Abstract: Systems and a method for determining a joint in a virtual kinematic device. Input data are received which contain data on two point cloud representations of two given links of a given virtual kinematic device and data on the specific joint type associated with the two links. A specific joint descriptor analyzer is applied to the input data. The specific joint descriptor analyzer is modeled with a function trained by a machine learning (ML) algorithm and the specific joint descriptor analyzer generates output data. The output data contains specific joint descriptor data for determining the mutual motion capabilities of the specific joint type associated with the two given links. From the output data, at least one joint is determined in the virtual kinematic device.

Abstract: Systems and a method determine a location of a virtual camera for virtually capturing an image sequence of a virtual scene of an industrial simulation. Input data are received on the virtual scene containing a set of objects wherein at least two objects are in relative motion during a given time interval. On at least two objects of the set, the at least two focus objects are in relative motion in the given time interval and are sufficiently visible in a captured image sequence of the virtual scene in at least two time points. Inputs on data are received on a set of camera locations candidates for capturing the image sequence. For each camera location candidate, a visibility map of pixels is generated indicating the presence of the at least two focus objects and their visibility level in the corresponding capturable image sequence.

Abstract: Systems and a method identify a kinematic capability in a virtual kinematic device. Input data are received, wherein the input data contains data on a point cloud representation of a given virtual kinematic device. A kinematic analyzer is applied to the input data, wherein the kinematic analyzer is modeled with a function trained by a machine learning algorithm and the kinematic analyzer generates output data. The output data contains data for associating a subset of the points of the point cloud representation to a set of kinematic descriptors of at least one link identified on the point cloud representation of the given virtual kinematic device. From the output data at least one identified kinematic capability is determined in the given virtual kinematic device.

Abstract: A computing system may include a data access engine and a toolpath adjustment engine. The data access engine may be configured to access a computer-aided design (CAD) model of a part design and a computer-aided manufacturing (CAM) setup for the part design. The CAM setup may include a nominal toolpath specified through the CAD model for performing a finishing operation for the part design. The data access engine may also be configured to obtain 3-dimensional (3D) scan data for a physical part manufactured from the part design. The toolpath adjustment engine may be configured to extract, from the 3D scan data, a manufactured geometry of the physical part manufactured from the part design and generate an adjusted toolpath for the physical part to account for the manufactured geometry extracted from the 3D scan data.

Abstract: A computing system may include a data access engine and a toolpath adjustment engine. The data access engine may be configured to access a computer-aided design (CAD) model of a part design and a computer-aided manufacturing (CAM) setup for the part design. The CAM setup may include a nominal toolpath specified through the CAD model for performing a finishing operation for the part design. The data access engine may also be configured to obtain 3-dimensional (3D) scan data for a physical part manufactured from the part design. The toolpath adjustment engine may be configured to extract, from the 3D scan data, a manufactured geometry of the physical part manufactured from the part design and generate an adjusted toolpath for the physical part to account for the manufactured geometry extracted from the 3D scan data.

Abstract: Methods for producing a robot program for a substantially-symmetric product and corresponding systems and computer-readable mediums. A method includes receiving a first-side robot program. The first-side robot program is a robot program for processing a first side of the substantially-symmetric product. The method includes identifying one or more resources of the first-side robot program by and producing corresponding mirrored resources in a second-side robot program. The method includes identifying one or more robots for the first-side robot program and producing corresponding mirrored robots in the second-side robot program. The method includes processing machine data files of the first-side robot program and updating logic block signal connections from the first-side robot program to the second-side robot program. The method includes replacing references to objects in the second-side robot program and assigning tool mounts to the second-side robot program.

Abstract: Methods for producing a robot program for a substantially-symmetric product and corresponding systems and computer-readable mediums. A method includes receiving a first-side robot program. The first-side robot program is a robot program for processing a first side of the substantially-symmetric product. The method includes identifying one or more resources of the first-side robot program by and producing corresponding mirrored resources in a second-side robot program. The method includes identifying one or more robots for the first-side robot program and producing corresponding mirrored robots in the second-side robot program. The method includes processing machine data files of the first-side robot program and updating logic block signal connections from the first-side robot program to the second-side robot program. The method includes replacing references to objects in the second-side robot program and assigning tool mounts to the second-side robot program.