Medical robot system based on compliant dragging and control method thereof

Abstract

The invention discloses a medical robot system based on compliant dragging and a control method thereof.The system comprises a control module, a mechanical arm, an end effector and a sensor arranged at the end effector, and the sensor is configured to detect force applied externally and send a detection result to the control module; the control module is provided with a compliant control model, parameters related to the model comprise the detection result of the sensor and the pose error, the speed and the acceleration of the mechanical arm, and the pose error is the deviation between the current actual pose and the expected pose of the mechanical arm; the control module outputs actual control force to the mechanical arm according to the compliance control model so as to dynamically adjust the motion trail of the end effector, and compliance parameters of the compliance control model are adaptively adjusted according to the pose error, the speed and the acceleration of the mechanical arm in the motion trail adjusting process. The medical robot disclosed by the invention can realize self-adaptive control of flexible dragging and accurate pose control on the premise of not depending on an ROS system.

Description

Technical Field

[0001] The present invention relates to the field of medical robots, and in particular to a medical robot system based on compliant dragging and a control method thereof. Background Art

[0002] With the rapid development of medical technology, medical robots, especially surgical robots, are increasingly used in modern surgical operations. Surgical robots have the advantages of high precision, strong operability, and minimally invasiveness. They have begun to play an important role in ablation surgery, complex anatomical surgery, and remote surgery. However, the robot's posture needs to be precisely controlled during surgery, such as adjusting the posture, dragging to the ablation area, etc. If there is a lack of precise force feedback and it cannot dynamically adapt to changes in external environmental forces, it will affect the safety and effectiveness of the operation. Existing surgical robots still have some key technical challenges in force control and posture accuracy, which limits their further application in certain high-precision surgeries.

[0003] In order to solve these problems, a surgical robot system that can achieve force control and compliance adjustment is urgently needed. However, currently, robots with compliance adjustment typically rely on the ROS (Robot Operating System) system, which is complex and has poor human-machine interaction.

[0004] The compliant control scheme in the prior art, such as the patent application with publication number CN118303980A, discloses a control method that estimates the actual external force by collecting the external force on the robot arm and calculating the gravity in quasi-static state, and then optimizes the output acceleration and deceleration parameters and speed parameters to achieve the compliant following of the robot arm by the movement of the human hand. The compliant control model here combines the force and its own gravity to make decisions and control the speed and acceleration of the robot arm. However, the accuracy of force feedback control may be affected by the accuracy and noise of the force sensor, and the optimization of multiple parameters of speed and acceleration based on force feedback involves complex calculations, which places high demands on the computing power of the system and greatly increases the system cost.

[0005] The disclosure of the above background technology content is only used to assist in understanding the concept and technical solution of the present application. It does not necessarily belong to the prior art of the present application, nor does it necessarily provide technical guidance. In the absence of clear evidence that the above content has been disclosed before the filing date of the present application, the above background technology should not be used to evaluate the novelty and creativity of the present application. Summary of the invention

[0006] The object of the present invention is to provide a device capable of adaptively adjusting the parameters of compliant control according to changes in the external environment, so as to quickly respond to changes in external environmental forces and make rapid adjustments to maintain operational stability and safety, especially in emergency situations.

[0007] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0008] A medical robot system based on compliant dragging comprises a control module, a robotic arm, an end effector, and a first sensor disposed at the end effector, wherein the first sensor is configured to detect an externally applied force and send the detection result to the control module;

[0009] The control module is configured with a compliance control model, and the parameters involved in the compliance control model include the detection result of the first sensor and the posture error, speed and acceleration of the manipulator, wherein the posture error is defined as the deviation between the current actual posture of the manipulator and the expected posture;

[0010] The control module outputs actual control force to the robotic arm according to the compliance control model to dynamically adjust the motion trajectory of the end effector, and adaptively adjusts the compliance parameters of the compliance control model according to the posture error, speed and acceleration of the robotic arm during the process of adjusting the motion trajectory.

[0011] Furthermore, based on any one of the technical solutions or a combination of multiple technical solutions mentioned above, the compliance parameters of the compliance control model include an elastic coefficient corresponding to the posture error, a damping coefficient corresponding to the velocity, and an inertia coefficient corresponding to the acceleration.

