Surgical robot registration method, device, equipment and medium

Abstract

The invention discloses a surgical robot registration method, device and equipment and a medium. The method comprises the steps that a mechanical arm base coordinate system constructed based on the center of a mechanical arm base of a surgical mechanical arm and a three-dimensional image coordinate system constructed based on the scanning center of a C-shaped arm are determined; determining a coarse registration matrix between the base coordinate system of the mechanical arm and the three-dimensional image coordinate system; determining a target mechanical arm shape and position of the surgical mechanical arm, and collecting a target image through a C-shaped arm; a first coordinate set of the first optical target set in a three-dimensional image coordinate system is determined according to the target target information, and a second coordinate set of the first optical target set in a mechanical arm base coordinate system under the target mechanical arm shape and position is determined through a target joint motion model; and determining a registration error matrix between the first coordinate set and the second coordinate set through a registration error equation, and determining a fine registration matrix according to the registration error matrix and the coarse registration matrix to perform fine registration. According to the method, the registration efficiency and accuracy of the surgical robot can be improved.

Description

Technical Field

[0001] The present invention relates to the field of computer application technology, and in particular to a surgical robot registration method, device, equipment and medium. Background Art

[0002] In image-guided surgical robot applications, registration and calibration between the surgical robot and the object being operated on is crucial to ensure the operating accuracy of the surgical robot.

[0003] In the related art, technicians usually first perform registration calculations on the structural data of the surgical robot and the pre-acquired image data, and then manually align the two using the calculated registration data. However, the registration efficiency and accuracy are often difficult to meet user needs. Summary of the invention

[0004] The present invention provides a surgical robot registration method, device, equipment and medium to solve the technical problem of low surgical robot registration efficiency and accuracy.

[0005] According to one aspect of the present invention, a registration method for a surgical robot is provided, wherein the method comprises:

[0006] In the case where a surgical robot arm of the surgical robot is rigidly connected to a C-arm, determining a robot arm base coordinate system constructed based on a robot arm base center of the surgical robot arm and a three-dimensional image coordinate system constructed based on a scanning center of the C-arm;

[0007] Determine a coarse registration matrix between the robot base coordinate system and the three-dimensional image coordinate system;

[0008] Determine the target manipulator shape and position of the surgical manipulator, and collect a target image through the C-arm, wherein the target image includes target target information of a first optical target set installed at the manipulator end of the surgical manipulator through a connector under the target manipulator shape and position;

[0009] Determine a first coordinate set of the first optical target set in the three-dimensional image coordinate system according to the target target information, and determine a second coordinate set of the first optical target set in the robotic arm base coordinate system under the target robotic arm shape and position through a target joint motion model;

[0010] A registration error matrix between the first coordinate set and the second coordinate set is determined by a registration error equation, a fine registration matrix is ​​determined according to the registration error matrix and the coarse registration matrix, and the three-dimensional image coordinate system and the robot arm base coordinate system are finely registered based on the fine registration matrix.

[0011] According to another aspect of the present invention, a registration device for a surgical robot is provided, wherein the device comprises:

[0012] A rigid connection module, used to determine a robot base coordinate system constructed based on the robot base center of the surgical robot and a three-dimensional image coordinate system constructed based on the scanning center of the C-arm when the surgical robot is rigidly connected to the C-arm of the surgical robot;

[0013] A coarse conversion module, used to determine a coarse registration matrix between the robot base coordinate system and the three-dimensional image coordinate system;

[0014] An image acquisition module, used to determine the target robot arm shape and position of the surgical robot arm, and to acquire a target image through the C-arm, wherein the target image includes target target information of a first optical target set installed at the robot arm end of the surgical robot arm through a connector under the target robot arm shape and position;

[0015] A coordinate set determination module, used to determine a first coordinate set of the first optical target set in the three-dimensional image coordinate system according to the target target information, and to determine a second coordinate set of the first optical target set in the robotic arm base coordinate system under the target robotic arm shape and position through a target joint motion model;

[0016] A fine registration module is used to determine a registration error matrix between the first coordinate set and the second coordinate set through a registration error equation, determine a fine registration matrix according to the registration error matrix and the coarse registration matrix, and perform fine registration on the three-dimensional image coordinate system and the robot base coordinate system based on the fine registration matrix.

[0017] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0018] at least one processor; and

[0019] a memory communicatively connected to the at least one processor; wherein,

[0020] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the surgical robot registration method described in any embodiment of the present invention.

[0021] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to implement the surgical robot registration method described in any embodiment of the present invention when executed by a processor.

[0022] The technical solution of the embodiment of the present invention is to determine a robot base coordinate system constructed based on the robot arm base center of the surgical robot and a three-dimensional image coordinate system constructed based on the scanning center of the C-arm when the surgical robot arm is rigidly connected to the C-arm of the surgical robot; determine a coarse registration matrix between the robot base coordinate system and the three-dimensional image coordinate system; determine the target robot arm shape and position of the surgical robot arm, and collect a target image through the C-arm, wherein the target image includes target target information of a first optical target set installed at the robot arm end of the surgical robot arm through a connector under the target robot arm shape and position; according to the The target target information determines the first coordinate set of the first optical target set in the three-dimensional image coordinate system, and the second coordinate set of the first optical target set in the robotic arm base coordinate system under the target robotic arm shape and position is determined by the target joint motion model; the registration error matrix between the first coordinate set and the second coordinate set is determined by the registration error equation, and the fine registration matrix is ​​determined according to the registration error matrix and the coarse registration matrix. The technical scheme of finely aligning the three-dimensional image coordinate system and the robotic arm base coordinate system based on the fine registration matrix realizes the automatic registration of the surgical robot and improves the efficiency and accuracy of the surgical robot registration.

