Autonomous UAV Fleet Harvesting With Ripeness-Based Fruit Selection
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Solution Overview
Problem
Current agricultural technologies for fruit harvesting and dilution are inefficient due to the limitations of conventional machinery, which are often large, expensive, and unable to navigate complex orchard environments, and existing drones lack the necessary tools and systems for selective harvesting and dilution of fruits, particularly for soft-shell fruits, and do not effectively manage fruit ripeness or quality.
Innovation Solution
A management system for autonomous unmanned aircraft vehicles (UAVs) that includes a computing system, fruit detection unit, anti-collision system, and a protruding netted cage to navigate and harvest fruits, along with a computerized method for optimal harvesting using a multi-layer database to track fruit ripeness and quality, allowing for selective and efficient harvesting and dilution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional large tracks with robotic arms are used for harvesting, then harvesting capability is improved, but device size and cost increase significantly
Solution Approach 1:
The patent replaces complex mechanical robotic arms with multiple degrees of freedom with a simpler drone-based system that uses flight control and positioning algorithms. The drone carries a harvesting mechanism that can be precisely positioned through aerial navigation rather than complex mechanical articulation, significantly reducing device complexity while maintaining harvesting capability.
Solution Approach 2:
The harvesting system is divided into separate functional modules: the drone platform for navigation and positioning, the harvesting mechanism for fruit collection, and the control system for coordination. This segmentation allows each component to be optimized independently and simplifies the overall system architecture compared to integrated robotic arm systems.
2Productivity
If large tracks with robotic arms are deployed, then harvesting function is improved, but adaptability to existing orchards and mountain mobility deteriorates
Solution Approach 1:
The patent transitions from ground-based harvesting to aerial harvesting by using drones that operate in the three-dimensional space above the orchard. This dimensional change allows the system to access trees and fruits without being constrained by ground terrain, orchard layout, or mobility limitations of ground vehicles, significantly improving adaptability to existing orchards and mountainous regions.
3Ease of operation
If existing drones are used without specialized harvesting equipment, then flight capability is maintained, but selective harvesting and fruit detection capability are lost
Solution Approach 1:
The patent merges the flight capability of existing drones with specialized harvesting equipment including fruit detection cameras, ripeness sensors, and harvesting mechanisms. This integration combines the mobility and ease of operation of drones with the selective harvesting functionality needed for productive fruit collection, creating a multi-functional system that achieves both goals simultaneously.
Solution Approach 2:
The drone platform is designed to perform multiple functions: navigation and positioning, fruit detection and ripeness assessment, and actual harvesting. This multi-functionality allows a single system to replace multiple separate operations (aerial surveying, fruit inspection, and manual harvesting), improving productivity while maintaining the operational simplicity of the drone platform.
4Manufacturing precision
If manual harvesting is performed, then selective harvesting of ripe fruits is achieved, but labor intensity and time consumption increase
Solution Approach 1:
The drone system performs self-detection and self-selection of ripe fruits using onboard cameras and sensors that automatically identify and assess fruit ripeness. The harvesting mechanism then automatically collects the selected fruits without human intervention. This self-service capability maintains the precision of selective harvesting while eliminating the time consumption and labor intensity of manual inspection and collection.
Solution Approach 2:
The system uses real-time feedback from fruit detection cameras and ripeness sensors to guide the harvesting process. The sensors continuously monitor fruit conditions, provide data to the control system, and enable dynamic adjustment of harvesting decisions. This feedback loop ensures high precision in fruit selection while automating the process to reduce time consumption compared to manual harvesting.
Data Source
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AI summary
The present invention provides a management system for autonomous unmanned aircraft vehicle (UAV) fleet management for harvesting or diluting fruits, and a computerized method for optimal harvesting using a UAV fleet.