Omron Corporation

Kennosuke Hayashi

Yohei Okawa

Yoshiya Shibata

Takeshi Kojima

Yoshihisa Ijiri

Chisato Saito

Haruka Fujii

Akane Nakashima

Naoki Tsuchiya

Sakon Yamamoto

Yu Maruyama

Kin Chung Denny Fu

Yuki Yamaguchi

Yu Tomono

Yasuhiro Ohnishi

Toshihiro Moriya

Masaki Suwa

The observation update unit increases a weight of a particle for a particle representing a position and a posture closer to a position and a posture of an operation object indicated by an observation result, and increases a weight of a corresponding particle for a particle closer to a state in which an object of interest and the operation object arranged in a position and a posture represented by each of particles are in contact with each other in a virtual space where shapes and a relative positional relationship of the object of interest and the operation object are expressed in a case in which the observation result indicates that the contact has occurred.

Robot control device, robot control method, and robot control program

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 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.

Model generation apparatus, model generation method, control apparatus, and control method

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

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.

Control apparatus, control method, and computer-readable storage medium storing a control program

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

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.

Image determination device, image determination method, and non-transitory computer readable medium storing program

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.

Image determination device, training method and non-transitory computer readable medium storing program

An image determination device includes: a training model which outputs, on the basis of an image to be examined, output data indicating a determination result about the image; a training part which trains the training model to output, by using training data including a training image and label data, output data indicating the label data associated with the training image, when the training image is input to the training model; a dividing part which divides the training data into a plurality of pieces of sub-training data; a measurement part which measures accuracy of determination when the training part trains the training model by using each of the plurality of pieces of sub-training data; and selection part which selects at least any one among the plurality of pieces of sub-training data on the basis of the accuracy of determination.

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 device sets a relative relation amount between a plurality of target objects that are to be final objectives, repeatedly acquires observation data from a sensor and calculates the relative relation amount between the plurality of target objects existing in the environment from the acquired observation data. Further, the control device determines a series of the relative relation amounts in a state that is to be an objective from the relative relation amount at a time point at which control of the behavior starts until the relative relation amount as the final objectives is realized, and repeatedly determines control instructions so as to change the relative relation amount in a present state calculated from the latest observation data into the relative relation amount in a state of an objective to be transitioned to next. Then, the control device outputs the determined control instruction to a robot device.

Control device, control method, and non-transitory computer-readable storage medium

A path planning apparatus is provided with a path planning unit that generates a path of a robot using a plurality of different path planning methods that respectively correspond to a plurality of different constraints determined from the posture of the robot and the characteristics of one or more obstacles that obstruct movement of the robot, an acquisition unit that acquires posture information indicating an initial posture of a robot for which a path is to be generated and a target posture of the robot, and obstacle information indicating a target obstacle that obstructs movement of the robot from the initial posture to the target posture, and a controller that controls the path planning unit so as to generate a path of the robot using a path planning method corresponding to a constraint determined from the posture information and the obstacle information acquired by the acquisition unit.

Path planning apparatus, path planning method, and path planning program

A motion generation device may be for generating a movement for changing the robot from a first orientation to a second orientation, and include a first acquisition unit that acquires first orientation information that specifies the first orientation and second orientation information that specifies the second orientation, a second acquisition unit that acquires at least one priority item regarding the movement for changing from the first orientation to the second orientation, and a movement generation unit that generates a motion of the robot that includes a movement path along which the robot moves from the first orientation to the second orientation, based on the first orientation information, the second orientation information, and the priority item that were acquired.

Motion generation method, motion generation device, system, and computer program

A control device assumes that observation light observed by an imaging device is composite light of primary reflection light and secondary reflection light. The control device acquires three or more samples of a brightness amplitude value of the observation light, calculates a phase error caused by the secondary reflection light using these samples, calculates a corrected phase value by correcting a phase value of the observation light using the phase error, and calculates a three-dimensional position of the measurement point on the measurement object based on the corrected phase value.

Growing community of inventors

Kizugawa, Japan

Kennosuke Hayashi