[0012] Further, based on any one of the above-mentioned technical solutions or a combination of multiple technical solutions, the compliance parameters of the compliance control model are adaptively adjusted in the following manner:

[0013] The deviation between the expected position and the current actual position is defined as the position deviation;

[0014] Calculating the rate of change of the elastic coefficient according to the position deviation and the posture error, and then obtaining the adjusted elastic coefficient;

[0015] Calculating the change rate of the damping coefficient according to the position deviation and the speed, and then obtaining the adjusted damping coefficient;

[0016] The rate of change of the inertia coefficient is calculated according to the position deviation and the acceleration, thereby obtaining the adjusted inertia coefficient.

[0017] Further, based on any one of the above-mentioned technical solutions or a combination of multiple technical solutions, the compliant control model is:

[0018] Among them, F ctrl To output the actual control force to the robot arm, F ext is the externally applied force, M S is the inertia coefficient, is the acceleration, K S is the elastic coefficient, Δx(t) is the posture error, B S is the damping coefficient, for speed;

[0019] Where △x(t)=x(t)-x e (t), x(t) is the current actual position of the robot arm, x e (t) is the desired pose.

[0020] Further, based on any one of the above-mentioned technical solutions or a combination of multiple technical solutions, the control module also adaptively adjusts the posture error, velocity and acceleration of the compliant control model in the following manner:

[0021] In the process of outputting the actual control force to the robot arm to dynamically adjust the motion trajectory of the end effector, the acceleration is calculated according to the following formula as the adjusted acceleration: in, is the acceleration, M S is the inertia coefficient, F ext is the externally applied force, F ctrl is the actual control force output to the robot arm, K S is the elastic coefficient, Δx(t) is the posture error, B S is the damping coefficient, for speed;

[0022] Based on the calculation result of the acceleration, the adjusted speed information is obtained through time integration;

[0023] Based on the adjusted speed, the desired posture is obtained through time integration, and then the deviation between the current actual posture of the robot arm and the expected posture is obtained as the adjusted posture error.

[0024] Further, based on any one of the above technical solutions or a combination of multiple technical solutions, the system further includes a second sensor disposed at the end effector, which is configured to detect acceleration information;

[0025] The control module also adaptively adjusts the posture error, velocity and acceleration of the compliant control model in the following manner:

[0026] using the detection result of the second sensor as the adjusted acceleration;

[0027] Based on the detection result of the second sensor, the adjusted speed information is obtained through time integration;

[0028] Based on the adjusted speed, the desired posture is obtained through time integration, and then the deviation between the current actual posture of the robot arm and the expected posture is obtained as the adjusted posture error.

[0029] Further, based on any one of the above technical solutions or a combination of multiple technical solutions, the system further includes a third sensor disposed at the end effector, which is configured to detect speed information;

[0030] The control module also adaptively adjusts the posture error, velocity and acceleration of the compliant control model in the following manner:

[0031] Using the detection result of the third sensor as the adjusted speed;

[0032] Based on the detection results of the continuous sampling of the third sensor and the sampling period, the ratio of the speed change to the corresponding time consumption is calculated as the adjusted acceleration;

[0033] Based on the adjusted speed, the desired posture is obtained through time integration, and then the deviation between the current actual posture of the robot arm and the expected posture is obtained as the adjusted posture error.

[0034] Further, based on any one of the above-mentioned technical solutions or a combination of multiple technical solutions, the posture error includes a posture deviation and a position deviation, wherein the position deviation is a deviation between a desired position and a current actual position;

[0035] The posture deviation is determined by the following formula: Δq = q e ×q -1 , where △q is the posture deviation, q e is the desired posture with respect to the rotation angle, and q is the current actual posture with respect to the rotation angle.

[0036] Further, based on any one of the above-mentioned technical solutions or a combination of multiple technical solutions, the control module performs noise reduction processing on the detection result of the first sensor in the following manner:

[0037] F filtered (t)=median({F(t-i)|i=1,2,...,N-1}), where F filtered (t) is the detection data after noise reduction processing, median() is a function of taking the median of the data set, F(t-i) is the original detection result of the first sensor, and N is a preset window size.

[0038] Further, based on any one of the technical solutions or a combination of multiple technical solutions mentioned above, a flange is provided at the end of the robotic arm, and the end effector is rigidly connected to the robotic arm through the flange.

[0039] Furthermore, based on any one of the technical solutions or a combination of multiple technical solutions mentioned above, the system uses Qt's network programming module to establish a TCP / IP connection with the control module and exchanges data according to the RTDE protocol.

[0040] Furthermore, based on any one of the technical solutions or a combination of multiple technical solutions mentioned above, the medical robot system is an endoscope robot system, a bronchoscope robot system, a puncture robot system or a radioactive particle implantation robot system.

