A numerical control device includes a drive-shaft movement-amount estimation unit to estimate a first movement amount of a first object that is a target to be moved by a first drive shaft by using a first drive signal, an undriven-object movement-amount estimation unit to estimate a second movement amount of a second object in a three dimensional space, which is generated due to a drive force of the first drive shaft, by using the first drive signal, a correction-amount calculation unit to calculate a correction amount for the first drive signal on the basis of the first movement amount and the second movement amount, and a first correction-signal output unit to output a first corrected drive signal obtained by correcting the first drive signal by the correction amount to a drive unit to drive the first drive shaft.

A method for tracking multiple target objects, moving objects to be tracked being projected onto a grid map having grid cells, the method including the following tasks to be executed in each time: computing the velocity distribution for the next time step with the aid of a transition velocity distribution, which indicates how the objects associated with a grid cell in question move from one time step to the next, based on the preceding velocity distribution; for each grid cell, calculating a transitional probability information item, which indicates, for objects in each grid cell, probabilities of the objects in question reaching possible, further grid cells, as a function of the velocity distribution; calculating an occupancy probability for each grid cell for a subsequent time, based on the transitional probability information item; operating a system as a function of the occupancy probabilities for the grid cells.

Various embodiments of systems and methods for collision-free trajectory planning in human-robot interaction through hand movement prediction from vision are disclosed.

Robust machine learning predictions. Temporal dependencies of process targets for different machine learning models can be captured and evaluated for the impact on process performance for target. The most robust of these different models is selected for deployment based on minimizing variance for the desired performance characteristic.

A synchronization control device includes a command movement amount calculation unit, a predicted command movement amount calculation unit, and a movement amount comparison unit for comparing a command movement amount with a predicted command movement amount, and synchronization of a driven shaft is not started when the predicted command movement amount is less than the command movement amount, and synchronization is started when the predicted command movement amount is equal to or greater than the command movement amount.

There is provided a thermal displacement correction apparatus for a machine tool which automatically determines necessity/unnecessity of actual measurement of the machine tool, the apparatus including: a thermal displacement correction unit that predicts a thermal displacement amount from an operation of a machine or a temperature of each portion of the machine and calculates a thermal displacement correction amount for correcting thermal displacement by adding, to a position command value of a feed axis, the thermal displacement correction amount for cancelling the thermal displacement amount thus predicted; and a thermal displacement correction amount adjustment unit that calculates an adjustment value for adjusting the thermal displacement correction amount on the basis of the thermal displacement correction amount, wherein a change amount E from the start of processing is obtained, E is compared with designated Em, and when EEm, actual measurement is performed with measurement means.

The present disclosure relates to a method for estimating physical properties of an object. The method includes generating a three-dimensional (3D) reconstruction of a real-world environment based on an input media. Further, the method includes estimating a current set of physical parameters of the object using a physics-based prediction model and a real-world visual content while the object is manipulated. Further, the method includes generating a simulation variant and computing a cost function based on comparing the simulation variant and the real-world visual content. Furthermore, the method includes estimating the physical properties of the object based on optimizing the current set of physical parameters with the cost function such that a similarity between the simulation variant and the real-world visual content increases.