CN114376726A

CN114376726A - Path planning method and related device for transcranial magnetic stimulation navigation process

Info

Publication number: CN114376726A
Application number: CN202210118146.0A
Authority: CN
Inventors: 秦伟; 曹霞霞; 孙金铂; 龙戈农; 崔亚朋
Original assignee: Xi'an Keyue Medical Co ltd
Current assignee: Xi'an Keyue Medical Technology Co ltd
Priority date: 2022-02-08
Filing date: 2022-02-08
Publication date: 2022-04-22
Anticipated expiration: 2042-02-08
Also published as: CN114376726B

Abstract

The method and the device are suitable for the technical field of medical treatment, provide a path planning method and a related device for a transcranial magnetic stimulation navigation process, and enrich the technical scheme of path planning in the transcranial magnetic stimulation navigation process. The method mainly comprises the following steps: determining the initial position point coordinates of the tool center point of the mechanical arm and the target magnetic stimulation point coordinates of the head of the patient; arranging a geometric envelope box for wrapping all magnetic stimulation point coordinates of the head of the patient on the head of the patient; projecting the target magnetic stimulation point coordinates to the surface of the geometric envelope box to obtain target mapping point coordinates of the target magnetic stimulation point coordinates; calculating a first section of path of the tool center point of the mechanical arm moving from the initial position point coordinate to the target mapping point coordinate by using an artificial potential field method; calculating a second section of path of the tool center point of the mechanical arm moving from the target mapping point coordinate to the target magnetic stimulation point coordinate by utilizing a mechanical arm inverse kinematics solving algorithm; and connecting the first section of path and the second section of path in sequence to obtain a planned path of the mechanical arm.

Description

Path planning method and related device for transcranial magnetic stimulation navigation process

Technical Field

The application belongs to the technical field of medical treatment, and particularly relates to a path planning method and a related device in a transcranial magnetic stimulation navigation process.

Background

The Transcranial Magnetic Stimulation (TMS) technology is a non-invasive, non-clear side effect neural regulation technology, and its basic principle is: the pulse magnetic field acts on the central nervous system (mainly cerebral cortex), and induced current generated by the pulse magnetic field can change the membrane potential of cortical nerve cells, thereby influencing metabolic activity and neural activity in the brain. The stimulation modes of the existing transcranial magnetic stimulation technology are mainly as follows: three stimulation modes of single pulse, double pulse and repetitive pulse. Single and double pulse stimulation modes are commonly used in conventional electrophysiological examinations. The repetitive pulse pattern can be applied to the treatment of dyskinesia diseases, mental diseases, pathological pain, epilepsy, addiction, functional recovery after the nervous system is damaged, and the like.

In the using process of the transcranial magnetic stimulation technology, a magnetic stimulation executing mechanism for treating the head of a patient is generally a mechanical arm, and the free end of the mechanical arm carries a magnetic stimulation coil to reach the head of the patient to be treated according to the guidance of a planned path. However, the prior art is less suitable for the technical scheme of mechanical arm path planning of the transcranial magnetic stimulation navigation process.

Disclosure of Invention

The application aims to provide a path planning method and a related device in a transcranial magnetic stimulation navigation process, and enriches the technical scheme of path planning in the conventional transcranial magnetic stimulation navigation process.

In a first aspect, the present application provides a path planning method for a transcranial magnetic stimulation navigation process, applied to a mechanical arm, including:

determining the initial position point coordinates of the tool center point of the mechanical arm and the target magnetic stimulation point coordinates of the head of the patient;

setting a geometry enveloping box for the head of the patient, wherein the geometry enveloping box envelops all magnetic stimulation point coordinates of the head of the patient;

projecting the target magnetic stimulation point coordinate to the surface of the geometric envelope box to obtain a target mapping point coordinate of the target magnetic stimulation point coordinate on the surface of the geometric envelope box;

calculating a first section of path for the tool center point of the mechanical arm to move from the initial position point coordinate to the target mapping point coordinate by using an artificial potential field method;

calculating a second section of path for the tool center point of the mechanical arm to move from the target mapping point coordinate to the target magnetic stimulation point coordinate by using a mechanical arm inverse kinematics solution algorithm;

and connecting the first section of path and the second section of path in sequence to obtain a planned path of the mechanical arm.

Optionally, the providing a geometry envelope box for the head of the patient includes:

and performing cubic bounding calculation on the head of the patient by using a bounding box algorithm to obtain a cubic envelope box of the head of the patient.

Optionally, the projecting the target magnetic stimulation point coordinate to the surface of the geometric envelope box to obtain the target mapping point coordinate of the target magnetic stimulation point coordinate on the surface of the geometric envelope box includes:

calculating the coordinates of the center point of the cubic envelope box;

taking the center point coordinates of the cubic envelope box as the head center point coordinates of the patient head;

connecting the coordinates of the head central point and the coordinates of the target magnetic stimulation point to obtain a straight line L, wherein the straight line L intersects the cube enveloping box at two intersection points;

and taking one of the two intersection points close to the target magnetic stimulation point coordinate as the target mapping point coordinate of the target magnetic stimulation point coordinate on the surface of the geometric envelope box.

