Puncture path planning method and system based on optimization strategy and needle tip retraction strategy

Abstract

The present invention relates to the field of medical puncture technology, and specifically to a puncture path planning method and system based on an optimization strategy and a needle tip retraction strategy, comprising the following steps: kinematic analysis of the puncture needle to construct a kinematic model of the puncture needle puncture path; based on the kinematic model of the puncture needle puncture path, a multi-objective function for puncture needle puncture path planning is constructed; based on the multi-objective function, the kinematic model of the puncture needle puncture path for puncturing multiple target points is optimized and solved by using an optimization algorithm combined with a needle tip retraction needle insertion strategy, to obtain the optimal puncture needle puncture path for puncturing each target point one by one. The present invention performs puncture path planning by means of an optimization strategy, establishes constraints between multiple objectives, and controls the constraint direction by setting weights, so that the optimization direction is controllable, and thus the effect of path planning is controllable, thereby achieving the optimization of path planning.

Description

Technical Field

[0001] The present invention relates to the field of medical control technology, and in particular to a puncture path planning method and system based on an optimization strategy and a needle tip retraction strategy. Background Art

[0002] With the rapid development of minimally invasive surgery, puncture has been widely used in clinical practice as a minimally invasive surgery, which can complete tasks such as biopsy, brachytherapy, drug delivery and targeted therapy.

[0003] Currently, the most widely used puncture surgeries basically require doctors to hold the puncture instrument and perform the puncture operation along the pre-operatively planned puncture path with the assistance of medical imaging equipment. The existing technology uses a single goal for planning the pre-operative puncture path, such as the shortest path goal. The single goal lacks constraints and only pursues the optimization of a single goal during planning. When the single goal is optimized to the extreme, the planned path will be unable to avoid obstacles and cannot accurately reach the target point, which ultimately leads to invalid planning.

[0004] However, when the existing technology uses multiple objectives for planning, although constraints between multiple objectives are established, the direction of the constraints cannot be controlled, and the constraints between multiple objectives are allowed to be random, resulting in the disadvantage of uncontrollable optimization objectives, and ultimately causing the defect of uncontrollable path planning effects. Therefore, it is difficult to achieve the optimization of path planning. Summary of the invention

[0005] The purpose of the present invention is to provide a puncture path planning method and system based on optimization strategy and needle tip retraction strategy, so as to solve the technical problem in the prior art that it is difficult to control the multi-objective optimization direction to achieve the optimization of path planning.

[0006] In order to solve the above technical problems, the present invention specifically provides the following technical solutions:

[0007] The puncture path planning method based on the optimization strategy and the needle tip retraction strategy includes the following steps:

[0008] Performing kinematic analysis on the puncture needle, constructing a kinematic model of the puncture needle for puncture path planning of the puncture needle, and constructing a kinematic model of the puncture path of the puncture needle;

[0009] Based on the kinematic model of the puncture needle puncture path, a multi-objective function for puncture needle puncture path planning is constructed;

[0010] Based on the multi-objective function, the kinematic model of the puncture needle puncture path for puncturing multiple target points is optimized and solved by using an optimization algorithm combined with a needle tip retraction strategy, so as to obtain the optimized puncture needle puncture path for puncturing each target point one by one.

[0011] As a preferred embodiment of the present invention, the method for constructing the kinematic model of the puncture needle includes:

[0012] Set the forward speed of the puncture needle to v The angular velocity of the puncture needle is ω, and the coordinate system of the puncture needle is Ψ p , the puncture needle is in the world coordinate system Ψ g The position and posture of g =[x,y,z,α,β,γ] T , where α, β, and γ are the distances of the puncture needle around the world coordinate system Ψ g The rotation angle of the x, y, and z axes;

[0013] In the world coordinate system Ψ g In the experiment, the speed of the puncture needle is determined as V g =x g & ; In the needle body coordinate system Ψ p In the experiment, the velocity of the puncture needle is determined as V p = v V1+wV2, where V1=[001k00] T , V2=[000001] T ; Based on the world coordinate system Ψ g and the needle body coordinate system Ψ p , the velocity conversion equation of the puncture needle is: V p =QV g , where , P T gp is the world coordinate system Ψ g and the needle body coordinate system Ψ p The rotation matrix of the puncture needle establishes the world coordinate system Ψ g and the needle body coordinate system Ψ p The speed transformation relationship between Ω is the matrix coefficient of the Euler kinematics equation for rigid body fixed-point motion, which establishes the world coordinate system Ψ g and the needle body coordinate system Ψ p The angular velocity transformation relationship between them;

[0014] According to V g =x g & 、Vp= v V1+wV2 and V p =QV g , the kinematic model of the puncture needle is determined as: ;

[0015] The time factor in the puncture needle kinematic model is separated to eliminate the puncture speed and rotation speed in the control quantity of the puncture needle motion model, and retain the needle insertion distance s and rotation angle ,get As a preferred embodiment of the present invention, the method for constructing the kinematic model of the puncture path of the puncture needle includes:

[0016] Kinematic model of puncture needle Applying the stop-and-turn strategy, the control sequence of the puncture needle puncture path is obtained as Y=((s1,q1),(s2,q2),L,(s n ,q n )), where s1, s2 and s n are the lengths of the first, second and nth segments of the puncture path of the puncture needle, q1, q2 and q n are the rotation angles at the 1st, 2nd and nth segments of the puncture path of the puncture needle respectively;

[0017] The control sequence based on the puncture path of the puncture needle is Y=((s1,q1),(s2,q2),L,(s n ,q n )), and the needle tip of the puncture needle moves along a standard arc along a fixed radius r, and the puncture needle puncture path is determined to be composed of n arc paths {s i | i ∈[1,n]}, s i The first i The length of the segment path, and ,in, For i The corresponding arc, r is the movement radius of the needle tip; the control sequence of the puncture needle puncture path is converted from the needle insertion distance s and the rotation angle q to the coordinates of the center of the path and the coordinates and length of the starting point of each path segment to obtain the kinematic model of the puncture needle puncture path Q={(λ i ,λ i c, O i ,s i )| i ∈[1,n]}, where λ i For the i The starting coordinates of the segment path, λ i c is the i Segment path starting point coordinates λ i The tangent vector at O i For the i The center coordinates of the segment path arc;

[0018] Among them, λ i ,λ i c, O i ,si The relationship between is:

[0019] l i+1 =l i coss i +(1-coss i ) i +rλ i csins i ;

[0020] O i+1 =2l i+1 -O i ;

[0021] λ i+1 c=(1-coss i ) i+1 +l i+1 coss i -l i ; In the formula, λ i+1 For the i +1 The starting point coordinates of the path, λ i+1 c is the i +1 path starting point coordinates λ i+1 The tangent vector at O i+1 For the i +1 The center coordinates of the arc of the path segment.

