An automated robotic assembly system is configured to assemble a device by fitting a first component made of a material liable to deformation by external force with a second component by means of a robot, and the first component is provided with a distortion detection unit for detecting distortion thereof. If the distortion detected by the distortion detection unit exceeds a predetermined value, a signal for notifying abnormality is output to stop an automated assembly operation by the robot.

Embodiments herein generally relate to methods, systems and devices for automated assembly of building structures. In at least one embodiment, there is provided a robotic assembly cell for assembling building structures. The robotic assembly cell comprises a perception sensor system; one or more assembly robots; and at least one processor operable to: receive instructions corresponding to an assembly sequence for assembling a building structure; determine a plurality of building parts required for assembling the building structure based on the assembly sequence; identify each building part within a facility, based on sensor data from the perception sensor system; configure the assembly robot to retrieve the target pieces; and configure the assembly robot to assemble the target pieces according to the assembly sequence.

A method for locating a first vehicle component relative to a second vehicle component includes the following steps: (a) moving the robotic arm to a first position such that a form feature of the first vehicle component is within a field of view of a camera; (b) capturing an image the form feature of the first vehicle component; (c) moving the robotic arm to a second position such that the form feature of the second vehicle component is within the field of view of the camera; (d) capturing an image of the form feature of the second vehicle component; (e) picking up the second vehicle component using the robotic arm; and (f) moving the robotic arm along with the second vehicle component toward the first vehicle component.

Provided is an automotive glass setting apparatus and a method for setting a vehicle glass. The method includes loading a glass having a plurality of edges onto a setting base, scanning, by a scanning unit, the plurality of edges of the loaded glass, and calculating a center of the glass based on data scanned by the scanning unit. The method further includes adjusting, by a plurality of alignment units and a plurality of moving mechanisms, a position of the glass to align the calculated center of the glass with a center of the setting base.

Aspects for implementing 3-D printed metrology feature geometries and detection are disclosed. The apparatus may a measurement device for a 3-D printed component. The component may include a plurality of printed-in metrology features arranged at different feature locations on a surface of the component. The measurement device can be configured to detect the feature locations of the printed-in metrology features and to determine a position or an orientation of the component based on the detected feature locations. In various embodiments, the metrology feature may be a protruding or recessed spherical portion, with the corresponding feature location at the center of the sphere.

Disclosed is a mobile robot for detecting and repairing damages of a hull, including: a mobile robot unit which includes at least one frame to which motor-driven drive wheels are installed, frame connectors which flexibly connect the frames with each other, and at least one robot electromagnet and adsorption module mounted on each of the frames, and is configured to be attached to the hull through the robot electromagnet so as to move or stop on a surface of the hull by the drive wheels; a stage unit which includes a rechargeable battery mounted therein to supply power to the mobile robot unit, and a docking module provided to dock with or separate from the mobile robot unit; and a connection line configured to be wound or unwound while receiving tension controlled by the stage unit, and electrically connected between the mobile robot unit and the stage unit.

Aspects herein use a feature detection system to visually identify a feature on a component. The feature detection system includes at least two cameras that capture images of the feature from different angles or perspectives. From these images, the system generates a 3D point cloud of the components in the images. Instead of projecting the boundaries of features onto the point cloud directly, the aspects herein identify predefined geometric shapes in the 3D point cloud. The system then projects pixel locations of the feature's boundaries onto the identified geometric shapes in the point cloud. Doing so yields the 3D coordinates of the feature which then can be used by a robot to perform a manufacturing process.

An absolute robot-assisted positioning method is provided which can be performed by a facility. The method optimises an assembly task which has been created theoretically at a computer workstation and which is implemented in reality by the facility. The disclosed facility includes at least one robot, at least one measurement system and a computer, wherein the at least one measurement system monitors the at least one robot while the assembly task is being performed, and the robot and the measurement system are connected to each other via the computer.

The present invention generates, from among paths that exist for a task to assemble target objects together, an operation path that can be executed at high speed without a probing operation.

An acquisition section 32, for an operation to assemble a main target object 90A gripped by a gripping section of a robot 42 together with an auxiliary target object 90B that is an assembly target, acquires a start position and orientation, and an end position and orientation, of the gripping section relative to the main target object 90A, and acquires environment information. Based on the acquired information, a simulation section 34 performs a simulation of a transition of contact states between the main target object 90A and the auxiliary target object 90B, from a contact state until there is a non-contact state. Based on the acquired information and on the simulated transition of contact states, a generation section 36 generates an operation path of the robot to reach a goal state from an initial state until reaching one or another contact state included in the transition of contact states, along a transition of contact states including the one or the other of the contact states.

A program generation apparatus according to one or more embodiments may extract, from a series of motions defined in a motion program, a motion to be corrected based on a difference in attribute between a first component indicated as a target of a component change and a second component to replace the first component, and generate a new motion program by correcting a command value of the extracted motion to compensate for the difference in the attribute.