Abstract: The objective of the present invention is to provide a robot system with which, if the position of a robot becomes displaced, it is easy to perform work by employing a camera or the like to apply a three-dimensional correction. This robot system is provided with: a robot 2; a robot conveying device 3 on which the robot is mounted, for moving the robot to a predetermined work space; at least two target marks 4 installed in the work space; a target mark position acquiring unit 5 for obtaining a three-dimensional position by using a vision sensor provided on the robot 2 to perform stereoscopic measurement of the at least two target marks 4; a displacement amount acquiring unit 6 for obtaining the displacement amount between the robot 2 and a desired relative position in the work space, from the acquired three-dimensional position; and a robot control unit 7 for activating the robot 2 using a value adjusted from a prescribed activation amount, using the acquired displacement amount.

Abstract: A three-dimensional-measurement device includes: a projector for projecting while scanning reference light onto an object; a light-receiver for receiving the reference light reflected by the object, monitoring a luminance change for each pixel, and outputting the position of the pixel, the time at which a luminance change occurred, and a polarity representing the direction of the luminance change as an event, when a luminance change is equal to or greater than a pre-set threshold value; and a calculator for selecting an event group including a designated number of events in which the events change from positive to negative polarity, calculating a passage time at which the reference light passes a pixel based on the time of an event included in the event group and the threshold value of the luminance change constituting occurrence of the event, and calculating three-dimensional information of the object by triangulation based on the passage time.

Abstract: This three-dimensional measurement device comprises: a projection unit that projects reference light to an object while performing scanning with the light; a light reception unit that receives the reference light reflected on the object; a time extent setting unit that sets a scanning time extent of the reference light in accordance with a distance-measuring range for each prescribed section of the light reception unit; and a three-dimensional information calculation unit that calculates three-dimensional information about the object W by means of triangulation based on information of the light reception unit within the set scanning time extent.

Abstract: An image processing apparatus, which receives an input image and detects an image of a target object based on a detection algorithm, includes a machine learning device which performs learning by using a plurality of partial images cut out from at least one input image, based on a result of detection of the image of the target object, and calculates a likelihood of the image of the target object.

Abstract: A distance image capturing system including: an image acquisition unit for capturing a plurality of images of an object at the same image capturing position and in the same image capturing orientation with respect to the object to acquire a plurality of first distance images; an image synthesis unit for synthesizing the plurality of first distance images to generate a second distance image; and a number-of-image-capturing-operation determination unit for estimating a distance measurement error in the second distance image and determining the number of image capturing operations for the first distance images at which the estimated distance measurement error is equal to or less than a predetermined target error.

Abstract: A three-dimensional measurement device includes a camera for acquiring position information for three-dimensional points on the surface of an object on the basis of the time of flight of light, and a control device. The camera acquires, at a plurality of relative positions of the camera with respect to a workpiece, three-dimensional point position information. A plurality of evaluation regions are defined for the workpiece. The control device specifies, for each evaluation region, the three-dimensional point closest to a reference plane from among three-dimensional points detected in the evaluation region. The control device generates, on the basis of the multiple three-dimensional points specified for the respective evaluation regions, three-dimensional point position information in which multiple pieces of three-dimensional point position information acquired by the camera are combined.

Abstract: Provided is an object detection device which can detect with high accuracy a symmetrical target object represented in an image.

Abstract: A robot system includes a target position calculation section which calculates, when a first feature can be detected from an image, a target position of a robot based on the calculated position of the first feature and a stored first positional relationship, and calculates, when the first feature cannot be detected from the image and a second feature can be detected from the image, a target position of the robot based on the calculated position of the second feature and the stored first positional relationship.

Abstract: An image management device includes: an image data acquisition unit that acquires image data snapped by a visual sensor; an image snap condition acquisition unit that acquires an image snap condition applied when the image data is snapped, from a manufacturing machine and the visual sensor; an archive data creation unit that creates archive data based on the image data and the image snap condition; and an archive data storage unit that stores the archive data. The archive data creation unit creates archive data after recording the image snap condition in a file. The image management device can easily reuse image data that is snapped by the visual sensor attached to the manufacturing machine and an image snap condition of the image data.

Abstract: A machine learning device includes a state observation unit for observing, as state variables, an image of a workpiece captured by a vision sensor, and a movement amount of an arm end portion from an arbitrary position, the movement amount being calculated so as to bring the image close to a target image; a determination data retrieval unit for retrieving the target image as determination data; and a learning unit for learning the movement amount to move the arm end portion or the workpiece from the arbitrary position to a target position. The target position is a position in which the vision sensor and the workpiece have a predetermined relative positional relationship. The target image is an image of the workpiece captured by the vision sensor when the arm end portion or the workpiece is disposed in the target position.

