Abstract: According to one embodiment, a training device is configured to perform first to third training. The first training includes training a first policy in a simulation environment, the first policy being configured to determine a gripping operation of a robot arm including a gripper. The second training includes training a second policy in a real environment, the second policy being configured to determine the gripping operation of the robot arm. The third training includes training a model configured to output, according to an input of an image, grip information for gripping an object. The second training includes training the second policy by using an output from the first policy and sensor information acquired in the gripping operation. The third training includes training the model by using, as teaching data, a first image of a first environment of reality and grip information output from the second policy.

Abstract: According to one embodiment, a medical image diagnostic apparatus includes a storage memory, processing circuitry, and a display. The storage memory stores data of a plurality of FFR distribution maps constituting a time series regarding a coronary artery, and data of a plurality of morphological images corresponding to the time series. The processing circuitry converts the plurality of FFR distribution maps into a plurality of corresponding color maps, respectively. The display displays a plurality of superposed images obtained by superposing the plurality of color maps and the plurality of morphological images respectively corresponding in phase to the plurality of color maps. The display restricts display targets for the plurality of color maps based on the plurality of FFR distribution maps or the plurality of morphological images.

Abstract: A handling apparatus includes a controller and a picking tool for a target object. The controller calculates surface information about a target object by using a first learning model for estimating the surface information from a feature map. The feature map represents a feature of an input image including the target object. The controller identifies surfaces in the input image from the surface information, and transforms the input image into projection images, each being seen from above a point on each of the surfaces in a normal vector direction. The controller calculates, for each projection image, a grasp posture for gripping the target object by using a second learning model. The controller transforms the grasp posture into a grasp posture in a first coordinate system. The controller calculates a final posture of the picking tool by projecting the grasp posture in the first coordinate system onto the input image.

Abstract: A handling apparatus includes a controller and a picking tool for a target object. The controller calculates surface information about a target object by using a first learning model for estimating the surface information from a feature map. The feature map represents a feature of an input image including the target object. The controller identifies surfaces in the input image from the surface information, and transforms the input image into projection images, each being seen from above a point on each of the surfaces in a normal vector direction. The controller calculates, for each projection image, a grasp posture for gripping the target object by using a second learning model. The controller transforms the grasp posture into a grasp posture in a first coordinate system. The controller calculates a final posture of the picking tool by projecting the grasp posture in the first coordinate system onto the input image.

Abstract: There is provided a medical image processing apparatus which includes a first extraction unit configured to extract coronary arteries depicted in images of a plurality of time phases relating to the heart, and to extract at least one stenosed part depicted in each coronary artery; a calculation unit configured to calculate a pressure gradient of each of the extracted coronary arteries, based on tissue blood flow volumes of the coronary arteries; a second extraction unit configured to extract an ischemic region depicted in the images; and a specifying unit configured to specify a responsible blood vessel of the ischemic region by referring to a dominance map, in which each of the extracted coronary arteries and a dominance territory are associated, for the extracted ischemic region, and to specify a responsible stenosis, based on the pressure gradient corresponding to a stenosed part in the specified responsible blood vessel.

Abstract: A handling apparatus includes a controller and a picking tool for a target object. The controller calculates surface information about a target object by using a first learning model for estimating the surface information from a feature map. The feature map represents a feature of an input image including the target object. The controller identifies surfaces in the input image from the surface information, and transforms the input image into projection images, each being seen from above a point on each of the surfaces in a normal vector direction. The controller calculates, for each projection image, a grasp posture for gripping the target object by using a second learning model. The controller transforms the grasp posture into a grasp posture in a first coordinate system. The controller calculates a final posture of the picking tool by projecting the grasp posture in the first coordinate system onto the input image.

