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 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.