Crop Location Detection Using Tool Depth and Bed Surface Profile
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Solution Overview
Problem
Existing agricultural technologies lack efficient methods for autonomously detecting and accurately locating crops in a field to perform precise agricultural operations such as weeding, watering, and fertilizing without relying on costly additional sensors like LIDAR or binocular vision.
Innovation Solution
An autonomous agricultural machine uses a ground-facing camera and tool modules with depth sensors to estimate the plant bed surface profile, allowing it to calculate the real lateral location of crops and actuate tool modules for precise agricultural functions like weeding, watering, and fertilizing, while reducing the need for multiple depth sensors by utilizing the tool modules to record depth information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple depth sensors like LIDAR or binocular vision are used to achieve high-accuracy crop location, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent combines the depth sensing function with existing agricultural tools by equipping tool modules with depth sensors. Instead of using separate LIDAR or binocular vision systems, the depth sensing capability is merged into the tool modules that are already present for agricultural operations, thereby reducing overall system complexity while maintaining measurement precision.
Solution Approach 2:
The tool modules serve multiple functions: they perform agricultural operations (weeding, watering, fertilizing) and simultaneously function as depth sensing devices. This multi-functionality eliminates the need for dedicated depth sensing systems like LIDAR, reducing device complexity while achieving accurate crop location through the depth information collected by the tool modules.
2Measurement precision
If multiple depth sensors are deployed to map the entire ground area, then measurement precision is improved, but the number of sensors and device complexity increase
Solution Approach 1:
The tool modules are designed to serve dual purposes: performing agricultural operations and collecting depth information. By making the tool modules universal devices that can both work the soil and sense depth, the patent eliminates the need for multiple dedicated depth sensors, thereby reducing the quantity of sensors while maintaining accurate depth mapping capability.
Solution Approach 2:
The tool modules perform self-service by simultaneously executing their primary agricultural function and collecting depth data for crop location determination. The depth sensors on the tool modules use the tool modules' own position and extension information to map the ground area, eliminating the need for separate sensing systems.
3Device complexity
If a single depth sensor is used to reduce component quantity, then device complexity is reduced, but measurement precision and coverage area decrease
Solution Approach 1:
Instead of using one complex high-precision depth sensor, the patent segments the depth sensing function across multiple tool modules distributed throughout the agricultural implement. Each tool module collects depth information from its local position, and the system integrates these segmented measurements to achieve comprehensive and accurate crop location determination across the entire field of view.
Solution Approach 2:
The patent transitions from using depth sensors positioned above ground to using depth sensors at ground level through the tool modules. This dimensional change allows the system to leverage the extension distance and lateral position of multiple tool modules to reconstruct the three-dimensional surface profile, achieving accurate depth mapping with simpler individual sensors distributed across the implement.
Data Source
AI summary
A method for detecting real lateral locations of target plants includes: recording an image of a ground area at a camera; detecting a target plant in the image; accessing a lateral pixel location of the target plant in the image; for each tool module in a set of tool modules arranged behind the camera and in contact with a plant bed: recording an extension distance of the tool module; and recording a lateral position of the tool module relative to the camera; estimating a depth profile of the plant bed proximal the target plant based on the extension distance and the lateral position of each tool module; estimating a lateral location of the target plant based on the lateral pixel location of the target plant and the depth profile of the plant bed surface proximal the target plant; and driving a tool module to a lateral position aligned with the lateral location of the target plant.