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公开(公告)号：US20210182459A1
公开(公告)日：2021-06-17
申请号：US17269531
申请日：2019-10-11
Applicant: OMRON Corporation
Inventor： Yohei OKAWA , Yoshiya SHIBATA , Chisato SAITO , Kennosuke HAYASHI , Kin Chung Denny FU , Yuki YAMAGUCHI
Abstract: Provided are a simulation device, a simulation method, and a computer-readable storage medium, which reduce a computation load required for simulation of movement of an operation subject. This simulation device is provided with: a first setting unit that sets framing conditions for a model representing the operation subject; a second setting unit that sets conditions for external force applied to the operation subject; a first simulation unit that simulates the movement of the operation subject under the framing conditions and the conditions for external force; a generation unit that generates learning data; and a learning unit that, by supervised learning using the learning data, generates a learning model that takes the framing conditions, the conditions for external force, and the initial conditions of the plurality of representative points as input and outputs data representing the movement of the plurality of representative points.
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公开(公告)号：US20210256302A1
公开(公告)日：2021-08-19
申请号：US17270450
申请日：2019-11-14
Applicant: OMRON Corporation
Inventor： Naoki TSUCHIYA , Yoshihisa IJIRI , Yu MARUYAMA , Yohei OKAWA , Kennosuke HAYASHI , Sakon YAMAMOTO
Abstract: An image determination device includes feature extractors which output, on the basis of an image to be examined, each piece of feature data indicating a specific feature of the image; a first training part which trains a first determiner so as to output first output data indicating first label data associated with a first training image on the basis of first feature data output when the first training image is input to the feature extractors; a second training part which trains a second determiner so as to output second output data indicating second label data associated with a second training image on the basis of second feature data output when the second training image is input to the feature extractors; and an output part which outputs, on the basis of the first output data and the second output data, output data indicating an overall determination result about an image.
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公开(公告)号：US20210049033A1
公开(公告)日：2021-02-18
申请号：US16978707
申请日：2019-03-01
Applicant: OMRON Corporation
Inventor： Yohei OKAWA , Yoshiya SHIBATA , Chisato SAITO , Kennosuke HAYASHI , Yu TOMONO
Abstract: The image processing device is provided with: a first input unit which, with respect to one or more virtual models including a virtual model of an operation machine, receives an input of a first parameter for identifying a type; a second input unit which receives an input of a second parameter relating to a stochastic distribution having, as a random variable, a characteristic of an element constituting the one or more virtual models; a virtual model generation unit which, using the first parameter and the second parameter, generates the one or more virtual model stochastically; a determination unit which determines the correctness of an operation of the virtual model of the operation machine when operated in a virtual space including the one or more stochastically generated virtual models; and a learning unit which learns a control module for the operation machine for achieving a predetermined operation.
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4.发明申请公开(公告)号：US20220258336A1
公开(公告)日：2022-08-18
申请号：US17628244
申请日：2020-07-22
Applicant: OMRON Corporation
Inventor： Yohei OKAWA , Kennosuke HAYASHI , Yoshiya SHIBATA
Abstract: A model generation apparatus according to one or more embodiments may include: a data obtainer configured to obtain a plurality of learning datasets each including a combination of training data and true data, the training data indicating a positional relationship between two objects, the true data indicating whether the two objects come in contact with each other in the positional relationship; and a machine learning unit configured to train, through machine learning, a determination model using the obtained plurality of learning datasets to cause the determination model to output, in response to an input of training data included in each of the plurality of learning datasets, an output value fitting true data included in a corresponding learning dataset of the plurality of learning datasets.
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公开(公告)号：US20210331311A1
公开(公告)日：2021-10-28
申请号：US17269992
申请日：2019-10-18
Applicant: OMRON Corporation
Inventor： Kin Chung Denny FU , Yuki YAMAGUCHI , Yohei OKAWA , Kennosuke HAYASHI , Chisato SAITO , Yoshiya SHIBATA
Abstract: Provided is an image generation device capable of generating, on the basis of inputted images, a learning image for training an action of a robot which carries out a prescribed operation on a workpiece. The image generation device comprises: a first image acquisition unit which acquires a first image capturing a real operation space including the robot and not including the workpiece; a second image acquisition unit which acquires a second image in which a virtual operation space including a virtual robot corresponding to the robot and a virtual workpiece corresponding to the workpiece is rendered; and a learning apparatus so that, in response to an input of the first image and the second image, the apparatus outputs a third image obtained by transforming the second image such that at least the virtual robot included in the second image is made to approximate the robot included in the first image.
