WO2021128755A1 - 骨注册方法、手术机器人及可读存储介质 - Google Patents
骨注册方法、手术机器人及可读存储介质 Download PDFInfo
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Definitions
- the present invention relates to the technical field of medical devices, in particular to a bone registration method, a surgical robot and a readable storage medium.
- Computer-aided navigation system has become an important part of modern surgical technology, helping operators to perform a variety of complex operations more accurately and safely. It has many irreplaceable advantages in all aspects of orthopedics, because of its accuracy, safety, and low cost. Radiation and other characteristics make it gradually widely used in clinical practice.
- the computer-assisted navigation system can be used to guide the operator to perform surgical training, make surgical plans, navigate surgical instruments in real time, and reduce patient trauma.
- computer-assisted osteotomy is more accurate, prosthesis installation is more accurate, and the postoperative force line recovery is closer to the physiological state.
- surgical robots need to register bones in advance to establish the correspondence between solid bones and virtual images, and provide three-dimensional information for the operator's operations such as osteotomy, bone surface treatment, and prosthesis placement.
- the traditional bone registration method is that the operator holds a target pen and selects the registration point on the patient's bone to complete the bone registration.
- the present invention provides a method for performing bone registration by a surgical robot, a surgical robot, and a readable storage medium, which are used to automatically complete or assist the operator in completing the bone registration process, improve the efficiency of bone registration, and help the operator to reduce the workload of the operator.
- it can also identify the force status of the end of the robotic arm, so as to ensure that the registration points on the bones are accurately selected, which improves the accuracy and safety of bone registration.
- a bone registration method for surgical robots which includes the following steps:
- the robotic arm system receives the information of the interested registration point on the predetermined object selected by the navigation system;
- the tracking device According to the force received by the end of the robotic arm, it is determined whether the tracking device has moved to the registered point of interest on the predetermined object.
- the method further includes the following steps:
- the tracking device According to the current location information of the tracking device, it is determined whether the tracking device has moved to a registered point of interest on a predetermined object.
- the priority of judging whether the tracking device has moved to the registered point of interest on a predetermined object based on the force received by the end of the robotic arm is higher than that based on the tracking device To determine whether the tracking device has moved to the registered point of interest on the predetermined object.
- the determination is made according to the force received by the end of the robotic arm to determine whether the tracking device has moved to a registered point of interest on a predetermined object.
- the steps include:
- the method further includes:
- the method further includes the following steps:
- control the mechanical arm to adjust the posture of the tracking device until the navigation system can normally collect the position information of the tracking device.
- the robotic arm system plans a motion trajectory, and the robotic arm drives the tracking device to move to the registration point of interest along the motion trajectory.
- the method before the step of judging whether the tracking device has moved to the registration point of interest on the predetermined object, the method further includes the following steps:
- the force recognition system is updated.
- the step of obtaining the force received by each mechanical arm joint by the force recognition system includes:
- the force received by each of the robot arm joints is detected.
- the step of obtaining the force received by the end of the robotic arm by the force recognition system includes:
- the force received by the end of the robotic arm is detected.
- a neural network calculation method is used to calculate the force received by the end of the robotic arm, and before outputting the force received by the end of the robotic arm , It also includes the step of performing neural network training on the force recognition system, and maintaining the network structure and weight files after neural network training.
- a surgical robot which includes a control system, a force recognition system, a robotic arm system, and a navigation system;
- the robotic arm system includes a robotic arm; the robotic arm end of the robotic arm is used for Connect a tracking device;
- the control system is respectively communicatively connected to the force recognition system, the robotic arm system, and the navigation system, and the navigation system is communicatively connected to the robotic arm system;
- the navigation system is configured to send information about the registration point of interest on a predetermined object to the robotic arm system; the robotic arm system is configured to control the robot arm system according to the information about the registration point of interest on the predetermined object.
- the robotic arm moves to drive the tracking device to move to a registered point of interest on a predetermined object;
- the force recognition system is provided on the mechanical arm, and the force recognition system is used to detect the force received by the end of the mechanical arm and send it to the control system; the control system is configured to be based on the mechanical arm The force received by the end of the arm determines whether the tracking device has moved to the registered point of interest on the predetermined object.
- the navigation system is configured to collect current position information of the tracking device and send it to the control system; the control system is configured to determine according to the current position information of the tracking device Whether the tracking device has moved to a registered point of interest on a predetermined object.
- control system is configured to determine whether the tracking device has moved to a predetermined object with a higher priority than the registration point of interest according to the force received by the end of the robotic arm. According to the current position information of the tracking device, it is a priority to determine whether the tracking device has moved to a registered point of interest on a predetermined object.
- control system is configured to determine whether the force recognition system is working normally; if so, control the mechanical arm to drive the tracking device to move to the registration point.
- the control system is configured to compare the force received by the end of the robotic arm with a calibration value pre-stored in the control system; if If it is equal to or greater than the calibration value, it is determined that the tracking device has moved to the registration point of interest on the predetermined object; if it is less than the calibration value, continue to control the robotic arm to drive the tracking device to the registration point Move until the force received by the end of the mechanical arm is equal to or greater than the calibration value.
- control system is further configured to determine whether the navigation system can normally collect the position information of the tracking device If yes, control the robotic arm to drive the tracking device to move to the next registration point of interest; if not, control the robotic arm to adjust the posture of the tracking device until the navigation system can normally collect the tracking Location information of the device.
- the mechanical arm includes a plurality of mechanical arm joints, and the force recognition system includes a first force recognition device and a second force recognition device;
- the first force recognition device includes a plurality of first sensors, and at least one first sensor is provided at each of the robot arm joints; the first sensor is used to detect the force received by the corresponding robot arm joint;
- the second force recognition device includes at least one second sensor arranged at the end of the mechanical arm, and the second sensor is used to detect the force received by the end of the mechanical arm;
- the control system is configured to:
- the force recognition system is updated.
- the first sensor includes at least one of a dual encoder, a torque sensor, and a distributed grating sensor
- the second sensor includes a six-axis sensor.
