Abstract: A gripping tool, usable on a manipulator device for picking up and handling items includes a support frame extending along a first axis, provided with an attachment element for connecting to the manipulator device; and a plurality of gripping devices distributed in assemblies. Each assembly is carried by a respective auxiliary frame connected to the support frame by means of respective connecting members configured to be able to adjust the auxiliary frames and the gripping devices in position with respect to the support frame.

Abstract: A gripping tool, usable on a manipulator device for picking up and handling items includes a support frame extending along a first axis, provided with an attachment element for connecting to the manipulator device; and a plurality of gripping devices distributed in assemblies. Each assembly is carried by a respective auxiliary frame connected to the support frame by means of respective connecting members configured to be able to adjust the auxiliary frames and the gripping devices in position with respect to the support frame.

Abstract: A method for performing a noise removal operation includes decomposing an acquired signal considered as one dimensional series. A trajectory matrix is constructed, transforming the trajectory matrix in a form to which single value decomposition is applicable. A single value decomposition is done on the transformed matrix computing eigenvalues and eigenvectors of the matrix. A one dimensional series is reconstructed, corresponding to the denoised signal. After the single value decomposition operation is provided, a single value decomposition is applied sequentially starting from a given window value. For each iteration, the root mean square value is calculated between a current and previous eigenvalue, calculating a minimum and its position of said root mean square value. The iterations are halted if the minimum is lower than a determined threshold value, otherwise increasing the window value and returning to the operation of decomposition of the acquired signal.

Abstract: A method for performing a noise removal operation includes decomposing an acquired signal considered as one dimensional series. A trajectory matrix is constructed, transforming the trajectory matrix in a form to which single value decomposition is applicable. A single value decomposition is done on the transformed matrix computing eigenvalues and eigenvectors of the matrix. A one dimensional series is reconstructed, corresponding to the denoised signal. After the single value decomposition operation is provided, a single value decomposition is applied sequentially starting from a given window value. For each iteration, the root mean square value is calculated between a current and previous eigenvalue, calculating a minimum and its position of said root mean square value. The iterations are halted if the minimum is lower than a determined threshold value, otherwise increasing the window value and returning to the operation of decomposition of the acquired signal.

Abstract: A method for locating a tool in a work space via ultrasound includes associating an ultrasound transmitter to a tool and calculating a position of the tool on the basis of determination of the position of the transmitter. At least three ultrasound receivers for receiving ultrasound signals from the transmitter are set in positions relative to the work space. A calculation of a position of the transmitter includes using a trilateration procedure that includes a change of reference of the positions of the receivers and is carried out to reference them in a second simplified reference system. An unknown point in the second simplified reference system is obtained. A rototranslation of the position of the unknown point obtained from the second simplified reference system is carried out into a first reference system, and a corresponding rototranslation matrix is calculated such that the unknown point is used as position of the transmitter.

Abstract: A method for locating a tool for industrial operations that is positioned in a sequence of operating points of an operating sequence associated to different positions on a component on which work is to be carried out, includes associating a light source to the tool and at least three light sources identifying a position reference triplet fixed with respect to the component. A stereovision apparatus having at least two video cameras acquires at least two respective images of the tool and component. The displacement of the operating points on the component is tracked when carrying out an industrial operation on the component by recognizing positions of the reference triplet and a point of the light source of the tool calculating the position of the operating points of an operating sequence with reference to the position assumed by the reference triplet and evaluating the position of the tool with respect to the calculated position of the operating points.

Abstract: A system and a method for monitoring painting quality of components, for example of motor-vehicle bodies, comprises a robot which moves a monitoring head to follow the components to be monitored while they move along a production line. The monitoring head moves with respect to the surface to be monitored and comprises both a source of light and a camera which receives the light emitted by the source of light which is reflected by the monitored surface. An electronic processing unit receives the signals coming from the camera and processes them according to different processing algorithms for detecting various categories of defects, specifically small defects, medium defects, and large defects.

Abstract: A method for locating a tool for industrial operations that is positioned in a sequence of operating points of an operating sequence associated to different positions on a component on which work is to be carried out, includes associating a light source to the tool and at least three light sources identifying a position reference triplet fixed with respect to the component. A stereovision apparatus having at least two video cameras acquires at least two respective images of the tool and component. The displacement of the operating points on the component is tracked when carrying out an industrial operation on the component by recognizing positions of the reference triplet and a point of the light source of the tool calculating the position of the operating points of an operating sequence with reference to the position assumed by the reference triplet and evaluating the position of the tool with respect to the calculated position of the operating points.

Abstract: A method for locating a tool in a work space via ultrasound includes associating an ultrasound transmitter to a tool and calculating a position of the tool on the basis of determination of the position of the transmitter. At least three ultrasound receivers for receiving ultrasound signals from the transmitter are set in positions relative to the work space. A calculation of a position of the transmitter includes using a trilateration procedure that includes a change of reference of the positions of the receivers and is carried out to reference them in a second simplified reference system. An unknown point in the second simplified reference system is obtained. A rototranslation of the position of the unknown point obtained from the second simplified reference system is carried out into a first reference system, and a corresponding rototranslation matrix is calculated such that the unknown point is used as position of the transmitter.

Abstract: A system and a method for monitoring painting quality of components, for example of motor-vehicle bodies, comprises a robot which moves a monitoring head to follow the components to be monitored while they move along a production line. The monitoring head moves with respect to the surface to be monitored and comprises both a source of light and a camera which receives the light emitted by the source of light which is reflected by the monitored surface. An electronic processing unit receives the signals coming from the camera and processes them according to different processing algorithms for detecting various categories of defects, specifically small defects, medium defects, and large defects.