[0041] According to another aspect of the present invention, the present invention provides a control method for a medical robot system based on compliant dragging, which does not rely on ROS, and the control method comprises the following steps:

[0042] A compliant control model is pre-built, and the parameters involved include the force applied to the medical robot from the outside, the posture error, velocity and acceleration of the medical robot, wherein the posture error is defined as the deviation between the current actual posture and the expected posture of the mechanical arm of the medical robot; the parameters output by the compliant control model include the actual control force on the medical robot;

[0043] According to the compliant control model, actual control force is output to the medical robot to dynamically adjust its motion trajectory, and in the process of adjusting the motion trajectory, the compliance parameters of the compliant control model are adaptively adjusted according to the posture error, speed and acceleration of the medical robot, which include the elastic coefficient corresponding to the posture error, the damping coefficient corresponding to the speed, and the inertia coefficient corresponding to the acceleration.

[0044] Further, based on any one of the above-mentioned technical solutions or a combination of multiple technical solutions, the compliance parameters of the compliance control model are adaptively adjusted in the following manner:

[0045] The rate of change of each compliance parameter is calculated using the following formula:

[0046] in, is the rate of change of elastic modulus, γ s is the adaptive gain of the elastic coefficient, Δx(t) is the posture error of the medical robot; is the rate of change of the damping coefficient, γ b is the adaptive gain of the damping coefficient, For the speed of medical robots; is the rate of change of the inertia coefficient, γ m is the adaptive gain of the inertia coefficient, is the acceleration of the medical robot; e(t) is the position deviation between the expected position and the current actual position of the medical robot;

[0047] Using the current elastic coefficient and the calculated rate of change of the elastic coefficient, an adjusted elastic coefficient is obtained;

[0048] Using the current damping coefficient and the calculated change rate of the damping coefficient, an adjusted damping coefficient is obtained;

[0049] The adjusted inertia coefficient is obtained by using the current inertia coefficient and the calculated rate of change of the inertia coefficient.

[0050] Further, based on any one of the above-mentioned technical solutions or a combination of multiple technical solutions, the acceleration used by the compliance parameter is adaptively adjusted. Obtained through:

[0051] The acceleration information is obtained by detecting with a sensor; or, after the speed information is obtained by detecting with a sensor, the ratio of the speed change to the corresponding time consumption is calculated to obtain the acceleration information; or, in the process of outputting the actual control force to the medical robot to dynamically adjust its motion trajectory, the acceleration is calculated according to the following formula: in, is the acceleration, M S is the inertia coefficient, F ext is the external force applied to the medical robot, F ctrl is the actual control force output to the medical robot, K S is the elastic coefficient, Δx(t) is the posture error of the medical robot, B S is the damping coefficient, for speed;

[0052] The speed used to adaptively adjust the compliance parameters Obtained through:

[0053] The velocity information is obtained by detecting the speed through a sensor; or, the velocity information is obtained by integrating the acceleration information over time;

[0054] The posture error Δx(t) of the medical robot used for adaptively adjusting the compliance parameter is obtained in the following manner:

[0055] After obtaining the velocity information, the desired posture is obtained through time integration, and then the posture error Δx(t) between the current actual posture of the medical robot and the desired posture is obtained.

[0056] The beneficial effects brought by the technical solution provided by the present invention are as follows:

[0057] a. Ability to achieve dynamic balance between force and position during robot operation. By combining compliant dragging technology, the surgical robot can calculate and adjust its posture when sensing changes in external force to maintain accurate posture during operation and meet the need for precise posture control in ablation surgery scenarios;

[0058] b. Automatically adapt to force changes encountered during surgery to reduce the risk of misoperation: By introducing an adaptive force control strategy, the surgical robot can automatically adjust the force it applies according to changes in external environmental forces to maintain stability and safety of the operation;

[0059] c. The implementation of the compliant dragging of the embodiment of the present invention does not rely on the ROS system, which can simplify the system architecture and reduce software dependence, thereby reducing development difficulty and maintenance costs, making the system easier to deploy and run stably in the long term. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0061] Figure 1 A control logic block diagram of a medical robot system based on compliant dragging provided for an exemplary embodiment of the present invention;

[0062] Figure 2 A schematic flow chart of a control method for a medical robot system provided as an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0063] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0064] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, device, product or equipment that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0065] The present invention aims to provide a medical robot system based on compliant dragging, which can not only accurately sense and adjust the actual control force during the operation, but also dynamically adapt to changes in the external environment during the operation, thereby ensuring the safety and accuracy of the operation and the human-computer interaction with the surgeon.