Optionally, the calculating, by using an artificial potential field method, a first segment of a path along which the tool center point of the mechanical arm moves from the initial position point coordinate to the target mapping point coordinate includes:

determining a current mechanical arm pose of the mechanical arm;

calculating the predicted mechanical arm positions corresponding to k joints of the mechanical arm when the k joints rotate at the angle of lambda, 0 degree and lambda respectively, wherein the predicted mechanical arm positions correspond to 3^kA combination of predicted joint angles, wherein lambda is any value from 0 to 360;

calculating the sum potential energy of the tool center points of each predicted mechanical arm pose to obtain 3^kSeed and potential energy;

from said 3^kSelecting a predicted mechanical arm pose with the minimum sum potential energy from the sum potential energies to serve as a target mechanical arm pose for the next movement of the mechanical arm;

judging whether the coordinate corresponding to the tool center point of the pose of the target mechanical arm is equal to the coordinate of the target mapping point or not;

if the coordinates corresponding to the tool center points of the target mechanical arm poses are equal to the coordinates of the target mapping points, connecting the initial position point coordinates with the coordinates corresponding to the tool center points of all the target mechanical arm poses to obtain the first section of path;

and if the coordinate corresponding to the tool center point of the target mechanical arm pose is not equal to the coordinate of the target mapping point, taking the target mechanical arm pose as the current mechanical arm pose, and triggering and executing the steps of calculating the predicted mechanical arm poses corresponding to the k joints of the mechanical arm when the k joints rotate at-lambda degrees, 0 degrees and lambda degrees respectively.

Optionally, before calculating the sum potential of the tool center points of each predicted pose of the robot arm, the method further comprises:

performing collision detection on the predicted mechanical arm pose, and determining m joint angle combinations with which the predicted mechanical arm pose cannot collide, wherein m is greater than 0 and less than or equal to 3^kA positive integer of (d);

the calculation of each predicted pose of the robot armThe sum potential of the tool center points is 3^kThe hybrid energy and potential energy comprises:

and calculating the sum potential energy of the tool center points of the m types of predicted mechanical arm poses to obtain m types of sum potential energy.

Optionally, the performing collision detection on the predicted pose of the mechanical arm and determining m joint angle combinations at which the pose of the mechanical arm does not collide includes:

judging whether the model data of the mechanical arm for predicting the pose of each mechanical arm is intersected with the geometry enveloping box or not;

if the intersection exists, eliminating a collision joint angle combination corresponding to the predicted mechanical arm pose with the intersection of the geometry envelope box;

if no intersection exists, summarizing all joint angle combinations corresponding to the predicted mechanical arm poses without intersection, and obtaining m joint angle combinations with which the measured mechanical arm poses cannot collide.

Optionally, the model data of the mechanical arm includes coil model data of the magnetic stimulation coil, the magnetic stimulation coil is installed at the tail end of the mechanical arm in an adaptive manner, the tool center point of the mechanical arm is located on the surface of the free end of the magnetic stimulation coil, and the coordinate value of the tool center point of the mechanical arm is equal to the coordinate value of the center point coordinate of the free end of the mechanical arm plus the coordinate value corresponding to the thickness value of the magnetic stimulation coil.

Optionally, the calculating the sum potential of the tool center points of each predicted pose of the mechanical arm includes:

establishing a repulsive force field of the geometry envelope box and a gravitational force field of the target mapping point;

calculating the repulsive potential energy of the tool center point of each predicted mechanical arm pose in the repulsive field;

calculating the gravitational potential energy of the tool center point of each predicted mechanical arm pose in the gravitational field;

and comprehensively calculating the repulsive potential energy and the gravitational potential energy and the potential energy applied to the tool center point of each predicted mechanical arm pose.

In a second aspect, the present application provides a path planning system for a transcranial magnetic stimulation navigation process, applied to a robotic arm, comprising:

the determination unit is used for determining the initial position point coordinates of the tool center point of the mechanical arm and the target magnetic stimulation point coordinates of the head of the patient;

the setting unit is used for setting a geometry envelope box for the head of the patient, and the geometry envelope box wraps all the magnetic stimulation point coordinates of the head of the patient;

the mapping unit is used for projecting the target magnetic stimulation point coordinate to the surface of the geometric envelope box to obtain a target mapping point coordinate of the target magnetic stimulation point coordinate on the surface of the geometric envelope box;

the calculation unit is used for calculating a first section of path of the tool center point of the mechanical arm moving from the initial position point coordinate to the target mapping point coordinate by using an artificial potential field method;

the calculation unit is further used for calculating a second section of path for the tool center point of the mechanical arm to move from the target mapping point coordinate to the target magnetic stimulation point coordinate by utilizing a mechanical arm inverse kinematics solution algorithm;

and the connecting unit is used for connecting the first section of path and the second section of path in sequence to obtain a planned path of the mechanical arm.