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Patent Agency Ranking
公开(公告)号：US20210326648A1
公开(公告)日：2021-10-21
申请号：US17270051
申请日：2019-10-24
Applicant: OMRON Corporation
Inventor： Naoki TSUCHIYA , Yoshihisa IJIRI , Yu MARUYAMA , Yohei OKAWA , Kennosuke HAYASHI , Sakon YAMAMOTO
Abstract: Provided is an image determination device. The image determination device is provided with: feature extractors which output, on the basis of an image to be examined, each piece of feature data indicating a specific feature of the image; a determiner which outputs, on the basis of the feature data output from the extractors, output data indicating the determination result pertaining to the image; and a training part which trains the determiner so as to output, output data indicating the label data associated with the training image on the basis of the feature data output when the training image is input to the extractors, wherein the training part further trains, by using new training data, the determiner so that the output data indicating the label data associated with the image is output by the determiner.
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公开(公告)号：US20210181728A1
公开(公告)日：2021-06-17
申请号：US17269534
申请日：2019-09-24
Applicant: OMRON Corporation
Inventor： Yuki YAMAGUCHI , Kennosuke HAYASHI , Kin Chung Denny FU , Yohei OKAWA , Chisato SAITO , Yoshiya SHIBATA
IPC: G05B19/418 , B25J9/16 , G06N20/20
Abstract: The disclosure is to constitute, while reducing a cost for collecting training data used in machine learning that makes a control module acquire an ability to control a robot device, the control module operatable in an actual environment by the machine learning. A learning device according to one aspect of the present invention executes machine learning of an extractor by using a first learning data set constituted by a combination of simulation data and first environmental information and a second learning data set constituted by a combination of actual data and second environmental information. Further, a learning device according to one aspect of the present invention executes machine learning of a controller by using a third learning data set constituted by a combination of third environmental information, state information, and a control command.
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8.发明申请公开(公告)号：US20220274255A1
公开(公告)日：2022-09-01
申请号：US17628271
申请日：2020-07-17
Applicant: OMRON Corporation
Inventor： Yohei OKAWA , Kennosuke HAYASHI , Yoshiya SHIBATA
IPC: B25J9/16
Abstract: A control apparatus according to one or more embodiments may calculate a first estimate value of the coordinates of an endpoint of a manipulator based on first sensing data obtained from a first sensor system, calculates a second estimate value of the coordinates of the endpoint of the manipulator based on second sensing data obtained from a second sensor system, and adjust a parameter value for at least one of a first estimation model or a second estimation model to reduce an error between the first estimate value and the second estimate value based on a gradient of the error.
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9.发明申请公开(公告)号：US20210323146A1
公开(公告)日：2021-10-21
申请号：US17269997
申请日：2019-10-28
Applicant: OMRON Corporation
Inventor： Kennosuke HAYASHI , Yohei OKAWA
Abstract: A robot control device 10 is provided with: a reading device 40 that reads a marker 21 attached to a robot 20 and markers 31 attached to individual objects 30; and a CPU 111 that performs image analysis concerning the individual positions of the robot 20 and the individual objects 30 in real space based on information read from the markers 21, 31, and that simulates the operation of the robot 20 while disposing three-dimensional shape models of the robot 20 and the individual objects 30 in a virtual space based on information indicating the positions of the robot 20 and the individual objects 30 in real space, information concerning the three-dimensional shape model of the robot 20, associated with the marker 21, and information concerning the three-dimensional shape models of the individual objects 30, associated with the individual markers 31.
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10.发明申请公开(公告)号：US20210323145A1
公开(公告)日：2021-10-21
申请号：US17269993
申请日：2019-10-31
Applicant: OMRON Corporation
Inventor： Kennosuke HAYASHI , Yohei OKAWA , Yuki YAMAGUCHI , Yoshiya SHIBATA
Abstract: A robot control device is provided to accept information (201) specifying an object 170) manipulated by a robot (20) from among objects of a plurality of kinds and accept information (202) specifying a target relative positional relationship between the specified object (70) and the distal end of a hand of the robot (20). The robot control device extracts the object (70) from image information (501) obtained by photographing the objects of the plurality of kinds and the surrounding environment thereof, generates information (301) indicating the position and orientation of the object (70), generates an action instruction (401) from the result of learning by a learning module (103), the action instruction (401) serving to match the relative positional relationship between the object (70) and the distal end of the hand of the robot (20) with the target relative positional relationship, and outputs the action instruction (401) to the robot (20).
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