A robot calibrating apparatus calibrating a command value for a robot body 2 whose position and orientation is controlled based on the command value, includes an operating unit configured to calculate a calibrating function of calibrating the command value, based on the difference between an ideal position and orientation of the robot body 2 and an actual position and orientation of the robot body 2. The ideal position and orientation is operated based on a command value .sup.RH.sub.T.sup.com for calibration used during calibration or on a control result value which is a result of control according to the command value. The actual position and orientation is operated based on a measurement value .sup.RH.sub.T.sup.meas for calibration acquired by a camera 3 arranged at a prescribed relative position and orientation with respect to the robot body 2 during the robot body 2 being controlled according to the command value for calibration.

An optical scale includes a tabular base material and an optical pattern provided above a principal plane of the base material and including a first region where a resin layer including photosensitive resin is formed and a second region where the resin layer is not formed. The optical pattern includes a pigment.

A robot controller, a measurement system and a calibration method, by which measurement regions for improving positioning accuracy of a robot can be appropriately generated. First and second measurement regions are specified in a movable range of the robot, the calibration of a mechanical parameter of the robot is executed in each measurement region, and calibration results are stored as first and second calibration results. When the difference between the calibration results exceeds a predetermined threshold, a third measurement region is specified between the first and second measurement regions, and the calibration is further executed in the third measurement region. The result of the further calibration is stored as a third calibration result.

A system and method for robustly calibrating a vision system and a robot is provided. The system and method enables a plurality of cameras to be calibrated into a robot base coordinate system to enable a machine vision/robot control system to accurately identify the location of objects of interest within robot base coordinates.

When a force sensor on a robot arm detects that the force of contact between an end of a calibration device and a calibration plate reaches a threshold, the robot arm stops, and the end of the calibration device performs marking at the contact position between the end of the calibration device and the calibration plate. The robot arm moves upward and stops at a position where the end of the robot arm is at a predetermined height. At this position, a camera at the end of the robot arm photographs marks on the calibration plate, records the coordinates of the marks in the camera coordinate system, and records the coordinates of the end of the calibration device in the robot coordinate system. A calibration transformation matrix is calculated according to the recorded coordinates of at least three marks.

An autonomous system can detect out-of-distribution (OOD) data in robotic grasping systems, based on evaluating image inputs of the robotic grasping systems. Furthermore, the system makes various decisions based on detecting the OOD data, so as to avoid inefficient or hazardous situations or other negative consequences (e.g., damage to products). For example, the system can determine whether a suction-based gripper is optimal for grasping objects in a given scene, based at least in part on determining whether an image defines OOD data.

A robot device includes an optical detection device configured to detect a surrounding area image of an area surrounding the robot device. The robot device further includes a control device storing a predetermined reference marking and a predetermined reference position of the reference marking. The control device is configured to detect an image detail that shows the reference marking of the interaction machine in the surrounding area image of the area surrounding the robot device, detect the predetermined reference marking in the image detail, determine a distortion of the predetermined reference marking in the image detail, determine a spatial position of the reference marking, determine an interaction machine position of at least one element of the interaction machine with respect to the robot device from the spatial position of the reference marking, and subject the robot device to closed-loop control and/or open-loop control.

This invention provides a system and method for guiding the workpieces to optimal positions to train an assembly system that is generally free of the use of a CMM or similar metrology device. The system and method expresses the image features of the workpieces, when they are in their respective stations, in a common coordinate system. This ability allows a user to visualize the result of assembling the workpieces without actually assembling them, in a virtual assembly. The virtual assembly assists guiding placement of workpieces in respective stations into a desired relative alignment. The system and method illustratively generates a composite image using the images from cameras used in guiding the workpieces that helps the user visualize how the part would appear following assembly. The user can reposition the images of workpieces in their respective stations until the composite image has a desired appearance.

This method is for calibrating a coordinate system of an image capture device and a coordinate system of a robot arm in a robot system that includes a display device, the image capture device, and the robot arm to which one of the display device and the image capture device is fixed, the robot arm having a drive shaft. The method includes: acquiring first captured image data based on first image data; acquiring second captured image data based on second image data different from the first image data; and calibrating the coordinate system of the image capture device and the coordinate system of the robot arm, using the first captured image data and the second captured image data.

Described are machine vision systems and methods for simultaneous kinematic and hand-eye calibration. A machine vision system includes a robot or motion stage and a camera in communication with a control system. The control system is configured to move the robot or motion stage to poses, and for each pose: capture an image of calibration target features and robot joint angles or motion stage encoder counts. The control system is configured to obtain initial values for robot or motion stage calibration parameters, and determine initial values for hand-eye calibration parameters based on the initial values for the robot or motion stage calibration parameters, the image, and joint angles or encoder counts. The control system is configured to determine final values for the hand-eye calibration parameters and robot or motion stage calibration parameters by refining the hand-eye calibration parameters and robot or motion stage calibration parameters to minimize a cost function.