[0023] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 is a flow chart of a surgical robot registration method provided according to Embodiment 1 of the present invention;

[0026] Figure 2 is a scene diagram for realizing the rigid connection between the surgical robot arm and the C-arm of an embodiment of the present invention;

[0027] Figure 3 is a flow chart of a surgical robot registration method provided according to Embodiment 2 of the present invention;

[0028] Figure 4 is an overall flow chart of a registration method for a surgical robot provided according to an embodiment of the present invention;

[0029] Figure 5 is a conversion relationship diagram between coordinate systems provided according to an embodiment of the present invention;

[0030] Figure 6 is a structural schematic diagram of a registration device for a surgical robot provided according to a third embodiment of the present invention;

[0031] Figure 7 It is a schematic diagram of the structure of an electronic device for implementing the registration method of a surgical robot according to an embodiment of the present invention. DETAILED DESCRIPTION

[0032] 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.

[0033] 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, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0034] Embodiment 1

[0035] Figure 1 A flowchart of a surgical robot registration method is provided for the first embodiment of the present invention. This embodiment can be applied to the situation where the surgical robot and the object operated by the surgical robot are calibrated by accurately registering the coordinate system of the surgical robot arm and the C-arm. The method can be performed by a surgical robot registration device, which can be implemented in the form of hardware and / or software, and the surgical robot registration device can be configured in a computer. Figure 1 As shown, the method includes:

[0036] S110. When a surgical robot arm is rigidly connected to a C-arm of the surgical robot, determine a robot arm base coordinate system constructed based on a robot arm base center of the surgical robot arm and a three-dimensional image coordinate system constructed based on a scanning center of the C-arm.

[0037] Figure 2 : is a scene diagram of the rigid connection between the surgical robot arm and the C-arm of the embodiment of the present invention. Figure 2 As shown, A represents a C-shaped arm, B represents a robot base, C represents a robot end, and D represents an optical locator, on which a binocular camera is installed. In the embodiment of the present invention, a coordinate system constructed based on the scanning center of the C-shaped arm is used as a three-dimensional image coordinate system; a coordinate system constructed based on the center of the robot base is used as a robot base coordinate system; a coordinate system constructed based on the robot end is used as a robot end coordinate system, and a coordinate constructed based on the midpoint of the optical center line of the binocular camera of the optical locator is used as a visual coordinate system.

[0038] In the embodiment of the present invention, the center of the robotic arm base and the scanning center of the C-arm are determined based on the hardware structure parameters of the surgical robot, which are not specifically limited here.

[0039] S120: Determine a coarse registration matrix between the robot base coordinate system and the three-dimensional image coordinate system.

[0040] In the embodiment of the present invention, the coarse registration matrix may be directly measured based on a common measurement method, which is not specifically limited herein.

[0041] S130, determining a target robot arm shape and position of the surgical robot arm, and acquiring a target image through the C-arm, wherein the target image includes target target information of a first optical target set installed at the robot arm end of the surgical robot arm through a connector under the target robot arm shape and position.

[0042] The target robot arm position can be understood as a position of the surgical robot arm. In the embodiment of the present invention, the target robot arm position can be a random robot arm position.

[0043] The target image can be understood as the image of the surgical robot arm in the target robot arm shape and position.

[0044] The first optical target set may include a plurality of first optical targets. The first optical target set may be installed at the end of the robotic arm of the surgical robotic arm based on a connector. The distance between each first optical target and the end of the robotic arm may be different or the same.

[0045] The target information may include position information of the first optical target set.

[0046] S140. Determine a first coordinate set of the first optical target set in the three-dimensional image coordinate system according to the target target information, and determine a second coordinate set of the first optical target set in the robotic arm base coordinate system under the target robotic arm shape and position through a target joint motion model.

[0047] Optionally, the joint motion model may be a DH (Denavit-Hartenberg) model, which may be used to describe parameters of the kinematic characteristics of a robot arm.

[0048] In the embodiment of the present invention, the first coordinate set of the first optical target set in the three-dimensional image coordinate system can be directly determined based on the target information in the target image.

[0049] The target joint motion model may be used for calculation of data conversion between the robot arm end coordinate system and the robot arm base coordinate system.

[0050] Optionally, the second coordinate set of the first optical target set in the manipulator base coordinate system under the target manipulator shape and position determined by the target joint motion model includes:

[0051] Determine a robot arm end coordinate system constructed based on the robot arm end of the surgical robot arm and first connector information of a connector connecting the robot arm end and the first optical target set;

[0052] Determine an end coordinate set of the first optical target set in the end coordinate system of the robot arm based on the first connection piece information;

[0053] The input end coordinate set is transformed through the target joint motion model to obtain a second coordinate set of the first optical target set in the robot arm base coordinate system.

[0054] In an embodiment of the present invention, the connector may include a plurality of connecting branches, each connecting branch being used to connect one of the first optical targets to the end of the robotic arm. The length of each connecting branch may be different or the same. The first connector information may include the length of the connecting branch of the connector corresponding to each first optical target, that is, the distance between each first optical target and the end of the robotic arm, that is, the distance between each first optical target and the origin of the coordinate system of the end of the robotic arm.

[0055] The end coordinate set may be understood as a coordinate set of the first optical target set in the end coordinate system of the robotic arm.

