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.

A system and method for predicting the location at which a feature that is being tracked during a robotic assembly operation will be located within one or more images captured by a vision device. A vision device can be mounted to a robot such that the location of the vision device as the robot moves can be known or determined. In the event of an interruption of the tracking of the feature by the vision device as the corresponding workpiece is moving, the location of the feature relative to a vision device can be predicted, such as, via use of current or past historical movement information for the feature and/or the associated workpiece. Using the predicted location of the feature and the known location of the vision device, the location at which the feature will be located in an image(s) captured by the vision device can be predicted.

A motion controller moves a cutting tool relative to a workpiece in a direction in which the cutting tool and the workpiece come into contact with each other while imparting rotary motion or motion along a predetermined locus to one of the cutting tool or the workpiece. An acquirer acquires a signal indicating whether the cutting tool and the workpiece are in contact with each other. A processor specifies a section during which the cutting tool and the workpiece are in contact with each other from the signal acquired by the acquirer and specifies a relative positional relationship between the cutting tool and the workpiece from the section thus specified.

A system and method for predicting the location at which a feature that is being tracked during a robotic assembly operation will be located within one or more images captured by a vision device. A vision device can be mounted to a robot such that the location of the vision device as the robot moves can be known or determined. In the event of an interruption of the tracking of the feature by the vision device as the corresponding workpiece is moving, the location of the feature relative to a vision device can be predicted, such as, via use of current or past historical movement information for the feature and/or the associated workpiece. Using the predicted location of the feature and the known location of the vision device, the location at which the feature will be located in an image(s) captured by the vision device can be predicted.

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 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 predictive system and process that predicts safety system activation in industrial environments when collaborative robots (COBOTs), automated guidance vehicles (AGVs), and other robots (individual or collectively robots) are interacting (i) between one another or (ii) between a robot and human. As provided herein, the predictive system is not meant to substitute traditional safety systems, but rather to detect and classify robot-to-robot and robot-to-human interactions and potential interactions thereof so as to limit or avoid those interactions altogether, thereby increasing safety and efficiency of the robots.

A numerical control device includes: a tool-side displacement measurement unit; a workpiece-side displacement measurement unit; a drive signal measurement unit; a relative displacement calculation unit between the tool and the workpiece; a relative displacement prediction unit calculating a relative displacement predicted value from the drive signal, from a prediction model representing a relationship between the drive signal and the relative displacement; a model parameter operation unit generating prediction model parameters constituting the prediction model, from the drive signal, the relative displacement, and the predicted value; and a command value correction unit outputting a post-correction position command obtained by correcting a position command to the drive unit using the prediction model parameters. The model parameter operation unit changes the prediction model parameters to reduce a difference between the relative displacement and the predicted value.

A numerical control device includes: a tool-side displacement measurement unit; a workpiece-side displacement measurement unit; a drive signal measurement unit; a relative displacement calculation unit between the tool and the workpiece; a relative displacement prediction unit calculating a relative displacement predicted value from the drive signal, from a prediction model representing a relationship between the drive signal and the relative displacement; a model parameter operation unit generating prediction model parameters constituting the prediction model, from the drive signal, the relative displacement, and the predicted value; and a command value correction unit outputting a post-correction position command obtained by correcting a position command to the drive unit using the prediction model parameters. The model parameter operation unit changes the prediction model parameters to reduce a difference between the relative displacement and the predicted value.

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.