A teaching method for generating an operation program of a robot based on an operation in which an operator sequentially moves a plurality of objects to an arrangement region and arranges the objects so as to form a target arrangement pattern, the teaching method including an imaging step of imaging the object moved to the arrangement region in the operation, a recognizing step of recognizing a position of the object imaged in the imaging step, an estimating step of estimating candidate arrangement patterns based on the position of the object recognized in the recognizing step, and a display step of displaying the candidates estimated in the estimating step.

A robot image display method includes (a) a step of recognizing the position and the posture of a base of a robot from a base section image of a base section for teaching, (b) a step of recognizing the position and the posture of a finger section of the robot from a finger section image of a finger section for teaching, (c) a step of calculating angles of one or more joints of the robot from the position and the posture of the base and the position and the posture of the finger section, and (d) a step of displaying, in a virtual space, a three-dimensional image of the robot in a state in which the joints are at the angles calculated in the step (c).

A robot image display method includes (a) a step of recognizing the position and the posture of a base of a robot from a base section image of a base section for teaching, (b) a step of recognizing the position and the posture of a finger section of the robot from a finger section image of a finger section for teaching, (c) a step of calculating angles of one or more joints of the robot from the position and the posture of the base and the position and the posture of the finger section, and (d) a step of displaying, in a virtual space, a three-dimensional image of the robot in a state in which the joints are at the angles calculated in the step (c).

There is provided a method and computer program product for programming a robot by manually operating it in gravity-compensation kinesthetic-guidance mode. More specifically there is provided method and computer program product that uses kinesthetic teaching as a demonstration input modality and does not require the installation or use of any external sensing or data-capturing modules. It requires a single user demonstration to extract a representation of the program, and presents the user with a series of easily-controllable parameters that allow them to modify or constrain the parameters of the extracted program representation of the task.

There is provided a method and computer program product for programming a robot by manually operating it in gravity-compensation kinesthetic-guidance mode. More specifically there is provided method and computer program product that uses kinesthetic teaching as a demonstration input modality and does not require the installation or use of any external sensing or data-capturing modules. It requires a single user demonstration to extract a representation of the program, and presents the user with a series of easily-controllable parameters that allow them to modify or constrain the parameters of the extracted program representation of the task.

Provided is an picking system which can suitably extract a workpiece by machine learning. The picking system is provided with: a robot which has a hand; an acquisition unit which acquires a two-dimensional camera image of an area where a plurality of workpieces are present; a teaching unit which can display the two-dimensional camera image and teach an picking position of a target workpiece to be extracted by the hand from among the plurality of workpieces; a training unit which generates a trained model on the basis of the two-dimensional camera image and the taught picking position; an inference unit which infers the picking position of the target work on the basis of the trained model and the two-dimensional camera image; and a control unit which controls the robot to extract the target workpiece by means of the hand on the basis of the inferred picking position.

The inventive concept provides a substrate treating apparatus. The substrate treating apparatus includes a chamber having an entrance for taking in and taking out a substrate at a side wall; a support unit provided inside of the chamber and supporting the substrate; an imaging unit for imaging a substrate being taken in by a transfer robot through the entrance; and a controller is configured to control a position of the transfer robot based on an image data from the imaging unit.

A control method for a robot system having a robot arm and executing an operation mode of the robot arm having an execution mode in which a motion program is executed and a teaching mode in which the motion program is taught, includes setting an upper limit velocity of a motion velocity of the robot arm to a first velocity when the operation mode is the execution mode, and setting the upper limit velocity to a second velocity lower than the first velocity when the operation mode is the teaching mode.

A teaching system includes a sensor that detects the intensity of reflected light and at least one processor configured to: receive inputs and perform a generation of teaching data that enables laser machining at all machining points by using a laser beam having an angle larger than or equal to the minimum value and smaller than the maximum value; determine whether or not intensities of reflected light at all the machining points include an intensity exceeding a predetermined threshold value; increase the minimum value at a corresponding machining point by a predetermined increment if the determination result indicates that the threshold value is exceeded; and repeat the generation of the teaching data using a most-recently adjusted minimum value, the determination, and adjustment of the minimum value until it is determined that the threshold value is not exceeded.

A teaching system includes a sensor that detects the intensity of reflected light and at least one processor configured to: receive inputs and perform a generation of teaching data that enables laser machining at all machining points by using a laser beam having an angle larger than or equal to the minimum value and smaller than the maximum value; determine whether or not intensities of reflected light at all the machining points include an intensity exceeding a predetermined threshold value; increase the minimum value at a corresponding machining point by a predetermined increment if the determination result indicates that the threshold value is exceeded; and repeat the generation of the teaching data using a most-recently adjusted minimum value, the determination, and adjustment of the minimum value until it is determined that the threshold value is not exceeded.