves change.
3Reliability
If laser distance measurement is used instead of camera imaging, then environmental stability improves, but device complexity increases
Solution Approach 1:
The patent replaces a camera system with a laser distance sensor system. While both are optical devices, the laser ranging system uses time-of-flight or phase-shift measurement principles that are fundamentally different from image capture, providing environmental stability at the cost of requiring specialized distance measurement electronics and signal processing.
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 stable and accurate recognition of crop rows regardless of environmental conditions, such as lighting and seasonal changes, by using laser-based distance information and advanced image processing techniques to filter out non-crop objects.
Implementation Method 1
a distance sensor configured to irradiate a plurality of objects present in the field with laser light and receive reflected light from the objects to thereby acquire distance information of each of the objects
Implementation Method 2
receive reflected light from the objects
Data Source
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AI summary
A work vehicle includes a distance sensor configured to irradiate a plurality of objects present in a field with laser light and receive reflected light from the objects to thereby acquire distance information of each of the objects; a bird's eye image generation unit 51 configured to detect a position of each of the objects on a basis of the distance information and generate a bird's eye image, including the detected position of each of the objects as a detection point; a row candidate region generation unit 52 configured to generate one or more row candidate regions including two or more detection points located within a predetermined distance, on a basis of the bird's eye image, and a crop row recognition unit 53 configured to recognize a straight line corresponding to a crop row using all of the detection points included in the row candidate regions.