- a dual encoder is provided at each joint of the robotic arm, and the dual encoder includes an absolute encoder and an incremental encoder;
- the robotic arm also includes a A driver and a reducer for an arm joint, the output end of the driver is connected to the input end of the reducer, and the output end of the reducer is connected to the mechanical arm joint; wherein, the absolute encoder and the incremental encoder One of the reducers is arranged at the input end of the reducer, and the other is arranged at the output end of the reducer.
- K is the stiffness model of the reducer
- ⁇ is the deformation of the manipulator joint
- T1 is the absolute position of the manipulator joint fed back by the absolute encoder
- T2 is the increment The relative position of the robotic arm joint fed back by the encoder
- c1 is the resolution of the absolute encoder
- c2 is the resolution of the incremental encoder
- S0 is the incremental encoder The start-up initialization position.
- the dual encoder is communicatively connected with the control system; the control system is used to map the data deviation of the dual encoder and the force received by the mechanical arm joint, Obtain the force received by the robotic arm joint.
- control system is configured to use a neural network calculation method to calculate the force received by the end of the robotic arm, and before outputting the force received by the end of the robotic arm, the The force recognition system conducts neural network training, and maintains the network structure and weight files after neural network training.
- the surgical robot includes an automatic operation mode and an auxiliary operation mode
- the robotic arm system plans a movement trajectory according to the received information of the registration point of interest, and controls the robotic arm to drive the tracking device along the movement The trajectory moves to the registered point of interest on the predetermined object;
- the mechanical arm is driven by an external force and the tracking device is driven to move to a registered point of interest on a predetermined object.
- a readable storage medium having a program stored thereon, and the above-mentioned bone registration method for a surgical robot is executed when the program is executed by a processor.
- the use of surgical robots for bone registration is convenient to improve the efficiency of bone registration and help operators reduce the workload.
- the recognition system can identify the force status of the end of the robotic arm, which is convenient for judging the cartilage penetration of the tracking device according to the force status of the robotic arm, thereby controlling the depth of cartilage insertion, ensuring that the registration point on the bone is correctly selected, and improving bone registration Accuracy and safety.
- multiple sensors in the force recognition system are used to obtain the force information received by the end of the manipulator, so that the force information can be verified with each other to ensure the accuracy and reliability of the force information detection.
- the bone registration process it is further judged whether the force recognition system is working normally. If it is not normal, the bone registration can be performed manually, which further ensures the accuracy and reliability of the force detection. Furthermore, the force information received by the end of the manipulator can be obtained according to the calculation method of the neural network, which further improves the accuracy of force detection.
- Fig. 1 is an overall schematic diagram of a surgical robot in an embodiment of the present invention performing a surgical procedure
- FIG. 2 is a schematic diagram of the structure of the robotic arm in the embodiment of the present invention.
- Fig. 3 is a general flow chart of bone registration performed by the surgical robot in an embodiment of the present invention.
- FIG. 5 is a flowchart of bone registration when the surgical robot in an embodiment of the present invention is in an automatic operation mode
- Fig. 6a is a schematic diagram of the target pen outside the field of view of the navigation system in the embodiment of the present invention.
- 6b is a schematic diagram of the target pen in the field of view of the navigation system in the embodiment of the present invention.
- FIG. 7 is a schematic diagram of a joint module in an embodiment of the present invention.
- Fig. 8 is a schematic diagram of measuring joint torque using dual encoders in an embodiment of the present invention.
- Figure 9 is a flowchart of protecting the joint module in an embodiment of the present invention.
- FIG. 11 is a flowchart of online model parameter update using a six-axis sensor in an embodiment of the present invention.
- Figures 12 to 13 are respectively schematic diagrams of using neural networks to update parameters in an embodiment of the present invention.
- the singular forms “a”, “an” and “the” include plural items unless the content clearly dictates otherwise.
- the term “or” is usually used in the meaning including “and/or” unless the content clearly indicates otherwise.
- the term “several” is usually used to include “at least one” unless the content clearly indicates otherwise.
- the term “at least two” is generally used in the meaning including “two or more” unless the content clearly indicates otherwise.
- the terms “first”, “second”, and “third” are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Thus, the features defined with “first”, “second”, and “third” may explicitly or implicitly include one or at least two of these features.
- One of the main purposes of the present invention is to provide a surgical robot, which aims to complete the bone registration process through collaborative operation of the surgical robot, and with the aid of a force recognition system, can obtain the force information (including force and torque) received by the end of the robotic arm. Information) to ensure that the target pen/tracking device can accurately select the registration point on the bone, and ensure the accuracy and safety of the bone registration.
- the sensor used in the present invention will not be damaged under the condition of excessive external force, which ensures the reliability of the sensor.
- the sensors can also verify each other to further ensure the accuracy and reliability of bone registration.
- FIG. 1 is an overall schematic diagram of the surgical robot 10 in this embodiment when performing knee joint surgery.
- this embodiment provides a surgical robot 10, which includes a robotic arm system/mechanical arm subsystem 100 and a navigation system/navigation subsystem 200, and the two systems communicate with each other.
- the robotic arm system 100 has an automatic operation mode and an auxiliary operation mode.
- the surgical robot 10 automatically completes the bone registration process; when the robotic arm system 100 is in the auxiliary operation mode, the surgical robot 10 guides the operator to complete the bone registration process.
- the navigation system 200 is used for preoperative planning and intraoperative navigation.
- the navigation system 200 is the visual recognition part of the surgical robot 10.
- FIG. 2 is a schematic diagram of the structure of the robot arm 110 in this embodiment.
- the robotic arm system 100 includes a robotic arm 110, which includes a number of robotic arm joints connected in sequence and a robotic arm end.
- the robotic arm joints may be revolving joints for controlling the robotic arm.
- the mechanical arm 110 includes at least five revolute joints connected in sequence to achieve at least five degrees of freedom. Further, any two adjacent revolute joints are connected by a connecting arm.
- the robotic arm 110 has five degrees of freedom and includes a first revolute joint 111, a second revolute joint 112, a rotation joint 113, a third revolute joint 114, and The fourth revolute joint 115.
- the rotation axis of the first revolute joint 111, the rotation axis of the second revolute joint 112, and the rotation axis of the third revolute joint 114 are parallel to each other; the rotation axes of the third revolute joint 114 and the fourth revolute joint 115 are perpendicular to each other.
