An object of the invention of the present application is to provide a medical supporting arm control apparatus that restricts an operation of a medical supporting arm apparatus.

A medical supporting arm control apparatus (20) according to the present disclosure includes: a position acquisition section (241) configured to detect a spatial position of an operating point on a multi-link structure (120) configured by coupling a plurality of links by a joint section; a comparison section (270) configured to compare a movable region of the operating point with the spatial position, the movable region being set in advance; and an operation restriction section (272) configured to restrict an operation of the operating point on a basis of a result of the comparison. According to this configuration, it is possible to restrict the operation of the medical supporting arm apparatus.

Systems and methods are provided for an automation system. The systems and methods calculate a motion trajectory of a manipulator and an end-effector. The end-effector is configured to grasp a target object. The motion trajectory defines successive positions of the manipulator and the end-effector along a plurality of via-points toward the target object. The systems and methods further acquire force/torque (F/T) data from an F/T sensor associated with the end-effector, and adjusts the motion trajectory based on the F/T data.

A method of improved quality inspection includes (i) receiving a first command to capture a first image of a surface of a product, (ii) positioning, by actuating a plurality of rotatable joints, a camera at a first position that is substantially adjacent to the surface of the product, and capturing the first image of the surface of the product. The method further includes, after capturing the first image: (i) processing the first image to identify a defect in the first image and a relative location of the defect in the first image, and (ii) determining a second position of the camera in accordance with the first position of the camera and the relative location of the defect in the first image, and (iii) repositioning, by actuating the plurality of rotatable joints, the camera from the first position to the second position. The method further includes capturing the second image.

A method of fabricating a laminated glass panel assembly having inner and outer glass layers includes masking a designated area of the inner glass layer to define an index feature and printing a first blackout layer onto the inner glass layer such that the first blackout layer is not present on the index feature. The method may include unmasking the index feature after printing the first blackout layer, then printing a second blackout layer onto a major surface of the outer glass layer. The major surface overlaps or covers the index feature such that the index feature is not visible to a human observer through the outer glass layer, but is detectable through the outer glass layer using a controller and machine vision logic. A glass panel assembly having the index feature is also described herein, as is a system for making the glass panel assembly.

Provided is a teaching device whereby it is possible to avoid twisting a fiber connected to a galvano scanner beyond an allowable range. A teaching device for teaching a robot in a laser machining system, wherein the teaching device includes a path determination unit for determining a motion path for a robot on the basis the positions of a plurality of machining points set on an object; a simulation execution unit for executing a robot motion simulation in accordance with the determined motion path; a torsion amount evaluation unit for ascertaining the amount of torsion of an optical fiber by simulating the behavior of the optical fiber in accordance with the movement of the robot according to the motion simulation, and evaluating the torsion amount by comparing the torsion amount and a prescribed allowable range; and a robot orientation changing unit for changing the orientation of the robot so as to reduce the torsion amount for motion of the robot in which the torsion amount exceeds the prescribed allowable range.

A robot system including: a robot with one or more movable elements respectively rotatable about one or more rotation axes; a control device that controls the robot; and a visual sensor attached to any of the movable elements of the robot, where the control device uses any of the movable elements of the robot as a subject element, compares a position of a predetermined target in a first image at an arbitrary first orientation of the robot at which the target fixed at a predetermined position is disposed inside a field of view of the visual sensor, and the position of the predetermined target in a second image at a second orientation at which the subject element is rotated about a rotation axis of the subject element with respect to the first orientation, and determines that the visual sensor is attached to the subject element.

A system for verifying quality of a part using an arm robot includes an arm robot, which includes a camera to acquire image data of a part assembled in each manufacturing process of a vehicle, a carrier, which includes a sliding rail allowing the arm robot to be movable around the vehicle along the sliding rail to acquire the image data, and a server which receives the image data acquired by the camera, compares the image data with modeling data of the vehicle, which is stored in a database, and determines whether the assembled part satisfies a preset inspection item, to verify quality of the assembled part, verifying the quality of the part in each process before the vehicle is completely manufactured.

An automated vehicle comprising: a control unit configured to control movement of the automated vehicle to a location adjacent an estimated location of a drill hole; a scanning portion including one or more scanning devices configured to scan an area of terrain in the vicinity of the estimated location of the drill hole in order to determine an actual location of the drill hole, and to generate a point cloud representing at least a portion of the interior of the drill hole; at least one arm associated with the scanning portion, the at least one arm configured to move the scanning portion between a home position and one or more scanning positions; and an end effector associated with the at least one arm, the end effector being configured to perform one or more operations;
wherein, upon generating the point cloud, the at least one arm is configured, based on the point cloud, to position the end effector in substantial alignment with the drill hole so that the end effector can perform the one or more operations.

A vision-guided picking and placing method for a mobile robot that has a manipulator having a hand and a camera, includes: receiving a command instruction that instructs the mobile robot to grasp a target item among at least one object; controlling the mobile robot to move to a determined location, controlling the manipulator to reach for the at least one object, and capturing one or more images of the at least one object using the camera; extracting visual feature data from the one or more images, matching the extracted visual feature data to preset feature data of the target item to identify the target item, and determining a grasping position and a grasping vector of the target item; and controlling the manipulator and the hand to grasp the target item according to the grasping position and the grasping vector, and placing the target item to a target position.

To easily and quickly detect a predetermined shape on an object. A shape detection method for detecting the shape of an object, the method comprising: a step of acquiring data indicating three-dimensional point group data from the object by a sensor, a step of displaying the three-dimensional point group data in a display area of a terminal, a step of acquiring the display area in which the three-dimensional point group data is displayed, as two-dimensional image data, and a step of performing image analysis on the two-dimensional image data, and detecting a predetermined shape of the object.