[0066] In one embodiment of the present invention, a medical robot system based on compliant drag is provided, including a control module, a robotic arm and an end effector. A flange is provided at the end of the robotic arm, and the end effector is rigidly connected to the robotic arm through the flange, that is, the positional relationship between the two is fixed. In a specific embodiment, the robotic arm adopts a six-degree-of-freedom UR10 robotic arm, which can perform complex spatial movement operations and dynamically adjust the actual control force applied to it through compliant drag technology, ultimately achieving adjustment of its motion posture.

[0067] The medical robot system also includes a first sensor for detecting an externally applied force, which can be arranged at the end effector, or force sensors can be arranged on the end effector and the mechanical arm respectively, and the first sensor is communicatively connected with the notification module to send the detection result to the control module. The force or torque data is obtained through the API matching the first sensor, and the data is sent to the control module.

[0068] In a specific embodiment, the control module further performs noise reduction processing on the detection data sent by the first sensor, for example, by taking the median of the data in the window: F filtered (t)=median({F(t-i)|i=1,2,...,N-1}), where F filtered (t) is the detection data after noise reduction processing, median() is a function of taking the median of the data set, F(t-i) is the original detection result of the first sensor, and N is the preset window size, which is particularly suitable for removing sudden noise, thereby reducing the impact of sensor noise and ensuring the precise posture control of the robot.

[0069] The development of the medical robot system in this embodiment does not rely on the ROS system, but uses the Qt network programming module to establish a TCP / IP connection with the control module to ensure fast and reliable transmission of data exchange between modules; according to the RTDE protocol, the correct commands and parameters are sent to initialize data exchange.

[0070] In this embodiment, the control module is configured with a compliance control model, and the parameters involved in the compliance control model include the detection result of the first sensor and the posture error, speed and acceleration of the manipulator, wherein the posture error is defined as the deviation between the current actual posture of the manipulator and the expected posture;

[0071] The compliance control model outputs the actual control force applied to the robot arm to dynamically adjust the motion trajectory of the end effector, and in the process of adjusting the motion trajectory, the compliance parameters of the compliance control model are adaptively adjusted according to the posture error, speed and acceleration of the robot arm.

[0072] First, the compliant control model of this embodiment more completely describes the response behavior of the robot in a dynamic environment. In addition to force feedback, it also takes into account the effects of velocity and inertia (acceleration), making the model output results closer to the control requirements.

[0073] Secondly, the compliant control model of this embodiment controls a single variable output, which greatly reduces the computational complexity involved and significantly reduces the computational cost of the system;

[0074] Thirdly, the control module dynamically adjusts the motion trajectory of the robot's end effector according to the sensor data and the preset compliance requirements, and calculates the force required to be applied in real time to make real-time posture adjustments, ensuring that the robot can adapt to changes in external forces. It also helps to maintain high-precision posture control through adaptive control during the compliant dragging process.

[0075] Among them, the core of adaptive control is to dynamically adjust the compliance parameters of the compliance control model according to the parameters of real-time feedback: the elastic coefficient corresponding to the posture error, the damping coefficient corresponding to the velocity, and the inertia coefficient corresponding to the acceleration.

[0076] See also Figure 1 , where x(t) is the current actual position of the robot arm, x e (t) is the desired posture, x(t)-x e (t) to obtain △x(t), which represents the posture error of the robot arm. The posture error includes posture deviation and position deviation, where the position deviation is the deviation between the expected position of the robot arm and the current actual position, that is, Figure 1In e(t), the expected position is the preset destination position, such as the ablation area position that the end effector is expected to reach, and the current actual position is the data that can be given by the positioning system of the manipulator;

[0077] The attitude deviation is determined by the following formula: △q = q e ×q -1 , where △q is the posture deviation, q e is the desired posture with respect to the rotation angle, q is the current actual posture with respect to the rotation angle, and similarly, q e is the desired rotation angle of the end effector at the target position, and the current actual posture q is the data that can be given by the positioning system of the manipulator.

[0078] In each control cycle, the posture error △x(t) is continuously iterated and calculated, and the elastic coefficient, damping coefficient, and inertia coefficient are updated and substituted into the compliant control model to obtain a new output, which is the actual control force applied to the robotic arm, adjust the motion trajectory of the robotic arm, and realize real-time error compensation.

