A behavior control method of yellow peach core-digging robot based on deep reinforcement learning

Abstract

The invention belongs to the technical field of computer application and artificial intelligence, and relates to a behavior control strategy of a yellow peach core digging robot based on deep reinforcement learning. Aiming at the problem that the traditional mechanical control method is difficult to effectively control the behavior of the yellow peach core digging robot, this invention proposes a method based on deep reinforcement learning to control the behavior of the yellow peach core digging robot with visual functions, in order to improve its work performance. This patent utilizes the perception ability of deep learning and the decision-making ability of intensive learning, so that the robot can use deep learning to identify the state of the peach pit, and then guide the single-chip microcomputer to control the motor to dig out the peach pit through the method of intensive learning, so as to finally complete the task of digging the pit. The present invention has advantages for the core digging task that utilizes machines instead of human labor.

Description

technical field [0001] The invention belongs to the technical field of computer application and artificial intelligence, and relates to a behavior control method of a yellow peach core digging robot based on deep reinforcement learning. Background technique [0002] With the development of society and technological progress, the emergence of social problems such as labor shortage and rising labor prices have greatly promoted the research, application and popularization of industrial robots. In recent years, the research and application of industrial robots has been one of the hot spots of scientific research and social concern. However, due to technical factors such as high dexterity, high stability, and high environmental tolerance required by industrial robots, the development and application of industrial robots have been plagued. The early industrial robots were the product of mechatronics, and as the market's requirements for the performance of industrial robots contin...

AI Technical Summary

Problems solved by technology

Because food production has high hygienic requirements, workers must wear work clothes, work boots, hats and masks that cover the whole body. The production season of canned yellow peaches is concentrated in July and August, and the weather is extremely hot, which makes the workers suffer from psychological and physical stress. The test made it very difficult for the cannery to recruit people

In addition, the quality of manual core digging has advantages and disadvantages depending on individual differences, and the quality of core digging cannot be fully guaranteed

For the robot used for core digging, due to the different shapes of the peach cores of yellow peaches, it is difficult to use the traditional mechanical control method to control the behavior strategy of core digging

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