[0022] As a preferred solution of the present invention, the method for constructing the multi-objective function includes: determining the total path length, path deviation and whether the needle tip encounters an obstacle as multiple optimization objectives of the puncture needle puncture path;

[0023] Determine a multi-objective function for puncture needle puncture path planning based on the kinematic model of the puncture needle puncture path and multiple optimization objectives;

[0024] The multi-objective function is:

[0025] Y=k1Y tip (Q)+k2Y s (Q)+Y d (Q);

[0026] Y tip (Q)=|P tip (Q)-P d |;

[0027] Y s (Q)= ;

[0028] Y d (Q)= ;

[0029] ; In the formula, Y is the multi-objective function value, k1 is the weight of the path deviation, k2 is the weight of the total path length, and Y tip (θ) is the error function between the target point and the needle tip of the puncture needle, P tip (Θ) is the coordinate of the end point of the puncture path determined by Θ, P d is the coordinate of the target point, Y s (Θ) is the path length function, s i It is the first i The length of the segment path, Y d (Θ) is the function to determine whether the needle tip collides with an obstacle, m is the number of obstacles, and y j (d) is the collision function of the jth obstacle, d is the safe distance between the obstacle and the needle tip of the puncture needle, when the needle tip collides with the obstacle, y j (d) The value is +∞, otherwise y j (d) value is zero;

[0030] Among them, k1 and k2 are dynamic functions related to the number of iterations of the optimization algorithm, which are used to dynamically balance the optimization objectives of the total path length and path deviation in the multi-objective function; ; In the formula, , k i (t) is k i The weight at iteration t, H i (t-1) is k i The degree of convergence at the t-1th iteration, G i (t-1) is k i The fitness value at the t-1th iteration, G i (t-2) is k i The fitness value at the t-2th iteration, N=2, N is the number of optimization targets for the total path length and path deviation, T is the total number of iterations of the optimization algorithm, i , j , t are all counting variables; the calculation function of the fitness value is:

[0031] G1(t)=|Y tip (Q(t))-Y tip (Q(t-1))|;

[0032] G2(t)=|Y s (Q(t))-Y s (Q(t-1))|; where G1(t) is the fitness value of k1 at the tth iteration, G2(t) is the fitness value of k2 at the tth iteration, and Y tip (Q(t)) and Ytip (Q(t-1)) are the path deviations at the t-th and t-1-th iterations, respectively, and Y s (Q(t)) and Y s (Q(t-1)) are the total lengths of the paths at the tth and t-1th iterations, respectively.

[0033] As a preferred embodiment of the present invention, a method for planning an optimized puncture needle puncture path for puncturing each target point one by one includes: sorting each target point from large to small according to the coordinate value in the z-axis direction to obtain a path planning sequence of the target points;

[0034] Using an optimization algorithm based on a multi-objective function to plan the puncture path of the first target point in the path planning sequence of the target points, the puncture path of the puncture needle is obtained;

[0035] After the initial path planning of the puncture needle is completed, the optimization algorithm will be used to perform a new planning operation on the second target point based on the multi-objective function starting from the end point of the initial path of the puncture needle.

[0036] If the puncture path to the second target point cannot be planned at the end point of the initial puncture path of the puncture needle, the puncture needle tip starts to retreat to the position where the needle stopped and turned last on the current path, and the puncture path is planned for the second target point again, and so on, until the path to the second target point is successfully planned;

[0037] If the path planning for the second target point cannot be successfully performed until the puncture needle tip retracts to the needle insertion point, a failure prompt will be given.

[0038] As a preferred solution of the present invention, the constraints for optimizing and solving the kinematic model of the puncture path of the puncture needle by the optimization algorithm include:

[0039] The total length of the optimal puncture path is less than or equal to the total length of the puncture needle;

[0040] The arc curvature of each segment of the optimal puncture path is less than or equal to the maximum bending curvature of the puncture needle stiffness.

[0041] As a preferred solution of the present invention, the starting point of the puncture needle puncture path planning is the needle entry point, wherein the needle entry point, target point and obstacle position information are obtained by obtaining puncture environment information labels through medical imaging equipment.

[0042] As a preferred embodiment of the present invention, the present invention provides a puncture path planning system based on an optimization strategy and a needle tip retraction strategy, which is applied to the puncture path planning method based on the optimization strategy and the needle tip retraction strategy, and the system comprises:

[0043] A data acquisition unit is used to obtain puncture environment information and mark the entry and exit points, target points and obstacle position information in the medical imaging device;

[0044] A data processing unit, used for performing kinematic analysis on the puncture needle, constructing a kinematic model of the puncture needle for planning the puncture path of the puncture needle, and constructing a kinematic model of the puncture path of the puncture needle;

[0045] Based on the kinematic model of the puncture needle puncture path, a multi-objective function for puncture needle puncture path planning is constructed;

[0046] The path planning unit is used to optimize and solve the kinematic model of the puncture needle puncture path for puncturing multiple target points based on a multi-objective function by using an optimization algorithm combined with a needle tip retraction and insertion strategy, so as to obtain the optimized puncture needle puncture path for puncturing each target point one by one.

[0047] As a preferred solution of the present invention, the method for constructing the kinematic model of the puncture path of the puncture needle by the data processing unit includes:

[0048] Kinematic model of puncture needle Applying the stop-and-turn strategy, the control sequence of the puncture needle puncture path is obtained as Y=((s1,q1),(s2,q2),L,(s n ,q n )), where s1, s2 and s n are the lengths of the first, second and nth segments of the puncture path of the puncture needle, q1, q2 and q n are the rotation angles of the 1st, 2nd and nth segments of the puncture path of the puncture needle respectively; the control sequence based on the puncture path of the puncture needle is Y=((s1,q1),(s2,q2),L,(s n ,q n )), and the needle tip of the puncture needle moves along a standard arc along a fixed radius r, and the puncture needle puncture path is determined to be composed of n arc paths {s i | i ∈[1,n]}, s i The first i The length of the segment path, and ,in, For i The corresponding arc, r is the movement radius of the needle tip; the control sequence of the puncture needle puncture path is converted from the needle insertion distance s and the rotation angle q to the coordinates of the center of the path and the coordinates and length of the starting point of each path segment to obtain the kinematic model of the puncture needle puncture path Q={(λ i ,λ i c, O i ,s i )|i ∈[1,n]}, where λ i For the i The starting coordinates of the segment path, λ i c is the i Segment path starting point coordinates λ i The tangent vector at O i For the i The center coordinates of the segment path arc;