- any two adjacent revolute joints are connected by a connecting arm 116.
- the first revolute joint 111 is connected to a connecting arm 116, one end of the connecting arm 116 is connected to the first revolving joint 111, and the other end is fixedly connected to a base.
- the base can be fixed on the hospital bed 20 or the operating trolley 120.
- the fourth revolute joint 115 is connected to a surgical tool or a target pen.
- the fourth revolute joint 115 is connected to the target pen, so that the target pen is connected through the robot arm 110, and the target pen is driven by the robot arm, and the registration point of interest is selected on the patient's bone to complete the bone registration. process.
- the surgical robot 10 further includes a force recognition system, which is arranged on the mechanical arm 110 and is used to detect the force received by the end of the mechanical arm.
- the force received by the end of the mechanical arm is the force received when the target pen punctures the cartilage or performs bone registration.
- the surgical robot 10 further includes a control system, which is respectively communicatively connected with the force recognition system, the robotic arm system 100 and the navigation system 200.
- the force recognition system feeds back information about the force received by the end of the robotic arm that it detects to the control system, and the control system determines whether the target pen has been activated based on the information about the force received by the end of the robotic arm. Pierce to the bone/hard bone surface, that is, determine whether the target pen moves to the registered point of interest on the bone.
- a calibration value of the force received by the end of the mechanical arm is stored in the control system, and the calibration value can be calibrated through experiments.
- the control system compares the force received by the detected end of the robotic arm with the calibration value.
- the actual detected force matches the calibration value (refers to the actual detected force reaches the calibration value, that is, greater than or equal to the calibration value )
- the actually detected force does not reach (that is, less than) the calibration value, continue to control the robotic arm drive station
- the target pen moves to the registration point (such as further deepening), and repeatedly compares the force received by the end of the robotic arm with the calibration value, until the force received by the end of the robotic arm reaches the calibration value .
- the force recognition system includes a first force recognition device and/or a second force recognition device.
- the first force recognition device includes a plurality of first sensors, and at least one first sensor is arranged on each mechanical arm joint, and these first sensors are used to detect the force received by the revolving joint.
- the control system calculates the force received by the end of the manipulator based on the information of the force of all the manipulator joints fed back by the first force identification device.
- the control system can calculate the force received by the end of the robot arm according to a method known in the art.
- the control system can use any existing PLC controller, single-chip microcomputer, microprocessor, FPGA, and those skilled in the art can know how to choose based on the disclosure of this application in combination with common knowledge in the field.
- the second force recognition device includes at least one second sensor.
- the second sensor is arranged on the end of the robot arm, for example, on the fourth revolute joint 115 of the robot arm, so as to directly detect the force received by the end of the robot arm.
- the second force recognition device can directly obtain the force information of the end of the mechanical arm without calculation, which is simpler and more convenient to use, and more accurate.
- the force received by the end of the robotic arm includes force and moment information.
- the first force recognition device includes at least one of a position sensor device, a pressure sensor device, and a grating sensor device.
- the position sensing device includes an absolute position sensing device and a relative position sensor device.
- Absolute position sensor devices include absolute encoders, such as optical encoders, absolute magnetic encoders, absolute rotary transformer encoders or rotary potentiometers.
- the relative position sensing device includes an incremental encoder.
- the pressure sensing device includes a pressure sensor.
- the grating sensing device includes a distributed grating sensor. That is, the first force recognition device includes one or more first sensors.
- the type of the first sensor arranged at each revolute joint on the robot arm 110 may be the same or different.
- a pressure sensor is provided on some revolving joints
- a dual encoder is provided on other revolving joints.
- Both dual encoders and pressure sensors are arranged on the same revolute joint.
- one or more combinations of dual codes, pressure sensors, and grating sensors are set on the same revolute joint.
- the second force recognition device preferably includes a six-axis sensor, and the number may be one or more.
- FIG. 3 is a general flowchart of bone registration performed by the surgical robot 10 in this embodiment. As shown in FIG. 3, the process of performing bone registration by the surgical robot 10 includes the following steps: first enter the bone registration mode and start the bone registration S00; then, perform the following steps.
- Step S01 Select the operating mode of bone registration, for example, select the mode in which the surgical robot automatically completes the bone registration, or select the mode in which the surgical robot assists in completing the bone registration.
- Step S02 After specifying the operating mode, the navigation system 200 sends the information of the registration point of interest to the robotic arm system 100. Specifically, during preoperative planning, the navigation system 200 selects the registered points of interest based on the image information collected before the operation, patient information, prosthesis information, or feature points selected by the operator, and selects the registered points of interest. The information of the registration point is sent to the robotic arm system. More specifically, the navigation system 200 reconstructs the three-dimensional bone model according to the CT registration result, where the algorithm used can be a multi-slice reconstruction or a maximum density projection reconstruction method, and selects near the characteristic points according to the characteristic points selected by the operator Points of interest.
- the algorithm used can be a multi-slice reconstruction or a maximum density projection reconstruction method
- the navigation system 200 After selecting the registration point of interest, the navigation system 200 sends the position information of the registration point of interest in space relative to the base coordinates of the surgical robot to the robotic arm system 100, that is, the navigation system 200 sends the position of the registration point of interest to the robot arm system 100. The information is sent to the robotic arm system 100.
- Step S03 After receiving the position information of the registration point of interest, the robotic arm system 100 plans a movement trajectory so that the end of the robotic arm moves to the registration point of interest along the preset movement trajectory.
- the robot arm 110 is connected to the target pen and performs trajectory planning according to the position of the registration point of interest.
- the robot arm system 100 preferably uses the robot's forward and inverse kinematics equations and dynamic equations to complete the trajectory planning.
- Step S04 After planning the movement trajectory, according to the selected bone registration operation mode, the robot arm 110 drives the target pen to move to the registration point of interest, and selects the registration point on the bone.
- the control system controls the robotic arm 110 to drive the target pen to move to the registration point of interest.
- the operator operates the robotic arm 110 and drives the target pen to move to the registration point of interest.
