A method for optimizing a machining time of a laser machining process includes: specifying a machining path of the laser machining process on the workpiece, said machining path having a plurality of machining path sections, specifying at least one boundary condition for at least one of the machining path sections; and determining control data for the laser machining process of the machining path taking into account the at least one boundary condition such that a machining time of the laser machining process is minimal. Furthermore, a method for performing a laser machining process on a workpiece includes such a method and a laser machining system is configured to perform the methods.

A laser processing robot system, in which an augmented reality processing technology is used to enable a processing laser beam and its irradiation position to be safely and easily seen, is provided. A laser processing robot system includes an image processing device having an augmented reality image processing unit for performing augmented reality image processing for an actual image including an image of a robot captured by an imaging device. The augmented reality image processing unit is adapted to superimpose a virtual image representing at least one of a laser beam obtained by assuming that the laser beam is emitted from a laser irradiation device to a workpiece, and an irradiation position of the laser beam, onto the actual image, and to display the superimposed image on the display device.

A building time for building an additively-manufactured object is calculated on the basis of the inter-pass time and the welding pass time and is compared with a preset upper limit value, and welding conditions in a depositing plan are repeatedly modified until the building time is equal to or less than the upper limit value. Alternatively, corrections are repeatedly performed until the shape difference between a building shape of built-up object shape data relating to the additively-manufactured object created on the basis of the inter-pass time and the inter-pass temperature, and a building shape of three-dimensional shape data, is smaller than a near net value.

There is described a method for welding a first panel to a second panel. The method comprises forming an approximate connection, such as a mortise-and-tenon or a tongue-and-groove connection, to preassemble the first panel and the second panel, thereby roughly creating a joint between the first panel and the second panel. With a laser camera, a location and a spatial orientation of the joint is determined using a tracking algorithm. A laser is eventually displaced at a given location which depends upon the location and the spatial orientation of the joint. The joint is then irradiated with the laser, while displacing the laser along the spatial orientation of the joint, to weld the first panel with the second panel.

Disclosed are systems, methods, and apparatuses, including computer programs encoded on computer storage media, for operation of an assembly robotic system. In one aspect, the assembly robotic system performs at least one of a first or second scan operation. In the first scan operation, one or more scan poses is selected from among a plurality of generated candidate poses. For each scan pose of the one or more scan poses, the controller initiates a scan operation associated with a region identified to include a seam associated with a feature of the object. As part of the second scan operation, for each candidate scan pose, a scan operation is simulated. Based on the generated simulated scan data, multiple scan poses are selected and a scan trajectory is generated for a scan operation. Other aspects and features are also claimed and described.

Disclosed are systems, methods, and apparatuses, including computer programs encoded on computer storage media, for operation of an assembly robotic system. In one aspect, the assembly robotic system performs at least one of a first or second scan operation. In the first scan operation, one or more scan poses is selected from among a plurality of generated candidate poses. For each scan pose of the one or more scan poses, the controller initiates a scan operation associated with a region identified to include a seam associated with a feature of the object. As part of the second scan operation, for each candidate scan pose, a scan operation is simulated. Based on the generated simulated scan data, multiple scan poses are selected and a scan trajectory is generated for a scan operation. Other aspects and features are also claimed and described.

An edge extraction unit extracts an edge image from a photographed image obtained by photographing a product with a camera. A constant edge acquisition unit acquires, as a constant edge image, an edge image in a constant surface where a positional deviation does not occur with respect to a welding point set by a processing program, the acquired image belonging to the extracted edge image. A correction amount acquisition unit performs pattern-matching between a master constant edge image and a workpiece edge image, which are acquired by the constant edge acquisition unit, and acquires a deviation amount between both thereof as a correction amount with respect to the welding point. A processing program correction unit corrects the welding point by the correction amount, and generates a corrected processing program for welding the workpiece. A welding robot welds the workpiece based on the corrected processing program.

Systems and methods are disclosed relating to welding sequence guidance using three-dimensional (3D) models. In some examples, a welding sequence program may use 3D models, rather than two-dimensional (2D) images, to guide operators through welding sequences. Since only one 3D model must be saved for each sequence, rather than potentially hundreds of 2D images, substantial memory space may be saved. Additionally, the same 3D model may be used for several welding sequences. Further, the 3D model may be animated to help the operator understand changes in perspective between steps of the welding sequence.

A method for object distance detection and focal positioning in relation thereto. The method comprising the steps of: (a) identifying (via a computing device) a desired distance among a plurality of designated sites on an object; (b) adjusting a focus (via an autofocus device) onto the plurality of designated sites; (c) calculating (via an image recognition module) the actual distance among the plurality of designated sites; (d) determining (via the image recognition module) if error exist between the actual distance and the desired distance; and (e) wherein (in no particular order) repeating the steps of (b), (c), and (d) until no substantial error exists between the actual distance and the desired distance.

Systems and methods are disclosed relating to welding sequence guidance using three-dimensional (3D) models. In some examples, a welding sequence program may use 3D models, rather than two-dimensional (2D) images, to guide operators through welding sequences. Since only one 3D model must be saved for each sequence, rather than potentially hundreds of 2D images, substantial memory space may be saved. Additionally, the same 3D model may be used for several welding sequences. Further, the 3D model may be animated to help the operator understand changes in perspective between steps of the welding sequence.