Abstract: According to one embodiment, a determination device is configured to acquire an image of an object to be gripped and input the image to a determination part. The determination device is configured to obtain, from the determination part, an acquisition method of a gripping point. According to the input of the image, the determination part outputs, as the acquisition method, one of a first method, a second method, or a third method. The first method is a method of calculating exterior shape data of the object based on the image and calculating the gripping point by using the exterior shape data. The second method is a method of inputting the image to a second model and acquiring the gripping point output from the second model, the second model being trained. The third method is a method of acquiring the gripping point by the gripping point being designated.

Abstract: According to one embodiment, a processing device is configured to communicate with a handling device including a handling robot and an inspection unit; the handling robot transfers an article; and the inspection unit inspects the transferred article. The processing device is configured to detect an occurrence of an error of the handling device. The processing device is configured to determine a process in which the error occurred and a cause of the occurrence of the error. The processing device is configured to determine a change of management information of the article due to the error by using a determination result of the process and a determination result of the cause.

Abstract: According to one embodiment, a processing device includes a memory and one or more processors coupled to the memory. The one or more processors are configured to: divide shape data of a surface of an inspection object into a plurality of curved surfaces; calculate a plurality of teaching points indicating positions at which the inspection object is inspected by an inspection device mounted on a movable body; calculate a path between curved surfaces transitioning the plurality of curved surfaces and a path in a curved surface transitioning teaching points within the curved surface of each of the plurality of curved surfaces; and calculate, based on the path between the curved surfaces, the path in the curved surface, and movement performance of the movable body, an orbit of the movable body so that an inspection time of the inspection object becomes shorter.

Abstract: A tightening device includes a mobile part, a bolt tensioner, a bolt tensioner operation part, a positioning part, and a controller. The mobile part can be moved by driving control. The bolt tensioner performs a tightening operation for a bolt by operation of the operation part. The positioning part is mounted on the mobile part and is mounted with the bolt tensioner and the operation part, and positions a three-dimensional position of the bolt tensioner. The controller causes the mobile part to move so that a distance to the bolt falls within a certain value, causes the positioning part to operate so that the three-dimensional position becomes a position where the bolt is tightened after the mobile part is moved, and drives the operation part so that the bolt tensioner performs the tightening operation after the three-dimensional position is determined to be the position where the bolt is tightened.

Abstract: In an embodiment, a processing device relating to an inspection of an inspection object by a photography unit is provided. A processor of the processing device calculates a plurality of photography points as positions photographing the inspection object based on shape data in which a shape of a surface of the inspection object is indicated by a point group, and information relating to a position and a normal vector on the surface of the inspection object is defined by the point group. The processor executes analysis regarding a path that passes through all of the calculated photography points and minimizes a sum of a movement cost from each of the photography points to a photography point of a next movement destination, and calculates a path corresponding to an analysis result as a path for moving the photography unit.

Abstract: According to an embodiment, a work support device includes a measurement unit and an irradiation control unit. The measurement unit measures an in-passage structure of a passage inside of which a user can work. The irradiation control unit controls an irradiation unit to emit light indicative of a work region to a corrected work position obtained by correcting work position information set based on a predetermined designed in-passage structure indicative of an ideal structure in the passage by using a result of the measurement by the measurement unit.

Abstract: According to one embodiment, a medical image diagnostic apparatus includes a storage memory, processing circuitry, and a display. The storage memory stores data of a plurality of FFR distribution maps constituting a time series regarding a coronary artery, and data of a plurality of morphological images corresponding to the time series. The processing circuitry converts the plurality of FFR distribution maps into a plurality of corresponding color maps, respectively. The display displays a plurality of superposed images obtained by superposing the plurality of color maps and the plurality of morphological images respectively corresponding in phase to the plurality of color maps. The display restricts display targets for the plurality of color maps based on the plurality of FFR distribution maps or the plurality of morphological images.

