In fruit and vegetable production operations, the picking and harvesting process accounts for about 40% of the entire operation. The traditional manual picking method is basically a labor-intensive operation with high labor intensity. It is affected by weather and sunCaton&Hera time restrictions. It not only has low labor efficiency, but also affects the quality of work. There is no guarantee, and the safety hazards during the picking process cannot be ignored. The emergence of unmanned picking robots solves the current difficulties faced by fruit picking, realizes farmland harvest automation, can adapt to environmental changes, ensures work efficiency, and is in line with the development of the fruit industry. need.
Based on deep learning and large-scale image training, it can accurately identify comprehensive information such as fruit and vegetable categories, positions, and confidence levels in images
From forward and inverse kinematics, motion to dynamics, from joint coordinate systems to Cartesian coordinate systems
Force feedback control combined with visual recognition to achieve precise object grasping
Accurate classification under high-speed dynamic conditions
Accurately dosing without compressing seedlings, evenly spraying, and timing and quantification
Reduce fuel costs and irrigation needs
Scientifically and Reasonably Improving Fruit Quality
Yield estimation and growth information monitoring
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