Plant Localization Using Invariant Anchor Points in High-Elevation Imagery
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Solution Overview
Problem
Existing plant localization techniques in precision agriculture are computationally expensive, error-prone, and time-consuming, particularly in large agricultural fields, due to the challenges of stitching high-elevation images with deformable crops that introduce distortion.
Innovation Solution
The method involves aligning high-elevation images using invariant anchor points instead of variant feature points, such as deformable plants, allowing for independent processing of individual images to localize plants relative to these anchor points, which are common across images, thereby avoiding the need for costly and error-prone image blending or fusion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If image blending or fusion is used to create a global image from multiple high-elevation images, then complete coverage of the agricultural area is achieved, but computational cost increases significantly
Solution Approach 1:
The patent divides the agricultural area into multiple overlapping high-elevation images captured from different positions. Instead of blending all images into one global image, the system segments the processing task by identifying and matching invariant anchor points across individual images, allowing independent processing of each image while maintaining spatial relationships.
Solution Approach 2:
The patent extracts invariant anchor points from each high-elevation image that remain consistent across different viewing angles and positions. These anchor points are extracted as key reference features, allowing the system to establish spatial relationships without processing or blending the entire image data, thereby reducing computational requirements.
2Measurement precision
If variant feature points such as deformable plants are used for alignment, then plant localization is possible, but alignment accuracy decreases due to wind-triggered deformation
Solution Approach 1:
Instead of using the deformable plant features themselves as anchor points for alignment, the patent inverts the approach by using invariant anchor points (such as stationary ground features, infrastructure elements, or stable natural features) to align the images. Once aligned, the plant localization is then performed relative to these stable reference points, thereby decoupling the alignment stability requirement from the plant features.
Solution Approach 2:
The patent introduces invariant anchor points as intermediary reference features between the camera system and the deformable plants. These anchor points serve as stable mediators that enable accurate image alignment and provide a reliable reference frame for localizing plants, without being affected by plant deformation themselves.
3Measurement precision
If multiple high-elevation images are processed to localize individual plants, then precision agriculture is enabled, but processing time increases
Solution Approach 1:
The patent performs preliminary action by identifying and matching invariant anchor points across multiple high-elevation images before processing the full plant localization task. This preliminary alignment using stable reference points establishes a coordinated reference frame, allowing subsequent plant detection and localization to be performed more efficiently on already-aligned images rather than on raw, unaligned data.
Data Source
AI summary
Systems, apparatus, articles of manufacture, and methods are disclosed. An example agricultural robot comprises interface circuitry; machine readable instructions; and at least one processor to execute the machine readable instructions to: spatially align, by execution of a trained machine learning model, an invariant anchor point within high-elevation images and a plant whose wind-triggered deformation is perceptible between the high-elevation images; localize, by execution of the trained machine learning model, the plant based on the spatial alignment; and cause the agricultural robot to perform, in response to the localization, one or more agricultural tasks to the plant.