公开(公告)号：US20230289596A1

公开(公告)日：2023-09-14

申请号：US18141262

申请日：2023-04-28

Applicant: Autodesk, Inc.

Inventor： David Patrick Lovell ,  Daniela Sofia Seixas Sousa ,  Chin-Yi Cheng

IPC: G06N3/08 ,  G06F30/20 ,  G05B19/4097

CPC classification number: G06N3/08 ,  G06F30/20 ,  G05B19/4097 ,  G05B2219/35134

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided repair of physical structures include: generating a two dimensional difference image from a first three dimensional model of at least one actual three dimensional surface of a manufactured object, and a second three dimensional model of at least one source three dimensional surface used as input to a manufacturing process that generated the manufactured object; obtaining from an image-to-image translation based machine learning algorithm, trained using pairs of input images representing deformed and deformed plus surface defected added versions of a nominal three dimensional surface, a translated version of the two dimensional image; generating from the translated version of the two dimensional image a third three dimensional model of at least one morphed three dimensional surface corresponding to the at least one source three dimensional surface. Further, defects can be removed based on the third three dimensional model.

公开(公告)号：US11676007B2

公开(公告)日：2023-06-13

申请号：US16524912

申请日：2019-07-29

Applicant: Autodesk, Inc.

Inventor： David Patrick Lovell ,  Daniela Sofia Seixas Sousa ,  Chin-Yi Cheng

IPC: G06N3/08 ,  G05B19/4097 ,  G06F30/20

CPC classification number: G06N3/08 ,  G05B19/4097 ,  G06F30/20 ,  G05B2219/35134

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided repair of physical structures include: generating a two dimensional difference image from a first three dimensional model of at least one actual three dimensional surface of a manufactured object, and a second three dimensional model of at least one source three dimensional surface used as input to a manufacturing process that generated the manufactured object; obtaining from an image-to-image translation based machine learning algorithm, trained using pairs of input images representing deformed and deformed plus surface defected added versions of a nominal three dimensional surface, a translated version of the two dimensional image; generating from the translated version of the two dimensional image a third three dimensional model of at least one morphed three dimensional surface corresponding to the at least one source three dimensional surface. Further, defects can be removed based on the third three dimensional model.

公开(公告)号：US20240061383A1

公开(公告)日：2024-02-22

申请号：US18240703

申请日：2023-08-31

Applicant: Autodesk, Inc.

Inventor： David Patrick Lovell ,  Akmal Ariff Bin Abu Bakar ,  Saaras Mehan

IPC: G05B13/02 ,  G06F30/27 ,  G05B19/4097 ,  G06F30/10 ,  G06N3/045

CPC classification number: G05B13/027 ,  G06F30/27 ,  G05B19/4097 ,  G06F30/10 ,  G06N3/045 ,  G05B2219/35167 ,  G05B2219/35134

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design and manufacture of physical structures using toolpaths generated by reinforcement learning for use with subtractive manufacturing systems and techniques, include: obtaining, in a computer aided design or manufacturing program, a three dimensional model of a manufacturable object; generating toolpaths that are usable by a computer-controlled manufacturing system to manufacture at least a portion of the manufacturable object by providing at least a portion of the three dimensional model to a machine learning algorithm that employs reinforcement learning, wherein the machine learning algorithm includes one or more scoring functions that include rewards that correlate with desired toolpath characteristics comprising toolpath smoothness, toolpath length, and avoiding collision with the three dimensional model; and providing the toolpaths to the computer-controlled manufacturing system to manufacture at least the portion of the manufacturable object.

公开(公告)号：US11782396B2

公开(公告)日：2023-10-10

申请号：US17153266

申请日：2021-01-20

Applicant: Autodesk, Inc.

Inventor： David Patrick Lovell ,  Akmal Ariff Bin Abu Bakar ,  Saaras Mehan

IPC: G05B13/02 ,  G06F30/27 ,  G06N3/045 ,  G05B19/4097 ,  G06F30/10

CPC classification number: G05B13/027 ,  G05B19/4097 ,  G06F30/10 ,  G06F30/27 ,  G06N3/045 ,  G05B2219/35134 ,  G05B2219/35167

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design and manufacture of physical structures using toolpaths generated by reinforcement learning for use with subtractive manufacturing systems and techniques, include: obtaining, in a computer aided design or manufacturing program, a three dimensional model of a manufacturable object; generating toolpaths that are usable by a computer-controlled manufacturing system to manufacture at least a portion of the manufacturable object by providing at least a portion of the three dimensional model to a machine learning algorithm that employs reinforcement learning, wherein the machine learning algorithm includes one or more scoring functions that include rewards that correlate with desired toolpath characteristics comprising toolpath smoothness, toolpath length, and avoiding collision with the three dimensional model; and providing the toolpaths to the computer-controlled manufacturing system to manufacture at least the portion of the manufacturable object.

公开(公告)号：US20210397142A1

公开(公告)日：2021-12-23

申请号：US17153266

申请日：2021-01-20

Applicant: Autodesk, Inc.

Inventor： David Patrick Lovell ,  Akmal Ariff Bin Abu Bakar ,  Saaras Mehan

IPC: G05B13/02 ,  G06F30/27 ,  G06N3/04 ,  G06F30/10 ,  G05B19/4097

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design and manufacture of physical structures using toolpaths generated by reinforcement learning for use with subtractive manufacturing systems and techniques, include: obtaining, in a computer aided design or manufacturing program, a three dimensional model of a manufacturable object; generating toolpaths that are usable by a computer-controlled manufacturing system to manufacture at least a portion of the manufacturable object by providing at least a portion of the three dimensional model to a machine learning algorithm that employs reinforcement learning, wherein the machine learning algorithm includes one or more scoring functions that include rewards that correlate with desired toolpath characteristics comprising toolpath smoothness, toolpath length, and avoiding collision with the three dimensional model; and providing the toolpaths to the computer-controlled manufacturing system to manufacture at least the portion of the manufacturable object.

公开(公告)号：US20210034961A1

公开(公告)日：2021-02-04

申请号：US16524912

申请日：2019-07-29

Applicant: Autodesk, Inc.

Inventor： David Patrick Lovell ,  Daniela Sofia Seixas Sousa ,  Chin-Yi Cheng

IPC: G06N3/08 ,  G06F17/50 ,  G05B19/4097

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided repair of physical structures include: generating a two dimensional difference image from a first three dimensional model of at least one actual three dimensional surface of a manufactured object, and a second three dimensional model of at least one source three dimensional surface used as input to a manufacturing process that generated the manufactured object; obtaining from an image-to-image translation based machine learning algorithm, trained using pairs of input images representing deformed and deformed plus surface defected added versions of a nominal three dimensional surface, a translated version of the two dimensional image; generating from the translated version of the two dimensional image a third three dimensional model of at least one morphed three dimensional surface corresponding to the at least one source three dimensional surface. Further, defects can be removed based on the third three dimensional model.