[0049] Among them, λ i ,λ i c, O i ,s i The relationship between is:

[0050] l i+1 =l i coss i +(1-coss i ) i +rλ i csins i ;

[0051] O i+1 =2l i+1 -O i ;

[0052] λ i+1 c=(1-coss i ) i+1 +l i+1 coss i -l i ; In the formula, λ i+1 For the i +1 The starting point coordinates of the path, λ i+1 c is the i +1 path starting point coordinates λ i+1 The tangent vector at O i+1 For the i +1 The center coordinates of the arc of the path. As a preferred solution of the present invention, the method for constructing the multi-objective function by the path planning unit includes:

[0053] Determining the total path length, path deviation, and whether the needle tip encounters an obstacle as multiple optimization targets of the puncture needle puncture path;

[0054] Determine a multi-objective function for puncture needle puncture path planning based on the kinematic model of the puncture needle puncture path and multiple optimization objectives;

[0055] The multi-objective function is:

[0056] Y=k1Y tip (Q)+k2Ys (Q)+Y d (Q);

[0057] Y tip (Q)=|P tip (Q)-P d |;

[0058] Y s (Q)= ;

[0059] Y d (Q)= ;

[0060] ; In the formula, Y is the multi-objective function value, k1 is the weight of the path deviation, k2 is the weight of the total path length, and Y tip (θ) is the error function between the target point and the needle tip of the puncture needle, P tip (Θ) is the coordinate of the end point of the puncture path determined by Θ, P d is the coordinate of the target point, Y s (Θ) is the path length function, s i It is the first i The length of the segment path, Y d (Θ) is the function to determine whether the needle tip collides with an obstacle, m is the number of obstacles, and y j (d) is the collision function of the jth obstacle, d is the safe distance between the obstacle and the needle tip of the puncture needle, when the needle tip collides with the obstacle, y j (d) The value is +∞, otherwise y j (d) value is zero;

[0061] Among them, k1 and k2 are dynamic functions related to the number of iterations of the optimization algorithm, which are used to dynamically balance the optimization objectives of the total path length and path deviation in the multi-objective function; ; In the formula, , , k i (t) is k i The weight at iteration t, H i (t-1) is k i The degree of convergence at the t-1th iteration, G i (t-1) is k i The fitness value at the t-1th iteration, G i (t-2) is k i The fitness value at the t-2th iteration, N=2, N is the number of optimization targets for the total path length and path deviation, T is the total number of iterations of the optimization algorithm, i , j ,t All are count variables;

[0062] The calculation function of the fitness value is:

[0063] G1(t)=|Y tip (Q(t))-Y tip (Q(t-1))|;

[0064] G2(t)=|Y s (Q(t))-Y s (Q(t-1))|; where G1(t) is the fitness value of k1 at the tth iteration, G2(t) is the fitness value of k2 at the tth iteration, and Y tip (Q(t)) and Y tip (Q(t-1)) are the path deviations at the t-th and t-1-th iterations, respectively, and Y s (Q(t)) and Y s (Q(t-1)) are the total path lengths at the t-th and t-1-th iterations, respectively. Compared with the prior art, the present invention has the following beneficial effects:

[0065] The present invention performs puncture path planning by means of multi-objective optimization, establishes constraints among multiple objectives, and controls the constraint direction by setting weights, so that the optimization direction is controllable, and thus the effect of path planning is controllable, thereby achieving the optimization of path planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the implementation methods or the description of the prior art. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0067] Figure 1 A flow chart of a puncture path planning method based on an optimization strategy and a needle tip retraction strategy provided in an embodiment of the present invention;

[0068] Figure 2 A block diagram of a puncture path planning system based on an optimization strategy and a needle tip retraction strategy provided in an embodiment of the present invention;

[0069] Figure 3 A schematic diagram of a kinematic model of a puncture needle provided in an embodiment of the present invention;

[0070] Figure 4 A schematic diagram of a kinematic model of a puncture needle puncture path provided in an embodiment of the present invention;

[0071] Figure 5A schematic diagram of needle tip retraction provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0072] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions 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 are within the scope of protection of the present invention.

[0073] like Figure 1 As shown, the present invention provides a puncture path planning method based on an optimization strategy and a needle tip retraction strategy, comprising the following steps:

[0074] Performing kinematic analysis on the puncture needle, constructing a kinematic model of the puncture needle for puncture path planning of the puncture needle, and constructing a kinematic model of the puncture path of the puncture needle;

[0075] Based on the kinematic model of the puncture needle puncture path, a multi-objective function for puncture needle puncture path planning was constructed;

[0076] Based on the multi-objective function, the kinematic model of the puncture needle path for puncturing multiple target points is optimized and solved by using the optimization algorithm combined with the needle tip retraction strategy, and the optimal puncture needle path for puncturing each target point one by one is obtained.

[0077] In order to achieve the optimization of puncture needle path planning, the present invention establishes a multi-objective function of puncture path planning that is adapted to the kinematic model of the puncture needle and the puncture path. The multiple optimization objectives include the total path length, the path deviation, and whether the needle tip encounters an obstacle. The three optimization objectives have constraint properties. For example, the shorter the total path length, the more problems such as being unable to avoid obstacles and being unable to accurately reach the target point will be caused, that is, the greater the path deviation, the more obstacles will be touched. Conversely, avoiding obstacles and accurately reaching the target point will increase the total path length. Therefore, the constraint properties of each optimization objective can be used to improve the effect of path planning, so that the planned path takes into account the characteristics of total length, deviation, and obstacle avoidance.

[0078] Furthermore, in order to control the constraint direction and make the optimization direction controllable, the present invention adjusts the optimization direction through weights during the process of path planning using the optimization algorithm, monitors the optimization degrees of the two optimization objectives, the total path length and the path deviation, and adjusts the optimization direction according to the optimization degree, so that in the optimization operation process of the entire path planning solution, the balance of the two optimization objectives, the total path length and the path deviation, is always maintained to avoid optimization imbalance, that is, the emphasis on the optimization objectives. For example, if the optimization degree of the total path length is higher than the optimization degree of the path deviation, the optimization objective of the total path length will occupy the calculation attention of the optimization algorithm, so that the optimization algorithm tends to optimize the total path length. Therefore, the puncture path planned in this unbalanced manner cannot achieve the optimization of each optimization objective.