[0056] S150. Determine a registration error matrix between the first coordinate set and the second coordinate set through a registration error equation, determine a fine registration matrix according to the registration error matrix and the coarse registration matrix, and perform fine registration on the three-dimensional image coordinate system and the robot base coordinate system based on the fine registration matrix.

[0057] The registration error equation may be used to calculate the registration error between the robot base coordinate system and the three-dimensional image coordinate system R. Optionally, the registration error equation may be as shown in the following formula:

[0058]

[0059] in, can represent the registration error matrix; Δα, Δβ, Δγ, Δx, Δy, Δz can represent the error parameters of the registration error equation; R x Can represent the rotation operator around the x-axis; R y Can represent the rotation operator around the y-axis; R z Can represent the rotation operator around the z-axis; D x Can represent the translation operator around the X axis; D y Can represent the translation operator around the y-axis; D z It can represent the translation operator around the z-axis.

[0060] Specifically, the calculation formula for determining the fine registration matrix according to the registration error matrix and the coarse registration matrix can be as follows:

[0061]

[0062] in, = can represent the precise registration matrix, can represent the coarse registration matrix, The registration error matrix can be expressed as .

[0063] Optionally, before determining the registration error matrix between the first coordinate set and the second coordinate set by using the registration error equation, the method further includes:

[0064] Controlling the surgical robot arm to move to each first robot arm position in a preset first robot arm position sequence in sequence and collecting a position image sequence through the C-arm, wherein the position image includes first target information of a first optical target set installed at a robot arm end of the surgical robot arm in the first robot arm position;

[0065] Optionally, before controlling the surgical robot arm to move sequentially to each first robot arm position in a preset first robot arm position sequence, the method further includes:

[0066] Determine the first robotic arm position sequence based on the preset imaging area of ​​the C-arm and the preset operating space of the surgical robotic arm. Determine the image coordinate set sequence of the first optical target set in the three-dimensional image coordinate system based on the first target information in each position image of the position image sequence;

[0067] Determine, by means of the target joint motion model, a base coordinate set sequence of the first optical target set in the base coordinate system of the robotic arm under the shape and position sequence of the first robotic arm;

[0068] The error parameters of the pre-constructed initial error equation are adjusted according to the image coordinate set sequence and the base coordinate set sequence to obtain a registration error equation.

[0069] Wherein, the position image sequence includes a plurality of position images.

[0070] The technical solution of the embodiment of the present invention is to determine a robot base coordinate system constructed based on the robot arm base center of the surgical robot and a three-dimensional image coordinate system constructed based on the scanning center of the C-arm when the surgical robot arm is rigidly connected to the C-arm of the surgical robot; determine a coarse registration matrix between the robot base coordinate system and the three-dimensional image coordinate system; determine the target robot arm shape and position of the surgical robot arm, and collect a target image through the C-arm, wherein the target image includes target target information of a first optical target set installed at the robot arm end of the surgical robot arm through a connector under the target robot arm shape and position; according to the The target target information determines the first coordinate set of the first optical target set in the three-dimensional image coordinate system, and the second coordinate set of the first optical target set in the robotic arm base coordinate system under the target robotic arm shape and position is determined by the target joint motion model; the registration error matrix between the first coordinate set and the second coordinate set is determined by the registration error equation, and the fine registration matrix is ​​determined according to the registration error matrix and the coarse registration matrix. The technical scheme of finely aligning the three-dimensional image coordinate system and the robotic arm base coordinate system based on the fine registration matrix realizes the automatic registration of the surgical robot and improves the efficiency and accuracy of the surgical robot registration.

[0071] Embodiment 2

[0072] Figure 3 A flowchart of a surgical robot alignment method provided in the second embodiment of the present invention is provided. This embodiment is to add the second coordinate set of the first optical target set in the robotic arm base coordinate system when the target robotic arm shape and position is determined by the target joint motion model as described in the above embodiment.

[0073] like Figure 3 As shown, the method includes:

[0074] S210, determining an optical locator and a visual coordinate system constructed based on the midpoints of a line connecting optical centers of binocular cameras of the optical locator.

[0075] The optical locator can be used to identify the position information of the optical target, and the placement of the surgical robot arm, the C-arm and the optical locator can be as follows: Figure 2 The scene diagram shown.

[0076] S220, determining a second optical target set based on a connector connected to the center of the robot base, and determining the target joint motion model based on the robot base coordinate system, the robot end coordinate system, the visual coordinate system and the second optical target set.

[0077] The second optical target set may include a plurality of second optical targets. The second optical target set may be installed at the center of the robotic arm base based on a connector. The distance between each second optical target and the center of the robotic arm base may be different or the same.

[0078] Optionally, determining the target joint motion model based on the manipulator base coordinate system, the manipulator end coordinate system, the visual coordinate system and the second optical target set includes:

[0079] Determining a homogeneous transformation matrix based on the robot base coordinate system, the robot end coordinate system, and the second optical target set;

[0080] The target joint motion model is determined based on the homogeneous transformation matrix and a pre-constructed preliminary joint motion model.