[0079] In a specific embodiment, the compliance parameters of the compliance control model are adaptively adjusted in the following manner:

[0080] The deviation between the expected position and the current actual position is defined as the position deviation, that is, e(t);

[0081] The rate of change of the elastic coefficient is calculated according to the position deviation and the posture error: in, is the rate of change of elastic modulus, γ b is the adaptive gain of the elastic coefficient, Δx(t) is the posture error of the medical robot, and e(t) is the position deviation of the manipulator; after obtaining the rate of change of the elastic coefficient, the adjusted elastic coefficient is obtained. Specifically, the adaptively adjusted elastic coefficient K can be obtained by time integration. S ;

[0082] Calculate the rate of change of the damping coefficient based on the position deviation and velocity: in, is the rate of change of the damping coefficient, γ b is the adaptive gain of the damping coefficient, is the speed of the medical robot, e(t) is the position deviation of the manipulator; after obtaining the change rate of the damping coefficient, the adjusted damping coefficient is obtained. Specifically, the adaptively adjusted damping coefficient B can be obtained by time integration. S ;

[0083] Calculate the rate of change of the inertia coefficient based on the position deviation and acceleration: in, is the rate of change of the inertia coefficient, γ m is the adaptive gain of the inertia coefficient, is the acceleration of the medical robot, e(t) is the position deviation of the manipulator; after obtaining the rate of change of the inertia coefficient, the adjusted inertia coefficient is obtained. Specifically, the adaptively adjusted inertia coefficient M can be obtained by time integration. S .

[0084] The above elastic coefficient K S , damping coefficient B S , inertia coefficient M S An empirical value or a random value may be preset. Even if the initial value has a large deviation, it can quickly converge to a suitable range through the subsequent calculation of the rate of change of the coefficient. The suitable range mentioned here refers to the range of compliant parameter values ​​for compliant dragging that can achieve precise posture control.

[0085] The adaptive gain γ of the above elastic coefficient s , adaptive gain of damping coefficient γ b , adaptive gain γ of inertia coefficient m can all be preset to 1; in different embodiments, the influence factors (weight scores) of the three parameters in the compliance control model: posture error, speed, and acceleration can be estimated according to the actual application scenario, and the adaptive gains of the corresponding compliance parameters can be determined according to the weights of the three. For example, in a scenario where the target moves a long distance and has a certain tolerance range for the target position and posture, it can be reasonably estimated that the weight scores are acceleration, speed, and posture error from high to low, respectively. Correspondingly, the adaptive gain γ of the inertia coefficient can be set m =1.05, adaptive gain of damping coefficient γ b =1, adaptive gain of elastic coefficient γ s =0.95.

[0086] In a specific embodiment, the compliance control model is:

[0087] Among them, F ctrl To output the actual control force to the robot arm, F ext is the externally applied force, M S is the inertia coefficient, is the acceleration, K S is the elastic coefficient, Δx(t) is the posture error, B S is the damping coefficient, for speed;

[0088] Adaptive adjustment of elastic coefficient K as described above S , damping coefficient B S , inertia coefficient MS , so that the compliance parameters of the compliance control model can be adaptively adjusted in real time.

[0089] As mentioned above, to adaptively adjust the inertia coefficient M S , it is necessary to obtain the acceleration of the medical robot It can obtain acceleration information by configuring a second sensor; or, in the process of outputting actual control force to the robot arm to dynamically adjust the motion trajectory of the end effector, the external force detected by the first sensor will also change accordingly. In this case, the acceleration is calculated using the following formula: in, is the acceleration, M S is the inertia coefficient, F ext is the externally applied force, F ctrl is the actual control force output to the robot arm, K S is the elastic coefficient, Δx(t) is the posture error, B S is the damping coefficient, For speed.

[0090] On the other hand, as mentioned above, to adaptively adjust the damping coefficient B S , need to obtain the speed of the medical robot It can obtain speed information by configuring a third sensor; or, when obtaining acceleration Then, the speed is obtained by time integration Right now in, is the speed at the next moment, Δt is the time difference; based on this, there is another way to get the acceleration Method: Based on the detection results of continuous sampling of the third sensor and the sampling period, the ratio of the speed change to the corresponding time consumption is calculated as the acceleration

[0091] On the other hand, as mentioned above, the elastic coefficient K should be adjusted adaptively. S , it is necessary to obtain the posture error Δx(t) of the medical robot, which can be obtained by After that, the desired posture is obtained through time integration, and then the deviation between the current actual posture of the robot arm and the desired posture is obtained, that is, the posture error Δx(t): In the formula, Δx(t+1) is the displacement at the next moment, and Δt is the time difference.