Optionally, when the setting unit sets the geometry envelope box on the head of the patient, the setting unit specifically includes:

Optionally, when the mapping unit projects the target magnetic stimulation point coordinate to the surface of the geometric envelope box to obtain a target mapping point coordinate of the target magnetic stimulation point coordinate on the surface of the geometric envelope box, the mapping unit is specifically configured to:

calculating the coordinates of the center point of the cubic envelope box;

Optionally, when the calculation unit calculates, by using an artificial potential field method, a first path along which the tool center point of the mechanical arm moves from the initial position point coordinate to the target mapping point coordinate, the calculation unit is specifically configured to:

determining a current mechanical arm pose of the mechanical arm;

Optionally, the system further includes:

a detection unit for performing collision detection on the predicted pose of the mechanical arm and determining m joint angle combinations at which the pose of the mechanical arm cannot collide, wherein m is greater than 0 and less than or equal to 3^kA positive integer of (d);

the computing unit computes the sum potential energy of the tool center points of each predicted mechanical arm pose to obtain 3^kIn the process of seed and potential energy, the method is specifically used for:

Optionally, the detecting unit performs collision detection on the predicted pose of the mechanical arm, and when determining that m joint angle combinations at which the pose of the mechanical arm does not collide are determined, is specifically configured to:

Optionally, when the computing unit calculates the sum potential energy of the tool center point of each predicted pose of the mechanical arm, the computing unit is specifically configured to:

In a third aspect, the present application provides a computer device comprising:

the system comprises a processor, a memory, a bus, an input/output interface and a network interface;

the processor is connected with the memory, the input/output interface and the network interface through a bus;

the memory stores a program;

the processor, when executing the program stored in the memory, implements the path planning method for the transcranial magnetic stimulation navigation process of the first aspect.

In a fourth aspect, the present application provides a computer-readable storage medium having instructions stored therein, which when executed on a computer, cause the computer to perform a path planning method for a transcranial magnetic stimulation navigation procedure as described in the first aspect above.

In a fifth aspect, the present application provides a computer program product which, when executed on a computer, causes the computer to perform a path planning method for a transcranial magnetic stimulation navigation procedure as described in the previous first aspect.

According to the technical scheme, the embodiment of the application has the following advantages:

the method comprises the steps of determining an initial position point coordinate of a tool center point of a mechanical arm and a target magnetic stimulation point coordinate of the head of a patient; then arranging a geometry enveloping box for the head of the patient, wherein the geometry enveloping box envelops all the magnetic stimulation point coordinates of the head of the patient; projecting the target magnetic stimulation point coordinate to the surface of the geometric envelope box to obtain a target mapping point coordinate of the target magnetic stimulation point coordinate on the surface of the geometric envelope box; calculating a first section of path of the tool center point of the mechanical arm moving from the initial position point coordinate to the target mapping point coordinate by using an artificial potential field method; calculating a second section of path for the tool center point of the mechanical arm to move from the target mapping point coordinate to the target laser point coordinate by using a mechanical arm inverse kinematics solution algorithm; and then connecting the first section of path with the second section of path in sequence to obtain a planned path of the mechanical arm. Therefore, when the magnetic stimulation center point of the magnetic stimulation coil is located at the tool center point of the mechanical arm, the mechanical arm can direct the tool center point of the mechanical arm to move from the initial position point coordinate to the target magnetic stimulation point coordinate according to the planned path, and the path planning navigation of the mechanical arm in the transcranial magnetic stimulation navigation process is realized.

Drawings

FIG. 1 is a schematic flow chart illustrating an embodiment of a path planning method for a transcranial magnetic stimulation navigation process according to the present application;

FIG. 2 is a schematic flow chart illustrating another embodiment of the path planning method for a transcranial magnetic stimulation navigation process according to the present application;

FIG. 3 is a schematic flow chart illustrating another embodiment of the path planning method for a transcranial magnetic stimulation navigation process according to the present application;

FIG. 4 is a schematic structural diagram of an embodiment of a path planning system for a transcranial magnetic stimulation navigation process according to the present application;

FIG. 5 is a schematic structural diagram of an embodiment of a computer apparatus of the present application;

FIG. 6 is a diagram illustrating the effect of one embodiment of the cubic envelope box set on the head model of a patient according to the present application;

FIG. 7 is a schematic view of an embodiment of a six-axis robotic arm of the present application;

fig. 8 is a diagram illustrating the effect of the tool center point of the six-axis robotic arm of the present application interfering with the coordinates of the target magnetic stimulation point on the head of the patient.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

It can be understood that the path planning method for the transcranial magnetic stimulation navigation process is established on the premise that the three-dimensional coordinate set of the patient head model is known in the spatial coordinate system of the mechanical arm, and a relatively mature prior art scheme is already used for mapping and registering the patient head model in the spatial coordinate system of the mechanical arm, and is not described herein any more. For example, a head model of a patient is created in advance, the head of the patient is visually positioned through a binocular vision camera, the position and the posture of the head of the patient in a coordinate system of the binocular vision camera are known, and then the position and the posture of the head model of the patient in the coordinate system of the binocular vision camera can be mapped to a space coordinate system of a mechanical arm according to the coordinate system conversion relation between the coordinate system of the binocular vision camera and the space coordinate system of the mechanical arm, so that the position and the posture of the head of the patient can be known in the space coordinate system of the mechanical arm.

Referring to fig. 1, an embodiment of the path planning method for a transcranial magnetic stimulation navigation process of the present application is applied to a mechanical arm, and includes:

101. and determining the initial position point coordinates of the tool center point of the mechanical arm and the target magnetic stimulation point coordinates of the head of the patient.

In this step, the initial position point coordinates of the tool center point of the mechanical arm need to be determined so as to obtain the starting point of the path planning technical scheme of the transcranial magnetic stimulation navigation process of the present application, for example, the initial position point coordinates may be the coordinate point of the tool center point of the mechanical arm in the spatial coordinate system of the mechanical arm when the mechanical arm is started, and the tool center point of the mechanical arm generally automatically returns to the known origin point of the mechanical arm when the mechanical arm is started. The Tool center Point of the robot arm generally refers to The Center Point (TCP) of the Tool (e.g. magnetic stimulation coil) installed at the end of the robot arm.