[0081] Specifically, a robot base coordinate system is constructed based on the center of the robot base of the surgical robot and is recorded as {R}, a connector is installed at the center of the robot base, and a plurality of spherical second optical targets are fixed on the connector; the distance from each second optical target to the origin of the robot base coordinate system is determined based on the length information of the connecting branch of the connector, and the three-dimensional coordinate point set of each second optical target in the robot base coordinate system is recorded as R P, based on the midpoint of the optical center line between the binocular cameras of the optical locator as the origin, the visual coordinate system is constructed and recorded as {C}, and the position information of each second optical target ball in the visual coordinate system is obtained to obtain the three-dimensional coordinate point set C P, through the objective function pre-constructed based on the rigid transformation principle, R and t are iteratively solved for nonlinear optimization to obtain the homogeneous transformation matrix between the visual coordinate system and the robot base coordinate system corresponding to the minimum value of the objective function Among them, the above objective function and the determined homogeneous transformation matrix can be as follows:

[0082]

[0083] Among them, R can represent the rotation matrix from the visual coordinate system to the robot base coordinate system, t can represent the translation vector from the visual coordinate system to the robot base coordinate system, R P i To represent the three-dimensional coordinates of the i-th second optical target ball in the visual coordinate system, C P i + can represent the three-dimensional coordinates of the i-th second optical target ball in the robot base coordinate system, Can represent homogeneous transformation matrices.

[0084] Optionally, determining the target joint motion model based on the homogeneous transformation matrix and a pre-constructed preliminary joint motion model includes:

[0085] Determine a plurality of sets of preset joint parameters corresponding to the preliminary joint motion model, and determine an intermediate joint motion model corresponding to the preliminary joint motion model based on the preset joint parameters;

[0086] Control the surgical robot arm to move to each second robot arm position in a preset second robot arm position sequence in sequence, and collect the coded position sequence of the end of the robot arm through an encoder;

[0087] Determine the theoretical position sequence of the encoded position sequence in the robot arm base coordinate system through the preliminary joint motion model;

[0088] Determine the actual position sequence of the encoded position sequence in the robot base coordinate system by using the optical locator and the homogeneous transformation matrix;

[0089] A theoretical-actual error is determined based on the theoretical position sequence and the actual position sequence, and model parameters of the intermediate joint motion model are adjusted based on the theoretical-actual error to obtain the target joint motion model.

[0090] Among them, the preset joint parameters can be understood as model parameters related to the joints of the robotic arm corresponding to the joint motion model.

[0091] The second robot arm position sequence may be a sequence including a plurality of robot arm positions determined based on a preset imaging area of ​​the C-arm and a preset operating space of the surgical robot arm. The second robot arm position sequence may be different from or the same as the first robot arm position sequence.

[0092] The coded position sequence may include multiple coded positions, the coded position is the position of the end of the robotic arm in the second robotic arm configuration, and the coded position can be obtained based on an encoder installed at the end of the robotic arm. The theoretical position sequence can be understood as a position sequence determined by theoretical calculation through a joint motion model. The actual position sequence can be understood as a position sequence determined by actual positioning through the optical locator.

[0093] The theoretical-actual error may be understood as the error between the theoretical position sequence and the actual position sequence.

[0094] Optionally, determining the actual position sequence of the encoded position sequence in the robot base coordinate system by using the optical locator and the homogeneous transformation matrix includes:

[0095] For the second manipulator shape and position sequence, determining the visual position sequence of the second optical target set in the visual coordinate system by the optical locator;

[0096] The actual position sequence of the encoded position sequence in the robot arm base coordinate system is determined based on the homogeneous transformation matrix and the visual position sequence.

[0097] Optionally, determining the intermediate joint motion model corresponding to the preliminary joint motion model based on the preset joint parameters includes:

[0098] For each set of the preset joint parameters, determining the theoretical transformation matrix between the robot arm base coordinate system and the robot arm end coordinate system under the preset joint parameters through the preliminary joint motion model;

[0099] The model parameters of the preliminary joint motion model are adjusted based on the plurality of theoretical transformation matrices to obtain an intermediate joint motion model.

[0100] Specifically, the calculation of the theoretical transformation matrix may be as follows:

[0101] T i i-1 =R x (α i-1 )D x (a i-1 )R z (θ i )D z (d i )

[0102] Among them, T i i-1 = can represent the theoretical transformation matrix; α i-1 , (a i-1 ), θ i), d i Can represent preset joint parameters; R x Can represent the rotation operator around the x-axis; R z Can represent the rotation operator around the z-axis; D x Can represent the translation operator around the X axis; D z It can represent the translation operator around the z-axis.

[0103] S230. When the surgical robot's surgical robot arm is rigidly connected to the C-arm, determine a robot arm base coordinate system constructed based on the robot arm base center of the surgical robot arm and a three-dimensional image coordinate system constructed based on the scanning center of the C-arm.

[0104] S240: Determine a coarse registration matrix between the robot base coordinate system and the three-dimensional image coordinate system.

[0105] S250, determining the target robot arm shape and position of the surgical robot arm, and acquiring a target image through the C-arm.

[0106] S260. Determine a first coordinate set of the first optical target set in the three-dimensional image coordinate system according to the target target information, and determine a second coordinate set of the first optical target set in the robotic arm base coordinate system under the target robotic arm shape and position through a target joint motion model.

[0107] S270. Determine a registration error matrix between the first coordinate set and the second coordinate set through a registration error equation, determine a fine registration matrix according to the registration error matrix and the coarse registration matrix, and perform fine registration on the three-dimensional image coordinate system and the robotic arm base coordinate system based on the fine registration matrix.

[0108] The technical solution of the embodiment of the present invention is to determine a visual coordinate system constructed by the midpoint of the optical center line of the optical locator and the binocular camera based on the optical locator; determine a second optical target set based on a connecting part connected to the center of the robot base, and determine the target joint motion model based on the robot base coordinate system, the robot end coordinate system, the visual coordinate system and the second optical target set. The present invention adopts the visual coordinate system constructed by the midpoint of the optical center line of the binocular camera of the optical locator as an intermediate medium to construct a target joint motion model with the function of calculating the conversion relationship between the robot base coordinate system and the robot end coordinate system, thereby improving the model accuracy of the constructed target joint motion model.