[0079] The present invention superimposes weights on the optimization target, and the weights are dynamic functions related to the number of iterations, which are used to dynamically balance the optimization targets of the total path length and path deviation in the multi-objective function, that is, the weights are related to the optimization degree of the optimization target. In the optimization algorithm, the optimization degree is characterized by the convergence degree. The faster the convergence, the higher the optimization degree. Therefore, the present invention superimposes weights on the optimization target, and assigns low weights to the optimization target with faster convergence and higher optimization degree to lower its convergence speed or optimization degree, and regulates the optimization direction toward another optimization target to avoid the optimization algorithm from entering the local optimum, and assigns high weights to the optimization target with slower convergence and lower optimization degree to speed up its convergence speed or optimization degree, and regulates the optimization direction toward itself to speed up the algorithm operation speed.

[0080] It can be seen from the above that the present invention regulates the optimization direction, thereby achieving balanced development of the optimization target, making the effect of path planning controllable, and achieving optimization of path planning.

[0081] In order to plan the path of the puncture needle, the kinematics of the puncture needle must be analyzed first. First, assume that the soft tissue being punctured is uniform and the tissue does not deform during the puncture process; when the needle tail is rotated, the bevel direction of the needle tip follows the rotation of the needle tail; the needle body completely follows the movement of the needle tip. After entering the soft tissue, the needle body is fixed by the tissue and does not change position in the radial direction. Based on the above assumptions, when puncturing in the soft tissue, the needle tip moves along an arc with a curvature of k. The arc is determined by the needle tip posture and the direction of the needle tip bevel. The kinematic model of the puncture needle is established as follows: Figure 3 As shown, the method for constructing the kinematic model of the puncture needle includes:

[0082] Set the forward speed of the puncture needle to v The angular velocity of the puncture needle is ω, and the coordinate system of the puncture needle is Ψ p , the puncture needle is in the world coordinate system Ψ g The position and posture of g=[x,y,z,α,β,γ] T , where α, β, and γ are the distances of the puncture needle around the world coordinate system Ψ g The rotation angle of the x, y, and z axes;

[0083] In the world coordinate system Ψ g In the experiment, the velocity of the puncture needle is determined as V g =x g & ; In the needle body coordinate system Ψ p In the experiment, the velocity of the puncture needle is determined as V p = v V1+wV2, where V1=[001k00] T , V2=[000001] T ; Based on the world coordinate system Ψ g and the needle body coordinate system Ψ p , the velocity conversion equation of the puncture needle is: V p =QV g , where , P T gp is the world coordinate system Ψ g and the needle body coordinate system Ψ p The rotation matrix of the puncture needle establishes the world coordinate system Ψ g and the needle body coordinate system Ψ p The speed transformation relationship between Ω is the matrix coefficient of the Euler kinematics equation for rigid body fixed-point motion, which establishes the world coordinate system Ψ g and the needle body coordinate system Ψ p The angular velocity transformation relationship between them;

[0084] According to V g =x g & 、Vp= v V1+wV2 and V p =QV g , the kinematic model of the puncture needle is determined as: ;

[0085] The time factor in the puncture needle kinematic model is separated to eliminate the puncture speed and rotation speed in the control quantity of the puncture needle motion model, and retain the needle insertion distance s and rotation angle ,get .

[0086] The puncture needle model is a nonlinear system and a non-holonomic constraint system, so it is difficult to plan the path directly based on this model. The puncture needle puncture trajectory is independent of the puncture speed and rotation speed, so the time factor can be separated from the control quantity, and only the needle insertion distance s and the rotation angle θ are used as the control quantity. The construction method of the kinematic model of the puncture needle puncture path includes:

[0087] Kinematic model of puncture needle Applying the stop-and-turn strategy, the control sequence of the puncture needle puncture path is obtained as Y=((s1,q1),(s2,q2),L,(s n ,q n )), where s1, s2 and s n are the lengths of the first, second and nth segments of the puncture path of the puncture needle, q1, q2 and q n are the rotation angles at the 1st, 2nd and nth segments of the puncture path of the puncture needle respectively;

[0088] The control sequence based on the puncture path of the puncture needle is Y=((s1,q1),(s2,q2),L,(s n ,q n )), and the needle tip of the puncture needle moves along a standard arc along a fixed radius r, and the puncture needle puncture path is determined to be composed of n arc paths {s i | i ∈[1,n]}, s i The first i The length of the segment path, and ,in, for The corresponding arc, r is the movement radius of the needle tip;

[0089] like Figure 4 As shown in the figure, the control sequence of the puncture needle puncture path is converted from the needle insertion distance s and the rotation angle q to the coordinates of the center of the path and the coordinates and length of the starting point of each path segment, and the kinematic model of the puncture needle puncture path Q={(λ i ,λ i c, O i ,s i )| i ∈[1,n]}, where λ i For the i The starting coordinates of the segment path, λ i c is the i Segment path starting point coordinates λ i The tangent vector at O i For the i The coordinates of the center of the arc of the segment path; where λ i ,λ i c, O i,s i The relationship between is:

[0090] l i+1 =l i coss i +(1-coss i ) i +rλ i csins i ;

[0091] O i+1 =2l i+1 -O i ;

[0092] λ i+1 c=(1-coss i ) i+1 +l i+1 coss i -l i ;

[0093] In the formula, λ i+1 For the i +1 The starting point coordinates of the path, λ i+1 c is the i +1 path starting point coordinates λ i+1 The tangent vector at O i+1 For the i +1 The center coordinates of the arc of the path. The construction method of the multi-objective function includes:

[0094] Determining the total path length, path deviation, and whether the needle tip encounters an obstacle as multiple optimization targets of the puncture needle puncture path;

[0095] According to the kinematic model of the puncture needle puncture path and multiple optimization objectives, a multi-objective function for puncture needle puncture path planning is determined;

[0096] The multi-objective function is:

[0097] Y=k1Y tip (Q)+k2Y s (Q)+Y d (Q);

[0098] Y tip (Q)=|P tip (Q)-P d |;

[0099] Y s (Q)= ;

[0100] Y d (Q)= ;