This step also requires determining the target magnetic stimulation point coordinates of the patient's head in order to know the end point of the path planning technical solution of the transcranial magnetic stimulation navigation process of the present application, for example, the target magnetic stimulation point coordinates may be the coordinate points selected by the operator on the patient's head model, and the target magnetic stimulation point coordinates correspond to the corresponding magnetic stimulation treatment points on the patient's head lying within the range of motion of the robotic arm in reality.

102. And arranging a geometry enveloping box for the head of the patient, wherein the geometry enveloping box envelops all the magnetic stimulation point coordinates of the head of the patient.

On the premise that the three-dimensional coordinate set of the patient head model is known in the spatial coordinate system of the mechanical arm, the geometric enveloping box can be arranged on the head (model) of the patient in the step, so that the geometric enveloping box wraps all the magnetic stimulation point coordinates of the head of the patient. Specifically, a bounding box algorithm is used to perform a cubic bounding calculation on the patient head, resulting in a cubic envelope box for the patient head, as shown in fig. 6.

103. And projecting the target magnetic stimulation point coordinates to the surface of the geometric envelope box to obtain target mapping point coordinates of the target magnetic stimulation point coordinates on the surface of the geometric envelope box.

Since the geometric envelope box for wrapping all the magnetic stimulation point coordinates of the head of the patient is set on the head of the patient in step 102, the target magnetic stimulation point coordinates can be projected onto the surface of the geometric envelope box in this step, so as to obtain the target mapping point coordinates of the target magnetic stimulation point coordinates on the surface of the geometric envelope box.

For example, referring to FIG. 6, assume the target magnetic stimulus point coordinate G (x)_g，y_g，z_g) On the forehead of the patient head model, this step may first calculate the center point coordinate O (x) of the cubic envelope box_o，y_o，z_o) Coordinate O (x) of center point of cubic envelope box_o，y_o，z_o) As head center point coordinates of the patient's head; connecting the coordinates of the central point of the head part with the coordinates G (x) of the target magnetic stimulation point_g，y_g，z_g) Obtaining a straight line L, wherein the straight line L intersects the cubic envelope box at two intersection points, and then a point J (x) close to the coordinates of the target magnetic stimulation point is selected from the two intersection points_j，y_j，z_j) Target mapping point coordinate J (x) on the surface of geometric envelope box as target magnetic stimulation point coordinate_j，y_j，z_j)。

104. And calculating a first section of path for the tool center point of the mechanical arm to move from the initial position point coordinate to the target mapping point coordinate by using an artificial potential field method.

In this step, a process of calculating a first path of the tool center point of the mechanical arm moving from the initial position point coordinate to the target mapping point coordinate is implemented by using an artificial potential field method, which is specifically referred to in the embodiment of fig. 2. It should be noted that, in the actual application process, the specific parameters of the artificial potential field method may be adjusted according to the actual situation in this step, and the specific calculation process of calculating the first segment of path where the tool center point of the mechanical arm moves from the initial position point coordinate to the target mapping point coordinate by using the artificial potential field method is not limited herein.

105. And calculating a second section of path for the tool center point of the mechanical arm to move from the target mapping point coordinate to the target magnetic stimulation point coordinate by using a mechanical arm inverse kinematics solution algorithm.

The so-called inverse kinematics solution algorithm of the mechanical arm is used for calculating the solvability of the mechanical arm moving from an initial point to a target point, namely, the situations of no solution, multiple solutions and the like are considered. That is, for a multi-axis robot, if a target point is within an reachable range of a robot arm, a plurality of solutions may exist for the joint angle combinations of each joint motion when the robot arm moves from an initial point to the target point; if the target point is out of the reachable range of the mechanical arm, the mechanical arm cannot reach the target point out of the reachable range by changing the joint angle combination of each joint motion of the mechanical arm, and no solution exists at the moment.

For example, referring to FIG. 7, for a typical six-axis robot arm, the first three joints (base joint 710, shoulder joint 720, elbow joint 730) are larger, and the last three joints (wrist 1 joint 740, wrist 2 joint 750, wrist 3 joint 760) are smaller. Different weights are generally given to different joints when defining the distance in a space coordinate system where the mechanical arm is located, for example, the first three joints are set with large weights, and the last three joints are set with small weights. Then moving the smaller joint rather than the larger joint may be prioritized in selecting a solution. When there is an obstacle, if the motion path of the "closest" solution collides with it, another solution with a longer motion distance ("fault" solution) is selected. Therefore, when considering problems of collision, path planning and the like, all possible solutions need to be calculated, and then an optimal solution is calculated according to the preset weight.