[0109] Based on the above embodiments, Figure 4 It is an overall flow chart of a surgical robot registration method provided according to an embodiment of the present invention. Figure 5is a conversion relationship diagram between coordinate systems provided according to an embodiment of the present invention. In which, {R} represents the robot base coordinate system, {C} represents the visual coordinate system, and {E} represents the robot end coordinate system. Figure 4 and Figure 5 As shown, the overall process of the surgical robot registration method of the present invention is described below. The surgical robot arm of the surgical robot in the present invention can be composed of a robot body and an electrical control system. The surgical robot arm can be a six-degree-of-freedom robot arm including a translation joint and five rotation joints. The surgical robot arm can be rigidly connected to the C-arm. The present invention can directly measure the conversion relationship between the three-dimensional image coordinate system constructed based on the scanning center of the C-arm and the robot base coordinate system constructed based on the robot base center of the surgical robot arm, so as to perform precise registration.

[0110] The optical target in the present invention can be an object that can be recognized by both an optical locator and a C-arm. For example, the optical target can be made of a material with a high CT (Computed tomography) value in the scanning image of the C-arm and the surface of the optical target can be covered with fluorescent powder to facilitate tracking and recognition by the optical locator.

[0111] Specifically, a robot base coordinate system is constructed based on the center of the robot base of the surgical robot and is recorded as {R}, a connector is installed at the center of the robot base, and a plurality of spherical second optical targets are fixed on the connector; the distance from each second optical target to the origin of the robot base coordinate system is determined based on the length information of the connecting branch of the connector, and the three-dimensional coordinate point set of each second optical target in the robot base coordinate system is recorded as R P, based on the midpoint of the optical center line between the binocular cameras of the optical locator as the origin, the visual coordinate system is constructed and recorded as {C}, and the position information of each second optical target ball in the visual coordinate system is obtained to obtain the three-dimensional coordinate point set C P, through the objective function pre-constructed based on the rigid transformation principle, R and t are iteratively solved for nonlinear optimization to obtain the homogeneous transformation matrix between the visual coordinate system and the robot base coordinate system corresponding to the minimum value of the objective function A target robotic arm forward kinematics model (target joint motion model) is established based on the joint motion model.

[0112] According to the joint sequence of the surgical robot arm, the transformation matrix established between each joint coordinate system is right-multiplied in sequence to calculate the transformation matrix of the end of the robot arm in the robot arm base coordinate system:

[0113] The Monte Carlo method is used to traverse the range of values ​​of each joint of the surgical robot arm, and the preset N groups of random joint variables are substituted into the pre-established preliminary joint motion model to obtain the reachable workspace of the surgical robot arm, and the small error value of the kinematic parameters is determined and recorded as δα i-1 ,δa i-1 ,δθ i ,δd i Based on the above error values, the model parameters of the preliminary DH equation are adjusted to obtain and differentiate the geometric parameter error model (the intermediate joint motion model).

[0114] The surgical robot arm is controlled to move to the randomly preset second robot arm position in sequence, the coded position sequence of the surgical robot arm joint is recorded, and the theoretical position sequence Q of the end of the robot arm in the robot arm base coordinate system is calculated according to the established preliminary joint motion model. R , use the optical locator to track the first optical target installed at the end of the robotic arm, and calculate the visual position sequence Q of the end of the robotic arm in the visual coordinate system C , using the homogeneous transformation matrix between the robot base coordinate system and the visual coordinate system The actual position sequence that the end of the robot arm actually reaches in the robot arm base coordinate system can be determined based on the following formula:

[0115]

[0116] in, = can represent the actual position of the end of the robot arm in the robot arm base coordinate system, Q C (It can represent the position of the end of the robot arm in the visual coordinate system, The homogeneous transformation matrix between the robot base coordinate system and the visual coordinate system can be expressed.

[0117] The theoretical actual error between the actual position and the theoretical position can be determined based on the following formula:

[0118]

[0119] Among them, ΔQ can represent the theoretical actual error, It can represent the actual position of the end of the robot arm in the robot arm base coordinate system, Q R The theoretical position of the end of the robot arm in the robot arm base coordinate system can be expressed.

[0120] In order to solve the multiple unknowns in the geometric error model, no less than 200 poses were selected for measurement to construct an overdetermined set of equations, and the approximate solution of the geometric parameter error was obtained. The error parameters were identified using a nonlinear optimization algorithm. The direct compensation method was used to substitute the identified error value into the established error model to calculate the pose deviation. The compensated pose can be obtained by subtracting the pose deviation from the expected pose.

[0121] In the case where the surgical robot arm is rigidly connected to the C-arm, a coarse registration matrix between a three-dimensional image coordinate system constructed based on the scanning center of the C-arm and a robot base coordinate system constructed based on the robot base center of the surgical robot arm is obtained by coarse measurement. However, due to a large number of uncertain factors that cause errors in the coarse measurement process, the accuracy of the coarse registration performed by coarse measurement cannot meet the user's requirements. The coarse registration matrix determined by the coarse measurement can be shown as follows:

[0122]

[0123] in, can represent the coarse registration matrix, It can represent the rough rotation matrix between the 3D image coordinate system and the robot base coordinate system. It can represent the rough translation vector between the 3D image coordinate system and the robot base coordinate system.

