China is a big producer of fruits and vegetables.The picking of fruits and vegetables is time-consuming and labor-intensive.Research and development of intelligent harvesting robots that automatically identify,harvest,and collect fruits and vegetables can reduce the labor intensity of agricultural practitioners and improve the automation level of the fruit and vegetable picking industry.The visual system is the key technology to realize the in-telligent picking of fruits and vegetables.The recognition model based on deep learning is helpful to improve the de-tection and positioning accuracy of fruits and vegetables.YOLOv3 network is used to train the picking recognition model.The model can identify the cross marks in the field,feed the three-dimensional coordinate value of the cross-mark center back to the unmanned vehicle control board,and calibrate the position of the unmanned vehicle twice.The model is also used to identify the variety and maturity of fruits and vegetables,and obtain the three-dimensional coordinate value of the center point of mature fruits and vegetables.The coordinate value of mature fruits and vegeta-bles is brought into the inverse kinematics solution to obtain the appropriate motion trajectory feedback to the manipu-lator to realize the'hand-eye coordination'between the manipulator and the camera.Finally,the designed and developed robot is used to grab fruits and vegetables on the experimental site,which verifies the feasibility of the in-telligent picking-robot.
NETL
NSTL
万方数据
维普