Assuming that when the tool center point of the mechanical arm moves from the target mapping point coordinate to the target magnetic stimulation point coordinate in the step, 8 sets of solutions are obtained after reverse kinematics solution of the mechanical arm is performed in a 6-axis mechanical arm, a reverse kinematics solution algorithm of the mechanical arm is a mature prior art, a calculation process is not described here, and the following table 1 is referred to in combination:

TABLE 1

The numerical position units in table 1 are radians (-2 pi represents one rotation in reverse, and 2 pi represents one rotation in positive), the numerical value is positive and represents the radian of the corresponding numerical value required for the joint to rotate in the preset positive direction, and the numerical value is negative and represents the radian of the corresponding numerical value required for the joint to rotate in the preset negative direction (opposite to the preset positive direction). As can be seen from the table, for the 6-axis robot, there are 8 solutions for the tool center point of the mechanical arm moving from the target mapping point coordinate to the target magnetic stimulation point coordinate, that is, the tool center point of the mechanical arm can be moved from the target mapping point coordinate to the target magnetic stimulation point by correspondingly executing the rotation of 8 different joint angle combinations; this step can then be given different weights in conjunction with different joints, for example: p is equal to base joint × a + shoulder joint × b + elbow joint × c + wrist 1 joint × d + wrist 2 joint × e + wrist 3 joint × f, where P represents a converted equivalent radian of a certain group of solutions, a represents a preset weight of the base joint, b represents a preset weight of the shoulder joint, c represents a preset weight of the elbow joint, d represents a preset weight of the wrist 1 joint, e represents a preset weight of the wrist 2 joint, and f represents a preset weight of the wrist 3 joint; the numerical values of all joints of the mechanical arm in the formula are calculated by taking absolute values, and preferably, a > b > c > d > e > f, so that when a plurality of solutions exist, a joint angle combination with a smaller converted equivalent radian is preferentially considered when the solutions are selected, rather than a joint angle combination with a larger converted equivalent radian, a group of most economical and energy-saving target solutions can be screened out, and the target solutions enable a path of a tool center point (see the center point of a magnetic stimulation coil 770 in fig. 7) of the mechanical arm to move from a target mapping point coordinate to a target magnetic stimulation point coordinate to be a second path.

106. And connecting the first section of path and the second section of path in sequence to obtain a planned path of the mechanical arm.

A first section of path of the tool center point of the mechanical arm moving from the initial position point coordinate to the target mapping point coordinate is obtained in step 104, and a second section of path from the target mapping point coordinate to the target magnetic stimulation point coordinate is obtained in step 105, so that the first section of path and the second section of path can be connected in sequence in this step to obtain a planned path of the mechanical arm.

Referring to fig. 8, when the magnetic stimulation center point of the magnetic stimulation coil is located at the tool center point of the mechanical arm, the mechanical arm may direct the tool center point of the mechanical arm to move from the initial position point coordinate to the target magnetic stimulation point coordinate according to the planned path, so as to implement the execution of the planned path of the mechanical arm during the transcranial magnetic stimulation navigation process.

Referring to fig. 2, the process of calculating the first segment of the path for the tool center point of the robot arm to move from the initial position point coordinate to the target mapping point coordinate in step 104 in the embodiment of fig. 1 by using the artificial potential field method may specifically include:

201. and determining the current mechanical arm pose of the mechanical arm.

Specifically, in this step, the current pose of the mechanical arm can be determined by acquiring the current angular position of each joint of the mechanical arm at the current time, the coordinates of the tool center point, the model data of the mechanical arm, and the like.

For example, assuming that the robot arm is a 6-axis robot arm, this step acquires the current angular position a (θ) of the robot arm₁，θ₂，θ₃，θ₄，θ₅，θ₆) And tool center point coordinates of 6-axis robotic arm, where θ₁、θ₂、θ₃、θ₄、θ₅、θ₆Respectively representing joint angles of a base joint, a shoulder joint, an elbow joint, a wrist 1, a wrist 2 and a wrist 3, and similarly obtaining model data of the 6-axis mechanical arm so as to obtain the size, the position and the posture of the space occupied by the whole 6-axis mechanical arm; and obtaining the current mechanical arm posture of the mechanical arm corresponding to the space position by combining the current angle position of all joints of the mechanical arm, the coordinates of the central point of the tool and the model data of the mechanical arm. The model data of the mechanical arm comprises coil model data of a magnetic stimulation coil, the magnetic stimulation coil is installed at the tail end of the mechanical arm in a matched mode, the tool center point of the mechanical arm is located on the surface of the free end of the magnetic stimulation coil, and the coordinate value of the tool center point of the mechanical arm is equal to the coordinate value of the center point of the free end of the mechanical arm plus the coordinate value corresponding to the thickness value of the magnetic stimulation coil. In another embodiment, the model data of the mechanical arm in this step can be simply equivalent to a specific link structure between every two adjacent joints, each link is a cylinder with a preset radius, and the commonly used "8" -shaped magnetic stimulation coil is equivalent to two cylinders.

202. And calculating the corresponding predicted mechanical arm positions of k joints of the mechanical arm when the k joints rotate at the angle of-lambda, 0 degree and lambda respectively, wherein the predicted mechanical arm positions correspond to a plurality of predicted joint angle combinations, and lambda is any value from 0 to 360.

Under the condition that the current pose of the mechanical arm corresponding to the mechanical arm is obtained in step 201, the corresponding predicted poses of the mechanical arm when-lambda degrees, 0 degrees and lambda degrees are respectively added to all joints of the predicted mechanical arm can be calculated and predicted by the step on the basis of the current pose of the mechanical arm, and lambda can be any value from 0 to 360, so that the predicted pose of the mechanical arm at the next moving position of the mechanical arm can be obtained in the step, and the joint angle combinations of various poses of the mechanical arm at the next moving position of the mechanical arm in the reachable range can be obtained. For example, λ is preferably 5, and considering only k joint rotations in the robot arm, the predicted robot arm pose of the robot arm at the next movement position corresponds to 3^kThe predicted joint angle combination is that each joint of k joints in the mechanical arm rotates for 5 degrees at most (or does not rotate)) To obtain different joint angle combinations 3^kThe mechanical arm takes the joint rotation precision as 5 degrees as a moving step length, the smaller the numerical value of lambda is, the higher the precision of each movement of the mechanical arm is, but the longer the planning calculation time is, the more the practical application can be chosen according to the practical requirements, and in the step, each joint of the mechanical arm rotates once at most in one predicted mechanical arm pose.