[0124] A more accurate transformation matrix between the position image and the robotic arm is obtained by using a joint calibration method. Specifically, a certain number of first robotic arm positions of the surgical robotic arm are randomly generated within the imaging area of ​​the C-arm and the operating space of the surgical robotic arm, and the robotic arm is controlled to move to each first robotic arm position. When the end of the surgical robotic arm moves to the target point, the C-arm is controlled to capture the target image without interfering with the surgical robotic arm, and the captured behavioral position image sequence is filtered and denoised, and the Hough transform method and threshold method are used to extract the center of each first optical target in the position image sequence. A three-dimensional reconstruction algorithm is used for the processed position image sequence to obtain the three-dimensional image coordinate system of the first optical target at the end of the surgical robotic arm and the coordinate value of the center of the sphere of the first optical target in the three-dimensional image coordinate system {I}, which is recorded as I P. The position of the first optical target in the robot base coordinate system {R} is recorded as R P, respectively, the preliminary error equation and objective function can be constructed as follows:

[0125]

[0126]

[0127] in, The registration error matrix can be expressed as can represent the coarse registration matrix, R P can represent the coordinates of the first optical target in the robot base coordinate system, I P may represent the coordinates of the first optical target in the three-dimensional image coordinate system.

[0128] After completing the data collection of multiple groups of shapes and positions, the Jacobian matrix of the objective function with respect to the error parameters is constructed, and the values ​​of the errors Δα, Δβ, Δγ, Δx, Δy, and Δz are obtained through iterative solution, and the precise registration matrix after joint calibration is obtained.

[0129] In the present invention, when the robot arm is fixedly connected to the C-arm, the optical target is used as a medium to complete the coordinate conversion alignment and calibration of the image and the surgical robot arm. There is no need to process and manufacture calibration tooling. The method has a high degree of automation and can effectively reduce errors introduced by human misoperation.

[0130] The overall joint calibration process of the present invention can be completed before the surgical robot is put into practical use. As long as the robotic arm system and the C-arm do not undergo significant deformation, there is no need to recalibrate, which can effectively reduce errors caused by interference from multiple factors during surgery.

[0131] In the present invention, when the surgical operating arm is fixedly connected to the X-ray imaging device, an optical locator is used to calibrate the mechanical arm and accurately align the surgical robot operating object with the mechanical arm.

[0132] In the present invention, when the surgical operating arm is fixedly connected to the X-ray imaging device (which may be a C-arm), an optical locator is used for joint calibration, thereby improving the registration efficiency before the surgical robot is applied.

[0133] The present invention uses a joint calibration method to obtain a more accurate coordinate transformation matrix and improve the solution efficiency of the optimization process.

[0134] Embodiment 3

[0135] Figure 6 This is a schematic diagram of the structure of a surgical robot registration device provided in Embodiment 3 of the present invention. Figure 6 As shown, the device includes: a rigid connection module 310 , a rough conversion module 320 , an image acquisition module 330 , a coordinate set determination module 340 and a fine registration module 350 .

[0136] Among them, the rigid connection module 310 is used to determine the robot base coordinate system constructed based on the robot base center of the surgical robot and the three-dimensional image coordinate system constructed based on the scanning center of the C-arm when the surgical robot's surgical robot is rigidly connected to the C-arm; the coarse conversion module 320 is used to determine the coarse registration matrix between the robot base coordinate system and the three-dimensional image coordinate system; the image acquisition module 330 is used to determine the target robot position of the surgical robot and acquire the target image through the C-arm, wherein the target image includes the first robot arm installed at the end of the surgical robot arm through a connector under the target robot position. A target target information of an optical target set; a coordinate set determination module 340, used to determine a first coordinate set of the first optical target set in the three-dimensional image coordinate system according to the target target information, and determine a second coordinate set of the first optical target set in the robotic arm base coordinate system under the target robotic arm shape and position through a target joint motion model; a fine registration module 350, used to determine a registration error matrix between the first coordinate set and the second coordinate set through a registration error equation, determine a fine registration matrix according to the registration error matrix and the coarse registration matrix, and perform fine registration on the three-dimensional image coordinate system and the robotic arm base coordinate system based on the fine registration matrix.

[0137] The technical solution of the embodiment of the present invention is to determine a robot base coordinate system constructed based on the robot arm base center of the surgical robot and a three-dimensional image coordinate system constructed based on the scanning center of the C-arm when the surgical robot arm is rigidly connected to the C-arm of the surgical robot; determine a coarse registration matrix between the robot base coordinate system and the three-dimensional image coordinate system; determine the target robot arm shape and position of the surgical robot arm, and collect a target image through the C-arm, wherein the target image includes target target information of a first optical target set installed at the robot arm end of the surgical robot arm through a connector under the target robot arm shape and position; according to the The target target information determines the first coordinate set of the first optical target set in the three-dimensional image coordinate system, and the second coordinate set of the first optical target set in the robotic arm base coordinate system under the target robotic arm shape and position is determined by the target joint motion model; the registration error matrix between the first coordinate set and the second coordinate set is determined by the registration error equation, and the fine registration matrix is ​​determined according to the registration error matrix and the coarse registration matrix. The technical scheme of finely aligning the three-dimensional image coordinate system and the robotic arm base coordinate system based on the fine registration matrix realizes the automatic registration of the surgical robot and improves the efficiency and accuracy of the surgical robot registration.