Abstract: An image processing device that detects an image of an object from input data captured by a vision sensor, on the basis of a model pattern including a set of a plurality of first feature points representing the shape of the object, includes an object detection unit that detects images of the object by matching between a plurality of second feature points extracted from the input data and a plurality of first feature points forming the model pattern, a corresponding point selection unit that selects, for each image of the object, second feature points corresponding to the first feature points and stores the selected second feature points as corresponding points, and a model pattern correction unit that calculates a statistic of a predetermined physical quantity of the plurality of corresponding points associated with each first feature point and corrects the first feature point on the basis of the statistic.

Abstract: An image processing device including an object detection unit for detecting one or more images of objects from an input picture image, on the basis of a model pattern of the object, and a detection result display unit for graphically superimposing and displaying a detection result. The detection result display unit includes a first frame for displaying the entire input picture image and a second frame for listing and displaying one or more partial picture images each including an image detected. In the input picture image displayed in the first frame, a detection result is superimposed and displayed on all the detected images, and in the partial picture image displayed in the second frame, a detection result of an image corresponding to each partial picture image is superimposed and displayed.

Abstract: An image processing apparatus includes a graphical image generator that generates a first graphical image and a second graphical image, and a mode switching unit that switches between a first display mode and a second display mode so that a display displays the first graphical image or the second graphical image. Each graphical image includes a color wheel indicating a two-dimensional color space of hue and saturation and a lightness bar indicating a one-dimensional color space of lightness. In the first graphical image, each position in the color wheel and the lightness bar is indicated by the hue and saturation indicated by that position. In the second graphical image, a distribution of colors included in the color image in the color space of hue and saturation or the color space of lightness is superposed on the color wheel and the lightness bar.

Abstract: An inspection system includes a first imaging device provided in a first inspection device; a second imaging device provided in a second inspection device; a first controller; and a second controller, wherein the first controller acquires a particular feature of a calibration jig, which is positioned in the first inspection device, from an image of the calibration jig obtained by the first imaging device as first feature data, and the second controller acquires the particular feature of the calibration jig, which is positioned in the second inspection device, from an image of the calibration jig obtained by the second imaging device as second feature data. The correction amount needed for correcting the image obtained by the second imaging device so that the second feature data matches the first feature data is acquired, and the second inspection device corrects an image of an inspection subject using this correction amount.

Abstract: A device capable of easily defining an area other than a surface to be inspected of a workpiece. The device includes a drawing acquisition section for acquiring drawing data of the workpiece; a designation reception section for receiving specification of the surface to be inspected of the workpiece in the drawing data; and a non-inspection area calculation section for calculating, as a non-inspection area, an image area other than the surface to be inspected in an image in a view of the imaging section when the workpiece and the imaging section are positioned at an imaging position at which at least a part of the surface to be inspected as specified falls within the view of the imaging section.

Abstract: An image processing apparatus, which receives an input image and detects an image of a target object based on a detection algorithm, includes a machine learning device which performs learning by using a plurality of partial images cut out from at least one input image, based on a result of detection of the image of the target object, and calculates a likelihood of the image of the target object.

Abstract: An apparatus capable of quickly constructing an operation program that causes an inspection system to carry out an operation for imaging the surface to be inspected. This apparatus includes a drawing acquisition section configured to acquire drawing data of the workpiece, a designation receiving section configured to accept designation of the surface to be inspected in the drawing data, a target position acquisition section configured to acquire, as a target position, a position of the movement mechanism when the workpiece and the imaging section are positioned such that the surface to be inspected is within a field of view of the imaging section, and a program generation section configured to generate an operation program for controlling a movement operation of the movement mechanism and an imaging operation of the imaging section on the basis of the target position.

Abstract: For calibration on a single camera or a stereo camera, a calibration range is set in advance in an image coordinate system and the calibration is performed in an arbitrary range. A visual sensor controller is a calibration device that associates a robot coordinate system at a robot and an image coordinate system at a camera by placing a target mark at the robot, moving the robot, and detecting the target mark at multiple points in a view of the camera. The calibration device comprises: an image range setting unit that sets an image range in the image coordinate system at the camera; and a calibration range measurement unit that measures an operation range for the robot corresponding to the image range before implementation of calibration by moving the robot and detecting the target mark.

Abstract: An object inspection system enabling a quick and easy registering of a master image and an inspection image when there is a displacement between the master image and the inspection image. The object inspection system includes an imaging section, a movement machine configured to move a first object or a second object and an imaging section relative to each other, a positional data acquisition section configured to acquire positional data of the movement machine when the movement machine disposes the first object or the second object and the imaging section at a relative position, an image data acquisition section configured to acquire a first image of the first object and a second image of the second object, and an image registering section configured to register the first image and the second image.

Abstract: A machine learning device that acquires state information from a robot control inspection system. The system has a robot hand to hold a workpiece or camera. The state information includes a flaw detection position of the workpiece, a movement route of the robot hand, an imaging point of the workpiece, and the number of imaging by the camera. A reward calculator calculates a reward value in reinforcement learning based on flaw detection information including the flaw detection position. A value function updater updates an action value function by performing the reinforcement learning based on the reward value, the state information, and the action.