Ground-Air Crop Scouting for GPS-Blocked Row Navigation
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Solution Overview
Problem
Agricultural machines, such as tractors and sprayer vehicles, face challenges in remote-controlled or autonomous operations due to limitations in sensing and navigation, particularly when crops grow tall, obscuring GPS signals and camera views, making it difficult to identify ground-level obstacles, weeds, or moisture levels effectively.
Innovation Solution
An intelligent scouting system comprising a ground scout and an air scout (drone) that communicate and collaborate to navigate, identify crop rows, and perform tasks like soil sampling and weed detection, using a buddy system with complementary capabilities to overcome the limitations of individual scouts, including GPS-independent location identification and data correlation with global coordinates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS and cameras are used for autonomous navigation, then location identification and obstacle detection are improved, but the system fails when crops grow tall and obscure GPS signals and camera views
Solution Approach 1:
The system transitions from ground-level sensing to aerial sensing by deploying a drone that operates above the crop canopy. This dimensional change allows the drone to access GPS signals and visual data that are blocked at ground level, resolving the contradiction between measurement precision and reliability in tall crop conditions.
Solution Approach 2:
The drone acts as an intermediary between the ground-based autonomous vehicle and the environment. It captures images and identifies landmarks that are invisible to ground cameras, then transmits this information to guide the vehicle's navigation, maintaining system reliability when direct ground-based sensing fails.
2Device complexity
If a single autonomous vehicle is used, then operational simplicity is maintained, but the ability to perform complex tasks like selective weeding and moisture sampling is limited
Solution Approach 1:
The drone is designed as a multi-functional platform that can perform various tasks including aerial imaging, landmark identification, communication relay, and data transmission. This universal design allows a single additional component to enable multiple complex functions that would otherwise require separate specialized systems.
Solution Approach 2:
The system dynamically adjusts its configuration based on task requirements. The drone can operate independently for aerial surveys, dock with the vehicle for recharging and data transfer, or work in coordination with the vehicle for combined ground-aerial operations, providing adaptability without permanent structural complexity.
3Difficulty of detecting and measuring
If cameras are mounted near ground level to improve ground-level obstacle detection, then near-ground vision is improved, but the view is obscured by crop leaf canopy
Solution Approach 1:
The system uses aerial imaging from the drone to detect ground-level obstacles and features that are invisible to ground cameras. By capturing images from above the canopy and processing them to identify landmarks and obstacles, the system overcomes the visibility blockage without requiring ground-level cameras to see through the canopy.
Data Source
AI summary
A scouting system can include an autonomous ground vehicle having a perception sensor and a motion sensor to construct an occupancy grid referenced to a coordinate system of the autonomous ground vehicle. The autonomous ground vehicle is configured to use information from the occupancy grid to detect crop rows in a crop field. The autonomous ground vehicle is configured to identify and classify one or more non-crop plant in-lier objects arranged within the crop rows and generate an output signal received by an external vehicle to cause the external vehicle to perform a task when the one or more non-crop plant in-lier objects are identified within the crop rows.