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 image processing parameter related to image processing on an image of a target object captured by a camera, by using machine learning, detect the target object on the basis of an image on which the image processing is performed by using the calculated image processing parameter, and control a robot on the basis of a detection result of the target object.

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 method for the start-up operation of a multi-axis system, the multi-axis system having segments which are movable by a controller in one or more axes, and a tool which is connected to one of the segments and is movable and drivable to a specified position by the controller. The method includes assigning a workspace and a safe space to the multi-axis system, arranging optical markers in an environment, making it possible for an augmented reality system to determine the position of a camera system which records the multi-axis system within the environment, defining a bounding body for each of the components such that the bounding body encloses the component, calculating a position of the bounding body during the movement of the multi-axis system, visualizing the bounding bodies together with an image recorded by the camera system, and checking whether the bounding body intersects with the safe space.

In a method for the start-up operation of a multi-axis system, with the multi-axis system including, as components, segments connected via respective joints and are movable in one or more axes, and a tool, connected to one of the segments and is movable to a specified position, optical markers are arranged in the environment. Position coordinates of the optical markers in a first, global coordinate system are ascertained and stored in the controller. The environment is captured as image data by a camera system. The image data are transmitted to an AR system and visualized in an output apparatus. The optical markers and virtual markers are represented during the visualization of the image data, wherein a respective virtual marker is assigned to an optical marker. A check is performed as to whether an optical marker and the virtual marker overlay one another in the visualized image data.

Data about a physical object in a real-world environment is automatically collected and labeled. A mechanical device is used to maneuver the object into different poses within a three-dimensional workspace in the real-world environment. While the object is in each different pose an image of the object is input from one or more sensors and data specifying the pose is input from the mechanical device. The image of the object input from each of the sensors for each different pose is labeled with the data specifying the pose and with information identifying the object. A database for the object that includes these labeled images can be generated. The labeled images can also be used to train a detector and classifier to detect and recognize the object when it is in an environment that is similar to the real-world environment.

Techniques are described for machining flat workpieces, such as metal sheets, or three-dimensional workpieces on a processing machine, such as a machine tool or laser cutting machine, including capturing a live image of a workpiece to be machined with an image capturing device for capturing two-dimensional images; displaying at least one workpiece machining operation to be performed in the live image of the workpiece by a predetermined forward transformation of the workpiece machining operation from the three-dimensional machine coordinate system into the two-dimensional live-image coordinate system; repositioning the workpiece machining operation to be performed in the live image of the workpiece; and performing the workpiece machining operation on the workpiece by a predetermined inverse transformation of the repositioned workpiece machining operation from the two-dimensional live-image coordinate system into the three-dimensional machine coordinate system.

The invention is related to a method and arrangement for calibrating the camera of an eye tracking device and compensate for a potential angular offset of the camera. The method comprises: the steps of capturing an eye image of a user, wherein the eye image contains a plurality of glints created by a plurality of illuminators in the eye tracking system; detecting glints in the eye image; projecting illuminator positions onto the eye image to determine expected glint positions; determining an angular offset between expected glint positions and detected glint positions for corresponding pairs of expected and detected glint positions; determining the angular correction for the eye tracking camera using the determined angular offset angle; and applying the angular correction for the eye tracking camera to an eye tracker camera model.

In a method for replicating performance of an automated visual inspection (AVI) station, a mimic AVI station that performs one or more AVI functions of the AVI station is constructed. One or more container images are captured by an imaging system of the AVI station while a container is illuminated by an illumination system of the AVI station, and one or more additional container images are captured by a mimic imaging system of the mimic AVI station. The method also includes identifying, by one or more processors, one or more differences between the one or more additional container images and the one or more container images, generating, by the one or more processors, a visual indication of the difference(s) and/or one or more suggestions for modifying the mimic AVI station, and modifying the mimic AVI station based on the visual indication.

A system is disclosed for providing extrinsic calibration of a camera to a relative working environment of a programmable motion device that includes an end-effector. The system includes a fiducial located at or near the end-effector, at least one camera system for viewing the fiducial as the programmable motion device moves in at least three degrees of freedom, and for capturing a plurality of images containing the fiducial, and a calibration system for analyzing the plurality of images to determine a fiducial location with respect to the camera to permit calibration of the camera with the programmable motion device.

An unloading method unloads a sheet metal machining product produced on a sheet metal working machine. The method includes: supplying the machining product to a supply device for unloading with a position and an orientation defined in a coordinate system of the supply device; moving an unloading member of the unloading device with a transfer movement into a transfer position on the machining product supplied to the supply device for unloading; calibrating, before the machining product is unloaded from the supply device, the numerical unloading control of the unloading device; and unloading the machining product from the supply device by the unloading device. The unloading of the machining product is controlled by the programmable numerical control which includes the programmable numerical unloading control of the unloading device and in which the coordinate system of the supply device and the similar coordinate system of the numerical unloading control are stored.