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 sunshine 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, locations, and confidence levels in pictures.
From forward and inverse kinematics, kinematics to dynamics, from joint coordinate system to Cartesian coordinate system
Force feedback control combined with visual recognition enables precise grasping of objects
Accurate grading under high-speed dynamics
Precise spraying without crushing the seedlings, spraying evenly, timing and quantity
Reduce fuel costs and irrigation needs
Scientifically and rationally improve fruit quality
Yield estimation, growth information monitoring
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