203. And performing collision detection on all predicted mechanical arm poses, and determining m joint angle combinations with which the predicted mechanical arm poses cannot collide.

This step may also perform collision detection on each predicted robot arm pose in step 202 to determine m joint angle combinations where the predicted robot arm pose does not collide, where m is greater than 0 and less than or equal to 3^kThe positive integer of the sum potential energy is used for avoiding the execution of the predicted mechanical arm position and posture corresponding to the joint angle combination which is selected by the mechanical arm and is likely to collide in the subsequent steps, avoiding the head of the patient from being accidentally injured by the mechanical arm, and reducing the workload of calculation of the sum potential energy in the subsequent steps by eliminating the joint angle combination which is likely to collide. The mode of collision detection on the predicted mechanical arm pose is various, and can be selected according to the actual situation in practical application, and the mode of collision detection on the predicted mechanical arm pose is not limited. In particular, please refer to the embodiment of fig. 3 for how to perform collision detection on the predicted pose of the mechanical arm.

204. And calculating the sum potential energy of the tool center points of the m types of predicted mechanical arm poses to obtain m types of sum potential energy.

Specifically, the geometric enveloping boxes except the target mapping point are set as the barriers, and the tool center point of the mechanical arm needs to avoid contact with the barriers, so that the repulsive force field of the geometric enveloping boxes needs to be established in the step, and according to the repulsive force potential energy formula:

wherein, U_rep(q) represents repulsive potential energy, η represents repulsive scale factor, d₀Indicating a disorderThe influence distance of the object, that is, when the distance between the tool center point of the mechanical arm and the obstacle is greater than the influence distance of the obstacle, the repulsive force potential energy received by the tool center point of the mechanical arm is 0.

And the target mapping point is used as the coordinate of the target mapping point which needs to be reached by the tool center point of the mechanical arm, so the step needs to establish the gravitational field of the target mapping point, and according to the gravitational potential energy formula:

wherein U is_att(q) denotes gravitational potential energy, S denotes gravitational scale factor, d (q, q)_goal) And the distance between the initial position point coordinate of the mechanical arm and the target mapping point coordinate is represented.

And according to a potential energy formula:

U_sum(q)＝U_att(q)+U_rep(q)

wherein U is_sum(q) represents gravitational potential energy U_att(q) and repulsive force potential energy U_rep(q) the sum of (q).

And calculating the repulsive potential energy of the tool center point of each predicted mechanical arm pose in the step 202 in the repulsive force field by using the repulsive force potential energy formula, calculating the attractive potential energy of the tool center point of each predicted mechanical arm pose in the step 202 in the attractive force field by using the attractive force potential energy formula, and comprehensively calculating the repulsive force potential energy and the attractive force potential energy sum potential energy of the tool center point of each predicted mechanical arm pose to obtain a plurality of kinds of sum potential energies. When m predicted joint angle combinations correspond to the predicted mechanical arm poses, m sum potential energies are obtained in the step.

205. And selecting the predicted mechanical arm pose with the minimum sum potential energy from the m sum potential energies as the target mechanical arm pose for the next movement of the mechanical arm.

The magnitude values of the m sum potential energies obtained in the step 204 can reflect the energy-saving degree of the m predicted joint angle combinations when the mechanical arm is executed, and the larger the sum potential energy is, the larger the relative energy consumption is, so that the predicted mechanical arm pose with the minimum sum potential energy is selected from the m sum potential energies in the step and used as the target mechanical arm pose for the next movement of the mechanical arm, and the method is more energy-saving and environment-friendly.

206. Judging whether the corresponding coordinate of the tool center point of the target mechanical arm pose is equal to the target mapping point coordinate or not, and if the corresponding coordinate of the tool center point of the target mechanical arm pose is equal to the target mapping point coordinate, executing the step 207; if the corresponding coordinates of the tool center point of the pose of the target robot arm are not equal to the coordinates of the target mapping point, go to step 208.

After the target mechanical arm pose is obtained in step 205, it is necessary to determine whether the coordinate corresponding to the tool center point of the target mechanical arm pose obtained in step 205 is equal to the target mapping point coordinate, because the coordinate corresponding to the tool center point of the target mechanical arm pose moved at each step of the mechanical arm is close to the target mapping point coordinate under the potential energy action of step 203, the movement can be suspended when the coordinate corresponding to the tool center point of the target mechanical arm pose is equal to the target mapping point coordinate, which indicates that the tool center point of the mechanical arm has completed moving from the initial position point coordinate to the target mapping point coordinate; and when the coordinate corresponding to the tool center point of the pose of the target mechanical arm is not equal to the coordinate of the target mapping point, the tool center point needs to move continuously, which indicates that the tool center point of the mechanical arm does not move from the initial position point coordinate to the coordinate of the target mapping point.

207. And connecting the initial position point coordinates with coordinates corresponding to all tool center points of the pose of the target mechanical arm to obtain a first section of path.

