A method for producing or assembling a product which includes at least two components, for example a motor vehicle or a motor vehicle module, by at least two fixing parts. The first fixing part is formed as a female part and the second fixing part is formed as a male part. The components disposed at a processing station and the first fixing part are measured by a measuring device, for example by a stationary camera or a camera fastened on a first or a second manipulator or photogrammetry bar having three cameras, and a deviation from a target geometry or target position is determined, and a corrected target position of the second fixing part is calculated on the basis of the determined deviation, such that the second fixing part is joined together with the first fixing part by the first manipulator and the product is thus produced.

Manufacturing of a shoe is enhanced by creating 3-D models of shoe parts. For example, a laser beam may be projected onto a shoe-part surface, such that a projected laser line appears on the shoe part. An image of the projected laser line may be analyzed to determine coordinate information, which may be converted into geometric coordinate values usable to create a 3-D model of the shoe part. Once a 3-D model is known and is converted to a coordinate system recognized by shoe-manufacturing tools, certain manufacturing steps may be automated.

Manufacturing and assembly of a shoe or a portion of a shoe is enhanced by automated placement and assembly of shoe parts. For example, a part-recognition system analyzes an image of a shoe part to identify the part and determine a location of the part. Once the part is identified and located, the part can be manipulated by an automated manufacturing tool.

Manufacturing of a shoe or a portion of a shoe is enhanced by automated placement of shoe parts. For example, a part-recognition system analyzes an image of a shoe part to identify the part and determine a location of the part. Once the part is identified and located, the part can be manipulated in an automated manner.

A work machine includes a pickup member configured to pick up a component; a storage device configured to store positional information on multiple pickup positions where the pickup member can pick up the component; a recognition device configured to optically recognize a multiple of the component including the pickup target; and a control device configured to select, from the multiple pickup positions of the pickup target component, one pickup position which is less likely to interfere with other components based on the positional information and a recognition result from the recognition device, and cause the pick member to pick up the pickup target component at the one selected pickup position.

Methods, systems, and software for controlling object picking and placement by a robot system are disclosed. The method includes assigning machine learning training data of a machine learning model for an object. The machine learning training data includes a plurality of known grasp location labels assigned to the object positioned in a plurality of different object poses. The method includes providing the object in a work space of the robot system. For the object in the work space in a first pose of the plurality of different object poses, the method includes: mapping a first candidate grasp location on the object; executing robotic movements for the first candidate grasp location on the object; and evaluating a result of the executing for the first candidate grasp location according to at least one predetermined performance criteria.

An execution plan segment of an execution plan can be received at a control unit of a computer numerically controlled machine from a general purpose computer. The execution plan segment can define operations for causing movement of a moveable head of the computer numerically controlled machine to deliver electromagnetic energy to effect a change in a material within an interior space of the computer numerically controlled machine. The execution plan segment can include a predefined safe pausing point from which the execution plan can be restarted while minimizing a difference in appearance of a finished work-product relative to if a pause and restart are not necessary. Operations of the computer numerically controlled machine can be commenced only after determining that the execution plan segment has been received up to and including the predefined safe pausing point by the computer numerically controlled machine.

A gripping element for arrangement on a component, wherein the component, in particular a cable harness, is of flexible design and has a changeable form, wherein the gripping element has at least one optically detectable marker via which a spatial orientation of the gripping element is detectable by an optical recognition device, and wherein the gripping element is grippable by a gripper.

Systems and methods for automated manufacture are provided. Nominal data measurements are obtained for an article. An identification scan is performed of parts within the work area by a machine vision system. An initial scan of the parts within or adjacent to the work area identified as being needed to form said article is performed by the machine vision system to identify target points. The target points are compared at a controller with the nominal data measurements. Automated material handling machines are commanded to grasp and move the parts within said work area to form the article.

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.