A grasping device includes: a grasping part module including a first surface and a second surface and configured to grasp an object between the first surface and the second surface; an arm part configured to change a position of the grasping part module; an imaging unit provided at a position that moves together with the grasping part module and configured to capture an image of at least a part of the object; and a control unit configured to control, based on specified amount information indicating a contact state in a case where a specified amount of the object and the first surface are in contact with each other, and information indicating a contact state captured by the imaging unit, at least one of the grasping part module and the arm part such that an amount of the object that is grasped approaches the specified amount.

There is described a system and a computer-implemented method for controlling a part-processing device of a computer numerical control machine to bend cannulas. The method comprises the step of receiving one or more set parameters relating to one or more desired bend characteristics. The method also comprises the step of determining one or more uncontrolled inputs, the one or more uncontrolled inputs comprising bend parameters of a previously bent cannula. The method also comprises the step of inputting the one or more set parameters and the one or more uncontrolled inputs into a machine learning model to produce a plurality of outputs. The method also comprises the step of determining control parameters using the plurality of outputs, the control parameters relating to one or more settings of the part-processing device. The method also comprises the steps of setting the part-processing device using the control parameters and the uncontrolled inputs and bending a cannula using the part-processing device.

In a bending system and a method for using the same, the bending system includes a bending robot provided between a press brake and a predetermined setting area that is arranged in front of the press brake to assist in bending a workpiece. The bending robot includes a robot hand for holding the workpiece on a pallet that is set in the predetermined setting area. An image pickup unit, which picks up an image of the workpiece on the pallet from an oblique upper direction, is provided above and anterior to the predetermined setting area (SA). A first illumination unit, which illuminates an image pickup area of the image pickup unit, is erected on a left front side of the predetermined setting area. A second illumination stand, which illuminates the image pickup area of the image pickup unit, is erected on a right front side of the predetermined setting area.

Disclosed is a method and device for controlling continuous processing of a flexible material, which includes generating an outer profile diagram and a defect profile diagram from an image of a collected flexible material; converting and merging the outer profile diagram and the defect profile diagram to generate a vector data format file of profile information; typesetting according to an outer profile and a defect profile of the vector data format file of profile information, so as to generate a graphic format file of a profile to be processed; converting the graphic format file of the profile to be processed into a graphic language format file of the profile to be processed; performing trajectory optimization to generate an industrial-standard HPGL instruction; compiling the industrial-standard HPGL instruction to generate a control signal; and transmitting the control signal to a motion execution system, and performing cutting by the motion execution system.

An intelligent digital controller of a flexible material cutting robot and a realization method are provided. The controller comprises: an ARM chip, a servo driver bus communication module and a CPLD module. The ARM chip has built-in two processor cores (Cortex-M0 and Cortex-M4) and is externally connected with a flash memory, an SD card, SRAMs and an Ethernet physical transceiver_2; the Cortex-M0 reads a corresponding graph in the SD card into SRAM_1 according to a graph number, and sends a graph data readiness interruption request to an interruption controller; and after the interruption request is responded, Cortex-M4 reads in graph data and conducts interpolation calculation on the graph; the servo driver bus communication module is used to receive an interpolation calculation result and transmit the calculation result to a data input end of a servo driver with a corresponding address number through a data sending port.

A robot system includes an end effector, a robot arm, and a controller. The end effector includes a pressure roller and a linear motion mechanism. The linear motion mechanism is configured to move the pressure roller with respect to a pressed surface. The robot arm is configured to support the end effector. The controller is configured to control the linear motion mechanism to move the pressure roller to make a pressing force of the pressure roller against the pressed surface approximately uniform.

A grasping device includes: a grasping part module including a first surface and a second surface and configured to grasp an object between the first surface and the second surface; an arm part configured to change a position of the grasping part module; an imaging unit provided at a position that moves together with the grasping part module and configured to capture an image of at least a part of the object; and a control unit configured to control, based on specified amount information indicating a contact state in a case where a specified amount of the object and the first surface are in contact with each other, and information indicating a contact state captured by the imaging unit, at least one of the grasping part module and the arm part such that an amount of the object that is grasped approaches the specified amount.