An active sensor calibration system includes a plurality of sensors configured to measure at least one physical quantity. Each sensor is configured to output a signal indicating at least one measured physical quantity. An electronic scenario library module is configured to store a plurality of scenarios. Each scenario is configured to excite two or more selected sensors among the plurality of sensors to generate redundancy among the selected sensors based on physical quantity models. An electronic calibration module is in signal communication with the plurality of sensors and the scenario library. The calibration module is configured to select at least one scenario from the scenario library module, determine at least one possible un-calibrated sensor among the plurality of sensors, and to identify a positive un-calibrated sensor in response to executing the at least one selected scenario.

An information processing apparatus includes: a determination unit configured to determine a plurality of measurement positions and/or orientations from which a 3D measurement sensor makes three-dimensional measurements; a controller configured to successively move the 3D measurement sensor to the plurality of measurement positions and/or orientations; a measurement unit configured to generate a plurality of 3D measurement data sets through three-dimensional measurement using the 3D measurement sensor at each of the plurality of measurement positions and/or orientations; and a data integration unit configured to integrate the plurality of 3D measurement data sets.

Creating NIR sensor calibration models and their use in agricultural work machines is disclosed. A database structure, such as a database structure system, for creating calibration models for an NIR sensor system is used. The database structure includes raw data of the NIR spectra of one or both of plant material and other substances. The raw data are generated by one or more NIR sensor systems assigned to an agricultural work machine. The one or more NIR sensor systems transmit the raw data via an interface for the data traffic with at least one data processing unit external to the agricultural work machine. The database structure comprises one or more calibration models and the raw data, generates user-specific calibration models by using the saved raw data and/or calibration models, and provide user-specific calibration models to a user.

A method of calibrating a torque sensor for a motor with a controller includes determining a gain of the torque sensor, zeroing a torque reading of the torque sensor, accelerating the motor at a known rate, and determining an inertia of the motor in response to accelerating the motor. Zeroing the torque reading occurs when the motor is in an unloaded and unactivated condition and accelerating the motor occurs when the motor is in an unloaded condition.

The invention is related to a method and arrangement for calibrating the camera of an eye tracking device and compensate for a potential angular offset of the camera. The method comprises: the steps of capturing an eye image of a user, wherein the eye image contains a plurality of glints created by a plurality of illuminators in the eye tracking system; detecting glints in the eye image; projecting illuminator positions onto the eye image to determine expected glint positions; determining an angular offset between expected glint positions and detected glint positions for corresponding pairs of expected and detected glint positions; determining the angular correction for the eye tracking camera using the determined angular offset angle; and applying the angular correction for the eye tracking camera to an eye tracker camera model.

A method for adjusting a system autonomy level of a cargo handling system configured for autonomous control by a processor is disclosed. In various embodiments, the method includes receiving by the processor a sensor database from a plurality of sensing agents in operable communication with the processor; determining by the processor a confidence level based on the sensor database; and adjusting by the processor the system autonomy level for continued operation of the cargo handling system.

An encoder apparatus includes a detection unit, a scale disposed to oppose the detection unit and relatively rotatable with respect to the detection unit, and a processor configured to process an output signal output from the detection unit to obtain a relative position of the scale with respect to a standard position and thus detect an absolute position of the scale. The processor is configured to execute a setting process in which a position where a deviation amount of the scale in a predetermined direction with respect to a rotation axis is equal to or smaller than a threshold value is set as the standard position, the deviation amount changing in accordance with relative rotation of the scale with respect to the detection unit.

A method of automated in-hand calibration including providing at least one robotic hand including a plurality of grippers connected to a body and providing at least one camera disposed on a periphery surface of the plurality of grippers. The method also includes providing at least one tactile sensor disposed in the at least one illumination surface and actuating the plurality of grippers to grasp an object. The method further includes locating a position of the object with respect to the at least one robotic hand and calibrating a distance parameter via the at least one camera. The method also includes calibrating the at least one tactile sensor with the at least one camera and generating instructions to grip and manipulate an orientation of the object via an image feed from the at least one camera for a visualization of the object.

A computer system generates a tactile force model for a tactile force sensor by performing a number of calibration tasks. In various embodiments, the calibration tasks include pressing the tactile force sensor while the tactile force sensor is attached to a pressure gauge, interacting with a ball, and pushing an object along a planar surface. Data collected from these calibration tasks is used to train a neural network. The resulting tactile force model allows the computer system to convert signals received from the tactile force sensor into a force magnitude and direction with greater accuracy than conventional methods. In an embodiment, force on the tactile force sensor is inferred by interacting with an object, determining the motion of the object, and estimating the forces on the object based on a physical model of the object.

An active sensor calibration system includes a plurality of sensors configured to measure at least one physical quantity. Each sensor is configured to output a signal indicating at least one measured physical quantity. An electronic scenario library module is configured to store a plurality of scenarios. Each scenario is configured to excite two or more selected sensors among the plurality of sensors to generate redundancy among the selected sensors based on physical quantity models. An electronic calibration module is in signal communication with the plurality of sensors and the scenario library. The calibration module is configured to select at least one scenario from the scenario library module, determine at least one possible un-calibrated sensor among the plurality of sensors, and to identify a positive un-calibrated sensor in response to executing the at least one selected scenario.