When it is determined in step 206 that the coordinate corresponding to the tool center point of the target robot arm pose is equal to the target mapping point coordinate, indicating that the tool center point of the robot arm has completed moving from the initial position point coordinate to the target mapping point coordinate, this step connects the initial position point coordinate with the coordinate(s) corresponding to all the tool center points of the target robot arm pose, to obtain the first segment of path.

208. And regarding the pose of the target mechanical arm as the pose of the current mechanical arm.

When it is determined in step 206 that the coordinate corresponding to the tool center point of the pose of the target mechanical arm is not equal to the coordinate of the target mapping point, it indicates that the tool center point of the mechanical arm has not completed moving from the initial position point coordinate to the coordinate of the target mapping point, in this step, in order to continue moving, the pose of the target mechanical arm is regarded as the current pose of the mechanical arm, and step 202 is triggered and executed, so that the next step of moving and planning of the mechanical arm is continued.

Therefore, in the embodiment, the potential energy minimum principle is utilized to screen out the most economical and energy-saving target mechanical arm pose in each step of movement, the joint angle combination of the target mechanical arm pose is called as the optimal joint angle combination, so that the tool center point of the mechanical arm moves to the target mapping point coordinate from the initial position point coordinate step by step in the optimal joint angle combination mode, and the planning execution of the first section of path is completed in an energy-saving and efficient manner.

Referring to fig. 3, the process of calculating the first segment of the path from the initial position point coordinate to the target mapping point coordinate of the tool center point of the robot arm by using the artificial potential field method in step 204 in the embodiment of fig. 2 may specifically include:

301. judging whether the model data of each mechanical arm for predicting the pose of the mechanical arm is intersected with the geometric occlusion box, and executing the step 302 if the model data of the mechanical arm for predicting the pose of the mechanical arm is intersected with the geometric occlusion box; if the model data of the mechanical arm for predicting the pose of the mechanical arm does not have an intersection with the geometry envelope box, step 303 is executed.

Specifically, it is determined whether the model data of each of the mechanical arms predicting the pose of the mechanical arm in step 202 intersects with the geometry envelope box to determine whether the mechanical arm collides with the geometry envelope box (the head of the patient), and if the model data of the mechanical arms predicting the pose of the mechanical arm does not intersect with the geometry envelope box, it indicates that the joint angle combinations corresponding to the poses of the mechanical arms can be executed; if the model data of the mechanical arm for predicting the pose of the mechanical arm is intersected with the geometry envelope box, the fact that the joint angle combinations corresponding to the pose of the mechanical arm cannot be executed is indicated, risks exist, and collision joint angle combinations corresponding to the predicted pose of the mechanical arm intersected with the geometry envelope box should be eliminated. In another embodiment, the step judges whether the distance from the point on the equivalent connecting rod of the mechanical arm to the geometric enveloping box (cubic enveloping box) is greater than the radius of the equivalent cylinder of the mechanical arm, if not, collision occurs; if so, no collision occurs.

302. And eliminating collision joint angle combinations corresponding to the predicted mechanical arm poses with intersections of the geometry envelope boxes.

If it is determined in step 301 that intersection exists between model data of the mechanical arm predicting the pose of the mechanical arm and the geometry enveloping box, joint angle combinations corresponding to dangerous mechanical arm poses that cannot be executed are removed, only the joint angle combinations corresponding to the mechanical arm poses that can be executed in step 301 are collected and summarized in subsequent steps, and joint angle combinations where the mechanical arm does not collide with the head of a patient are obtained, so that the pose of the target mechanical arm at each step of the first section of path in the embodiment needs to be selected and executed from the joint angle combinations where collision does not occur.

303. And summarizing all joint angle combinations corresponding to the predicted mechanical arm poses without intersection to obtain m joint angle combinations with which the mechanical arm poses cannot collide.

If it is determined in step 301 that there is no intersection between the model data of the mechanical arm predicting the pose of the mechanical arm and the geometry enveloping box, it is indicated that all the joint angle combinations corresponding to the predicted pose of the mechanical arm are joint angle combinations that will not collide, and the joint angle combinations corresponding to the pose of the mechanical arm in step 301 are collected and summarized to obtain m joint angle combinations where the mechanical arm will not collide with the head of the patient, so that each step of the target pose of the mechanical arm in the first segment of the path in the above embodiment needs to be selectively executed in the joint angle combinations that will not collide.

The foregoing embodiment describes a path planning method for a transcranial magnetic stimulation navigation process of the present application, and the following describes a path planning system for a transcranial magnetic stimulation navigation process of the present application, referring to fig. 4, an embodiment of the path planning system for a transcranial magnetic stimulation navigation process is applied to a mechanical arm, and includes:

a determining unit 401, configured to determine an initial position point coordinate of a tool center point of the mechanical arm and a target magnetic stimulation point coordinate of a head of a patient;

a setting unit 402, configured to set a geometry envelope box for the head of the patient, where the geometry envelope box encloses all magnetic stimulation point coordinates of the head of the patient;

a mapping unit 403, configured to project the target magnetic stimulation point coordinate to the surface of the geometric envelope box, so as to obtain a target mapping point coordinate of the target magnetic stimulation point coordinate on the surface of the geometric envelope box;

a calculating unit 404, configured to calculate a first segment of a path along which the tool center point of the mechanical arm moves from the initial position point coordinate to the target mapping point coordinate by using an artificial potential field method;

the calculating unit 404 is further configured to calculate a second path along which the tool center point of the mechanical arm moves from the target mapping point coordinate to the target magnetic stimulation point coordinate by using a mechanical arm inverse kinematics solution algorithm;

and a connection unit 405, configured to connect the first section of path and the second section of path in order to obtain a planned path of the mechanical arm.