[0101] ; In the formula, Y is the multi-objective function value, k1 is the weight of the path deviation, k2 is the weight of the total path length, and Y tip (θ) is the error function between the target point and the needle tip of the puncture needle, P tip (Θ) is the coordinate of the end point of the puncture path determined by Θ, P d is the coordinate of the target point, Y s (Θ) is the path length function, s i It is the first i The length of the segment path, Y d (Θ) is the function to determine whether the needle tip collides with an obstacle, m is the number of obstacles, and y j (d) is the collision function of the jth obstacle, d is the safe distance between the obstacle and the needle tip of the puncture needle. When the needle tip collides with the obstacle, y j (d) The value is +∞, otherwise y j (d) The value is zero; where k1 and k2 are dynamic functions related to the number of iterations of the optimization algorithm, which are used to dynamically balance the optimization objectives of the total path length and path deviation in the multi-objective function; ; In the formula, k i (t) is k i The weight at iteration t, H i (t-1) is k i The degree of convergence at the t-1th iteration, G i (t-1) is k i The fitness value at the t-1th iteration, G i (t-2) is k i The fitness value at the t-2th iteration, N=2, N is the number of optimization targets for the total path length and path deviation, T is the total number of iterations of the optimization algorithm, i , j , t All are count variables;

[0102] The calculation function of the fitness value is:

[0103] G1(t)=|Y tip (Q(t))-Y tip (Q(t-1))|;

[0104] G2(t)=|Y s (Q(t))-Y s (Q(t-1))|; where G1(t) is the fitness value of k1 at the tth iteration, G2(t) is the fitness value of k2 at the tth iteration, and Y tip(Q(t)) and Y tip (Q(t-1)) are the path deviations at the t-th and t-1-th iterations, respectively, and Y s (Q(t)) and Y s (Q(t-1)) are the total lengths of the paths at the tth and t-1th iterations, respectively.

[0105] The present invention superimposes weights on the optimization target, and the weights are dynamic functions related to the number of iterations, which are used to dynamically balance the optimization targets of the total path length and path deviation in the multi-objective function, that is, the weights are related to the optimization degree of the optimization target. In the optimization algorithm, the optimization degree is characterized by the convergence degree. The faster the convergence, the higher the optimization degree. Therefore, the present invention superimposes weights on the optimization target, and assigns low weights to the optimization target with faster convergence and higher optimization degree to lower its convergence speed or optimization degree, and regulates the optimization direction toward another optimization target to avoid the optimization algorithm from entering the local optimum, and assigns high weights to the optimization target with slower convergence and lower optimization degree to speed up its convergence speed or optimization degree, and regulates the optimization direction toward itself to speed up the algorithm operation speed.

[0106] When dealing with the problem of multiple target points, the general oblique needle tip puncture needle path planning method needs to re-plan the path from the needle entry point to the target target for each target point. The overall distance of the puncture path planned by this needle entry strategy is relatively long, which will undoubtedly increase the operation time, cause more unnecessary damage to healthy tissues, and also increase the pain of patients. Therefore, the present invention uses the needle tip entry and retraction strategy to plan multiple target points, effectively shortening the operation time and reducing the damage and pain caused to patients. The needle tip retraction strategy plans the optimal puncture needle puncture path for puncturing each target point one by one as follows:

[0107] Sort each target point from large to small according to the coordinate value in the z-axis direction to obtain the path planning sequence of the target points;

[0108] Using an optimization algorithm based on a multi-objective function to plan the puncture path of the first target point in the path planning sequence of the target points, the puncture path of the puncture needle is obtained;

[0109] After the initial path planning of the puncture needle is completed, the optimization algorithm will be used to perform a new planning operation on the second target point based on the multi-objective function starting from the end point of the initial path of the puncture needle.

[0110] If the puncture path to the second target point cannot be planned at the end point of the initial puncture path of the puncture needle, the puncture needle tip starts to retreat to the position where the needle stopped and turned last on the current path, and the puncture path is planned for the second target point again, and so on, until the path to the second target point is successfully planned;

[0111] If the path planning for the second target point cannot be successfully performed until the puncture needle tip retracts to the needle insertion point, a failure prompt will be given.

[0112] like Figure 5 As shown, in process ①, the needle tip retreats along the original trajectory; in process ②, the needle tip rotates a certain angle; in process ③, the needle tip moves forward in other directions.

[0113] The constraints for optimizing the kinematic model of the puncture path of the puncture needle by the optimization algorithm include:

[0114] The total length of the optimal puncture path is less than or equal to the total length of the puncture needle;

[0115] The arc curvature of each segment of the optimal puncture path is less than or equal to the maximum bending curvature of the puncture needle stiffness.

[0116] The optimization algorithm in the present invention can adopt the currently commonly used swarm intelligence search algorithm and particle swarm algorithm for path planning.

[0117] Particle Swarm Optimization (PSO) is an optimization algorithm based on swarm intelligence. The algorithm simulates the foraging behavior of bird flocks and finds the optimal solution to the problem through information sharing and collaboration between particles. The path planning process includes:

[0118] Step 1: Initialization: Randomly generate a group of particles, each with a random position and speed, with each segment of the puncture path (λ i ,λ i c, O i ,s i ), i ∈[1,n] construct particle position X h (t)=[λ h ,λ h c, O h ,s h ] T , and set the particle velocity to V h (t)=[ v 1h , v 2h , v 3h , v 4h ] T , where X h (t) is the position of the hth particle after the tth iteration, V h (t) is the velocity of the hth particle after the tth iteration, λ h ,λ h c, Oh ,s h are the starting point coordinate vectors of the n-segment path of the h-th particle, λ h c is the coordinate vector λ of the starting point of the n-segment path h The tangent vector at O h is the coordinate vector of the center of the n-segment path arc, s n is the length vector of the n-segment path, v 1h , v 2h , v 3h , v 4h They are h ,λ h c, O h ,s h The second step: evaluate the fitness: construct the fitness function based on the objective function and calculate the fitness value of each particle.

[0119] Step 3: Individual best and global best update: For each particle, compare its current fitness value with the historical best position (P besth )’s fitness value, if the current value is better, update P besth Find the particle with the best fitness value among all particles and set its position as the global best (G best ).

[0120] Step 4: Speed ​​and position update: Update the speed and position of each particle according to the current speed, individual best position and global best position of the particle, V h (t+1)=V h (t)+c1r1(P Besth -X h (t))+c2r2(G Best -X h (t));

[0121] X h (t+1)=X h (t)+V h (t+1); where V h (t+1) is the velocity of the hth particle after the t+1th iteration, is the inertia weight, c1 is the individual learning factor of each particle, c2 is the social learning factor of the particle group, r1 and r2 are random numbers that obey uniform distribution in the interval [0,1], P Besth is the historical optimal position of the hth particle, G Best is the best historical position of all particles.

[0122] Iteration: Repeat steps 2 to 4 until the termination condition is met, such as obtaining the optimal solution for the puncture path of the puncture needle after reaching the maximum number of iterations T.

[0123] In actual use, swarm intelligence algorithms such as genetic algorithms and simulated annealing algorithms can also be used as optimization algorithms, which will not be described in detail here.

