Uncalibrated target region positioning and tracking method based on surgical robot system

Abstract

The embodiment of the invention discloses an uncalibrated target region positioning and tracking method based on a surgical robot system. The method comprises the following steps: S1, constructing a simulated puncture path by two marking balls; s2, constructing an image jacobian matrix; s3, filtering by a volume Kalman filter to obtain a mechanical arm control quantity estimated value at the next moment; s4, the target joint angle is converted into a mechanical arm joint speed domain control quantity through a PID algorithm; and S5, repeating the steps S3 to S4 until the filtering error is smaller than a preset threshold value, stopping filtering at the moment, and completing target positioning. According to the method, a technical route of non-calibration visual servo is adopted, hand-eye calibration operation does not need to be carried out before an operation, the preparation time before the operation can be greatly saved, meanwhile, the situation that a calibrated system coordinate system conversion relation fails due to hand-eye position change can be avoided, the anti-interference performance of a surgical robot system is enhanced, and the overall efficiency of the system is improved.

Description

technical field [0001] The invention relates to the technical field of surgical robots, in particular to a method for positioning and tracking a target area without calibration based on a surgical robot system. Background technique [0002] In recent years, the field of surgical robotics has developed rapidly. Surgical robot is an emerging surgical solution that integrates computer technology, imaging technology and robotic technology. It can better overcome the problems of insufficient precision, excessive radiation, and operational fatigue in traditional manual surgery. The surgical navigation system generally includes an image workstation, a positioning system, and surgical instruments. From the positioning system level, it can be divided into mechanical positioning, ultrasonic positioning, electromagnetic positioning and optical positioning. [0003] In optical information guided robotic systems, cameras are typically installed in two ways: [0004] (1) Eye-fixed conf...

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Problems solved by technology

[0009] (1) Hand-eye calibration first needs to control the robot to move within the field of view of the optical positioning system, and collect the data required for subsequent calibration calculations, which takes a long time

[0010] (2) Since it takes a long time to collect data, in order to make the collected data correct, it is necessary to ensure that the environment is not disturbed during the entire collection process, so the requirements for the environment are more stringent and the fault tolerance rate is low

[0011] (3) Hand-eye calibration requires a series of complex matrix operations, and the process of verifying the calibration results is also relatively complicated, and may introduce robot motion errors

[0012] (4) After the calibration is completed, if the position of the optical positioning system changes, the relative position relationship between it and the robot will also change, and unpredictable errors will occur when calculating the target pose, resulting in positioning failure

[0013] (5) There are many instruments and medical personnel in the surgical scene, which increases the probability of the above situation. Repeated calculation and updating of calibration results will introduce new robot motion errors and reduce the real-time performance of robot motion tracking and target positioning

[0014] (6) After the calibration is completed, a series of coordinate system transformations are required to control the movement of the robot, which requires a large amount of calculation and makes it difficult to track the moving target in real time

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