A deterioration degree of a robot body is precisely evaluated. A robot control device 300 includes: a drive control unit 309 controlling operation of a robot body 200; a detection unit 310 detecting a signal used for analysis of a feature amount quantitatively indicating a deterioration degree of the robot body 200 deteriorated over time as the robot body 200 is operated; a determination unit 304 determining whether a data section of the signal includes a constant speed section equal to or greater than a given section; a normalization unit 305 normalizing a signal in a non-constant speed section when the data section of the signal does not include the constant speed section equal to or greater than the given section; an analysis unit 307 analyzing the feature amount; and an estimation unit 308 estimating a remaining life of the robot body 200 based on the feature amount.

A robot control device, abnormality diagnosis method, and non-transitory computer readable medium are provided. The robot control device (300) performs abnormality diagnosis of a robot body (200) including a motor (201) that rotates, from a starting angle position to a target angle position, a rotational shaft (204) for transmitting power to an arm (203) so that the arm performs a predetermined operation. The robot control device includes: a drive control unit (304) driving the motor so that the rotational shaft rotates from the starting angle position to the target angle position within a rotational speed range of the rotational shaft in which it is possible to detect a vibration component caused by an abnormality from among the vibration components generated along with the rotation of the rotational shaft; a vibration detection unit (305) detecting the vibration component; and a diagnosis unit performing abnormality diagnosis based on the detected vibration component.

A state monitoring system for monitoring a state of a robot configured to perform work on a workpiece executes: a step of obtaining state data from a sensor and deriving a deterioration index parameter based on the obtained state data; a step of determining whether or not the deterioration index parameter is greater than a first threshold that is preset to a level lower than a level at which corrective maintenance is required; a step of further determining whether or not a frequency of having determined that the deterioration index parameter is greater than the first threshold is greater than a preset frequency threshold; and a step of suppressing an operation of the robot without stopping the robot if it is determined that the frequency is greater than the frequency threshold.

An apparatus for controlling a robot arm includes: the robot arm; a calibration board on which calibration marks for self-diagnosis are shown; a distance sensor mounted on the robot arm and configured to measure a distance; an image sensor mounted on the robot arm and configured to obtain an image; and a processor configured to move the robot arm to a position for the self-diagnosis, measure a distance from a predetermined part of the robot arm to the calibration board by using the distance sensor, obtain an image of the calibration board by using the image sensor, and output a signal indicating a malfunction of the robot arm in response to the measured distance being outside a distance error range, and an image measurement value of the obtained image being outside an image error range.

A method verifies functional/structural integrity of a hand-held unconstrained master device to control a robotic system for medical or surgical teleoperation. The master device includes a body having two rigid parts constrained to relatively rotate or translate on a common axis. Position vectors of two-plus points are measured and/or detected, each belonging to a respective one of the two rigid parts, and measuring and/or detecting evolution of the position vectors. An orientation of each of the points, and the evolution of the orientations are measured and/or detected. Constraints from constructional/structural features of the master device are defined, deriving from degrees of freedom. Mathematical relations associated with each of the defined constraints are calculated based on detected and/or measured position vectors, orientations and evolutions. A state of functional/structural integrity or non-integrity of the master device is determined, based on verification of the mathematical relations and degrees of freedom.

A system and related systems for detecting and diagnosing fault of a robot is provided. The method comprises: performing simulations according to robot control commands; calculating discrepancy between actual performance of robot based on the control commands and the results generated by the simulation, wherein a presence of discrepancy is indicative of fault; performing diagnostic exercises according to the discrepancy to identify a cause of the fault.

A method verifies functional/structural integrity of a hand-held unconstrained master device to control a robotic system for medical or surgical teleoperation. The master device includes a body having two rigid parts constrained to relatively rotate or translate on a common axis. Position vectors of two-plus points are measured and/or detected, each belonging to a respective one of the two rigid parts, and measuring and/or detecting evolution of the position vectors. An orientation of each of the points, and the evolution of the orientations are measured and/or detected. Constraints from constructional/structural features of the master device are defined, deriving from degrees of freedom. Mathematical relations associated with each of the defined constraints are calculated based on detected and/or measured position vectors, orientations and evolutions. A state of functional/structural integrity or non-integrity of the master device is determined, based on verification of the mathematical relations and degrees of freedom.

An apparatus for controlling a robot arm includes: the robot arm; a calibration board on which calibration marks for self-diagnosis are shown; a distance sensor mounted on the robot arm and configured to measure a distance; an image sensor mounted on the robot arm and configured to obtain an image; and a processor configured to move the robot arm to a position for the self-diagnosis, measure a distance from a predetermined part of the robot arm to the calibration board by using the distance sensor, obtain an image of the calibration board by using the image sensor, and output a signal indicating a malfunction of the robot arm in response to the measured distance being outside a distance error range, and an image measurement value of the obtained image being outside an image error range.

Methods and systems for determining a status of a component of a device are provided. An example method includes triggering an action of a component of a device, and responsively receiving information associated with the action of the component from a sensor. The method further includes a computing system having a processor and a memory comparing the information with calibration data and determining a status of the component based on the comparison. In some examples, the calibration data may include information derived from data received from a pool of one or more devices utilizing same or similar components as the component. The determined status may include information associated with a performance of the component with respect to performances of same or similar components of the pool of devices. In one example, the device may self-calibrate the component based on the status.

Methods and systems for determining a status of a component of a device are provided. An example method includes triggering an action of a component of a device, and responsively receiving information associated with the action of the component from a sensor. The method further includes a computing system having a processor and a memory comparing the information with calibration data and determining a status of the component based on the comparison. In some examples, the calibration data may include information derived from data received from a pool of one or more devices utilizing same or similar components as the component. The determined status may include information associated with a performance of the component with respect to performances of same or similar components of the pool of devices. In one example, the device may self-calibrate the component based on the status.