A machining control system includes: a numerical control device controlling a machine tool; and a robot control device communicating with the numerical control device and controlling a robot having a plurality of drive axes. The numerical control device includes: a coordinate position command generation unit generating a coordinate position command specifying a target coordinate position at each time of a leading end part of the robot, based on a machining program; and a communication unit sending the current target coordinate position to the robot control device. The robot control device includes: a target drive position calculation unit calculating a target drive position of each of the plurality of drive axes to position the leading end part at the target coordinate position; and a drive command generation unit generating a drive command to each of the drive axes to position the drive axes at the calculated target drive position.

The method includes the steps of: detecting a part, of a surface of a target, that is located on an inner circumferential side of a predetermined circle centered on a rotation axis and passing the target, by an object detection sensor, at plural rotation positions when at least one of a rotation position of the target about the rotation axis on a substrate placement portion and a rotation position of a detection area about a robot reference axis is changed; calculating a quantity correlated with an index length representing a distance from the robot reference axis to the target when the target is detected by the object detection sensor, for each rotation position; and calculating the positional relationship between the robot reference axis and the rotation axis on the basis of, among the rotation positions, the one at which the quantity correlated with the index length is maximized or minimized.

A method for correcting the processing path of a robot-guided tool for processing at least one component, wherein: a target position for a plurality of points of a target processing path is specified; from the specified points, points to be corrected are selected; the actual position for the selected points to be corrected is measured or detected on at least one component to be processed; and the processing path corresponding to the measured or detected actual position of the points of the component to be processed is correspondingly corrected. The method is suitable, for example, for welding a component into a borehole using a laser beam, wherein the processing path of the laser beam is corrected so as to correspond to the contour of the component.

Provided are a device and a method for efficiently creating a following path of the target to be followed by a mobile device to enable reliable follow-up. A movement path creation unit is included that creates a path that is a following path on which a target is to be followed by a mobile device. The movement path creation unit sequentially sets a piece of path position information (waypoint) near the target, and sequentially connects the set pieces of path position information to create the path. The movement path creation unit sets the piece of path position information at a position determined in accordance with a predetermined rule based on a position and a travel direction of the target. When the target has moved a predetermined distance, a new piece of path position information is set.

A system for controlling a robotic arm performing insertion of a component along an insertion line accepts measurements of force experienced by the wrist of robotic arm at current position along insertion line and determines probability of value of the force conditioned on the current value of the position according to a probabilistic relationship for the force experienced by the wrist of the robotic arm along the insertion line as a probabilistic function of the positions of the wrist of the robotic arm along the line of insertion. The probabilistic function is learned from measurements of the operation repeatedly performed by one or multiple robotic arms having the configuration of the robotic arm under the control. The system determines a result of anomaly detection based on the probability of the current value of the force and controls the robotic arm based on the result of anomaly detection.

A detection system includes a first detection apparatus that detects an object that is being moved, within a predetermined detection region, a number of times, a work-data creation device that creates, every time the first detection apparatus detects the object, work data having a first data element that indicates at least a position of the object obtained by the first detection apparatus and a second data element that includes at least an index related to the object and obtained at the time of the detection, and a work-data storage unit that stores the work data created by the work-data creation means. The work-data storage unit selects, as the work data that should be stored, one of the work data that is newly created for the object and the work data for the object that has been stored by the work-data storage unit, on the basis of the index.

A method of communication between a robot and an elevator system using a robot communication system including: collecting data on a landing of a building using a sensor system of the robot; and transmitting the data to the elevator system of the building, the data being transmitted to the elevator system directly from the robot, through a cloud computing network, or through a building system manager.

The present disclosure relates to positioning technology, and particularly to a positioning method a positioning device, and a robot. In which, the method includes: obtaining first location information of the target object at a current moment being predicted by an extended Kalman filter model at a last moment; obtaining second location information of the target object at the current moment being collected by a sensor; predicting third location information of the target object at the current moment through the extended Kalman filter model based on the first location information and the second location information; and determining an error value of the third location information under a preset constraint condition, and correcting the third location information according, to the error value to obtain final location information of the target object at the current moment.

A machining control system includes: a numerical control device which controls a machine tool; a robot control device which communicates with the numerical control device and controls a robot having a plurality of drive axes, in which the numerical control device includes: a coordinate position command generation unit which generates a coordinate position command specifying a target coordinate position at each time of a leading end part of the robot, based on a machining program; and a communication unit which sends the target coordinate position that is current to the robot control device, and in which the robot control device includes: a target drive position calculation unit which calculates a target drive position of each of the plurality of drive axes so as to position the leading end part at the target coordinate position received from the communication unit; and a drive command generation unit which generates a drive command to each of the drive axes so as to position the drive axes at the target drive position calculated by the target drive position calculation unit.

A computer-implemented method executed by a robotic system for performing a positional search process in an assembly task is presented. The method includes decomposing, by the robotic system, a perturbation motion into a plurality of actions, the perturbation motion being a motion for an assembly position searched by the robotic system, each action of the plurality of actions related to a specific direction. The method further includes performing reinforcement learning by selecting an action among decomposed actions and assembly movement actions at each step of the positional search process based on corresponding force-torque data received from at least one sensor associated with the robotic system. The method also includes outputting a best action at each step for completion of the assembly task as a result of the reinforcement learning.