[0092] According to the above compliance calculation results, the controller generates corresponding control instructions to adjust the motion position and posture of the robot arm in real time to adapt to the changes in different forces. The medical robot system in the above embodiments can be an endoscope robot system, a bronchoscope robot system, a puncture robot system or a radioactive particle implantation robot system. The system can also set a human-computer interaction interface, which is implemented using Qt and provided to surgeons for controlling and monitoring the surgical robot. Doctors can set operating parameters and compliance control modes through the interface and perform manual intervention when necessary.

[0093] In one embodiment of the present invention, a control method for a medical robot system based on compliant drag is provided, which does not rely on ROS, such as Figure 2 As shown, the control method comprises the following steps:

[0094] A compliant control model is pre-built, and the parameters involved include the force applied to the medical robot from the outside, the posture error, velocity and acceleration of the medical robot, wherein the posture error is defined as the deviation between the current actual posture and the expected posture of the mechanical arm of the medical robot; the parameters output by the compliant control model include the actual control force on the medical robot;

[0095] According to the compliant control model, actual control force is output to the medical robot to dynamically adjust its motion trajectory, and in the process of adjusting the motion trajectory, the compliant parameters of the compliant control model are adaptively adjusted according to the posture error, speed and acceleration of the medical robot, including the elastic coefficient corresponding to the posture error, the damping coefficient corresponding to the speed, and the inertia coefficient corresponding to the acceleration, until the posture error is less than a preset threshold, which means that the robotic arm / end effector has reached the destination position and the compliant dragging can be ended.

[0096] Specifically, the compliance parameters of the compliance control model are adaptively adjusted in the following manner:

[0097] The rate of change of each compliance parameter is calculated using the following formula:

[0098] in, is the rate of change of elastic modulus, γ s is the adaptive gain of the elastic coefficient, Δx(t) is the posture error of the medical robot; is the rate of change of the damping coefficient, γ b is the adaptive gain of the damping coefficient, For the speed of medical robots; is the rate of change of the inertia coefficient, γ m is the adaptive gain of the inertia coefficient, is the acceleration of the medical robot; e(t) is the position deviation between the expected position and the current actual position of the medical robot;

[0099] Using the current elastic coefficient and the calculated rate of change of the elastic coefficient, an adjusted elastic coefficient is obtained;

[0100] Using the current damping coefficient and the calculated change rate of the damping coefficient, an adjusted damping coefficient is obtained;

[0101] The adjusted inertia coefficient is obtained by using the current inertia coefficient and the calculated rate of change of the inertia coefficient.

[0102] Among them, the acceleration used to adaptively adjust the compliance parameter Obtained through:

[0103] The acceleration information is obtained by detecting with a sensor; or, after the speed information is obtained by detecting with a sensor, the ratio of the speed change to the corresponding time consumption is calculated to obtain the acceleration information; or, in the process of outputting the actual control force to the medical robot to dynamically adjust its motion trajectory, the acceleration is calculated according to the following formula: in, is the acceleration, M S is the inertia coefficient, F ext is the external force applied to the medical robot, F ctrl is the actual control force output to the medical robot, K S is the elastic coefficient, Δx(t) is the posture error of the medical robot, B S is the damping coefficient, for speed;

[0104] The speed used to adaptively adjust the compliance parameters Obtained through:

[0105] The velocity information is obtained by detecting the speed through a sensor; or, the velocity information is obtained by integrating the acceleration information over time;

[0106] The posture error Δx(t) of the medical robot used for adaptively adjusting the compliance parameter is obtained in the following manner:

[0107] After obtaining the velocity information, the desired posture is obtained through time integration, and then the posture error Δx(t) between the current actual posture of the medical robot and the desired posture is obtained.

[0108] The control method of the medical robot system based on flexible drag provided in this embodiment and the medical robot system based on flexible drag provided in the above-mentioned embodiment belong to the same inventive concept. The entire contents of the medical robot system based on flexible drag embodiment are introduced into the present control method embodiment by quoting the full text here, and will not be repeated here.

[0109] The medical robot system based on compliant drag provided by the present invention exhibits significant advantages in accuracy, adaptability and safety, and can achieve a dynamic balance between force and position during robot operation. By combining compliant drag technology, the surgical robot can calculate and adjust its posture when sensing changes in external force to maintain accurate posture during operation.

