A grid plate encoder based positioning system (1) for positioning of an element is provided, the positioning system (1) comprises a grid plate (2) with a grid plate surface (21); an encoder unit (3) with one or more optical sensors (31) for sensing a grid plate surface pattern (23) of the grid plate surface (21); an input (7) to receive coordinates (Xd, Yd) specifying a desired position of the element; a mapping unit (8) to compute compensated coordinate data (Xa, Ya) corresponding to estimated position data expected from the encoder unit (3) when the element is positioned at a desired position (Xd, Yd) specified by the setpoint coordinates; a feedback control unit (9) providing the compensated coordinate data (Xa, Ya) as a setpoint (Xs, Ys) to a positioning unit (12), with feedback control based on the estimated position data obtained from the encoder unit.

Additionally, a grid plate encoder based positioning method and a method for computing compensation data are provided.

A method for machining a selected part with a machine tool, comprises obtaining a master part replicating at least a portion of a geometry of a selected part. The master part is loaded in a machine tool. A signature of the machine tool is defined by measuring at least dimensional data of the master part relative to the machine tool, the dimensional data being limited to a selected-part-specific working volume substantially smaller than a complete working volume of the machine tool. The machine tool is certified as being within tolerances to machine the selected part within the working volume, using the dimensional data of the signature. The selected part is machined from a workpiece with the machine tool.

A method for machining a selected part with a machine tool, comprises obtaining a master part replicating at least a portion of a geometry of a selected part. The master part is loaded in a machine tool. A signature of the machine tool is defined by measuring at least dimensional data of the master part relative to the machine tool, the dimensional data being limited to a selected-part-specific working volume substantially smaller than a complete working volume of the machine tool. The machine tool is certified as being within tolerances to machine the selected part within the working volume, using the dimensional data of the signature. The selected part is machined from a workpiece with the machine tool.

A sensing system bias is reduced across a first agricultural machine and a second agricultural machine. A collection of agronomic data is accessed, that is indicative of an estimated crop yield. The collection that is accessed, for example, includes at least a first set of data sensed by the first agricultural machine and a second set of data sensed by the second agricultural machine. In addition, the first and second sets of data can be scaled based on a yield correction factor. A bias between the scaled first set of data and the scaled second set of data is determined, and a smoothing operation is performed on the scaled first and second sets of data. For example, performing the smoothing operation can include generating a calibration correction factor based on the determined bias, removing the bias between the scaled first set of data and the scaled second set of data to obtain a corrected set of crop yield data, and using the calibration correction factor in sensing the first set of data on the first agricultural machine and the second set of data on the second agricultural machine.

A method and system for piece-picking or piece put-away within a logistics facility. The system includes a central server and at least one mobile manipulation robot. The central server is configured to communicate with the robots to send and receive piece-picking data which includes a unique identification for each piece to be picked, a location within the logistics facility of the pieces to be picked, and a route for the robot to take within the logistics facility. The robots can then autonomously navigate and position themselves within the logistics facility by recognition of landmarks by at least one of a plurality of sensors. The sensors also provide signals related to detection, identification, and location of a piece to be picked or put-away, and processors on the robots analyze the sensor information to generate movements of a unique articulated arm and end effector on the robot to pick or put-away the piece.

A method for calibrating a machining system includes providing the machining system which includes a base, a cantilevered arm, and a rotary table positioned at the second arm end of the cantilevered arm. The rotary table is rotatable relative to the cantilevered arm about a first axis. The first axis has a first unloaded position and a first unloaded orientation with the machining system in an unloaded condition. The method further includes installing a measurement artifact on the rotary table, measuring a first position of the measurement artifact, and installing a load on the rotary table. The first axis has a first loaded position and a first loaded orientation with the machining system in a loaded condition. The method further includes measuring a second position of the measurement artifact and determining a positional deviation of the second position from the first position.

A method and system for piece-picking or piece put-away within a logistics facility. The system includes a central server and at least one mobile manipulation robot. The central server is configured to communicate with the robots to send and receive piece-picking data which includes a unique identification for each piece to be picked, a location within the logistics facility of the pieces to be picked, and a route for the robot to take within the logistics facility. The robots can then autonomously navigate and position themselves within the logistics facility by recognition of landmarks by at least one of a plurality of sensors. The sensors also provide signals related to detection, identification, and location of a piece to be picked or put-away, and processors on the robots analyze the sensor information to generate movements of a unique articulated arm and end effector on the robot to pick or put-away the piece.

Data about a physical object in a real-world environment is automatically collected and labeled. A mechanical device is used to maneuver the object into different poses within a three-dimensional workspace in the real-world environment. While the object is in each different pose an image of the object is input from one or more sensors and data specifying the pose is input from the mechanical device. The image of the object input from each of the sensors for each different pose is labeled with the data specifying the pose and with information identifying the object. A database for the object that includes these labeled images can be generated. The labeled images can also be used to train a detector and classifier to detect and recognize the object when it is in an environment that is similar to the real-world environment.

Embodiments of the present disclosure provide methodology to match and calibrate processing chamber performance in a processing chamber. In one embodiment, a method for calibrating a processing chamber for semiconductor manufacturing process includes performing a first predetermined process in a processing chamber, collecting a first set of signals transmitted from a first group of sensors disposed in the processing chamber to a controller while performing the predetermined process, analyzing the collected first set of signals, comparing the collected first set of signals with database stored in the controller to check sensor responses from the first group of sensors, calibrating sensors based on the collected first set of signals when a mismatch sensor response is found, subsequently performing a first series of processes in the processing chamber, and collecting a second set of signals transmitted from the sensors to the controller while performing the series of processes.

A machine tool is provided with a toolsetting probe mounted on a bed or table, and a workpiece-sensing probe which can be mounted in a movable spindle. Both probes are calibrated by using them to make measurements against each other. The arbitrary length of the workpiece-sensing probe is used to calibrate the toolsetting probe, rather than using a pre-calibrated artefact of known length mounted in the spindle. A stylus disc of the toolsetting probe has a pre-calibrated size or dimension, and the workpiece-sensing probe is calibrated with respect to that. This obviates the need for skilful manual calibration procedures using pre-calibrated artefacts and manual measurement tools.