A measurement system and a method of measuring an object is provided. The system includes a measurement platform having a planar surface. At least two optical sensors are coupled to the measurement platform that emit light in a plane and determines a distance to an object based on a reflection of the light. A linear rail is coupled to the measurement platform. A cooperative robot is coupled to move along the linear rail. A 3D measuring system is coupled to the end of the robot. A controller coupled to the at least two optical sensors, the robot, and the 3D measuring system, the controller changing the speed of the robot and the 3D measuring system to less than a threshold in response to a distance measured by at least one of the at least two optical sensors to a human operator being less than a first distance threshold.

A robot arm apparatus according to the present disclosure includes: one or a plurality of a joint unit that joins a plurality of links constituting a multi-link structure; an acquisition unit that acquires an on-screen enlargement factor of a subject imaged by an imaging unit attached to the multi-link structure; and a driving control unit that controls driving of the joint unit based on a state of the joint unit and the enlargement factor.

Provided is an object conveying system including: a conveying apparatus that conveys an object; one or more cameras that capture images of feature points of the object; a position measuring portion that measures positions of the feature points from the acquired images; a detecting portion that detects a position or a movement velocity of the object; a position correcting portion that corrects the positions of the feature points so as to achieve positions at which the feature points are disposed at the same time; a line-of-sight calculating portion that calculates lines of sight that pass through the feature points on the basis of the corrected positions of the feature points and the positions of the cameras; and a position calculating portion that calculates a three-dimensional position of the object by applying a polygon having a known shape to the calculated lines of sight.

A method of quality inspection is performed by a robotic arm that includes a plurality of segments, a camera at an end of the robotic arm, and a plurality of joints connecting two segments of the plurality of segments. The method includes (i) inspecting, via the camera, a surface of a product with the camera positioned at a first position, (ii) based on the inspecting, identifying: (a) an area of interest on the surface of the product, and (b) a relative location of the area of interest on the surface, (iii) positioning, based on the relative location of the area of interest on the surface, the camera at a second position, and (iv) inspecting, via the camera, the area of interest on the surface of the product with the camera positioned at the second position. Inspecting the area of interest includes inspecting a subset of the surface of the product.

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 robotic gripping device is provided. The robotic gripping device includes a palm and a plurality of digits coupled to the palm. The robotic gripping device also includes a time-of-flight sensor arranged on the palm such that the time-of-flight sensor is configured to generate time-of-flight distance data in a direction between the plurality of digits. The robotic gripping device additionally includes an infrared camera, including an infrared illumination source, where the infrared camera is arranged on the palm such that the infrared camera is configured to generate grayscale image data in the direction between the plurality of digits.

An analog-to-digital converter includes: a first to an (m+1)-th capacitive element each of which has a first end connected to a first terminal of a comparison circuit and have a predetermined capacitance ratio; and selection circuits which are connected to second ends of the capacitive elements, respectively. Each of the capacitive elements includes: a first electrode disposed in a semiconductor substrate and electrically connected to the second end; a third electrode disposed above the semiconductor substrate to oppose the first electrode and electrically connected to the second end; a second electrode disposed between the first electrode and the third electrode, above the semiconductor substrate, and electrically connected to the first end; a first insulation film disposed between the first and second electrodes; and a second insulation film disposed between the third and second electrodes.

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 covariate shift generally refers to the change of the distribution of the input data (e.g., noise distribution) between the training and inference regimes. Such covariate shifts can degrade the performance grasping neural networks, and thus robotic grasping operations. As described herein, an output of a grasp neural network can be transformed, so as to determine appropriate locations on a given object for a robot or autonomous machine to grasp.

It is described an image labeling system (100) comprising: a support (2) for an object (3) to be labeled; a digital camera (1) configured to capture a plurality of images of a scene including said object (3); a process and control apparatus (5) configured to receive said images and generate corresponding labeling data (21-24, L1-L4) associated to said object (3); a digital display (4) associated with said support (2) and connected to the process and control apparatus (5) to selectively display additional images (7-13) selected from the group comprising: first images (7-11) in the form of backgrounds for the plurality of images and introducing a degree of variability in the scene; second images (12) indicating position and/or orientation according to which place said object (3) by a user on the support (2); third images (13) to be captured by the digital camera (1) and provided to the process and control apparatus (5) to evaluate a position of the digital camera (1) with respect the digital display (4); fourth images to be captured by the digital camera (1) and provided to the process and control apparatus (5) to evaluate at least one of the following data of the object (3): position, orientation, 3D shape.