A system for inspecting a structure includes a laser ultrasound device configured to direct laser light onto a surface of the structure that generates ultrasonic waves within the structure and to generate an array of ultrasound data representative of the ultrasonic waves. The system includes a robotic arm configured to move the laser light across the surface. The system includes a multiplex controller configured to trigger generation of the ultrasonic waves within the structure at an inspection location and to receive the array of ultrasound data for the inspection location. The system includes a computer system that includes a motion-control module configured to control movement of the laser light relative to the surface of the structure, a motion-tracking module configured determine when the laser light is at the inspection location, and an inspection module configured to process the array of ultrasound data to inspect the structure at the inspection location.

A calibration method for an industrial robot includes receiving a first model of the industrial robot, the first model is synchronized with an attitude state of the industrial robot located at a specific position in an actual environment; receiving an environment model around the industrial robot, the environment model including a second model of the industrial robot; obtaining registration information of the second model, at least by selecting at least three corresponding non-collinear point pairs in the first model and the second model to perform registration; and based on the registration information, calibrating a coordinate system of the environment model to a base coordinate system of the industrial robot.

A method for supporting designing and operation of a robotic system includes operating a computer-based Inventory configured to operate in a robotic system having Hardware Modules to perform a task, the Inventory including Hardware Module Descriptions including a unique identifier, a description of physical characteristics, a current status and historical data the Hardware Module. The method including the steps of collecting status data of the Hardware Module; collecting operating data representing usage of the Hardware Module and updating the historical data accordingly;

and at least one of the steps of scheduling maintenance actions to be performed on the Hardware Module; deriving or modifying, based on the operating data, historical data that is associated with a type of the Hardware Module.

A method of determining an installation site of a robot manipulator at a workstation, the method including: recording a respective image of the robot manipulator and of the workstation of the robot manipulator, and of a workpiece to be machined at the workstation via a camera unit, wherein the respective image contains spatial information; transmitting the respective image to a computing unit; and determining the installation site of the robot manipulator by applying a non-linear optimization of a predefined cost function and/or of a neural network via the computing unit based on a predefined task for machining the workpiece and based on the spatial information determined by the computing unit from the respective image.

Systems and a method for facilitating a concurrent simulation of multiple tasks of a plurality of robots in a virtual environment, wherein at least one virtual robot is foreseen to concurrently simulate one robotic motion task and a set of robotic logic tasks by concurrently executing one corresponding robotic motion program and a set of corresponding robotic logic programs on a set of operands. During a concurrent execution of the plurality of robotic motion programs and the plurality of sets of robotic logic programs of the plurality of robots, the execution of at least one given logic program is suspended and resumed by repetitively: executing a run of the given logic program; collecting a subset of operands used in the executed run; if none of the collected operands is modified in the execution run, suspending the execution of the given logic program and resuming its execution when one of the collected operands is modified.

Automatically performing an operation on an object-with a tool-carried by a polyarticulated system-that can be moved in a working environment, the object-and the working environment being open-ended or insufficiently defined to carry out the operation. A method comprises: capturing a scatter plot image of the object-and the working environment-with a 3D sensor, merging this image with the CAD model of the system and the environment into a working image, and defining anti-collision parameters;— defining a path of the tool-on the portion of the working image representing the object and executing a simulation of the corresponding movement of the system-and the tool in the working image so as to ensure that the operation is feasible;— and if the operation is feasible executing the actual movement of the system carrying the tool-according to the path defined for performing the operation on the object.

A control system includes: a robot controller configured to control a robot to execute a plurality of tasks included in a process for a workpiece in a real space; and circuitry configured to: control a virtual robot to execute the plurality of tasks in a virtual space; collect a real execution record from the real space during execution of each of the plurality of tasks by the robot; collect a virtual execution record from the virtual space during execution of each of the plurality of tasks by the virtual robot; and extract, from the plurality of tasks, one or more inconsistent tasks for which the real execution record and the virtual execution record are inconsistent with each other.

A system for trajectories imitation for robotic manipulators is provided. The system includes an interface configured to receive a plurality of task descriptions, wherein the interface is configured to communicate with a real-world robot, a memory to store computer-executable programs including a robot simulator, a training module and a transfer module, and a processor, in connection with the memory. The processor is configured to perform training using the training module, for the task descriptions on the robot simulator, to produce a plurality of source policy with subgoals for the task descriptions. The processor performs training using the training module, for the task descriptions on the real-world robot, to produce a plurality of target policy with subgoals for the task descriptions, and update the parameters of the transfer module from corresponding trajectories with the subgoals for the robot simulator and real-world robot.

One embodiment of the present invention sets forth a technique for controlling the execution of a physical process. The technique includes receiving, as input to a machine learning model that is configured to adapt a simulation of the physical process executing in a virtual environment to a physical world, simulated output for controlling how the physical process performs a task in the virtual environment and real-world data collected from the physical process performing the task in the physical world. The technique also includes performing, by the machine learning model, one or more operations on the simulated output and the real-world data to generate augmented output. The technique further includes transmitting the augmented output to the physical process to control how the physical process performs the task in the physical world.

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.