Optionally, when the setting unit 402 sets the geometry envelope box on the head of the patient, the setting unit specifically includes:

Optionally, when the mapping unit 403 projects the target magnetic stimulation point coordinate to the surface of the geometric envelope box to obtain a target mapping point coordinate of the target magnetic stimulation point coordinate on the surface of the geometric envelope box, the mapping unit is specifically configured to:

calculating the coordinates of the center point of the cubic envelope box;

Optionally, when the calculation unit 404 calculates, by using an artificial potential field method, a first segment of path along which the tool center point of the mechanical arm moves from the initial position point coordinate to the target mapping point coordinate, the calculation unit is specifically configured to:

determining a current mechanical arm pose of the mechanical arm;

Optionally, the system further includes:

a detection unit 406 for performing collision detection on the predicted pose of the mechanical armDetermining m joint angle combinations with which the pose of the mechanical arm cannot collide, wherein m is greater than 0 and less than or equal to 3^kA positive integer of (d);

Optionally, when the detecting unit 406 performs collision detection on the predicted pose of the mechanical arm and determines that m joint angle combinations at which the pose of the mechanical arm does not collide are determined, the detecting unit is specifically configured to:

Optionally, when the calculating unit 404 calculates the sum potential of the tool center point of each predicted pose of the mechanical arm, the calculating unit is specifically configured to:

The operation performed by the path planning system in the transcranial magnetic stimulation navigation process according to the embodiment of the present application is similar to the operation performed in the embodiments of fig. 1, fig. 2, and fig. 3, and is not repeated herein.

Referring to fig. 5, a computer device according to an embodiment of the present application is described below, where an embodiment of the computer device according to the present application includes:

the computer device 500 may include one or more processors (CPUs) 501 and a memory 502, where the memory 502 stores one or more applications or data. Wherein the memory 502 is volatile storage or persistent storage. The program stored in memory 502 may include one or more modules, each of which may include a sequence of instructions operating on a computer device. Still further, the processor 501 may be arranged in communication with the memory 502 to execute a series of instruction operations in the memory 502 on the computer device 500. The computer device 500 may also include one or more network interfaces 503, one or more input-output interfaces 504, and/or one or more operating systems, such as Windows Server, Mac OS, Unix, Linux, FreeBSD, etc. The processor 501 may perform the operations performed in the embodiments shown in fig. 1 to fig. 3, which are not described herein again.

In the several embodiments provided in the embodiments of the present application, it should be understood by those skilled in the art that the disclosed system, apparatus and method can be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the unit is only one logical functional division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method of the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and the like.

The above description is only exemplary of the present application and should not be taken as limiting the present application, as any modification, equivalent replacement or improvement made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A path planning method for a transcranial magnetic stimulation navigation process is applied to a mechanical arm and comprises the following steps:

2. The path planning method according to claim 1, wherein the setting of the geometry envelope box for the head of the patient comprises:

3. The path planning method according to claim 2, wherein the projecting the target magnetic stimulation point coordinate to the surface of the geometric envelope box to obtain a target mapping point coordinate of the target magnetic stimulation point coordinate on the surface of the geometric envelope box comprises:

calculating the coordinates of the center point of the cubic envelope box;

4. The path planning method according to claim 1, wherein the calculating a first segment of the path for the tool center point of the robot arm to move from the initial position point coordinates to the target mapping point coordinates by using an artificial potential field method comprises:

determining a current mechanical arm pose of the mechanical arm;

5. The path planning method according to claim 4, wherein before calculating the sum potential of the tool center points of each predicted pose of the robot arm, the method further comprises:

performing collision detection on the predicted mechanical arm pose, and determining m joint angle combinations with which the mechanical arm pose cannot collide, wherein m is more than 0 and less than or equal to 3^kA positive integer of (d);

calculating the sum potential energy of the tool center points of each predicted mechanical arm pose to obtain 3^kThe hybrid energy and potential energy comprises:

6. The path planning method according to claim 5, wherein the performing collision detection on the predicted pose of the robot arm and determining m joint angle combinations at which the pose of the robot arm does not collide comprises:

7. The path planning method according to claim 6, wherein the model data of the robot arm includes coil model data of a magnetic stimulation coil, the magnetic stimulation coil is mounted at the end of the robot arm in a fitting manner, a tool center point of the robot arm is located on a free end surface of the magnetic stimulation coil, and a coordinate value of the tool center point of the robot arm is equal to a coordinate value corresponding to a sum of a coordinate value of the free end center point of the robot arm and a thickness value of the magnetic stimulation coil.

8. The path planning method according to claim 4, wherein the calculating the sum potential of the tool center points of each predicted robot arm pose comprises:

9. A path planning system for a transcranial magnetic stimulation navigation process is applied to a mechanical arm and comprises:

10. A computer device, comprising:

the memory stores a program;

the processor, when executing the program stored in the memory, implements a path planning method for a transcranial magnetic stimulation navigation procedure as recited in any one of claims 1-8.