This control device calculates a parameter, which represents transformation between a first coordinate system for image information obtained by capturing an image of a target to be controlled and a second coordinate system for defining the movement of the target to be controlled, by using position information indicating the position of the target to be controlled in the first coordinate system and position information indicating the position of the target to be controlled in the second coordinate system. Further, the control device uses image information containing the target to be controlled and the calculated parameter to calculate the position information of the target to be controlled for the second coordinate system, and controls the target to be controlled on the basis of the calculated position information of the target to be controlled.

A calibration pod for calibrating a robotic wafer pod handling apparatus includes a pod body configured for handling by the robotic pod handling apparatus, at least one laser disposed on a bottom of the pod body, and a power module disposed on or in the pod body and operatively connected to power the at least one laser. In a manufacturing method, the pod body comprises a wafer carrier for carrying a cassette of semiconductor wafers, which has a bottom with a plurality of holes for aligning placement of the wafer carrier in a load port of a semiconductor device fabrication facility. The at least one laser here includes a plurality of lasers corresponding to the plurality of holes in the bottom of the wafer carrier, and each laser is mounted in a respective hole of the bottom of the wafer carrier.

A model generator implements a data-driven approach to generating a robot model that describes one or more physical properties of a robot. The model generator generates a set of basis functions that generically describes a range of physical properties of a wide range of systems. The model generator then generates a set of coefficients corresponding to the set of basis functions based on one or more commands issued to the robot, one or more corresponding end effector positions implemented by the robot, and a sparsity constraint. The model generator generates the robot model by combining the set of basis functions with the set of coefficients. In doing so, the model generator disables specific basis functions that do not describe physical properties associated with the robot. The robot model can subsequently be used within a robot controller to generate commands for controlling the robot.

Methods and apparatuses for calibrating an end effector feature for robotic assembly are disclosed. A method in accordance with an aspect of the present disclosure may comprise obtaining a first set of images of an effector feature coupled to an engagement feature of a robot, the first set of images including at least a first image of the effector feature from a first perspective and a second image of the effector feature from a second perspective, detecting an edge in each of the first image and the second image, determining a coordinate position of the effector feature in a first coordinate system based on the edge of the first image and the edge of the second image, and calibrating the robot based on the coordinate position of the effector feature in the first coordinate system.

A method for characterising the environment of a robot, the robot having a flexible arm having a plurality of joints, a datum carried by the arm, a plurality of drivers arranged to drive the joints to move and a plurality of position sensors for sensing the position of each of the joints, the method comprising: contacting the datum carried by the arm with a first datum on a second robot in the environment of the first robot, wherein the second robot has a flexible arm having a plurality of joints, and a plurality of drivers arranged to drive those joints to move; calculating in dependence on the outputs of the position sensors a distance between a reference location defined in a frame of reference local to the robot and the first datum; and controlling the drivers to reconfigure the first arm in dependence on at least the calculated distance.

A control apparatus causes a robot device to move a suction head to a predetermined position at which a workpiece is fed and attempt to pick up the workpiece with the suction head at the predetermined position. Upon determining that the suction head has yet to pick up the workpiece, the control apparatus causes the robot device to rotationally move the suction head spirally in a horizontal direction while causing the suction head to perform a suction operation for the workpiece, and estimates a direction in which the workpiece is located with respect to the predetermined direction based on a change in compressed air pressure during the rotational movement of the suction head.

In one embodiment, a method includes by a robotic system: sending, by an automatic tuning controller, driving commands to actuators of the robotic system, performing, for each of the actuators, one or more measurements of an actual pose of the respective actuator in response to the driving commands, generating, for each of the actuators, one or more configuration parameters for the respective actuator based on the one or more measurements, and storing the configuration parameters for the actuators in a data store of the robotic system.

An apparatus and method for calibrating or teaching a robot, the apparatus includes a reflective photoelectric sensor arranged on a gripper of the robot and a controller. The controller is configured to: cause the reflective photoelectric sensor to scan over a target object; monitor changes in an output signal from the reflective photoelectric sensor; for each detected change exceeding a threshold, determine a coordinate of a gripping component on the gripper in a robot coordinate system, to obtain a set of coordinates; determine a position of the target object in the robot coordinate system based on the set of coordinates and a predefined offset value (PO) between the reflective photoelectric sensor and the gripping component; and store the position of target object for future use in assembling objects.

Provided is a mastering method that can be easily carried out with respect to a processing tool mounted to an arm tip portion of a robot having a driving shaft. The present invention provides a processing tool mastering method for mastering a processing tool by: controlling a driving unit of a multi-joint robot which carries, at an arm tip portion, a processing tool for performing a predetermined process on a workpiece and which is provided with a plurality of driving units for driving one or a plurality of driving shafts; and controlling a processing position of the processing tool with respect to the workpiece. The mastering method comprises obtaining, from the movement of the robot, reference direction information which is information pertaining to a reference direction of the robot, and carrying out mastering of the processing tool on the basis of the reference direction information thus obtained.

An arrangement for the model-based calibration of a mechanism in a workspace with calibration objects that are either directed laser radiation patterns together with an associated laser radiation-pattern generator or radiation-pattern position sensors. Functional operation groups made up of at least one laser radiation pattern and at least one position sensor interact in such a way when a radiation pattern impinges on the sensor that measured sensor position information values are passed along to computing devices that determine the parameters of a mathematical mechanism model with the aid of these measured values. In the process, at least two different functional operation groups are used to calibrate the mechanism, and at least two calibration objects from different functional operation groups are rigidly connected to one another.