[0138] Wherein, the registration device of the surgical robot further includes: an image sequence acquisition module, an image coordinate recognition module, a model calculation module and an error equation determination module;

[0139] The image sequence acquisition module is used to control the surgical robot arm to move to each first robotic arm position in the preset first robotic arm position sequence in sequence and acquire a position image sequence through the C-arm before determining the registration error matrix between the first coordinate set and the second coordinate set through the registration error equation, wherein the position image includes the first target information of the first optical target set installed at the robotic arm end of the surgical robot arm in the first robotic arm position;

[0140] An image coordinate recognition module, configured to determine an image coordinate set sequence of the first optical target set in the three-dimensional image coordinate system based on the first target information in each of the form image sequences;

[0141] A model calculation module, used for determining a base coordinate set sequence of the first optical target set in the robotic arm base coordinate system under the first robotic arm shape sequence through the target joint motion model;

[0142] The error equation determination module is used to adjust the error parameters of the pre-constructed initial error equation according to the image coordinate set sequence and the base coordinate set sequence to obtain the registration error equation.

[0143] Optionally, the coordinate set determination module is specifically used to:

[0144] Determine a robot arm end coordinate system constructed based on the robot arm end of the surgical robot arm and first connector information of a connector connecting the robot arm end and the first optical target set;

[0145] Determine an end coordinate set of the first optical target set in the end coordinate system of the robot arm based on the first connection piece information;

[0146] The input end coordinate set is transformed through the target joint motion model to obtain a second coordinate set of the first optical target set in the robot arm base coordinate system.

[0147] Optionally, the surgical robot registration device further includes: an optical positioning module and a target model determination module;

[0148] The optical positioning module is used to determine the optical locator and the visual coordinate system constructed based on the midpoint of the optical center line of the binocular camera of the optical locator before the second coordinate set of the first optical target set in the robotic arm base coordinate system under the target joint motion model is determined;

[0149] The target model determination module is used to determine a second optical target set based on a connector connected to the center of the robot base, and to determine the target joint motion model based on the robot base coordinate system, the robot end coordinate system, the visual coordinate system and the second optical target set.

[0150] Optionally, the target model determination module includes: a homogeneous transformation unit and a target model determination unit;

[0151] Wherein, the homogeneous transformation unit is used to determine a homogeneous transformation matrix based on the robot base coordinate system, the robot end coordinate system and the second optical target set;

[0152] The target model determination unit is used to determine the target joint motion model based on the homogeneous transformation matrix and the pre-constructed preliminary joint motion model.

[0153] Optionally, the target model determination unit includes: an intermediate model determination subunit, a coding position acquisition subunit, a theoretical position determination subunit, an actual position determination subunit and a model parameter adjustment subunit;

[0154] Wherein, the intermediate model determination subunit is used to determine a plurality of groups of preset joint parameters corresponding to the preliminary joint motion model, and determine the intermediate joint motion model corresponding to the preliminary joint motion model based on the preset joint parameters;

[0155] A coding position acquisition subunit, used for controlling the surgical robot arm to move to each second robot arm position in a preset second robot arm position sequence in sequence and acquiring the coding position sequence of the end of the robot arm through an encoder;

[0156] A theoretical position determination subunit, used for determining a theoretical position sequence of the encoded position sequence in the robot arm base coordinate system through the preliminary joint motion model;

[0157] An actual position determination subunit, used to determine the actual position sequence of the encoded position sequence in the robot base coordinate system through the optical locator and the homogeneous transformation matrix;

[0158] The model parameter adjustment subunit is used to determine the theoretical actual error based on the theoretical position sequence and the actual position sequence, and adjust the model parameters of the intermediate joint motion model based on the theoretical actual error to obtain the target joint motion model.

[0159] Optionally, the actual position determination subunit is specifically used to:

[0160] For the second manipulator shape and position sequence, determining the visual position sequence of the second optical target set in the visual coordinate system by the optical locator;

[0161] The actual position sequence of the encoded position sequence in the robot arm base coordinate system is determined based on the homogeneous transformation matrix and the visual position sequence.

[0162] Optionally, the intermediate model determines the subunit, specifically for:

[0163] For each set of the preset joint parameters, determining the theoretical transformation matrix between the robot arm base coordinate system and the robot arm end coordinate system under the preset joint parameters through the preliminary joint motion model;

[0164] The model parameters of the preliminary joint motion model are adjusted based on the plurality of theoretical transformation matrices to obtain an intermediate joint motion model.

[0165] The surgical robot registration device provided in the embodiment of the present invention can execute the surgical robot registration method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0166] Embodiment 4

[0167] Figure 7 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0168] like Figure 7 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0169] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0170] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a coordinate system precision registration method for a surgical robot.

[0171] In some embodiments, the coordinate system precision registration method of the surgical robot can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the coordinate system precision registration method of the surgical robot described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to execute the coordinate system precision registration method of the surgical robot by any other appropriate means (for example, by means of firmware).

[0172] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0173] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0174] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0175] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0176] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0177] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0178] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0179] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A surgical robot registration method, characterized in that: include: In the case where a surgical robot arm of the surgical robot is rigidly connected to a C-arm, determining a robot arm base coordinate system constructed based on a robot arm base center of the surgical robot arm and a three-dimensional image coordinate system constructed based on a scanning center of the C-arm; Determine a coarse registration matrix between the robot base coordinate system and the three-dimensional image coordinate system; Determine the target manipulator shape and position of the surgical manipulator, and collect a target image through the C-arm, wherein the target image includes target target information of a first optical target set installed at the manipulator end of the surgical manipulator through a connector under the target manipulator shape and position; Determine a first coordinate set of the first optical target set in the three-dimensional image coordinate system according to the target target information, and determine a second coordinate set of the first optical target set in the robotic arm base coordinate system under the target robotic arm shape and position through a target joint motion model; A registration error matrix between the first coordinate set and the second coordinate set is determined by a registration error equation, a fine registration matrix is ​​determined according to the registration error matrix and the coarse registration matrix, and the three-dimensional image coordinate system and the robot arm base coordinate system are finely registered based on the fine registration matrix.

