A surgical robotic system includes: a surgical console having a display and a user input device configured to generate a user input and a surgical robotic arm having a surgical instrument configured to treat tissue and being actuatable in response to the user input; and a video camera configured to capture video data that is displayed on the display. The system also includes a control tower coupled to the surgical console and the surgical robotic arm. The control tower is configured to: process the user input to control the surgical instrument and to record the user input as input data; train a machine learning system using the input data and the video data; and execute the at least one machine learning system to determine probability of failure of the surgical instrument.

A relay failure detection circuit includes a first voltage acquiring section configured to acquire an AC voltage input to a power supply circuit and output the AC voltage as a first voltage signal, a second voltage acquiring section configured to acquire an inter-terminal voltage of a relay provided in the power supply circuit and output the inter-terminal voltage as a second voltage signal, a comparing section configured to compare a waveform of the first voltage signal and a waveform of the second voltage signal, and a determining section configured to determine a failure of the relay according to a result of the comparison.

Methods and systems according to one or more examples are provided for testing an automated platform, such as a robot. In one example, a system comprises a first robot configured to perform one or more processing operations on a workpiece. The system further comprises a second robot configured to simulate one or more parameters of the workpiece and an associated processing operation to provide one or more test conditions corresponding to each of the one or more processing operations the first robot would perform on the workpiece to test the first robot.

The present invention relates to a method and system for health monitoring of a collaborative robot, includes the steps of calling a test program installed in a collaborative robot for health monitoring of the collaborative robot when the collaborative robot satisfies a call condition of the test program, performing a test by operating the collaborative robot based on the test program, and collecting and analyzing a result of the test by the collaborative robot, and may be applicable as another embodiment.

Techniques are described for testing whether an end effector, or component thereof, is correctly or incorrectly installed to a manipulation system. In an example, a manipulation system can include a manipulator arm configured to receive an end effector having a first moveable jaw, a transducer configured to provide first effort information of the end effector as the end effector moves, and a processor configured to provide a command signal to effect a first test move of the first moveable jaw, and to provide an installation status of the of the end effector using the first effort information of the first test move.

A remaining life of a robot body is precisely estimated. A robot control apparatus 300 includes: a drive control unit 305 that controls drive of a robot body 200; a detection unit 306 that detects a feature amount quantitatively indicating a deterioration degree of the robot body 200 that is deteriorated over time as the robot body 200 is driven; a determination unit 303 that determinates presence/absence of a sign of malfunction of the robot body 200 based on the feature amount; and an estimation unit 304 that estimates a remaining life of the robot body 200 when presence of a sign of malfunction of the robot body 200 is determined.

An example welding-type power supply includes: power conversion circuitry configured to convert input power to welding-type output power; auxiliary power output circuitry configured to output auxiliary power via an auxiliary power connection; communications circuitry configured to communicate via the auxiliary power connection; and processor(s) configured to: detect, via the communications circuitry, that a robot control system is coupled to the auxiliary power connection; and in response to detecting the robot control system, configuring the welding-type power supply based on receiving a communication from the robot control system via the communications circuitry.

Embodiments of the present invention provide methods and systems to analyze wearable technology. A robot with snake assembly works in conjunction with a server in order to simulate the locomotive actions of appendages and to concomitantly determine the response of wearable technology devices, which are attached to the snake robot assembly, to the simulated locomotive actions.

A method, a robot, and a robot controller for automatically scheduling the timing of a plurality of brake tests, that succeed one another at time intervals, at a plurality of brakes of a robot arm equipped with a plurality of joints and a plurality of links connecting the joints to one another and is connected to a robot controller which is designed and configured to control the joints and the brakes, in order to move the robot arm. At least one individual parameter is configured for each of the brakes. A brake test method associated with the robot arm is automatically initialized, and the initialized brake test method is automatically carried out in accordance with the configured parameters.

A method, a robot, and a computer program product for detecting and evaluating a friction status in at least one joint of a robotic arm, wherein, within the scope of a brake test program, at least one motor of a plurality of electric motors is driven automatically in a first rotational direction, wherein a detection of a first motor torque in the driven motor takes place during its rotation in the first rotational direction. The at least one motor is then driven in a second rotational direction opposite the first rotational direction, wherein a detection of a second motor torque in the driven motor takes place during its rotation in the second rotational direction. An automatic evaluation of the first motor torque and the second motor torque takes place in order to obtain the friction torque of the joint associated with the driven motor.