- step S05 is executed: the navigation system 20 collects the current position information of the target pen, and the control system determines whether the target pen has moved to the point of interest according to the current position information of the target pen The registration point, if yes, it is determined that the registration of the registration point has been completed, and the registration of the next registration point S06 can be performed, and the steps S03 to S05 are repeated until the bone registration of all the registration points of interest is completed.
- the control system when judging whether the target pen has moved to the registration point of interest, the control system also judges whether the target pen has passed through the cartilage to the surface of the bone, that is, whether it has reached the surface of the hard bone, based on the information of the force received by the end of the robotic arm. . If you have passed through the cartilage to the hard bone surface, you can confirm that the target pen has moved to the registration point of interest and correctly selected the registration point on the bone. In some embodiments, the control system simultaneously judges whether the target pen has moved to the registration point of interest based on the current position information of the target pen and the information of the force received by the end of the robot arm.
- control system preferentially judges whether the target pen has moved to the registration point of interest based on the information of the force received by the end of the robotic arm. Specifically, although the target pen has not moved to the target position, if the force received by the end of the robotic arm has reached the calibrated value at this time, it is considered that the target pen has moved to the registration point of interest. Further, if the target pen moves to the target position, but at this time the force received by the end of the mechanical arm has not reached the calibrated value, it is preferable that the operator determine whether to continue to puncture the bone surface.
- the step of judging whether the target pen has moved to the registration point of interest has a higher priority than judging whether the target pen has moved to the registration point of interest according to the current position information of the target pen The priority of the point.
- Fig. 4 is a flowchart of bone registration in the auxiliary operation mode in the preferred embodiment. As shown in Fig. 4, if the auxiliary operation mode is selected in step S01, the surgical robot 10 performs the following steps:
- Step S101 the navigation system 200 sends the location information of the registration point of interest to the robotic arm system 100.
- Step S102 After receiving the location information of the registration point of interest, under the guidance of the robotic arm 110, the operator operates the robotic arm 110 to drive the target pen to move to the registration point of interest, that is, the operator controls the robotic arm to drive The target pen pierces the cartilage until it reaches the surface of the bone, and selects a registration point on the bone.
- the robotic arm system 100 can guide the operator to operate the robotic arm 110 through a method known in the art, such as an impedance control method.
- step S1031 the control system judges whether the target pen moves in place according to the current position information of the target pen collected by the navigation system 200:
- step S104 the operator intervenes and further determines whether to continue to puncture the bone surface
- step S102 If not, continue to perform step S102.
- step S1031 is performed, step S1032 is also preferably performed: the control system judges whether the cartilage piercing force reaches the calibrated value according to the information of the force received by the end of the manipulator:
- step S105 If yes, it can be confirmed that the target pen has moved to the registration point of interest, that is, the result of step S105 is obtained;
- step S102 If not, continue to perform step S102.
- step S104 when performing step S104, if the operator thinks that the puncture to the bone surface is to be continued, it is preferable to perform step S1032; otherwise, if the operator believes that the puncture to the bone surface does not need to be continued, the result of step S105 can be directly obtained. This is because there may be slight differences between the actual patient’s bones and the results obtained by CT reconstruction, resulting in the fact that the actual bone surface reached and the surface of the three-dimensional model reconstructed by CT may be inconsistent. If only the force recognition system determines whether the bone surface has reached the bone surface, there is A certain risk, therefore, it is necessary to rely on the human judgment of the operator to reduce the risk of inaccurate selection of registration points, and to further ensure the accuracy of bone registration.
- step S106 determine whether the navigation system 200 can normally collect the position information of the target pen:
- step 200 drive the target pen to move, and register the next registration point
- step S107 under the guidance of the robotic arm, the operator operates the robotic arm to adjust the posture of the target pen until the navigation system 200 can observe the position of the target pen.
- Fig. 5 is a flowchart of bone registration in the automatic operation mode in the preferred embodiment. As shown in FIG. 5, if the automatic operation mode is selected in the above step S01, the surgical robot 10 performs the following steps:
- Step S201 the navigation system 200 sends the location information of the registration point of interest to the robotic arm system 100.
- Step S202 After receiving the location information of the registration point of interest, the robotic arm system 100 plans a movement trajectory.
- Step S203 After planning the movement trajectory, the control system controls the robotic arm 110 to drive the target pen to move to the registered point of interest along the movement trajectory, that is, the target pen punctures the cartilage under the drive of the robotic arm until it reaches the surface of the bone, and selects on the bone Registration point.
- step S2041 the control system judges whether the target pen moves in place according to the current position information of the target pen collected by the navigation system 200:
- step S205 the operator intervenes and further determines whether to continue to puncture the bone surface
- step S203 If not, continue to perform step S203.
- step S2042 the control system determines whether the cartilage piercing force reaches the calibrated value according to the information of the force received by the end of the robotic arm:
- step S206 If yes, it can be directly confirmed that the target pen has moved to the registration point of interest, that is, the result of step S206 is obtained;
- step S205 if the operator thinks that the puncture to the bone surface is to be continued, step S2042 is preferably performed; on the contrary, if the operator believes that the puncture to the bone surface is unnecessary, the result of step S206 can be obtained.
- step S206 the robotic arm system 100 sends a completion signal to the navigation system 200, and the navigation system 200 collects the position information of the target pen according to the completion signal, and executes step S207: judging whether the navigation system 200 can collect the target normally Pen location information:
- step S200 drive the target pen to move, and register the next registration point
- step S208 the control system controls the movement of the robotic arm to adjust the posture of the target pen until the navigation system 200 can observe the position of the target pen.
- the robotic arm 110 drives the target pen to perform a rotational movement with the same spatial position, that is, the spatial position of the target pen remains unchanged and only the posture is changed.
- the robot arm part of the rotating joint remains stationary, the other part of the rotating joint drives the target pen to rotate around an active stationary point, until the navigation system 200 can normally collect the position information of the target pen and then the robot arm stops moving. This is convenient for smooth operation. Perform bone registration at a registration point locally.
- the robotic arm can guide the operator to hold the target pen to rotate around the active immobile point, and adjust the posture of the target pen.
- the navigation system 200 includes a camera/optical sensing system 210 and an optical target 220.
- the camera 210 is, for example, a binocular camera.
