Vascular intervention robot system master end control method based on self-adaptive force feedback

Abstract

The embodiment of the invention discloses a vascular intervention robot system master end control method based on self-adaptive force feedback. The method comprises the steps that a motor model is constructed; constructing a slide rail model; acquiring a slave end sensor signal, and filtering the slave end sensor signal; constructing a reference model of the motor, and setting a controller to correct parameters of the motor model in real time based on the reference model; estimating a friction force based on the corrected motor model and the sliding rail model, and compensating the friction force; and based on the processed sensor signal, the reduced torque force borne by the slave end equipment and the reduced resistance in the horizontal direction borne by the slave end equipment act on an operating rod, and the reduced force acting on the operating rod is force feedback. According to the method, accurate force feedback can be realized, so that the vascular intervention robot system has high interference resistance and robustness, and output fluctuation can be avoided to a greater extent.

Description

technical field [0001] The invention relates to the field of control, in particular to a control method for a main end of a vascular intervention robot system based on adaptive force feedback. Background technique [0002] In recent years, with the advancement of robotic technology and people's greater emphasis on health issues, robot-assisted interventional therapy has gradually become the focus of attention. The current vascular interventional surgery has a low degree of equipment utilization, and most of them are performed by experienced doctors. The training time required for interventional doctors is also longer, and the operation of interventional surgery relies more on empirical operations. In addition, because human blood vessels are narrow and have many branches, and the walls of blood vessels are relatively fragile, this puts great demands on the accuracy of the catheter operation during the experiment, and requires the doctor's very delicate operation techniques....

AI Technical Summary

Problems solved by technology

However, the existing vascular interventional robot system cannot judge the current position of the intervention by sensing the current resistance of the catheter, balloon, and guide wire during the operation, as in the traditional surgical process. It is impossible to judge the current state of the operation through the "feel" in real time, but to judge by intraoperative CT by injecting more doses of contrast agent

This will not only prolong the operation time, but also cause secondary damage to the patient.

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