Abstract: Methods and data processing systems simulate and handle anti-collision management for an area of a production plant controlled by a data processing system. The method includes determining possible spatial trajectories of objects, such as humans, production components, stationary and mobile robots, AGV's and the like, in a predefined area in an industrial scenario, such as a production process, an assembling process, material handling, item sorting and the like. A static 4D structure of the area where the possible locations of the objects are determined in terms of their location and the time that the object will be in that location is determined in order to identify potential collision events and remedy those potential collision events.

Abstract: Systems and a method predict a generation of a robotic program for industrial coating. Inputs are received including a virtual representation of a robot, a coating gun, elements of the object surface to be coated and a set of desired coating thickness ranges. Inputs on a coating dispersion object are also received. Training data of a plurality of robotic programs for industrial coating and of their corresponding coating thickness coverage on a plurality of surfaces are received. The training data are processed in x, y tuples so as to learn a mapping function to generate a coating prediction module. Starting with a given selected valid thickness coverage as input parameters, it is proceeded in an iterative manner to predict a robotic program via the coating prediction module. A coating robotic program is generated for each surface element based on the resulting predicted coating programs.

Abstract: A system and a method predict a collision free posture of a kinematic system. The method includes: receiving a 3D virtual environment, receiving a 3D representation of the kinematic system and a set of 3D postures defined for the 3D virtual kinematic system, receiving a target task to be performed by the kinematic system with respect to the surrounding environment, and receiving a prescribed location within the 3D virtual environment. The prescribed location defines a position at which the 3D virtual kinematic system has to be placed within the 3D virtual environment. A collision free detection function (CFD) is applied to a set of input data containing the 3D virtual environment, the target task, the prescribed location and the set of postures. The CFD function outputs a set of collision free postures enabling the kinematic system to perform the target task when located at the prescribed location.

Abstract: A system and method is provided for determining grasping positions for two-handed grasps of industrial objects. The system may include a processor configured to determine a three dimensional (3D) voxel grid for a 3D model of a target object. In addition, the processor may be configured to determine at least one pair of spaced apart grasping positions on the target object at which the target object is capable of being grasped with two hands at the same time based on processing the 3D voxel grid for the target object with a neural network trained to determine grasping positions for two-handed grasps of target objects using training data. Such training data may include 3D voxel grids of a plurality of 3D models of training objects and grasping data including corresponding pairs of spaced-apart grasping positions for two-handed grasps of the training objects. Also, the processor may be configured to provide output data that specifies the determined grasping positions on the target object for two-handed grasps.

Abstract: Systems and a method predict a generation of a robotic program for industrial coating. Inputs are received including a virtual representation of a robot, a coating gun, elements of the object surface to be coated and a set of desired coating thickness ranges. Inputs on a coating dispersion object are also received. Training data of a plurality of robotic programs for industrial coating and of their corresponding coating thickness coverage on a plurality of surfaces are received. The training data are processed in x, y tuples so as to learn a mapping function to generate a coating prediction module. Starting with a given selected valid thickness coverage as input parameters, it is proceeded in an iterative manner to predict a robotic program via the coating prediction module. A coating robotic program is generated for each surface element based on the resulting predicted coating programs.

Abstract: A system may include an insighter engine configured to access conceptual plans for previously manufactured products, and a given conceptual plan may include a bill of materials (BoM), a bill of processes (BoP), and a bill of resources (BoR). The insighter engine may be configured to represent the conceptual plans according to an insighter ontology and apply machine learning, using the conceptual plans represented according to the insighter ontology as training data, to learn a manufacturing constraint not already represented in the conceptual plans. The system may also include a predictor engine configured to access a BoM for a variant product that differs from the previously manufactured products and apply the learned manufacturing constraint to generate a predicted BoP and a predicted BoR for the BoM of the variant product.

Abstract: A system and method is provided for determining grasping positions for two-handed grasps of industrial objects. The system may include a processor configured to determine a three dimensional (3D) voxel grid for a 3D model of a target object. In addition, the processor may be configured to determine at least one pair of spaced apart grasping positions on the target object at which the target object is capable of being grasped with two hands at the same time based on processing the 3D voxel grid for the target object with a neural network trained to determine grasping positions for two-handed grasps of target objects using training data. Such training data may include 3D voxel grids of a plurality of 3D models of training objects and grasping data including corresponding pairs of spaced-apart grasping positions for two-handed grasps of the training objects. Also, the processor may be configured to provide output data that specifies the determined grasping positions on the target object for two-handed grasps.

Abstract: Systems and a method for determining a configuration of a virtual robot in a virtual environment include identifying a real robot from a 3D image of a 3D camera. The identified real robot it is linked to its corresponding virtual robot. The configuration data of the specific configuration in the real scene of the at least one identified real robot is extracted. The extracted location data is used to determine a specific virtual configuration of the virtual robot in the virtual environment reflecting the configuration of the corresponding real robot in the real scene.