[0124] In order to further improve the puncture path planning effect of the optimization algorithm, the present invention solves the defects of the simple particle swarm algorithm in puncture path planning (for example, most of them do not have a strategy to enhance the search for particles that perform well in the search process; secondly, the fitness values ​​of some particles no longer continue to improve after a certain number of iterations, and these particles may stagnate and there is no strategy to deal with this problem, resulting in poor optimization results).

[0125] The present invention also provides another embodiment, a particle swarm algorithm of a swarm strategy obtained by combining a swarm strategy with a particle swarm algorithm, that is, a method for planning a puncture needle puncture path among multiple target points by using an improved particle swarm algorithm, which is specifically as follows:

[0126] Sort each target point from large to small according to the coordinate value in the z-axis direction to obtain the path planning sequence of the target points;

[0127] The bee colony strategy particle swarm algorithm is used to plan the puncture path of the first target point in the path planning sequence of the target points, and the initial puncture path of the puncture needle is obtained;

[0128] After the initial path planning of the puncture needle is completed, the bee colony strategy particle swarm algorithm will be used to perform a new planning operation on the second target point starting from the end point of the initial path of the puncture needle.

[0129] If the puncture path to the second target point cannot be planned at the end point of the initial puncture path of the puncture needle, the puncture needle tip starts to retreat to the position where the needle stopped and turned last on the current path, and the puncture path is planned for the second target point again, and so on, until the path to the second target point is successfully planned;

[0130] If the path planning for the second target point cannot be successfully performed until the puncture needle tip retracts to the needle insertion point, a failure prompt will be given.

[0131] The starting point of the puncture needle puncture path planning is the needle entry point, where the needle entry point, target point and obstacle position information are obtained by obtaining the puncture environment information mark through medical imaging equipment. i ,λ i c, O i ,s i ), i∈[1,n] construct particle position X h (t)=[λ h ,λ h c, O h ,s h ] T , and set the particle velocity to V h (t)=[ v 1h , v 2h , v 3h , v 4h ] T , where X h (t) is the position of the hth particle after the tth iteration, V h (t) is the velocity of the hth particle after the tth iteration, λ h ,λ h c, O h ,s h are the starting point coordinate vectors of the n-segment path of the h-th particle, λ h c is the coordinate vector λ of the starting point of the n-segment path h The tangent vector at O h is the coordinate vector of the center of the n-segment path arc, s n is the length vector of the n-segment path, v 1h , v 2h , v 3h , v 4h They are h ,λ h c, O h ,s h The movement speed is calculated; the employed learning stage, the spectator learning stage and the reconnaissance learning stage of the bee colony particle swarm algorithm are used to perform particle optimization respectively, and an enhanced search is performed around particles with better fitness values, and particles whose fitness values ​​have not improved after a preset threshold number of iterations are initialized, and the puncture needle puncture path is obtained after the total number of iterations is completed.

[0132] Like other optimization algorithms, artificial bee colony is a swarm intelligence algorithm strategy inspired by the foraging behavior of bee colonies, but the bee colony strategy has the characteristics of division of labor, which divides the bee colony into three groups, namely employed bee colonies, spectator bee colonies and scout bee colonies. The employed bee colonies are responsible for searching near a food source to find a better food source, the spectator bee colonies perform enhanced search around the food source with better fitness value, and the scout bee colonies perform random search when a food source is exhausted. By combining the bee foraging search mechanism with the particle swarm algorithm, a new bee foraging learning particle swarm algorithm is proposed. BFL divides the original particle swarm optimization algorithm into three stages, namely the employed learning stage, the spectator learning stage and the scout learning stage. The employed learning stage is equivalent to the optimization stage of the traditional particle swarm optimization algorithm. The spectator learning stage further performs enhanced search around the particles with better fitness value, and the scout learning initializes the particles whose fitness value has not improved after a certain number of iterations.

[0133] During the employment learning phase, the update status of each particle will be recorded, among which,

[0134] If the fitness value of the hth particle is not updated after the iteration, its counter count(h) is incremented by one;

[0135] If the fitness value of the hth particle is updated after the iteration, its counter count(h) is set to zero;

[0136] The particle position and velocity update formula is:

[0137] V h (t+1)=V h (t)+c1r1(P Besth -X h (t))+c2r2(G Best -X h (t));

[0138] X h (t+1)=X h (t)+V h (t+1);

[0139] ;

[0140] Where V h (t+1) is the velocity of the hth particle after the t+1th iteration, is the inertia weight, c1 is the individual learning factor of each particle, c2 is the social learning factor of the particle group, r1 and r2 are random numbers that obey uniform distribution in the interval [0,1], P Besth is the historical optimal position of the hth particle, G Bestis the best historical position of all particles, count(h) and x h-new are the counter value of the hth particle and the new particle value, respectively, f(x h-new ) is the h The fitness of the new particle value of each particle. The spectator learning stage calculates the fitness value according to the optimal position of each particle and calculates the probability of each particle being selected;

[0141] The fitness value calculation formula is: ; In the formula, F(x h ) is the fitness value of the hth particle;

[0142] The probability formula for a particle to be selected is: ; In the formula, p h is the probability of the hth particle being selected, and N is the total number of particles.

[0143] According to the probability of particles being selected, the roulette strategy is used to select particles, where

[0144] When the hth particle is selected, the hiring learning phase is performed on the particle alone, and the particle's position and speed update formula in the hiring learning phase is used to update the particle's speed and position. If the updated position is better than the original one, the particle's counter count(h) is reset to zero, otherwise it is incremented by 1. In the reconnaissance learning phase, if the hth particle's fitness value does not improve after the preset number of iterations, the particle's counter reaches the upper limit of the count, and the particle's position X is reset to zero. h and speed V h Perform initialization processing.

[0145] like Figure 2 As shown, the present invention provides a puncture path planning system based on optimization strategy and needle tip retraction strategy, which is applied to a puncture path planning method based on optimization strategy and needle tip retraction strategy, and the system includes:

[0146] A data acquisition unit is used to obtain puncture environment information and mark the entry and exit points, target points and obstacle position information in the medical imaging device;

[0147] A data processing unit, used for performing kinematic analysis on the puncture needle, constructing a kinematic model of the puncture needle for planning the puncture path of the puncture needle, and constructing a kinematic model of the puncture path of the puncture needle;

[0148] Based on the kinematic model of the puncture needle puncture path, a multi-objective function for puncture needle puncture path planning was constructed;

[0149] The path planning unit is used to optimize and solve the kinematic model of the puncture needle puncture path for puncturing multiple target points based on a multi-objective function by using an optimization algorithm combined with a needle tip retraction and insertion strategy, and obtain the optimized puncture needle puncture path for puncturing each target point one by one.

