A robot system includes at least one robot, a first sensor, at least one second sensor, and circuitry. The at least one robot is to work on a workpiece. The first sensor is to detect a three-dimensional shape of the workpiece. The at least one second sensor is to detect a three-dimensional position of the workpiece. The circuitry is configured to control the at least one robot based on teaching data. The circuitry is configured to correct the teaching data according to the three-dimensional shape detected by the first sensor. The circuitry is configured to correct the teaching data according to the three-dimensional position detected by the at least one second sensor.

A system and method for operation of an autonomous vehicle (AV) yard truck is provided. A processor facilitates autonomous movement of the AV yard truck, and connection to and disconnection from trailers. A plurality of sensors are interconnected with the processor that sense terrain/objects and assist in automatically connecting/disconnecting trailers. A server, interconnected, wirelessly with the processor, that tracks movement of the truck around and determines locations for trailer connection and disconnection. A door station unlatches/opens rear doors of the trailer when adjacent thereto, securing them in an opened position via clamps, etc. The system computes a height of the trailer, and/or if landing gear of the trailer is on the ground and interoperates with the fifth wheel to change height, and whether docking is safe, allowing a user to take manual control, and optimum charge time(s). Reversing sensors/safety, automated chocking, and intermodal container organization are also provided.

Computerized RPA methods and systems that increase the flexibility and lower the cost with which RPA systems may be deployed are disclosed herein. In one embodiment, an RPA system and method avoids the need for preinstalled RPA software on a device employed by a user to create and/or execute software robots to perform RPA. In another embodiment, an RPA system and method provides a capability to execute software robots that may have been encoded in one or more programming languages to execute on an operating system different than that employed by a server of the RPA system.

A humanoid robot balance control method, a humanoid robot, and a storage medium are provided. The method includes: obtaining a task equation of each of a plurality of deconstructed tasks in a corresponding control cycle by solving a plurality of deconstructed task models using a relevant actual state and a corresponding expected state of the humanoid robot; calculating an optimal solution of a multi-task error optimization function based on each task equation; and generating a joint control instruction of the corresponding control cycle based on the optimal solution in response to the optimal solution being obtained within the corresponding control cycle so as to control corresponding joint(s) to execute the tasks. In such manner, it can ensure that the robot satisfies the necessary constraints while executing multiple tasks, and also comprehensively considers the errors of all the tasks to ensure the execution of all the tasks.

According to the present invention, provided is a robot control device that can improve relatively easily the positioning accuracy of a robot. A robot control device according to one aspect of the present disclosure comprises: a position information acquisition unit which acquires position information indicating the actual position of a reference point at the end of a robot having a plurality of drive shafts; a parameter storage unit which stores a plurality of error parameters used to calculate the accurate position of the reference point from a command value for the robot; a sensitivity calculation unit which calculates a sensitivity value representing the magnitude of the change amount of the calculated position of the reference point with respect to the change amount for each error parameter; a target selection unit which selects, on the basis of the sensitivity value, an error parameter to be corrected by the parameter correction unit; and a parameter correction unit which corrects the error parameter to be corrected on the basis of the command value for the robot and the position information, assuming that error parameters other than the error parameter to be corrected do not affect the position of the reference point.

A control system includes circuitry configured to: generate, based on a command profile representing a temporal change of a command for driving a controlled object and a response profile representing a temporal change of a state of the controlled object responding to the command profile, a first model representing at least a part of a relation between the command and the state of the controlled object; generate, based on the command profile, the response profile, and the first model, a second model representing another part of the relation that is not represented by the first model; generate, based on the first model and the second model, one or more control parameters representing a relation between a control reference and the command for causing the controlled object to follow the control reference; and control the controlled object to cause the state of the controlled object to follow the control reference based at least in part on the control reference and the one or more control parameters.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving, by one or more non-real-time processors, data defining a light illumination pattern for a robotic device. Generating, by the one or more non-real-time processors and based on the data, a spline that represents the light illumination pattern, where a knot vector of the spline defines a timing profile of the light illumination pattern. Providing the spline to one or more real-time processors of the robotic system. Calculating, by the one or more real-time processors, an illumination value from the spline at each of a plurality of time steps. Controlling, by the one or more real-time processors, illumination of a lighting display of the robotic system in accordance with the illumination value of the spline at each respective time step.

Teaching including adjustment of an inclination of a suction tool with respect to an object is performed in teaching of a suction position of the suction tool. A sticker affixing system includes an articulated robot, a controller, a suction tool attached to a distal end of the articulated robot, a force sensor, and a storage. The controller causes the articulated robot to execute an operation of bringing the suction tool close to a sticker on a release paper in a teaching mode, an operation of adjusting a suction position of the suction tool and an inclination in a traveling direction (roll axis X) of the suction tool in peeling off the sticker based on a signal from the force sensor, and an operation of storing the teaching data including information about the adjusted suction position and the inclination of the suction tool in the storage.

An information technology system for a distributed manufacturing network includes an additive manufacturing platform configured to manage workflows for a set of distributed manufacturing network entities associated with the distributed manufacturing network. The information technology system includes a set of digital twins generated by the additive manufacturing platform. The information technology system includes an artificial intelligence system configured to be executed by a data processing system in communication with the additive manufacturing platform. The artificial intelligence system is trained to generate process parameters for the workflows managed by the additive manufacturing platform using data collected from the set of distributed manufacturing network entities. The information technology system includes a control system configured to adjust the process parameters during an additive manufacturing process performed by at least one of the set of distributed manufacturing network entities.

A learning dataset generation device includes: a memory that stores three-dimensional CAD data of a workpiece and a container; and one or more processors including hardware, wherein the one or more processors are configured to use the three-dimensional CAD data of the workpiece and the container, stored in the memory, to generate, in a three-dimensional virtual space, a plurality of imaging objects in which a plurality of the workpieces are bulk-loaded in different forms inside the container, acquire a plurality of virtual distance images by measuring each of the generated imaging objects by means of a virtual three-dimensional measurement machine disposed in the three-dimensional virtual space, accept at least one teaching position for each of the acquired virtual distance images, and generate a learning dataset by associating the accepted teaching position with each of the virtual distance images.