The present invention corrects errors made by a machining tool having a discretionary machine configuration, by using a graph in which constituent elements serve as nodes. This control device comprises: a control point coordinate system insertion unit that inserts, as nodes, a control point and a coordinate system, for each node of a machine configuration graph; an identifier allocation unit that allocates an identifier to the inserted control points and coordinate systems; an error information storage unit that stores information relating to a machine error on a control subject, and the identifier allocated to the coordinate system in which the machine error was observed; an error node generation unit that converts the machine error to an equivalent error node; and an error node addition unit that adds the error node to the machine configuration graph.

A detection and tracking system and method using a camera unit on a robot, or alternatively a camera mounted inside the pool overlooking the bottom of the pool, for safety monitoring for use in and around water-related environments. The robot is able to propel itself and move throughout the body of water, both on the surface and underwater, and the camera unit functions both on the surface and underwater. The robot optimizes the cleaning cycle of the body of water utilizing deep learning techniques. The robot has localization sensors and software that allow the robot to be aware of the robot's position in the pool. The camera is able to send its video feed live over the internet, the processing is performed in the cloud, and the robot sends and receives data from the cloud. The processing utilizes deep learning algorithms, including artificial neural networks, that perform video analytics.

The present disclosure relates to a drilling robot and a method for controlling a drilling robot including a driven mechanical structure allowing to place a drilling tool in a sequence of drillings programmed in terms of position and orientation of the drilling of a part such as a technical skin. The method includes a step of determining the acceleration of the drilling tool at the end of the approach on a drilling position, then also testing a stabilization condition of the drilling tool to finally establish a drilling authorization.

A non-transitory computer-readable storage medium stores a computer program that controls a processor to execute (a) processing of displaying an operation window for operation of a position and an attitude of a control point for a robot arm, (b) processing of storing the position and the attitude of the control point as a teaching point according to an instruction of a user, and (c) processing of associating and storing the operation window when the instruction is received in the processing (b) with the teaching point.

A computer-implemented method, executed by data processing hardware of a robot, includes receiving sensor data for a space within an environment about the robot. The method includes receiving, from a user interface (UI) in communication with the data processing hardware, a user input indicating a user-selection of a location within a two-dimensional (2D) representation of the space. The location corresponds to a position of a target object within the space. The method includes receiving, from the UI, a plurality of grasping inputs designating an orientation and a translation for an end-effector of a robotic manipulator to grasp the target object. The method includes generating a three-dimensional (3D) location of the target object based on the received sensor data and the location corresponding to the user input. The method includes instructing the end-effector to grasp the target object using the generated 3D location and the plurality of grasping inputs.

There is provided a display control method for controlling a display section configured to display a display image including a virtual robot, which is a simulation model of a robot including a robot arm that performs work according to force control, the display control method including a receiving step for receiving information concerning force control parameters including first information concerning a target force, which is a target of force received by the robot arm during the work, and a display step for displaying, in the display image, the virtual robot, a first indicator indicating the first information, and a second indicator indicating second information concerning force applied to the robot arm during the work, the virtual robot, the first indicator, and the second indicator temporally overlapping one another and being distinguished from one another.

A robot teaching system includes: a robot position and attitude calculation unit that calculates positions and attitudes of a robot corresponding to respective teaching instructions and points between the respective teaching instructions included in a working program for operating the robot; an imaginary robot information generation unit that generates imaginary robot information corresponding to the respective teaching instructions and the points between the respective teaching instructions on a basis of the positions and attitudes of the robot; a teaching instruction selection unit that selects at least one of the respective teaching instructions included in the working program; and a display unit that displays the imaginary robot information on a basis of the selected teaching instruction. The robot teaching system is able to easily confirm the position and attitude of the robot in an arbitrary teaching instruction of the working program.

A detection and tracking system and method using a camera unit on a robot, or alternatively a camera mounted inside the pool overlooking the bottom of the pool, for safety monitoring for use in and around water-related environments. The robot is able to propel itself and move throughout the body of water, both on the surface and underwater, and the camera unit functions both on the surface and underwater. The robot optimizes the cleaning cycle of the body of water utilizing deep learning techniques. The robot has localization sensors and software that allow the robot to be aware of the robot's position in the pool. The camera is able to send its video feed live over the internet, the processing is performed in the cloud, and the robot sends and receives data from the cloud. The processing utilizes deep learning algorithms, including artificial neural networks, that perform video analytics. The robot acts as a game platform such that the camera unit on the robot facilitates augmented reality games. The user of those games is not in the pool, but instead is using a mobile device outside the pool. The game on the mobile device constantly receives and sends data to the cloud, and the robot constantly sends and receives data to the cloud, such that the game involves creatures and locations throughout the pool that are not physically present, but are visible to the user on the mobile device. The data the robot sends to the cloud is based on the robot's sensors and software, and this data is used as part of the game to display creatures and other aspects of an augmented reality game.

A teach pendant includes an input unit and allowing teaching of operation of a robot by an input to the input unit, the teach pendant further includes a measurement reference surface which comes into surface contact with a measured surface of the robot, a tilt sensor whose position is fixed with respect to the measurement reference surface, and an output means which outputs a detection value of the tilt sensor to a control device of the robot in a state where the measurement reference surface is in surface contact with the measured surface and when a predetermined input operation is performed on the input unit or a contact detection sensor for detecting surface contact between the measurement reference surface and the measured surface detects the surface contact.

Provided is a robot center-of-gravity display device including: a specification setting unit that sets specifications including the weights, center-of-gravity positions, and dimensions of components of respective shafts; a posture setting unit that sets position information of the respective shafts; a robot-image generating unit that generates a three-dimensional model image of the robot in a state where the respective shafts are located at the positions indicated by the position information, based on the set position information of the respective shafts and the specifications of the components; a center-of-gravity-position calculation unit that calculates the center-of-gravity position of the overall robot, based on the set position information of the respective shafts and the specifications of the components; an image combining unit that superimposes an indication showing the center of gravity of the overall robot on the three-dimensional model image at the calculated center-of-gravity position; and a display unit that displays the generated image.