Characteristics of surroundings are extracted from signals of sensors mounted on different of a stationary industrial robot and an absolute co-ordinate system and a map of the surroundings are determined simultaneously using a SLAM-algorithm for simultaneous localization and mapping, the map of the surroundings depicting the extracted characteristics and an absolute pose of a mobile part of the industrial robot being determined in the absolute co-ordinate system. The method transfers the technique of simultaneous localization and of establishing a map of characteristics of the surroundings, from the field of mobile robotics to the orientation of a stationary industrial robot. The method is based on the measurements of sensors attached to the mobile parts. Sensors which calculate the positions of the joints are also taken into consideration, and an absolute position and orientation is calculated even for imprecise or flexible industrial robots and for different loads.

A calibration device is provided. The calibration device includes a frame, a first optical sensing device, a second optical sensing device and a third optical sensing device. The frame includes a bottom plate and at least four sidewalls, wherein the sidewalls have a first grating hole, a second grating hole, a third grating hole and a fourth grating hole at a first height. The bottom plate has an image recognition pattern, a first measurement point, a second measurement point and a third measurement point.

A robot system includes a robot, a vision sensor, a target position generation circuit, an estimation circuit, and a control circuit. The robot includes an end effector and is configured to work via the end effector on a workpiece which is disposed at a relative position and which is relatively movable with respect to the end effector. The vision sensor is configured to take an image of the workpiece. The target position generation circuit is configured to, based on the image, generate a target position of the end effector at every generation interval. The estimation circuit is configured to, at least based on relative position information related to the relative position, estimate a change amount in the relative position at every estimation interval. The control circuit is configured to control the robot to move the end effector based on the target position and the change amount.

This invention provides a system and method that automatically decides motion parameters of hand-eye calibration, and conducts the calibration procedure with minimal human intervention. It automatically computes hand-eye calibration motion parameters and spatial positions during pre-calibration, whereby the calibration pattern can continuously remain inside, and covering, the entire field of view FOV of the vision system camera, providing a fully automatic hand-eye calibration process. This system and method advantageously operates in a robot-based hand-eye calibration environment and can compensate for a cantilever effect between the calibration target and the FOV. A hand-eye calibration computes the transformation from the robot coordinate space to the camera coordinate space. This generally avoids a need to manually move the robot through a set of spatial positions in which the camera then acquires images and locates calibration features on the object at each position to establish the relationship between the robot and camera.

A hand-eye calibration system and method are provided. The system includes a robot on which a small pattern is mounted, a camera configured to photograph the robot, a memory, and a processor configured to move the robot, acquire posture information of the moved robot, acquire an image from the camera, move the camera after performing the robot movement, the posture information acquisition, and the image acquisition a first predetermined number of times, and perform hand-eye calibration for the robot based on the posture information and the images, which are obtained by repeatedly performing of the robot movement, the posture information acquisition, the image acquisition, and the camera movement.

A method to control operation of a robot includes generating at least one virtual image by an optical 3D measurement system and with respect to a 3D measurement coordinate system, the at least one virtual image capturing a surface region of a component. The method further includes converting a plurality of point coordinates of the virtual image into point coordinates with respect to a robot coordinate system by a transformation instruction and controlling a tool element of the robot using the point coordinates with respect to the robot coordinate system so as to implement the operation.

A robot arm apparatus including: an arm unit made up of a plurality of links joined by one or a plurality of joint units, the arm unit is connectable to an imaging unit. An internal model including at least geometric information of the arm unit and focus position information of the imaging unit is updated based on internal model information acquired in a state in which the imaging unit is pointed at a reference point in a real space.

The robot system for which the position of a camera attached to the arm is changeable to multiple positions. The robot system memorizes offset information between the arm and the camera for each of multiple positions. Further, the robot system moves the arm to the position offset by the offset information corresponding to the attachment position of the selected camera. As a result, even when the mounting position of the camera is changed, the robot system can move the camera to an appropriate position when imaging and perform imaging without requiring troublesome teaching.

A robot includes an instruction receiving unit that receives a calibration initiation instruction, and an arm that changes a positional relationship between a marker which indicates a reference point and a capturing unit when the calibration initiation instruction is received, in which the calibration of a coordinate system of the capturing unit and a coordinate system of the robot is performed on the basis of an image in which the marker is captured by the capturing unit after the positional relationship between the capturing unit and the marker changes.

This invention provides a system and method that automatically decides motion parameters of hand-eye calibration, and conducts the calibration procedure with minimal human intervention. It automatically computes hand-eye calibration motion parameters and spatial positions during pre-calibration, whereby the calibration pattern can continuously remain inside, and covering, the entire field of view FOV of the vision system camera, providing a fully automatic hand-eye calibration process. This system and method advantageously operates in a robot-based hand-eye calibration environment and can compensate for a cantilever effect between the calibration target and the FOV. A hand-eye calibration computes the transformation from the robot coordinate space to the camera coordinate space. This generally avoids a need to manually move the robot through a set of spatial positions in which the camera then acquires images and locates calibration features on the object at each position to establish the relationship between the robot and camera.