Other

Kabushiki Kaisha Yaskawa Denki

Ai Cube Inc.

Koji Sokabe

Keita Shimamoto

Ryokichi Hirata

Masaru Adachi

Yuichi Sasaki

Hiroyuki Handa

Takeshi Hatanaka

Keisuke Nakamura

Shota Ishikawa

Antoine Pasquali

Masayuki Fujita

Thomas Wilmotte

Junya Yamauchi

Kosei Noda

A robot control system includes circuitry configured to: generate a command to a robot; receive a frame image in which a capture position changes according to a motion of the robot based on the command; extract a partial region from the frame image according to the command; superimpose a delay mark on the partial region to generate an operation image; and display the operation image on a display device, so as to represent a delay of the motion of the robot with respect to the command.

Generation of image for robot operation

A robot control system includes circuitry configured to: acquire an input command value indicating a manipulation of a robot by a subject user; acquire a current state of the robot and a target state associated with the manipulation of the robot; determine a state difference between the current state and the target state; acquire from a learned model, a degree of distribution associated with a motion of the robot, based on the state difference, wherein the learned model is generated based on a past robot manipulation; set a level of assistance to be given during the manipulation of the robot by the subject user, based on the degree of distribution acquired; and generate an output command value for operating the robot, based on the input command value and the level of assistance.

Assistance for robot manipulation

A robot control system includes circuitry configured to: determine a necessity of assisting a robot to complete an automated work, based on environment information of the robot; select a remote operator from candidate remote operators based on stored operator data in response to determining that it is necessary to assist the robot to complete the automated work; transmit the environment information to the selected remote operator via a communication network; receive an operation instruction based on the environment information from the selected remote operator via the communication network; and control the robot to complete the automated work based on the operation instruction.

Robot control system and robot control method

To generate a more appropriate path, provided is a robot path generation device including circuitry configured to: hold a track planning module learning data set, in which a plurality of pieces of path data generated based on a motion constraint condition of a robot, and evaluation value data, which corresponds to each of the plurality of pieces path data and is a measure under a predetermined evaluation criterion, are associated with each other; and generate, based on a result of a machine learning process that is based on the track planning module learning data set, a path of the robot between a set start point and a set end point, which are freely set.

Robot path generating device and robot system

A gripping system includes a hand that grips a workpiece, a robot that supports the hand and changes at least one of a position and a posture of the hand, and an image sensor that acquires image information from a viewpoint interlocked with at least one of the position and the posture of the hand. Additionally, the gripping system includes a construction module that constructs a model by machine learning based on collection data. The model corresponds to at least a part of a process of specifying an operation command of the robot based on the image information acquired by the image sensor and hand position information representing at least one of the position and the posture of the hand. An operation module executes the operation command of the robot based on the image information, the hand position information, and the model, and a robot control module operates the robot based on the operation command of the robot operated by the operation module.

Gripping system with machine learning

Growing community of inventors

Fukuoka, Japan

Koji Sokabe