[0110] The medical robot based on compliant dragging provided by the present invention can automatically adapt to the force changes encountered during surgery and reduce the risk of misoperation. By introducing an adaptive force control strategy, the surgical robot can automatically adjust the force it applies according to the changes in the external environmental force to maintain the stability and safety of the operation.

[0111] The compliant dragging-based medical robot provided by the present invention does not rely on the ROS system, reduces system complexity, simplifies system architecture, reduces software dependence, thereby reducing development difficulty and maintenance costs, making the system easier to deploy and operate stably in the long term.

[0112] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0113] The above is only a specific implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A medical robot system based on compliant dragging, characterized in that: The invention comprises a control module, a mechanical arm, an end effector, and a first sensor disposed at the end effector, wherein the first sensor is configured to detect an externally applied force and send the detection result to the control module; The control module is configured with a compliance control model, and the parameters involved in the compliance control model include the detection result of the first sensor and the posture error, speed and acceleration of the manipulator, wherein the posture error is defined as the deviation between the current actual posture of the manipulator and the expected posture; The control module outputs actual control force to the robotic arm according to the compliance control model to dynamically adjust the motion trajectory of the end effector, and adaptively adjusts the compliance parameters of the compliance control model according to the posture error, speed and acceleration of the robotic arm during the process of adjusting the motion trajectory.

2. The medical robot system based on compliant dragging according to claim 1, characterized in that: The compliance parameters of the compliance control model include an elastic coefficient corresponding to the posture error, a damping coefficient corresponding to the velocity, and an inertia coefficient corresponding to the acceleration.

3. The medical robot system based on compliant dragging according to claim 2, characterized in that: The compliance parameters of the compliance control model are adaptively adjusted in the following manner: The deviation between the expected position and the current actual position is defined as the position deviation; Calculating the rate of change of the elastic coefficient according to the position deviation and the posture error, and then obtaining the adjusted elastic coefficient; Calculating the change rate of the damping coefficient according to the position deviation and the speed, and then obtaining the adjusted damping coefficient; The rate of change of the inertia coefficient is calculated according to the position deviation and the acceleration, thereby obtaining the adjusted inertia coefficient.

4. The medical robot system based on compliant dragging according to claim 2, characterized in that: The compliant control model is: Wherein, Fctrl is the actual control force output to the robot arm, Fext is the externally applied force, M S is the inertia coefficient, is the acceleration, K S is the elastic coefficient, Δx(t) is the posture error, B S is the damping coefficient, for speed; Where △x(t)=x(t)-x e (t), x(t) is the current actual position of the robot arm, x e (t) is the desired pose.

5. The medical robot system based on compliant dragging according to claim 1, characterized in that: The control module also adaptively adjusts the posture error, velocity and acceleration of the compliant control model in the following manner: In the process of outputting the actual control force to the robot arm to dynamically adjust the motion trajectory of the end effector, the acceleration is calculated according to the following formula as the adjusted acceleration: in, is the acceleration, M S is the inertia coefficient, Fext is the externally applied force, Fctrl is the actual control force output to the robot arm, K S is the elastic coefficient, Δx(t) is the posture error, B S is the damping coefficient, for speed; Based on the calculation result of the acceleration, the adjusted speed information is obtained through time integration; Based on the adjusted speed, the desired posture is obtained through time integration, and then the deviation between the current actual posture of the robot arm and the expected posture is obtained as the adjusted posture error.

6. The medical robot system based on compliant dragging according to claim 1, characterized in that: The system further includes a second sensor disposed at the end effector and configured to detect acceleration information; The control module also adaptively adjusts the posture error, velocity and acceleration of the compliant control model in the following manner: using the detection result of the second sensor as the adjusted acceleration; Based on the detection result of the second sensor, the adjusted speed information is obtained through time integration; Based on the adjusted speed, the desired posture is obtained through time integration, and then the deviation between the current actual posture of the robot arm and the expected posture is obtained as the adjusted posture error.

7. The medical robot system based on compliant dragging according to claim 1, characterized in that: The system further includes a third sensor disposed at the end effector and configured to detect speed information; The control module also adaptively adjusts the posture error, velocity and acceleration of the compliant control model in the following manner: Using the detection result of the third sensor as the adjusted speed; Based on the detection results of the continuous sampling of the third sensor and the sampling period, the ratio of the speed change to the corresponding time consumption is calculated as the adjusted acceleration; Based on the adjusted speed, the desired posture is obtained through time integration, and then the deviation between the current actual posture of the robot arm and the expected posture is obtained as the adjusted posture error.

