Omron Corporation

Mitsubishi Gas Chemical Company, Inc.

Chisato Saito

Yoshiya Shibata

Kennosuke Hayashi

Yohei Okawa

Yoshihiro Kato

Masanobu Sogame

Yoshinori Mabuchi

Kin Chung Denny Fu

Yuki Yamaguchi

Toshihiro Moriya

Daisuke Ueyama

Yu Tomono

Yoshihisa Ijiri

Haruna Shimakawa

Yumi Tsutsumi

Kazutoshi Tanaka

Yukihisa Karako

Felix Vondrigalski

Masashi Hamaya

Masayoshi Abe

A simulation device that reduces the computation load required for simulation of the movement of an operation subject is provided. The simulation device includes a processor configured to set framing conditions for a model representing the operation subject, set conditions for external force applied to the operation subject, simulate the movement of the operation subject under the framing conditions and the conditions for external force, generate learning data that includes data representing the framing conditions, the conditions for external force, and the movement of representative points located on the surface of the operation subject during simulation of the movement of the operation subject, and by supervised learning using the learning data, generate a learning model that takes the framing conditions, the conditions for external force, and the initial conditions of the representative points as input and outputs data representing the movement of the representative points.

Simulation of liquid objects manipulated by robots using supervised learning

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.

Image generation device, robot training system, image generation method, and non-transitory computer readable storage medium

A calculation device, a calculation method, and a storage medium are provided. The present invention is provided with: a first calculation unit which, with respect to input data, performs calculations relating to predetermined processing by using a first model in which a corresponding relationship between input data and output data changes by performing machine learning that uses learning data, and outputs a first output; a second calculation unit which, with respect to input data, performs calculations relating to predetermined processing using a second model for which the correspondence relationship between input data and output data is fixed, and outputs a second output; and a comparison unit which, on the basis of a comparison result obtained by comparing the first output and the second output with a prescribed determination standard, outputs the first output, the second output, or a third output that is a combination of the first and second outputs.

Calculation device, calculation method, and storage medium

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.

Learning device, control device, learning method, and recording medium

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.

Information processing device, information processing method, and non-transitory computer-readable storage medium

A control apparatus of a robot may include a state obtaining unit configured to obtain state observation data including flexible related observation data, which is observation data regarding a state of at least one of a flexible portion, a portion of the robot on a side where an object is gripped relative to the flexible portion, and the gripped object; and a controller configured to control the robot so as to output an action to be performed by the robot to perform predetermined work on the object, in response to receiving the state observation data, based on output obtained as a result of inputting the state observation data obtained by the state obtaining unit to a learning model, the learning model being learned in advance through machine learning and included in the controller.

Control apparatus, robot, learning apparatus, robot system, and method

The purpose of the present invention is to provide a device for outputting holding detection results by a highly accurate simulation in consideration of parameters related to a holding member. A user enters workpiece information through an input UI unit. A selection control unit executes an automatic selection process of a suction pad based on the workpiece information input through the input UI unit, an automatic selection process of a workpiece physical model, an automatic selection process of a robot, and a confirmation process of a vibration tolerance, and then displays the selection results. The selection control unit determines whether there is a problem with the selection results based on an input instruction from the user.

Device for outputting holding detection results

A mobile manipulator includes a moving apparatus, a manipulator that is connected to the moving apparatus, a controller configured to control the moving apparatus and the manipulator, and an environment acquisition sensor configured to acquire predetermined environmental data originating from an environment at the movement destination to which the mobile manipulator is moved by the moving apparatus in association with a position at the movement destination, and the controller controls at least one of the moving apparatus and the manipulator based on the environmental data.

Mobile manipulator, method for controlling mobile manipulator, and program therefor

The present invention provides a resin composition which can simply provide, with good reproducibility, a laminate, a printed wiring board, and the like that not only have excellent heat dissipation properties but have good moldability, good mechanical drillability and excellent appearance, and a prepreg, a metal foil-clad laminate, and the like using the same. A resin composition having a cyanate ester compound (A), an epoxy resin (B), a first inorganic filler (C), a second inorganic filler (D), and a molybdenum compound (E), wherein an average particle diameter ratio of the first inorganic filler (C) to the second inorganic filler (D) is in a range of 1:0.02 to 1:0.2.

Resin composition, prepreg and laminate

The present invention provides a resin composition with which a laminate, a printed wiring board, and the like that not only have high thermal conductivity but have good moldability with the occurrence of cracks and voids suppressed can be implemented simply and with good reproducibility, and a prepreg, a laminate, a metal foil-clad laminate, and the like using the same. The resin composition of the present invention is a resin composition comprising at least a cyanate ester compound (A), an epoxy resin (B), a first inorganic filler (C), and a second filler (D), wherein an average particle diameter ratio of the first inorganic filler (C) to the second inorganic filler (D) is in the range of 1:0.02 to 1:0.2.

Resin composition, and prepreg and laminate using the same

To provide a prepreg resin composition which has good solubility in a solvent and with which moreover a cured product having excellent flame resistance and a low water absorption rate can be made simply and with good reproducibility, and a prepreg and a laminate and a printed wiring board and the like using the same. The prepreg resin composition of the present invention including at least a cyanate compound (A) obtained by cyanation of a phenol-modified xylene formaldehyde resin, an epoxy resin (B), and an inorganic filler.

Growing community of inventors

Tokyo, Japan

Chisato Saito