A robotic system validates brake bleeding by detecting one or more forces generated by a machine assembly acting to move a brake lever of a vehicle in order to open a valve of an air brake system of the vehicle. The system also detects displacement of the machine assembly as the machine assembly acts to move the brake lever, monitors one or more sounds generated one or more of during or after the machine assembly acts to move the brake lever, and determines that the brake lever has been moved to a position to open the valve of the air brake system to release the air brake system based on the one or more forces that are detected, the displacement that is detected, and/or the one or more sounds that are monitored.

A control apparatus according to one or more embodiments generates poses of the measurement device to measure an object, determines, for the measurement device, a measurement path including the poses to cause the measurement device to move along the measurement path including the poses and to measure the object, instructs the robot to move the measurement device along a movement path including the measurement path and instructs the measurement device to measure the object in the poses, recognizes the object using obtained measurement data, and determines the measurement path for the measurement device for a next operating cycle.

An interference avoidance device is provided with: a three-dimensional sensor that is attached to a tip portion of a robot arm and acquires a distance image of an area around a robot; a position data creating portion that converts coordinates of a nearby object in the distance image to coordinates on a robot coordinate system and creates the position data of the nearby object based on the coordinates of the nearby object on the robot coordinate system; a storage portion that stores the position data; and a control portion that controls the robot based on the robot coordinate system; and the control portion controls the robot to avoid interference of the robot with the nearby object, based on the position data stored in the storage portion.

A position calibration system and method are disclosed, in which a control unit is provided to control a positioner sensing module to scan a circular positioner provided on a positioning substrate in a first direction and a second direction so as to acquire midpoints of two scanned line segments and acquire an intersection of lines extending from the two center points in a direction perpendicular to the first and the second directions as a calibration reference point, which correspond to a centroid (a center) of the circular positioner. The calibration reference point functions as a reference point for positioning the positioning substrate with respect to the positioner sensing module and is stored in a memory unit. The calibration reference point can be used as a positioning point during installation of a machine and can also be used for calibration of a position of the machine.

A machining system includes a laser irradiation device, a camera that captures an image of a workpiece, and a display that displays the image captured by the camera. The machining system includes a robot control device that controls the camera and the display. The camera captures the image of the workpiece before machining. The robot control device calculates a laser-beam irradiation position on the workpiece and virtually displays the laser-beam irradiation position on the display so as to overlap the workpiece image captured by the camera.

A robot system includes a robot, a vision sensor, a controller, and an input unit. The vision sensor configured to measure a feature point and obtain a measured coordinate value. The controller configured to control the robot. The input unit configured to receive an input from a user toward the controller. The controller obtains, via the input unit, setting information data on a determination point which is different from the feature point. The robot system uses a coordinate value of the determination point and the measured coordinate value, and determines whether the robot is taking a target position and orientation.

A control device includes a processor that is configured to execute computer-executable instructions so as to control a robot, wherein the processor is configured to calculate an operation parameter related to an operation of a robot by using machine learning, and control the robot on the basis of the calculated operation parameter.

A control device includes a processor that is configured to execute computer-executable instructions so as to control a robot, wherein the processor is configured to calculate a force control parameter related to force control of a robot by using machine learning, and control the robot on the basis of the calculated force control parameter.

A system includes a machine assembly, an imaging sensor, an encoder, and one or more processors. The machine assembly is movable to actuate a brake lever of a vehicle in order to open a valve of an air brake system of the vehicle. The imaging sensor acquires perception information of a working environment that includes the brake lever. The encoder detects a displaced position of the machine assembly relative to a reference position of the machine assembly. The one or more processors detect a position of the brake lever relative to the machine assembly based on the acquired perception information and the detected displacement of the arm. The one or more processors generate a motion trajectory for the machine assembly that provides a path to the brake lever. The one or more processors drive movement of the machine assembly along the motion trajectory towards the brake lever.

Provided is a control system that controls an imaging condition of a camera equipped on a robot to capture an image in which a blur is suppressed.

The control system includes a robot control unit that controls a motion of the robot equipped with the camera, and a camera control unit that controls an imaging operation of the camera. The camera control unit determines an exposure time for suppressing a blur that occurs in a captured image of the camera within an allowable pixel number for the moving speed of the camera, and in a case where the camera control unit cannot set the exposure time, the camera control unit instructs the robot control unit to update a speed limit value of the robot.