- An optical target 220 is mounted on a target pen, and another optical target 220 Installed on the patient's bones and immobilized.
- the posture of the target pen can be changed to make the optical target 220 rotate around the active immobile point to enter the field of view of the camera 210, namely As shown in Figure 6b.
- the position sensing device includes two encoders (or called dual encoders), an absolute encoder 301 and an incremental encoder 302, respectively.
- two encoders or called dual encoders
- an absolute encoder 301 and an incremental encoder 302, respectively.
- the torque detection of a revolute joint Take the torque detection of a revolute joint as an example.
- a driver 303 and a reducer 304 are provided at the revolute joint.
- the output end of the reducer 304 is connected to the revolving joint, and the input end of the reducer 304 is connected to the driver 303.
- the driver 303 drives the revolute joint to rotate through the speed reducer 304.
- the driver 303 includes a drive motor.
- One of the absolute encoder 301 and the incremental encoder 302 is installed at the output end of the drive motor, and the other encoder is installed at the output end of the reducer 304 (such as the output shaft of a rotating joint) .
- the absolute encoder 301 collects the absolute state parameter T1 of the revolute joint in real time
- the incremental encoder 302 collects the relative state parameter T2 of the revolute joint in real time. Both the absolute state parameter T1 and the relative state parameter T2 are sent to the control system.
- the output torque ⁇ of the drive motor should be equal to the external force torque ⁇ 'received by the revolute joint, and the output torque ⁇ of the drive motor is related to the deformation of the revolute joint:
- K is the stiffness model of the reducer 304, such as the stiffness model of the harmonic reducer
- ⁇ is the deformation of the rotating joint.
- the deformation of the revolute joint has a corresponding relationship with the absolute state parameter T1 and the relative state parameter T2, and the corresponding relationship can be calibrated through experiments in advance. Or, calculated by the following formula:
- T1 is the absolute position of the revolute joint fed back by the absolute encoder, the absolute position is, for example, the absolute rotation angle;
- T2 is the relative position of the revolute joint fed back by the incremental encoder, and the relative position is, for example, the relative rotation angle ;
- C1 is the resolution of the absolute encoder;
- c2 is the resolution of the incremental encoder;
- S0 is the startup initialization position of the incremental encoder.
- control system can obtain the output torque ⁇ of the drive motor according to the deformation of the revolute joint and the stiffness model of the reducer, and can determine the external torque ⁇ 'of the revolute joint according to the output torque of the drive motor.
- two encoders are respectively installed at the input end of the reducer 304 and the output end of the reducer.
- the reducer and other transmission elements can be equivalent to an elastic body 306.
- the equivalent elastic body 306 between the two encoders will be deformed, resulting in a deviation in the data collected between the two encoders, and this deviation is related to the external force. Therefore, through test calibration, the mapping relationship between the reading deviation of the two encoders and the external force can be obtained. Then use the driver to obtain the readings of the two encoders, and then upload the readings to the control system.
- the control system obtains the deviation value of the two encoders according to the reading, and can obtain the external force on the joint according to the deviation value.
- the joint module may also include at least one torque sensor 305.
- 305 may be an optical mechanical deformation type, an electromagnetic induction type, or a resistance strain type, etc.
- the torque information received by the revolute joint is directly detected by the torque sensor 305.
- the position sensing device and the torque sensor can be mutually verified to monitor the working status of the two, so as to further improve the accuracy of the torque recognition of the revolute joint.
- the torque sensor 305 can be installed on the output end of the reducer, such as a joint output shaft. Further, the output current of the driving motor can also be collected, so that the control system can obtain the external force information received by the rotating joint according to the output current of the driving motor, so as to realize redundant detection.
- the torque sensor 305 is a pressure sensor.
- the pressure sensor Before leaving the factory, the pressure sensor can be calibrated to the zero point. Specifically, the external force is applied to the rotating joint of the robotic arm and the output data of the pressure sensor is read, so that the pressure sensor can be zero-calibrated according to the measured output data. Further in use, when the rotating joint of the mechanical arm is subjected to an external force, the deformation of the pressure sensor is converted into an electric signal and sent to the control system, and the control system can calculate the external force received by the rotating joint according to the electric signal of the pressure sensor.
- the torque sensor 305 may also be a distributed grating sensor.
- the distributed grating sensor is arranged at the revolving joint and can be connected to the housing of the mechanical arm.
- the grating sensor includes a fiber grating strain gauge, which constitutes a strain bridge.
- the bridge layout method can refer to the existing resistance strain bridge layout method.
- fiber grating strain gauges are installed at each rotating joint, and the fiber grating strain gauges of each joint module share one fiber channel. More specifically, the broadband light source placed at the back end of the robotic arm (such as the base) emits modulated light, passes through the fiber grating strain gauges of each joint module, and is reflected back. The control system demodulates and calculates the wavelength of the reflected light. .
- the wavelength of the reflected light will change.
- the amount of wavelength change is proportional to the strain of the distributed grating sensor. From this, the strain of each distributed grating sensor can be measured. The strain amount of the distributed grating sensor is calculated to obtain the external force experienced by the joint module.
- the force recognition system can further verify the accuracy of the torque information. That is, the force recognition system preferably includes a first force recognition device and a second force recognition device, wherein the first force recognition device may include a variety of first sensors to detect torque information in different ways, such as the first force recognition device at the end of the robotic arm.
- the second force recognition device directly senses the torque information at the end of the robotic arm through the six-axis sensor, while the first force recognition device can sense the torque received by the rotating joint through one or more of dual encoders, pressure sensors, and grating sensors. Information, the first force recognition device can also obtain torque information received by the joint by detecting the output current of the drive motor.
- the force information at the end of the robotic arm can be obtained through multiple detection methods during the bone registration process, and the detection information can be verified to determine whether the torque information used in the calibration calculation is accurate.
- the detection information received by the rotating joint it can also protect the joint module.
- the robot arm has an active adjustment mode and/or a passive adjustment mode.
- the power mechanism on the robot arm 110 is such as The working mode of driving the motor to drive the movement of the mechanical arm is the active adjustment of the mechanical arm.
- the working mode of driving the movement of the mechanical arm by the Cartesian force is the passive adjustment of the mechanical arm.