Abstract: According an embodiment, a work support device includes an arm unit, a brake unit, a state determination unit, and a brake control unit. The arm unit includes a grasping part configured to grasp an object, a plurality of joint parts, and a plurality of link parts actuatably coupled through each joint part. The brake unit is provided to at least one of the joint parts to restrict actuation of the arm unit. The state determination unit determines the state of the arm unit. The brake control unit controls the brake unit to restrict actuation of the arm unit in accordance with the state of the arm unit.

Abstract: A control apparatus according to an embodiment includes one or more hardware processors. The processors acquire, for each of elements, pieces of input data representing first physical field of a corresponding one of the elements at a first time point. The elements are obtained by discretization of an object to be controlled. The processors calculate, for each element, second physical field of a corresponding element at a second time point after the first time point. The second physical field is calculated based on a value of an energy functional representing energy of the corresponding element. The value of the energy functional is obtained by inputting the pieces of input data into an estimation model. The processors control the object such that control quantity based on the second physical field becomes a target value.

Abstract: In an embodiment, a processing device relating to an inspection of an inspection object by a photography unit is provided. A processor of the processing device calculates a plurality of photography points as positions photographing the inspection object based on shape data in which a shape of a surface of the inspection object is indicated by a point group, and information relating to a position and a normal vector on the surface of the inspection object is defined by the point group. The processor executes analysis regarding a path that passes through all of the calculated photography points and minimizes a sum of a movement cost from each of the photography points to a photography point of a next movement destination, and calculates a path corresponding to an analysis result as a path for moving the photography unit.

Abstract: There is provided a medical image processing apparatus which includes a first extraction unit configured to extract coronary arteries depicted in images of a plurality of time phases relating to the heart, and to extract at least one stenosed part depicted in each coronary artery; a calculation unit configured to calculate a pressure gradient of each of the extracted coronary arteries, based on tissue blood flow volumes of the coronary arteries; a second extraction unit configured to extract an ischemic region depicted in the images; and a specifying unit configured to specify a responsible blood vessel of the ischemic region by referring to a dominance map, in which each of the extracted coronary arteries and a dominance territory are associated, for the extracted ischemic region, and to specify a responsible stenosis, based on the pressure gradient corresponding to a stenosed part in the specified responsible blood vessel.

Abstract: According to one embodiment, a medical image diagnostic apparatus includes a storage memory, processing circuitry, and a display. The storage memory stores data of a plurality of FFR distribution maps constituting a time series regarding a coronary artery, and data of a plurality of morphological images corresponding to the time series. The processing circuitry converts the plurality of FFR distribution maps into a plurality of corresponding color maps, respectively. The display displays a plurality of superposed images obtained by superposing the plurality of color maps and the plurality of morphological images respectively corresponding in phase to the plurality of color maps. The display restricts display targets for the plurality of color maps based on the plurality of FFR distribution maps or the plurality of morphological images.

Abstract: There is provided a medical image processing apparatus which includes a first extraction unit configured to extract coronary arteries depicted in images of a plurality of time phases relating to the heart, and to extract at least one stenosed part depicted in each coronary artery; a calculation unit configured to calculate a pressure gradient of each of the extracted coronary arteries, based on tissue blood flow volumes of the coronary arteries; a second extraction unit configured to extract an ischemic region depicted in the images; and a specifying unit configured to specify a responsible blood vessel of the ischemic region by referring to a dominance map, in which each of the extracted coronary arteries and a dominance territory are associated, for the extracted ischemic region, and to specify a responsible stenosis, based on the pressure gradient corresponding to a stenosed part in the specified responsible blood vessel.

Abstract: A control apparatus according to an embodiment includes one or more hardware processors. The processors acquire, for each of elements, pieces of input data representing first physical field of a corresponding one of the elements at a first time point. The elements are obtained by discretization of an object to be controlled. The processors calculate, for each element, second physical field of a corresponding element at a second time point after the first time point. The second physical field is calculated based on a value of an energy functional representing energy of the corresponding element. The value of the energy functional is obtained by inputting the pieces of input data into an estimation model. The processors control the object such that control quantity based on the second physical field becomes a target value.