This disclosure relates to a method of controlling a collaborative robot, or “cobot”. According to the disclosed method the “cobot” is controlled so as to make it ready to perform a task in collaboration with the human operator only when the latter is about to move into a work sector to carry out the task collaborating with the robot. The control method of the present disclosure can be implemented by means of a control system comprising detection devices, such as for example one or more cameras or a mat equipped with sensors, which detect the position of the hands or of the entire body of the operator in the space of work, a memory in which to store identification data of the sectors of work engaged by the human operator, of the times of permanence in them and of the successive sectors of work in which the human operator moves, as well as a control microprocessor unit which processes this data stored in the memory according to the method of this disclosure to predict in which work sector the operator will move his hands and when that will happen, and which controls a robot based on this prediction information. The method of this disclosure can be implemented by means of software executed by a microprocessor unit.

An inspection robot incudes a robot body, at least two sensors, a drive module, a stability assist device and an actuator. The at least two sensors are positioned to interrogate an inspection surface and are communicatively coupled to the robot body. The drive module includes at least two wheels that engage the inspection surface. The drive module is coupled to the robot body. The stability assist device is coupled to at least one of the robot body or the drive module. The actuator is coupled to the stability assist device at a first end, and coupled to one of the drive module or the robot body at a second end. The actuator is structured to selectively move the stability assist device between a first position and a second position. The first position includes a stored position. The second position includes a deployed position.

A robotic surgical system and method are disclosed for transitioning control to a secondary robotic arm controller. In one embodiment, a robotic surgical system comprises a user console comprising a display device and a user input device; a robotic arm configured to be coupled to an operating table; a primary robotic arm controller configured to move the robotic arm in response to a signal received from the user input device at the user console; and a secondary robotic arm controller configured to move the robotic arm in response to a signal received from a user input device remote from the user console. Control over movement of the robotic arm is transitioned from the primary robotic arm controller to the secondary robotic arm controller in response to a failure in the primary robotic arm controller. Other embodiments are provided.

An industrial robot system including a first robot. The first robot includes a first manipulator with a base and a tool movable in relation to the base about a plurality of axes, and a first primary controller having a primary robot functionality, the primary robot functionality including control of manipulator motion. The industrial robot system further includes a plurality of secondary controllers, each having a secondary robot functionality, wherein the primary robot functionality is different from all of the secondary robot functionalities, and wherein an overall robot functionality is defined by the primary robot functionality and one or more secondary robot functionalities.

A processing system having at least one processor operatively coupled to at least one memory. The processor receives sensor data from the at least one sensor indicating one or more characteristics of the asset. The processor generates, updates, or maintains a digital representation that models the one or more characteristics of the asset. The processor detects a defect of the asset based at least in part on the one or more characteristics. The processor generate an output signal encoding or conveying instructions to provide a recommendation to an operator, to control the at least one robot to address the defect on the asset, or both, based on the defect and the digital representation of the asset.

A method for controlling a robot includes applying a setpoint force to a contact point; measuring a contact stiffness at the contact point; and slowing down the moving robot using its drives and/or braking the robot to apply the setpoint force to the contact point by the slowing down and/or slowed down robot depending on the measured contact stiffness, wherein the robot is slowed down before the setpoint force is reached.

A system is disclosed and includes an electronic controller configured to generate a virtual reality representation of an environment. The electronic controller is configured to generate a menu within the virtual reality representation of the environment comprising at least one task user interface element and determine when an option for configuring a force parameter is selected from the at least one task user interface element in the menu. The electronic controller is configured to prompt a user to configure the force parameter for a virtual robot manipulation task and assign at least one of a force magnitude or a force direction to the virtual robot manipulation task in response to an input received from the prompt to configure the force parameter.

Methods, apparatus, and computer-readable media for determining and utilizing human corrections to robot actions. In some implementations, in response to determining a human correction of a robot action, a correction instance is generated that includes sensor data, captured by one or more sensors of the robot, that is relevant to the corrected action. The correction instance can further include determined incorrect parameter(s) utilized in performing the robot action and/or correction information that is based on the human correction. The correction instance can be utilized to generate training example(s) for training one or model(s), such as neural network model(s), corresponding to those used in determining the incorrect parameter(s). In various implementations, the training is based on correction instances from multiple robots. After a revised version of a model is generated, the revised version can thereafter be utilized by one or more of the multiple robots.

A total time necessary for work is shortened by reducing program correcting. A control device has a teaching program storage storing a teaching program, a command interpreter transmitting a movement-related command to a movement-related command separator, determining whether the command is a synchronous interval command or an asynchronous interval command and separating the movement-related command into command of each device according to a determination result, and executing a non-movement-related command, a movement-related command buffer selecting one of the transmission of the movement-related command to the sub-locus calculator and accumulating movement-related command therein based on a device movement state, a main locus calculator calculating movement information on the device on which synchronous control is performed from the movement-related command, a sub-locus calculator calculating movement information on the device that is not a synchronous control target based on the movement-related command, and a motor driver performing operations of the devices.

A system includes an inspection robot having an input sensor comprising a laser profiler and a plurality of wheels structured to engage a curved portion of an inspection surface, wherein the laser profiler is configured to provide laser profiler data of the inspection surface; a controller, comprising: a profiler data circuit structured to interpret the laser profiler data; determine a feature of interest is present at a location of the inspection surface in response to the laser profiler data; and wherein the feature of interest comprises a shape description of the inspection surface at the location of the feature of interest.