- the control system obtains the torque of each revolute joint on the robotic arm, and then controls all the drive motors on the revolute joints whose torque is greater than the preset calibration value (that is, the drive torque is greater than the preset calibration value).
- the drive motor of the joint stop output.
- the calibration value is, for example, zero. In this way, the problem of mechanical posture adjustment caused by human misoperation during the active adjustment mode operation of the mechanical arm can be avoided, thereby increasing the safety and reliability of the mechanical arm during use.
- the control system obtains the torque of each joint on the manipulator, it then controls all the drive motors on the revolute joints whose torque is greater than the preset calibration value (the calibration value is zero, for example).
- the drive motor on the revolute joint whose torque on the robotic arm is greater than the preset calibration value can cooperate with the operator to drive the revolute joint movement of the robotic arm, so that the operator can overcome the resistance of the revolute joint on the robotic arm, so that The control system can assist the operator to smoothly move the mechanical arm to a predetermined position. In this way, the comfort and convenience of the passive adjustment operation of the mechanical arm are increased.
- the drive motors on the revolute joints whose torque on the robotic arm is greater than the preset calibration value (the calibration value is for example zero) output power, so that the operator It is more labor-saving and simple to adjust the mechanical arm passively.
- each force recognition device transmits the torque information obtained to the control system, and the control system compares the calculations based on the dual encoders
- the force received by the end of the robotic arm is the same as the force received by the end of the robotic arm directly detected by the six-axis sensor. That is, the control system verifies the received torque information and determines whether to update the calibration based on the verification result. According to the verification results, the control system can also take corresponding safety protection measures. For example, using the six-axis sensor as the calibration reference, update the stiffness coefficient K of the reducer in the dual encoder, or update the relevant parameters in the pressure sensor and the grating sensor.
- control system is also used to determine whether the torque sensor exceeds the range of the torque sensor according to the received torque information, protect the torque sensor, and further ensure the accuracy of the joint torque information during the bone registration process, thereby further determining the cartilage puncture force information To ensure the accuracy of bone registration.
- Fig. 9 is a flowchart of bone registration in a preferred embodiment.
- step S301 is executed when the target pen moves to the registration point of interest
- step S302 is also executed: the control system determines whether the torque sensors of each joint are working properly; if not, then Stop the automatic operation mode or auxiliary operation mode, and change to manual registration S303.
- the operator manually drives the target pen to perform bone registration; if so, execute step S304: the control system continues to control the robotic arm to drive the target pen to the Register point movement, and judge whether the cartilage puncture force reaches the calibration value, that is, whether the torque value fed back by the six-axis sensor reaches the calibration value.
- step S306 continue to drive the target pen to penetrate cartilage and other tissues. During this process, return to step S304 at any time , Until the puncture cartilage force reaches the calibration value.
- two empirical thresholds can be set in the control system.
- the first threshold is used for mutual calibration of sensors, and the second threshold is used to determine whether the torque sensor exceeds its range.
- the control system determines whether the sensors on each joint module work normally according to the two thresholds. Specifically, the control system compares the force value received by the end of the robot arm measured according to the detection model of the dual encoder with the force value received by the end of the robot arm measured by the six-axis sensor. The deviation of the latter two exceeds the range defined by the first threshold, it indicates that the sensor is abnormal, and the relevant parameters of the sensor need to be updated. If the deviation of the two is within the range of the first threshold, it indicates that the sensor is working normally.
- the data detected by the force recognition system can be used to control the depth of insertion of the target pen into the cartilage.
- the present invention does not limit the specific size of the two thresholds, and can be determined through experiments according to the performance, detection accuracy and other requirements of the sensor.
- the surgical robot 10 of this embodiment also provides a function of maintaining the force recognition system before surgery.
- Fig. 10 is a flowchart of maintaining the force recognition system in a preferred embodiment.
- step S401 before leaving the factory, the deviation of the encoder when each mechanical arm rotating joint receives an external force can be recorded and stored in the control system.
- step S402 before leaving the factory, a verification program can be started to verify the reliability of the encoder. After the verification, in step S403, the surgical robot is automatically run and the verification parameters are updated to ensure that the encoder works normally.
- step S404 it is also necessary to calibrate the data information collected by other torque sensors and ensure the accuracy of the collected data information, that is, to update the parameters of each sensor on the joint module according to the six-axis sensor. And to ensure the accuracy of these sensors.
- step S405 can be performed before the operation to compare the data collected by each sensor with the factory data to ensure the rigidity of the reducer.
- the present invention mainly checks the main mechanical components in the surgical robot, that is, the harmonic reducer, to ensure that the harmonic reducer operates normally.
- the database will record the empirical value range of the different stiffness of each robot product. According to the time and empirical value range of the product, as well as the original mechanical and hardware design parameters, confirm whether the torque sensor is still used for a certain period of time. Can work normally.
- a third threshold can be set in the control system. If the detection result of the torque sensor exceeds the third threshold, it is considered that the torque sensor cannot reach the required accuracy, and the torque sensor needs to be re-maintained and calibrated or replaced.
- the third threshold is based on the empirical value range of different stiffness of each robot product, the time the product is used, and the original mechanical and hardware design parameters, such as the resolution and accuracy of dual encoders, torque sensors and six-axis torque sensors The resolution, zero drift, temperature drift, stiffness of the harmonic reducer, reduction ratio, reduction ratio error, and the stiffness model of the connector are determined.
- control system of the surgical robot 10 adopts a neural network calculation method to update the sensor model parameters.
- a neural network calculation method to update the sensor model parameters.
- online neural network learning is added to update the sensor model parameters.
- the neural network calculation method can provide online model parameter updates to ensure that the force of each revolute joint is more reliable, and the reliability of the force recognition system is further improved.
- the flow chart of online model parameter update using six-axis sensors is shown in Figure 11.
- the coefficients of the torque sensor model of each joint and the stiffness model of the reducer are used as the neural network input parameters, and in process S509, the input parameters are used for online neural network learning to update the parameters of the known model .