8. The medical robot system based on compliant dragging according to claim 1, characterized in that: The posture error includes posture deviation and position deviation, wherein the position deviation is the deviation between the expected position and the current actual position; The posture deviation is determined by the following formula: Δq = q e ×q -1 , where △q is the posture deviation, q e is the desired posture with respect to the rotation angle, and q is the current actual posture with respect to the rotation angle.

9. The medical robot system based on compliant dragging according to claim 1, characterized in that: The control module performs noise reduction processing on the detection result of the first sensor in the following manner: Ffiltered(t)=median({F(t-i)|i=1,2,…,N-1}), wherein Ffiltered(t) is the detection data after noise reduction processing, median() is a function that takes the median of the data set, F(t-i) is the original detection result of the first sensor, and N is the preset window size.

10. The medical robot system based on compliant dragging according to any one of claims 1 to 9, characterized in that: A flange is provided at the end of the mechanical arm, and the end effector is rigidly connected to the mechanical arm through the flange.

11. The medical robot system based on compliant dragging according to claim 10, characterized in that: Use Qt's network programming module to establish a TCP / IP connection with the control module, and perform data exchange according to the RTDE protocol.

12. The medical robot system based on compliant dragging according to claim 10, characterized in that: The medical robot system is an endoscope robot system, a bronchoscope robot system, a puncture robot system or a radioactive seed implantation robot system.

13. A control method for a medical robot system based on compliant dragging, characterized in that: Independent of ROS, the control method comprises the following steps: A compliant control model is pre-built, and the parameters involved include the force applied to the medical robot from the outside, the posture error, velocity and acceleration of the medical robot, wherein the posture error is defined as the deviation between the current actual posture and the expected posture of the mechanical arm of the medical robot; the parameters output by the compliant control model include the actual control force on the medical robot; According to the compliant control model, actual control force is output to the medical robot to dynamically adjust its motion trajectory, and in the process of adjusting the motion trajectory, the compliance parameters of the compliant control model are adaptively adjusted according to the posture error, speed and acceleration of the medical robot, which include the elastic coefficient corresponding to the posture error, the damping coefficient corresponding to the speed, and the inertia coefficient corresponding to the acceleration.

14. The control method of the medical robot system based on compliant dragging according to claim 13, characterized in that: The compliance parameters of the compliance control model are adaptively adjusted in the following manner: The rate of change of each compliance parameter is calculated using the following formula: in, is the rate of change of elastic modulus, γ s is the adaptive gain of the elastic coefficient, Δx(t) is the posture error of the medical robot; is the rate of change of the damping coefficient, γ b is the adaptive gain of the damping coefficient, For the speed of medical robots; is the rate of change of the inertia coefficient, γ m is the adaptive gain of the inertia coefficient, is the acceleration of the medical robot; e(t) is the position deviation between the expected position and the current actual position of the medical robot; Using the current elastic coefficient and the calculated rate of change of the elastic coefficient, an adjusted elastic coefficient is obtained; Using the current damping coefficient and the calculated change rate of the damping coefficient, an adjusted damping coefficient is obtained; The adjusted inertia coefficient is obtained by using the current inertia coefficient and the calculated rate of change of the inertia coefficient.

15. The control method of the medical robot system based on compliant dragging according to claim 14, characterized in that: The acceleration used to adaptively adjust the compliance parameters Obtained through: The acceleration information is obtained by detecting with a sensor; or, after the speed information is obtained by detecting with a sensor, the ratio of the speed change to the corresponding time consumption is calculated to obtain the acceleration information; Alternatively, in the process of outputting the actual control force to the medical robot to dynamically adjust its motion trajectory, the acceleration is calculated according to the following formula: in, is the acceleration, M S is the inertia coefficient, Fext is the force applied to the medical robot from the outside, Fctrl is the actual control force output to the medical robot, K S is the elastic coefficient, Δx(t) is the posture error of the medical robot, B S is the damping coefficient, for speed; The speed used to adaptively adjust the compliance parameters Obtained through: The velocity information is obtained by detecting the speed through a sensor; or, the velocity information is obtained by integrating the acceleration information over time; The posture error Δx(t) of the medical robot used for adaptively adjusting the compliance parameter is obtained in the following manner: After obtaining the velocity information, the desired posture is obtained through time integration, and then the posture error Δx(t) between the current actual posture of the medical robot and the desired posture is obtained.

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