[0150] The method for constructing the kinematic model of the puncture path of the puncture needle by the data processing unit includes: constructing the kinematic model of the puncture needle Applying the stop-and-turn strategy, the control sequence of the puncture needle puncture path is obtained as Y=((s1,q1),(s2,q2),L,(s n ,q n )), where s1, s2 and s n are the lengths of the first, second and nth segments of the puncture path of the puncture needle, q1, q2 and q n are the rotation angles of the 1st, 2nd and nth segments of the puncture path of the puncture needle respectively; the control sequence based on the puncture path of the puncture needle is Y=((s1,q1),(s2,q2),L,(s n ,q n )), and the needle tip of the puncture needle moves along a standard arc along a fixed radius r, and the puncture needle puncture path is determined to be composed of n arc paths {s i | i ∈[1,n]}, s i The first i The length of the segment path, and ,in, For i The corresponding arc, r is the movement radius of the needle tip;

[0151] The control sequence of the puncture needle puncture path is converted from the needle insertion distance s and the rotation angle q into the coordinates of the center of the path and the coordinates and length of the starting point of each path segment to obtain the kinematic model of the puncture needle puncture path Q = {(λ i ,λ i c, O i ,s i )| i ∈[1,n]}, where λ i For the i The starting coordinates of the segment path, λ i c is the i Segment path starting point coordinates λ i The tangent vector at O i For the i The center coordinates of the segment path arc;

[0152] Among them, λ i ,λ i c, O i ,s iThe relationship between is: i+1 =l i coss i +(1-coss i ) i +rλ i csins i ;

[0153] O i+1 =2l i+1 -O i ;

[0154] λ i+1 c=(1-coss i ) i+1 +l i+1 coss i -l i ; In the formula, λ i+1 For the i +1 The starting point coordinates of the path, λ i+1 c is the i +1 path starting point coordinates λ i+1 The tangent vector at O i+1 For the i +1 The center coordinates of the arc of the path segment.

[0155] The method for constructing the multi-objective function of the path planning unit includes:

[0156] Determining the total path length, path deviation, and whether the needle tip encounters an obstacle as multiple optimization targets of the puncture needle puncture path;

[0157] According to the kinematic model of the puncture needle puncture path and multiple optimization objectives, the multi-objective function of the puncture needle puncture path planning is determined; the multi-objective function is:

[0158] Y=k1Y tip (Q)+k2Y s (Q)+Y d (Q);

[0159] Y tip (Q)=|P tip (Q)-P d |;

[0160] Y s (Q)= ;

[0161] Y d (Q)= ;

[0162] ; In the formula, Y is the multi-objective function value, k1 is the weight of the path deviation, k2 is the weight of the total path length, and Y tip (θ) is the error function between the target point and the needle tip of the puncture needle, P tip (Θ) is the coordinate of the end point of the puncture path determined by Θ, P d is the coordinate of the target point, Y s (Θ) is the path length function, s i It is the first i The length of the segment path, Y d (Θ) is the function to determine whether the needle tip collides with an obstacle, m is the number of obstacles, and y j (d) is the collision function of the jth obstacle, d is the safe distance between the obstacle and the needle tip of the puncture needle. When the needle tip collides with the obstacle, y j (d) The value is +∞, otherwise y j (d) value is zero;

[0163] Among them, k1 and k2 are dynamic functions related to the number of iterations of the optimization algorithm, which are used to dynamically balance the optimization objectives of the total path length and path deviation in the multi-objective function; ; In the formula, , k i (t) is k i The weight at iteration t, H i (t-1) is k i The degree of convergence at the t-1th iteration, G i (t-1) is k i The fitness value at the t-1th iteration, G i (t-2) is k i The fitness value at the t-2th iteration, N=2, N is the number of optimization targets for the total path length and path deviation, T is the total number of iterations of the optimization algorithm, i , j , t They are all counting variables; the calculation function of the fitness value is:

[0164] G1(t)=|Y tip (Q(t))-Y tip (Q(t-1))|;

[0165] G2(t)=|Y s (Q(t))-Y s (Q(t-1))|;

[0166] Where G1(t) is the fitness value of k1 at the tth iteration, G2(t) is the fitness value of k2 at the tth iteration, and Y tip (Q(t)) and Ytip (Q(t-1)) are the path deviations at the t-th and t-1-th iterations, respectively, and Y s (Q(t)) and Y s (Q(t-1)) are the total lengths of the paths at the tth and t-1th iterations, respectively.

[0167] The present invention performs puncture path planning by means of an optimization strategy, establishes constraints among multiple objectives, and controls the constraint direction by setting weights, so that the optimization direction is controllable, thereby making the effect of path planning controllable, thereby achieving the optimization of path planning.

[0168] The above embodiments are only exemplary embodiments of the present application and are not intended to limit the present application. The protection scope of the present application is defined by the claims. Those skilled in the art may make various modifications or equivalent substitutions to the present application within the essence and protection scope of the present application, and such modifications or equivalent substitutions shall also be deemed to fall within the protection scope of the present application.

Claims

1. A puncture path planning method based on optimization strategy and needle tip retraction strategy, characterized in that: The following steps are involved: Performing kinematic analysis on the puncture needle, constructing a kinematic model of the puncture needle for puncture path planning of the puncture needle, and constructing a kinematic model of the puncture path of the puncture needle; Based on the kinematic model of the puncture needle puncture path, a multi-objective function for puncture needle puncture path planning is constructed; Based on the multi-objective function, the kinematic model of the puncture needle puncture path for puncturing multiple target points is optimized and solved by using the optimization algorithm combined with the needle tip retraction needle insertion strategy, so as to obtain the optimized puncture needle puncture path for puncturing each target point one by one; The construction methods of multi-objective functions include: Determining the total path length, path deviation, and whether the needle tip encounters an obstacle as multiple optimization objectives of the puncture needle puncture path; According to the kinematic model of the puncture needle puncture path and multiple optimization objectives, a multi-objective function for puncture needle puncture path planning is determined; The multi-objective function is: ; ； ； ； ； In the formula, is the value of the multi-objective function, is the weight of the path deviation, is the weight of the total path length, is the error function between the target point and the needle tip of the puncture needle, for The determined endpoint coordinates of the puncture needle puncture path, are the coordinates of the target point, is the path length function, It is the first i The length of the segment path, is a function to determine whether the needle tip of the puncture needle collides with an obstacle. is the number of obstacles, is the total number of arc paths in the puncture path of the puncture needle, For the The collision function of obstacles, is the safe distance between the obstacle and the needle tip of the puncture needle. When the needle tip collides with the obstacle, The value is +∞, otherwise The value is zero, is the kinematic model identifier of the puncture needle puncture path; in, ; In the formula, , , , for In the The weight at the iteration, for In the The degree of convergence at the iteration, for In the The fitness value at the iteration, for In the The fitness value at the iteration, is the number of optimization targets for the total path length and path deviation, is the total number of iterations of the optimization algorithm, All are count variables; The calculation function of the fitness value is: ; ; In the formula, for In the The fitness value at the iteration, for In the The fitness value at the iteration, and Respectively and The path deviation at iteration, and Respectively and The total length of the path at iterations.