- Including the stiffness model of the reducer, the joint torque sensor model, and the Cartesian force at the end of the new manipulator is calculated according to the learning results in the process S510, and then the output result of the neural network (the calculated Compare the Cartesian force at the end of the new robotic arm with the data collected by the actual six-axis sensor (the actual Cartesian force at the end of the robotic arm) to confirm whether to update the model parameters of the sensor.
- Fig. 12 is a schematic diagram of a process of obtaining a torque sensor model based on a neural network model provided by a preferred embodiment.
- the neural network has a three-layer structure of input layer, hidden layer and output layer.
- the input layer has three nodes, which are torque sensor parameters 1, 2, and 3; the hidden layer has two nodes; and the output layer has one node, which is used to output a single joint torque.
- the input of the three nodes of the input layer corresponds to the stiffness of the harmonic reducer, the angular velocity of the joint and the angular position of the joint; if it is a torque sensor, the input parameters are the torque conversion coefficient, Torque sensor zero point and torque sensor temperature.
- the node output of the output layer is the actual torque of the torque sensor.
- a neural network model after online training that is, the weights and thresholds of all nodes are first obtained through training samples when leaving the factory.
- the model parameters in the neural network are continuously updated.
- the specific training method may adopt the gradient descent method or other existing technologies, which is not limited in the present invention.
- this embodiment also provides a model update method that is closer to the actual physical meaning, and the flow can refer to FIG. 13.
- the neural network has a three-layer structure of input layer, hidden layer and output layer. And the input layer has three nodes, the hidden layer has two nodes, and the output layer has one node. Among them, the input of the three nodes of the input layer corresponds to the angular velocity of the joint, the angular position of the joint, and the output torque of the joint motor. The node output of the output layer is the actual torque of the torque sensor.
- the least square method is used to update the parameter coefficients of the dual-encoder torque model and the torque sensor based on the obtained torque results, and use the updated coefficients as calculation confirmation.
- control system of this embodiment includes a memory and a processor, and a program is stored in the memory, so that the processor can perform the above functions by running the program.
- the surgical robot utilizes the force recognition system to achieve the purpose of automatically completing or assisting in completing the bone registration by the surgical robot, greatly improving the efficiency of bone registration, and at the same time improving the bone registration. Registration accuracy and success rate. Furthermore, the use of multiple force recognition devices ensures the accuracy of the cartilage puncture force during the operation, and improves the accuracy of the operation. Furthermore, the surgical robot also provides maintenance methods after leaving the factory, which can effectively protect the core components of the surgical robot, and confirm the operating status and component status of the robot to ensure that there will be no problems during the operation. Furthermore, for the six-axis sensor, the surgical robot also provides a method for online neural network learning and updating model parameters. This method can provide online model parameter updates to ensure that the force of each joint is more reliable, and the force recognition system is more reliable. Reliability has been further improved.
