3D printing path planning method for complex thin-walled structure object based on reinforcement learning

A technology of path planning and reinforcement learning, applied in manufacturing auxiliary devices, processing data acquisition/processing, additive processing, etc., can solve problems such as large printing span, redundant curing burrs, easy disconnection, etc., to improve printing efficiency Effect

Active Publication Date: 2018-12-14
DALIAN UNIV OF TECH
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AI Technical Summary

Problems solved by technology

However, for objects with thin-walled external and internal structures (often used for lightweight industrial production), the existing traditional path planning methods have certain limitations. If the stress is too concentrated, the heat dissipation effect of the material will be reduced, which will directly lead to deformation, cracks and o

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  • 3D printing path planning method for complex thin-walled structure object based on reinforcement learning
  • 3D printing path planning method for complex thin-walled structure object based on reinforcement learning
  • 3D printing path planning method for complex thin-walled structure object based on reinforcement learning

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Embodiment Construction

[0049] The specific implementation manners of the present invention will be further described below in conjunction with the accompanying drawings and technical solutions.

[0050] The flow chart of the present invention is as figure 1 shown. In the following, the present invention will be further described in detail for the actual printed object, and compared with the traditional algorithm.

[0051] Step1: Preparatory work, complete the initialization of the required matrix and model.

[0052] (1) To print model A, build a 3D simulation model, see figure 2 , and slice the 3D model, and then get the 2D layer target object C of each printing layer i (i=1,...,50), and establish a printing path planning simulation environment for each layer. Since the object structure of each layer of the model A is consistent, a certain layer is taken as an example below to describe the implementation process of the present invention in detail.

[0053] (2) In the simulation environment, se...

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Abstract

The invention belongs to the field of artificial intelligence and 3D printing and relates to a 3D printing path planning method for a complex thin-walled structure object based on reinforcement learning. The method comprises the following steps: firstly, establishing a simulation environment for path planning; then establishing a return matrix R based on a Q-learning algorithm in reinforcement learning, and generating a status-action matrix Q of the return matrix R; analyzing data of the status-action matrix Q to obtain a printed path planning simulation result; and finally, combining parameter of an actual printer with the simulation result to finish an actual printing process. By means of the Q-learning algorithm, the 3D printing path is learned intelligently. By means of learning and training, a computer can find a proper printed path intelligently, so that the printing efficiency can be improved greatly. The formed effect is also obviously better than that of a conventional path planning algorithm. The method provided by the invention is of universality to a complex thin-walled pattern.

Description

technical field [0001] The invention belongs to the field of artificial intelligence and 3D printing, and relates to a 3D printing path planning method for complex thin-walled structural objects based on reinforcement learning. Background technique [0002] 3D printing technology, also known as additive manufacturing technology, was originally used in the field of industrial design and mold manufacturing to manufacture part mold models, and then used in direct manufacturing of products. After nearly ten years of rapid development, 3D printing technology has been widely used in medical, aerospace, education and other fields. At present, the most widely used method is the layered 3D printing method. By layering the target object model and accumulating printing layer by layer from bottom to top, the target entity is finally obtained. [0003] Among them, after the target object model is layered, the movement path planning of the print head for each layer is an important step i...

Claims

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Application Information

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IPC IPC(8): B29C64/386B33Y50/00
CPCB29C64/386B33Y50/00
Inventor 李佳奕王祎李凤岐王胜法杨德成
Owner DALIAN UNIV OF TECH
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