K2 relies on the deep learning of artificial intelligence, robot control and machine vision technology ?to provide innovative agricultural robot intelligent equipment for the planting industry, which is mainly used in fruit and vegetable picking, intelligent sorting, precise spraying, fruit bagging, asset inventory, precise weeding, flower thinning, fruits and vegetables, precise pollination, etc.
The imaging system is used to sense the surrounding environment, "see" the fruit crop, understand the fruit status and ripening in real time, and calculate the number of fruits.
Hand-eye coordination in robots
By integrating machine vision and robotic arm control technology, robots can better adapt to the complex non-structural working environment of agriculture and complete the picking task through hand-eye cooperation like people.
The deep learning technology of AI
The imaging system is used to sense the surrounding environment, "see" the fruit crop, understand the fruit status and ripening in real time, and calculate the number of fruits.
Hand-eye coordination in robots
By integrating machine vision and robotic arm control technology, robots can better adapt to the complex non-structural working environment of agriculture and complete the picking task through hand-eye cooperation like people.
Multi-sensor fusion technology
Through automatic analysis and synthesis of the algorithm, the location coordinate information of the birds in the space is obtained.
Manipulator control technology
Based on the fruit and environment information feedback from the vision system, the manipulator plans the motion path in real time and guides the end actuator to the actual position of the fruit.
Application scenario
Fruit picking robot
In field/greenhouse/orchard and other application scenarios, sensors are used to sense and analyze crops and the surrounding environment to realize high-speed real-time data transmission. Seamless driving manipulator can be widely used in fruit picking, precise sowing.
01
Intelligent grading and sorting of fruit
Using machine learning and other intelligent cognitive and autonomous learning technologies, fruits are graded and sorted according to the comprehensive information of fruit color, fruit shape and defect.
02
Fruit and vegetable growth prediction
Through robot inspection, efficient and accurate machine identification, real-time attention to the growth of fruits and vegetables, and prediction of orchard yield.
03
Early warning of crop diseases and pests
Through the multidimensional data model for the establishment of early warning, greatly improve the efficiency of the recognition of the key plant diseases and insect pests and timeliness