Siemens Product Lifecycle Management Software Inc.

Siemens Industry Software Gmbh

Ulrich Raschke

Rafael Blumenfeld

Suraj Ravi Musuvathy

Erhan Arisoy

Guannan Ren

Rishi Tirumali

Ofer Ohayion

Yizhar Alon

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.

Method and system for predicting a collision free posture of a kinematic system

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.

System and method for determining grasping positions for two-handed grasps of industrial objects

Product Data Management systems, methods, and mediums. A method includes receiving data representing motion of a human generated by a motion capture device. The method includes identifying a generated posture of the human relative to objects in a virtual environment. The method includes determining whether the generated posture of the human intersects with an object in the virtual environment. Additionally, the method includes responsive to determining that the generated posture intersects with the object by a threshold amount, identifying a posture that will avoid intersection with the object by the threshold amount.

Semi-autonomous digital human posturing

According to one embodiment of the invention, a computerized method for predicting posture of a living object includes storing a plurality of posturing rules for a respective activity in a storage location, receiving a start posture of a first living object for the activity, receiving a location of a target for the activity, dividing the activity into a plurality of movements based on the start posture and the location of the target, and determining an end posture of the first living object for the activity. Determining the end posture includes applying at least one of the posturing rules for each of the movements and checking at least one of a plurality of constraints associated with each of the movements.

System and method for predicting human posture using a rules-based sequential approach

According to one embodiment of the invention, a computerized method for simulating human movement includes storing a plurality of sets of data, in which each set of data is indicative of a measured movement of a first human, receiving a start point and an end point for a desired movement of a second human, and comparing the desired movement to the stored sets of data. The method further includes selecting, based on the comparison, a stored set of data that is representative of the desired movement and simulating the desired movement based on the start point, the end point, and the relative change in position of a first joint associated with the selected set of data from an empirical start point to an empirical end point.

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Ann Arbor, MI, United States of America

Ulrich Raschke