Calibration method and automation machining apparatus using the same

    公开(公告)号:US10209698B2

    公开(公告)日:2019-02-19

    申请号:US14696049

    申请日:2015-04-24

    Abstract: A calibration method applicable for an automation machining apparatus includes building a first stereoscopic characteristic model corresponding to an object, obtaining a stereoscopic image of the object, building a second stereoscopic characteristic model corresponding to the object based on the stereoscopic image, obtaining at least one error parameter corresponding to the second stereoscopic characteristic model by comparing the second stereoscopic characteristic model with the first stereoscopic characteristic model, and calibrating a machining parameter of the automation machining apparatus based on the at least one error parameter.

    METHOD AND APPARATUS FOR RECONSTRUCTING THREE DIMENSIONAL MODEL
    3.
    发明申请
    METHOD AND APPARATUS FOR RECONSTRUCTING THREE DIMENSIONAL MODEL 有权
    用于重构三维模型的方法和装置

    公开(公告)号:US20140099017A1

    公开(公告)日:2014-04-10

    申请号:US13686927

    申请日:2012-11-28

    Abstract: A method and an apparatus for reconstructing a three dimensional model of an object are provided. The method includes the following steps. A plurality of first depth images of an object are obtained. According to a linking information of the object, the first depth images are divided into a plurality of depth image groups. The linking information records location information corresponding to a plurality of substructures of the object. Each depth image group includes a plurality of second depth images, and the substructures correspond to the second depth images. According to the second depth image and the location information corresponding to each substructure, a local module of each substructure is built. According to the linking information, the local models corresponding to the substructures are merged, and the three-dimensional model of the object is built.

    Abstract translation: 提供了一种用于重建物体的三维模型的方法和装置。 该方法包括以下步骤。 获得对象的多个第一深度图像。 根据对象的链接信息,将第一深度图像分割为多个深度图像组。 链接信息记录与对象的多个子结构对应的位置信息。 每个深度图像组包括多个第二深度图像,并且子结构对应于第二深度图像。 根据第二深度图像和对应于每个子结构的位置信息,构建每个子结构的局部模块。 根据链接信息,对应于子结构的局部模型进行合并,构建对象的三维模型。

    Method and apparatus for reconstructing three dimensional model
    4.
    发明授权
    Method and apparatus for reconstructing three dimensional model 有权
    重建三维模型的方法和装置

    公开(公告)号:US09262862B2

    公开(公告)日:2016-02-16

    申请号:US13686927

    申请日:2012-11-28

    Abstract: A method and an apparatus for reconstructing a three dimensional model of an object are provided. The method includes the following steps. A plurality of first depth images of an object are obtained. According to a linking information of the object, the first depth images are divided into a plurality of depth image groups. The linking information records location information corresponding to a plurality of substructures of the object. Each depth image group includes a plurality of second depth images, and the substructures correspond to the second depth images. According to the second depth image and the location information corresponding to each substructure, a local module of each substructure is built. According to the linking information, the local models corresponding to the substructures are merged, and the three-dimensional model of the object is built.

    Abstract translation: 提供了一种用于重建物体的三维模型的方法和装置。 该方法包括以下步骤。 获得对象的多个第一深度图像。 根据对象的链接信息,将第一深度图像分割为多个深度图像组。 链接信息记录与对象的多个子结构对应的位置信息。 每个深度图像组包括多个第二深度图像,并且子结构对应于第二深度图像。 根据第二深度图像和对应于每个子结构的位置信息,构建每个子结构的局部模块。 根据链接信息,对应于子结构的局部模型进行合并,构建对象的三维模型。

    Machining parameter automatic generation system

    公开(公告)号:US10762699B2

    公开(公告)日:2020-09-01

    申请号:US16225931

    申请日:2018-12-19

    Abstract: A machining parameter automatic generation system includes a geometric data capturing module, a feature recognition learning network and a machining parameter learning network. The geometric data capturing module captures a geometric shape of a workpiece to generate a candidate feature list. The feature recognition learning network trains the candidate feature list according to a first neural network model to obtain an applicable feature list. The machining parameter learning network trains the applicable feature list and the candidate machining parameter according to a second neural network model to obtain an applicable machining parameter. The applicable machining parameter is used to generate a machining program, and the machining program is read by a machine tool for processing.

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