- the surgical robot also has an online verification function, which can perform verification on the machine after the factory is used, to ensure that the state of the robot before the operation is intact and to ensure the smooth progress of the operation.
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Abstract
Description
Claims (25)
- 一种用于手术机器人的骨注册方法,其特征在于,包括以下步骤:机械臂***接收导航***所选择的预定对象上感兴趣的注册点的信息;控制机械臂***中的机械臂的运动,以使所述机械臂控制跟踪装置运动至所述预定对象上感兴趣的注册点;获取由力识别***检测的机械臂末端所受到的作用力;以及根据所述机械臂末端所受到的作用力,判断所述跟踪装置是否已运动到所述预定对象上感兴趣的注册点。
- 根据权利要求1所述的方法,其特征在于,,还包括以下步骤:获取由导航***采集的所述跟踪装置的当前位置信息;根据所述跟踪装置的当前位置信息,判断所述跟踪装置是否已运动到预定对象上感兴趣的注册点。
- 根据权利要求2所述的方法,其特征在于,根据所述机械臂末端所受到的作用力,以判断所述跟踪装置是否已运动到预定对象上感兴趣的注册点的优先级高于根据所述跟踪装置的当前位置信息,以判断所述跟踪装置是否已运动到预定对象上感兴趣的注册点的优先级。
- 根据权利要求1所述的方法,其特征在于,所述根据所述机械臂末端所受到的作用力,判断所述跟踪装置是否已运动到预定对象上感兴趣的注册点的步骤包括:判断力识别***是否工作正常;若是,则控制所述机械臂驱动所述跟踪装置向所述注册点运动。
- 根据权利要求4所述的方法,其特征在于,若所述力识别***判断为 工作正常,则在控制所述机械臂驱动所述跟踪装置向所述注册点运动的步骤之后,还包括:将所述机械臂的末端所受到的作用力与标定值进行比较;若等于或大于所述标定值,则确定所述跟踪装置已运动到预定对象上感兴趣的注册点;若小于所述标定值,则继续控制所述机械臂驱动所述跟踪装置向所述注册点运动,直至所述机械臂末端所受到的作用力达到所述标定值。
- 根据权利要求1所述的方法,其特征在于,在确定所述跟踪装置已运动到预定对象上感兴趣的注册点之后,还包括以下步骤:判断所述导航***是否能够正常采集所述跟踪装置的位置信息;若是,控制所述机械臂以驱动所述跟踪装置向下一个感兴趣的注册点运动;若否,控制所述机械臂以调整所述跟踪装置的姿态,直至所述导航***能够正常采集所述跟踪装置的位置信息。
- 根据权利要求1所述的方法,其特征在于,在控制机械臂运动之前,还包括以下步骤:根据所述导航***所选择的预定对象上感兴趣的注册点,所述机械臂***规划一运动轨迹,所述机械臂驱动所述跟踪装置沿所述运动轨迹运动至感兴趣的注册点。
- 根据权利要求1所述的方法,其特征在于,在判断所述跟踪装置是否已运动到预定对象上感兴趣的注册点的步骤之前,还包括以下步骤:根据所述力识别***获取的每个机械臂关节所受到的作用力,计算得到所述机械臂的末端所受到的作用力;获取所述力识别***所得到的所述机械臂末端所受到的作用力;比较计算得到的所述机械臂的末端所受到的作用力,与利用力识别***所得到的所述机械臂末端所受到的作用力;若两者的偏差超出预定范围,则更新所述力识别***。
- 根据权利要求8所述的方法,其特征在于,所述力识别***获取每个机械臂关节所受到的作用力的步骤包括:根据安装在每个所述机械臂关节的第一传感器,检测每个所述机械臂关节所受到的作用力。
- 根据权利要求8所述的方法,其特征在于,所述力识别***得到所述机械臂末端所受到的作用力的步骤包括:根据安装在所述机械臂末端的第二传感器,检测所述机械臂末端所受到的作用力。
- 根据权利要求8-10中任一项所述的方法,其特征在于,采用神经网络计算的方法计算所述机械臂末端所受到的作用力,且在输出所述机械臂末端所受到的作用力之前,还包括对所述力识别***进行神经网络训练的步骤,并保持神经网络训练后的网络结构以及权值文件。
- 一种手术机器人,其特征在于,包括控制***、力识别***、机械臂***和导航***;所述机械臂***包括机械臂;所述机械臂的机械臂末端用于连接跟踪装置;所述控制***分别与所述力识别***、所述机械臂***和所述导航***通信连接,所述导航***与所述机械臂***通信连接;所述导航***被配置为将预定对象上感兴趣的注册点的信息发送给所述机械臂***;所述机械臂***被配置为根据所述预定对象上感兴趣的注册点的信息,控制所述机械臂运动,以驱动所述跟踪装置运动至预定对象上感兴 趣的注册点;所述力识别***设置在所述机械臂上,所述力识别***用于检测所述机械臂末端所受到的作用力并发送给所述控制***;所述控制***被配置为根据所述机械臂末端所受到的作用力,判断所述跟踪装置是否已运动到预定对象上感兴趣的注册点。
- 根据权利要求12所述的手术机器人,其特征在于,所述导航***被配置为:采集所述跟踪装置的当前位置信息并发送给所述控制***;所述控制***被配置为根据所述跟踪装置的当前位置信息,判断所述跟踪装置是否已运动到预定对象上感兴趣的注册点。
- 根据权利要求13所述的手术机器人,其特征在于,所述控制***被配置为,根据所述机械臂末端所受到的作用力,以判断所述跟踪装置是否已运动到预定对象上感兴趣的注册点的优先级高于根据所述跟踪装置的当前位置信息,以判断所述跟踪装置是否已运动到预定对象上感兴趣的注册点的优先级。
- 根据权利要求12所述的手术机器人,其特征在于,所述控制***被配置为,判断力识别***是否工作正常;若是,则控制所述机械臂驱动所述跟踪装置向所述注册点运动。
- 根据权利要求15所述的手术机器人,其特征在于,若所述力识别***判断为工作正常,所述控制***被配置为将所述机械臂末端所受到的作用力与所述控制***内预存的标定值进行比较;若等于或大于所述标定值,则确定所述跟踪装置已运动到预定对象上感兴趣的注册点;若小于所述标定值,则继续控制所述机械臂驱动所述跟踪装置向所述注册点运动,直至所述机械臂末端所受到的作用力等于或大于所述标定值。
- 根据权利要求12所述的手术机器人,其特征在于,在确定所述跟踪装置已运动到预定对象上感兴趣的注册点之后,所述控制***还被配置为判断所述导航***是否能够正常采集所述跟踪装置的位置信息;若是,控制所述机械臂驱动所述跟踪装置向下一个感兴趣的注册点运动;若否,控制所述机械臂调整所述跟踪装置的姿态,直至所述导航***能够正常采集所述跟踪装置的位置信息。
- 根据权利要求12所述的手术机器人,其特征在于,所述机械臂包括多个机械臂关节,所述力识别***包括第一力识别装置和第二力识别装置;所述第一力识别装置包括多个第一传感器,每个所述机械臂关节处设置至少一个所述第一传感器;所述第一传感器用于检测对应的机械臂关节所受到的作用力;所述第二力识别装置包括至少一个设置在所述机械臂末端的第二传感器,所述第二传感器用于检测所述机械臂末端所受到的作用力;所述控制***被配置为:根据多个所述第一传感器检测到的所述机械臂关节所受到的作用力,计算得到所述机械臂末端所受到的作用力;比较计算得到的所述机械臂末端所受到的作用力,与所述第二传感器所检测得到的所述机械臂末端所受到的作用力;若两者的偏差超出预定范围,则更新所述力识别***。
- 根据权利要求18所述的手术机器人,其特征在于,所述第一传感器包括双编码器、力矩传感器以及分布式光栅传感器中的至少一种,所述第二传感器包括六轴传感器。
- 根据权利要求19所述的手术机器人,其特征在于,每个所述机械臂 关节处设置有双编码器,所述双编码器包括绝对式编码器和增量式编码器;所述机械臂还包括用于驱动所述机械臂关节的驱动器和减速器,所述驱动器的输出端连接所述减速器的输入端,所述减速器的输出端连接所述机械臂关节;其中,所述绝对式编码器和增量式编码器中的一个设置在所述减速器的输入端,另一个设置在所述减速器的输出端。
- 根据权利要求20所述的手术机器人,其特征在于,所述双编码器与所述控制***通信连接;所述控制***用于根据所述双编码器的数据偏差与所述机械臂关节所受到的作用力的映射关系,获取所述机械臂关节所受到的作用力。
- 根据权利要12所述的手术机器人,其特征在于,所述控制***被配置为采用神经网络计算的方法计算所述机械臂末端所受到的作用力,且在输出所述机械臂末端所受到的作用力之前,对所述力识别***进行神经网络训练,并保持神经网络训练后的网络结构以及权值文件。
- 根据权利要12所述的手术机器人,其特征在于,所述手术机器人包括自动运行模式和辅助运行模式;当所述手术机器人处于所述自动运行模式时,所述机械臂***根据接收到的感兴趣的注册点的信息,规划运动轨迹,并控制所述机械臂驱动所述跟踪装置沿着所述运动轨迹运动至预定对象上感兴趣的注册点;当所述手术机器人处于所述辅助运行模式时,由外力驱动所述机械臂运动并带动所述跟踪装置运动至预定对象上感兴趣的注册点。
- 一种可读存储介质,其上存储有程序,其特征在于,当所述程序被处理器运行时执行如权利要求1-11中任一项所述的用于手术机器人的骨注册方法。
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