2. The method according to claim 1, characterized in that Before determining the registration error matrix between the first coordinate set and the second coordinate set by the registration error equation, the method further includes: Controlling the surgical robot arm to move to each first robot arm position in a preset first robot arm position sequence in sequence and collecting a position image sequence through the C-arm, wherein the position image includes first target information of a first optical target set installed at a robot arm end of the surgical robot arm in the first robot arm position; Determine a sequence of image coordinate sets of the first optical target set in the three-dimensional image coordinate system based on the first target information in each of the form images in the form image sequence; Determine, by means of the target joint motion model, a base coordinate set sequence of the first optical target set in the base coordinate system of the robotic arm under the shape and position sequence of the first robotic arm; The error parameters of the pre-constructed initial error equation are adjusted according to the image coordinate set sequence and the base coordinate set sequence to obtain a registration error equation.

3. The method according to claim 1, characterized in that The second coordinate set of the first optical target set in the robot arm base coordinate system under the target robot arm shape and position determined by the target joint motion model includes: Determine a robot arm end coordinate system constructed based on the robot arm end of the surgical robot arm and first connector information of a connector connecting the robot arm end and the first optical target set; Determine an end coordinate set of the first optical target set in the end coordinate system of the robot arm based on the first connection piece information; The input end coordinate set is transformed through the target joint motion model to obtain a second coordinate set of the first optical target set in the robot arm base coordinate system.

4. The method according to claim 1, characterized in that: Before determining the second coordinate set of the first optical target set in the robot arm base coordinate system under the target joint motion model of the target robot arm shape and position, the method further includes: Determine an optical locator and a visual coordinate system constructed based on the midpoint of a line connecting optical centers of binocular cameras of the optical locator; A second optical target set is determined based on a connector connected to the center of the robot base, and the target joint motion model is determined based on the robot base coordinate system, the robot end coordinate system, the visual coordinate system and the second optical target set.

5. The method according to claim 4, characterized in that The determining the target joint motion model based on the manipulator base coordinate system, the manipulator end coordinate system, the visual coordinate system and the second optical target set includes: Determining a homogeneous transformation matrix based on the robot base coordinate system, the robot end coordinate system, and the second optical target set; The target joint motion model is determined based on the homogeneous transformation matrix and a pre-constructed preliminary joint motion model.

6. The method according to claim 5, characterized in that The step of determining the target joint motion model based on the homogeneous transformation matrix and the pre-constructed preliminary joint motion model comprises: Determine a plurality of sets of preset joint parameters corresponding to the preliminary joint motion model, and determine an intermediate joint motion model corresponding to the preliminary joint motion model based on the preset joint parameters; Control the surgical robot arm to move to each second robot arm position in a preset second robot arm position sequence in sequence, and collect the coded position sequence of the end of the robot arm through an encoder; Determine the theoretical position sequence of the encoded position sequence in the robot arm base coordinate system through the preliminary joint motion model; Determine the actual position sequence of the encoded position sequence in the robot base coordinate system by using the optical locator and the homogeneous transformation matrix; A theoretical-actual error is determined based on the theoretical position sequence and the actual position sequence, and model parameters of the intermediate joint motion model are adjusted based on the theoretical-actual error to obtain the target joint motion model.

7. The method according to claim 6, characterized in that The determining the actual position sequence of the encoded position sequence in the robot base coordinate system by using the optical locator and the homogeneous transformation matrix comprises: For the second manipulator shape and position sequence, determining the visual position sequence of the second optical target set in the visual coordinate system by the optical locator; The actual position sequence of the encoded position sequence in the robot arm base coordinate system is determined based on the homogeneous transformation matrix and the visual position sequence.

8. The method according to claim 6, characterized in that The determining of the intermediate joint motion model corresponding to the preliminary joint motion model based on the preset joint parameters includes: For each set of the preset joint parameters, determining the theoretical transformation matrix between the robot arm base coordinate system and the robot arm end coordinate system under the preset joint parameters through the preliminary joint motion model; The model parameters of the preliminary joint motion model are adjusted based on the plurality of theoretical transformation matrices to obtain an intermediate joint motion model.

9. A surgical robot registration device, characterized in that: include: A rigid connection module, used to determine a robot base coordinate system constructed based on the robot base center of the surgical robot and a three-dimensional image coordinate system constructed based on the scanning center of the C-arm when the surgical robot is rigidly connected to the C-arm of the surgical robot; A coarse conversion module, used to determine a coarse registration matrix between the robot base coordinate system and the three-dimensional image coordinate system; An image acquisition module, used to determine the target robot arm shape and position of the surgical robot arm, and to acquire a target image through the C-arm, wherein the target image includes target target information of a first optical target set installed at the robot arm end of the surgical robot arm through a connector under the target robot arm shape and position; A coordinate set determination module, used to determine a first coordinate set of the first optical target set in the three-dimensional image coordinate system according to the target target information, and to determine a second coordinate set of the first optical target set in the robotic arm base coordinate system under the target robotic arm shape and position through a target joint motion model; A fine registration module is used to determine a registration error matrix between the first coordinate set and the second coordinate set through a registration error equation, determine a fine registration matrix according to the registration error matrix and the coarse registration matrix, and perform fine registration on the three-dimensional image coordinate system and the robot base coordinate system based on the fine registration matrix.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the surgical robot registration method according to any one of claims 1 to 8 when executed.

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