2. The puncture path planning method based on optimization strategy and needle tip retraction strategy according to claim 1, characterized in that: The method for constructing the puncture needle kinematic model comprises: Set the forward speed of the puncture needle to The angular velocity of the axial rotation of the puncture needle is , the needle body coordinate system of the puncture needle is , the puncture needle is in the world coordinate system The position and posture of , where The puncture needle is in the world coordinate system Identifiers of the position and attitude matrices in , The puncture needle revolves around the world coordinate system of The rotation angle of the axis, The puncture needle revolves around the world coordinate system of The position coordinates of the axis, is the transpose operator; in the world coordinate system In the experiment, the speed of the puncture needle is determined as , where The puncture needle is in the world coordinate system The speed of is the identifier of the puncture needle kinematic model; In the needle coordinate system In the experiment, the speed of the puncture needle is determined as ,in , , where The puncture needle is in the needle body coordinate system The speed of for The control vector of for The control vector of is the motion curvature of the puncture needle tip; Based on the world coordinate system and needle body coordinate system , the velocity conversion equation of the puncture needle is obtained as: ,in, , , where for and The identifier of the transformation matrix between The world coordinate system and needle body coordinate system The rotation matrix that establishes the world coordinate system of the puncture needle and needle body coordinate system The speed transformation relationship between is the matrix coefficient of the Euler kinematics equation for rigid body fixed-point motion, which establishes the world coordinate system and needle body coordinate system The angular velocity transformation relationship between them; according to , as well as , the kinematic model of the puncture needle is determined as: ; Separate the time factor in the puncture needle kinematic model to eliminate the puncture speed and rotation speed in the control quantity of the puncture needle motion model and retain the needle insertion distance and rotation angle , and the kinematic model of the puncture needle after separation is obtained , where is the identifier of the control matrix.

3. The puncture path planning method based on optimization strategy and needle tip retraction strategy according to claim 2 is characterized in that: The method for constructing the kinematic model of the puncture needle puncture path includes: Kinematic model of puncture needle Apply the stop-and-turn strategy to obtain the control sequence of the puncture needle puncture path ,in, is the identifier of the control sequence, , and The first, second and Segment path length, , and The first, second and The rotation angle at the segment path; Control sequence based on puncture needle puncture path , and the tip of the puncture needle moves along a fixed radius Make standard circular motion to determine the puncture path of the puncture needle. Segment arc path composition, The first i The length of the segment path, and ,in, for The corresponding arc, is the moving radius of the needle tip; The control sequence of the puncture needle puncture path is changed from the needle insertion distance and rotation angle The kinematic model of the puncture path of the puncture needle is obtained by converting the coordinates of the center of the path and the coordinates and length of the starting point of each path segment. , where is the kinematic model identifier of the puncture needle puncture path, For the The starting coordinates of the segment path, For the Segment path starting point coordinates The tangent vector at For the The coordinates of the center of the arc of the segment path, is the total number of arc paths in the puncture path of the puncture needle; in, The relationship between is: ; ； ； In the formula, For the The starting coordinates of the segment path, For the Segment path starting point coordinates The tangent vector at For the The coordinates of the center point of the segment path arc.

4. The puncture path planning method based on optimization strategy and needle tip retraction strategy according to claim 1, characterized in that: The planning method of optimizing the puncture needle path for puncturing each target point one by one includes: Sort each target point from large to small according to the coordinate value in the z-axis direction to obtain the path planning sequence of the target points; Using an optimization algorithm based on a multi-objective function to plan the puncture path of the first target point in the path planning sequence of the target points, the puncture path of the puncture needle is obtained; After the initial path planning of the puncture needle is completed, the optimization algorithm will be used to perform a new planning operation on the second target point based on the multi-objective function starting from the end point of the initial path of the puncture needle. If the puncture path to the second target point cannot be planned at the end point of the initial puncture path of the puncture needle, the puncture needle tip starts to retreat to the position where the needle stopped and turned last on the current path, and the puncture path is planned for the second target point again, and so on, until the path to the second target point is successfully planned; If the path planning for the second target point cannot be successfully performed until the puncture needle tip retracts to the needle insertion point, a failure prompt will be given.

5. The puncture path planning method based on optimization strategy and needle tip retraction strategy according to claim 1, characterized in that: The constraints for optimizing and solving the kinematic model of the puncture path of the puncture needle by the optimization algorithm include: The total length of the optimal puncture path is less than or equal to the total length of the puncture needle; The arc curvature of each segment of the optimal puncture path is less than or equal to the maximum bending curvature of the puncture needle stiffness.

6. The puncture path planning method based on optimization strategy and needle tip retraction strategy according to claim 1, characterized in that: The starting point of the puncture needle puncture path planning is the needle entry point, wherein the needle entry point, target point and obstacle position information are obtained by obtaining the puncture environment information mark through medical imaging equipment.

7. A puncture path planning system based on optimization strategy and needle tip retraction strategy, characterized in that: The puncture path planning method based on the optimization strategy and the needle tip retraction strategy applied to any one of claims 1 to 6, the system comprising: A data acquisition unit, used to obtain puncture environment information and mark the entry and exit points, target points and obstacle position information in the medical imaging device; A data processing unit, used for performing kinematic analysis on the puncture needle, constructing a kinematic model of the puncture needle for planning the puncture path of the puncture needle, and constructing a kinematic model of the puncture path of the puncture needle; Based on the kinematic model of the puncture needle puncture path, a multi-objective function for puncture needle puncture path planning is constructed; The path planning unit is used to optimize and solve the kinematic model of the puncture needle puncture path for puncturing multiple target points based on a multi-objective function by using an optimization algorithm combined with a needle tip retraction and insertion strategy, so as to obtain the optimized puncture needle puncture path for puncturing each target point one by one.

Images