A method of determining a form measurement for a curved feature of an artefact. The method includes a positioning apparatus relatively moving the artefact and a measurement device relative along a curved path in a first direction, to obtain a first set of data points along the surface of the curved feature, and the positioning apparatus relatively moving the artefact and the measurement device other along a curved path in a second direction, opposite to the first direction, to obtain a second set of data points along the surface of the curved feature. The method further includes using the first and second sets of data points to determine a form measurement for the artefact.

A method according to the disclosure configures a processor to predict metal loss in a structure for remediation. The method uses a machine learning model, trained based upon historical data, to predict metal loss over locations of a structure at a time of the prediction. The method identifies from among the predicted locations a high-risk location on the structure in which a magnitude of metal loss indicates potential remediation being needed, dispatches a robotic vehicle to the high-risk location on the structure and inspects the high-risk location using the robotic vehicle to confirm whether the magnitude of metal loss at the location requires remediation. In further methods, remediation is performed. In still further methods, a three-dimensional visualization of the structure is generated with an overlay which depicts predicted metal loss over the sections of the structure.

A three-dimensional measurement device includes a camera for acquiring position information for three-dimensional points on the surface of an object on the basis of the time of flight of light, and a control device. The camera acquires, at a plurality of relative positions of the camera with respect to a workpiece, three-dimensional point position information. A plurality of evaluation regions are defined for the workpiece. The control device specifies, for each evaluation region, the three-dimensional point closest to a reference plane from among three-dimensional points detected in the evaluation region. The control device generates, on the basis of the multiple three-dimensional points specified for the respective evaluation regions, three-dimensional point position information in which multiple pieces of three-dimensional point position information acquired by the camera are combined.

A control device according to an embodiment receives first posture data of a posture of a first robot. The first robot includes a first manipulator and a first end effector. Furthermore, the control device sets the posture of the first robot based on the first posture data and causes the first robot to perform a first task on a first member. The first posture data is generated based on second posture data. The second posture data is of a posture when a second robot that includes a second manipulator and a second end effector performs a second task on the first member.

Provided is a process including: receiving inspection path information indicating a path for a robot to travel, and a plurality of locations along the path to inspect; determining, based on information received via a location sensor, that a distance between a location of the robot and a first location of the plurality of locations is greater than a threshold distance; in response, causing a refrigeration system of an optical gas imaging (OGI) camera to decrease cooling; moving along the path; in response to determining that the robot is at a first location of the plurality of locations, sending a second command to the sensor system, wherein the second command causes the refrigeration system of the OGI camera to increase cooling; causing the sensor system to record a first video with an OGI camera; and causing the sensor system to store the first video in memory.

Methods of performing a plurality of operations within a region of a part utilizing an end effector of a robot and robots that perform the methods are disclosed herein. The methods include collecting a spatial representation of the part and aligning a predetermined raster scan pattern for movement of the end effector relative to the part with the spatial representation of the part. The methods also include defining a plurality of normality vectors for the part at a plurality of predetermined operation locations for operation of the end effector. The methods further include moving the end effector relative to the part and along the predetermined raster scan pattern. The methods also include orienting the end effector such that an operation device of the end effector faces toward each operation location along a corresponding normality vector and executing a corresponding operation of the plurality of operations with the operation device.

A bead appearance inspection device includes an input unit configured to enter input data related to a welding bead of a workpiece produced by welding, a first determination unit configured to perform a first inspection determination related to a shape of the welding bead based on a comparison between the input data and a master data, k second determination units, where k is an integer of 1 or more, that are equipped with k types of artificial intelligence and that are configured to perform a second inspection determination related to a welding defect of the welding bead based on processings of the k types of artificial intelligence targeting the input data, and a comprehensive determination unit configured to output a result of an appearance inspection of the welding bead to an output device based on determination results of the first determination unit and the k second determination units.

A system for verifying quality of a part using an arm robot includes an arm robot, which includes a camera to acquire image data of a part assembled in each manufacturing process of a vehicle, a carrier, which includes a sliding rail allowing the arm robot to be movable around the vehicle along the sliding rail to acquire the image data, and a server which receives the image data acquired by the camera, compares the image data with modeling data of the vehicle, which is stored in a database, and determines whether the assembled part satisfies a preset inspection item, to verify quality of the assembled part, verifying the quality of the part in each process before the vehicle is completely manufactured.

The invention is a flexible and configurable inspection system for the inspection of container units that combines and integrates a holding assembly for multiple containers integrating servo-controlled rotation of the units, transport and positioning of the containers that simulate human handling, and camera stations employing automated vision inspection. The system performs horizontal inspection for particulate and any other container defect that promotes particulate to better locate within the inspection area of the cameras. Inspection sequences and product recipes combine the typical manual inspection agitation with automated inspection rotational techniques to optimize detection. The system allows for semi-automatic operation with the operator at the front of the station feeding and out-feeding material manually or fully automated with conveyance system feeding and out-feeding material from the back of the station.

A portable device repair machine may be configured to receive portable devices, identify the portable device, diagnose, repair and/or upgrade the portable device, collect payment for the service and return the portable device to the payee. The portable device repair machine may include an audio/video interface for interaction with a portable device user as well as a mechanized connection, inspection, diagnostic and upgrade system. The mechanized connection, inspection, diagnostic and upgrade system may comprise a conveyance mechanism for conveying the portable device among multiple stations such as a physical inspection station, device connection mechanism station, diagnostic, repair and upgrade station, and a physical upgrade station. Various mechanical devices, such as robotic arms may interact with the portable device, based in part on feedback obtained via various image sensors within the portable device repair machine.