Abstract
During the process of automated crop picking, the two hand–eye coordination operation systems, namely “eye to hand” and “eye in hand” have their respective advantages and disadvantages. It is challenging to simultaneously consider both the operational accuracy and the speed of a manipulator. In response to this problem, this study constructs a “global–local” visual servo picking system based on a prototype of a picking robot to provide a global field of vision (through binocular vision) and carry out the picking operation using the monocular visual servo. Using tomato picking as an example, experiments were conducted to obtain the accuracies of judgment and range of fruit maturity, and the scenario of fruit-bearing was simulated over an area where the operation was ongoing to examine the rate of success of the system in terms of continuous fruit picking. The results show that the global–local visual servo picking system had an average accuracy of correctly judging fruit maturity of 92.8%, average error of fruit distance measurement in the range 0.485 cm, average time for continuous fruit picking of 20.06 s, and average success rate of picking of 92.45%.
Highlights
Selective fruit harvesting is among the most time-consuming and labor-intensive agricultural operations
In the “eye in hand” hand–eye coordination operation system, the camera is fixed at the end of the manipulator, and the target object is close to it to prevent the manipulator from occluding the target object and to achieve a high-resolution image [11]
The tomatoes were randomly placed within 20 cm–130 cm of the camera, and their maturity was determined using binocular vision
Summary
Selective fruit harvesting is among the most time-consuming and labor-intensive agricultural operations. Owing to the complex operating environment and unstructured physical parameters of the operational objects, several key factors affect the smooth operation of fruit-harvesting robots. In the “eye to hand”-based hand–eye coordination operation system, the camera and the manipulator are installed separately, which can help obtain image-related information of the fruit over a larger field of view, where it is easy to realize visual feedback control, but in this system, the movement of the manipulator causes the target object to be occluded. In the “eye in hand” hand–eye coordination operation system, the camera is fixed at the end of the manipulator, and the target object is close to it to prevent the manipulator from occluding the target object and to achieve a high-resolution image [11]
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