Orchard Mapping Drone With Protruding Cage for Selective Harvesting
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Solution Overview
Problem
Conventional orchard harvesting devices are large, expensive, and inefficient, with limitations in mobility and the ability to reach fruit at high branches, while drones lack the necessary arm protrusion, protection, and feedback mechanisms for selective harvesting of ripe fruits without damaging them.
Innovation Solution
A computerized system using drones equipped with a camera, anti-collision system, and a protruding cage for navigating and harvesting fruits, featuring a robust algorithm for fruit detection and precise positioning, enabling selective harvesting and pruning with minimal manual intervention.
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 complexity 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 aerial mobility and a single protruding arm. The drone hovers positionally using its flight control system rather than requiring complex mechanical positioning mechanisms, thereby reducing device complexity while maintaining harvesting capability.
Solution Approach 2:
The drone system serves multiple functions: it performs harvesting, mapping, and monitoring tasks. The same drone platform that harvests fruits can also capture images for mapping and detect fruit ripeness, eliminating the need for separate specialized equipment and reducing overall system complexity.
2Productivity
If conventional large tracks are used for harvesting, then harvesting capability is improved, but mobility and adaptability to existing orchards deteriorate
Solution Approach 1:
The patent replaces ground-based mechanical tracks with an aerial drone system that flies above the orchard. This substitution eliminates the mobility constraints of ground vehicles, allowing the system to access any area of the orchard without being limited by terrain, tree density, or infrastructure requirements.
3Device complexity
If existing drones are used without protruding arms, then device simplicity is maintained, but ability to reach and harvest high fruits deteriorates
Solution Approach 1:
The patent adds a vertical dimension to the harvesting system by extending the arm upward from the drone body. This protruding arm reaches into the three-dimensional space of the orchard canopy, allowing the drone to access fruits at various heights without requiring complex mechanical articulation or multiple drones at different altitudes.
4Measurement precision
If manual selective harvesting is performed, then fruit selection quality is improved, but labor cost and time consumption increase
Solution Approach 1:
The drone system incorporates cameras and sensors that detect fruit ripeness and provide real-time feedback to the control system. This automated detection and selection process maintains the quality of manual selection while dramatically reducing the time required, as the drone can rapidly scan and identify ripe fruits across the entire orchard without human fatigue or interruption.
Solution Approach 2:
The system performs self-service by autonomously detecting, selecting, and harvesting ripe fruits without continuous human intervention. The drone navigates independently, identifies fruits based on ripeness criteria, and executes harvesting actions, thereby maintaining selection quality while reducing labor time and costs.
5Area of stationary object
If mapping is performed from high altitude (914m), then coverage area is improved, but image resolution deteriorates
Solution Approach 1:
The patent uses a dynamic mapping approach where the drone adjusts its flight altitude and position based on the required resolution. For areas requiring high detail, the drone flies at lower altitudes to capture high-resolution images. For broader overview needs, it operates at higher altitudes. This dynamic adjustment allows the system to optimize between coverage area and image resolution based on task requirements.
Data Source
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AI summary
The present invention provides a computerized system for mapping an orchard, and a method for producing precise map and database with high resolution and accuracy of all trees in an orchard.