CN115890659A - Method for optimizing dexterity of continuum robot - Google Patents
Method for optimizing dexterity of continuum robot Download PDFInfo
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- CN115890659A CN115890659A CN202211384554.7A CN202211384554A CN115890659A CN 115890659 A CN115890659 A CN 115890659A CN 202211384554 A CN202211384554 A CN 202211384554A CN 115890659 A CN115890659 A CN 115890659A
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- 210000000056 organ Anatomy 0.000 claims abstract description 23
- 238000013178 mathematical model Methods 0.000 claims abstract description 20
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- 238000005457 optimization Methods 0.000 claims description 9
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- 238000001514 detection method Methods 0.000 claims description 5
- 229910052731 fluorine Inorganic materials 0.000 claims 1
- 125000001153 fluoro group Chemical group F* 0.000 claims 1
- 210000001035 gastrointestinal tract Anatomy 0.000 description 10
- 238000001356 surgical procedure Methods 0.000 description 6
- 230000000968 intestinal effect Effects 0.000 description 3
- 210000002435 tendon Anatomy 0.000 description 3
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- 230000001413 cellular effect Effects 0.000 description 1
- 210000001731 descending colon Anatomy 0.000 description 1
- 238000002674 endoscopic surgery Methods 0.000 description 1
- 208000014674 injury Diseases 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
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- 235000001968 nicotinic acid Nutrition 0.000 description 1
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- 210000000664 rectum Anatomy 0.000 description 1
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- 210000001599 sigmoid colon Anatomy 0.000 description 1
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- 201000005112 urinary bladder cancer Diseases 0.000 description 1
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Abstract
The invention relates to a method for optimizing the dexterity of a continuum robot, which comprises the steps of establishing a point cloud map model of tissue organs, establishing a positive kinematic formula of the continuum robot according to a constant curvature model of the continuum robot, establishing a mathematical model of an accessible space of the continuum robot, constructing the mathematical model of the dexterity index of the continuum robot by calculating the occupation ratio of the accessible space in a task space, and optimizing the size parameter of the continuum robot by taking the mathematical model of the dexterity index of the continuum robot as a target function so that the target function meets the constraint condition: the end point of the continuum robot reaches the target point, and the minimum distance between the end point and the edge of the tissue organ is larger than a set distance threshold value. The invention ensures that the robot meets geometric constraint and anatomical constraint based on operation tasks, improves the flexibility of the continuum robot, avoids the collision and contact between the continuum robot and tissues and organs, and reduces the pain of patients.
Description
Technical Field
The invention belongs to the technical field of artificial intelligence, relates to a continuum robot, and particularly relates to a method for optimizing the flexibility of the continuum robot.
Background
The inspiration of continuum robots comes from bionics, usually made of flexible materials with low elastic modulus. The continuum robot can change its natural shape using flexibility of materials, and the change of shape enables the robot to reach a narrow space.
Single-port access surgery (SPAS), natural orifice intraluminal endoscopic surgery and cellular surgery are modern surgical procedures aimed at shortening the recovery time and reducing the trauma of healthy tissues, which can be well met by continuum robots. Some examples of applications include cerebral hemorrhage clearance, bladder cancer, upper laryngeal airway surgery, and continuum robots can bypass obstacles and enter closed environments due to their high flexibility and compliance. Thus, they can be used for inspection tasks, disaster relief or surgical procedures.
Most continuum robots use a single backbone to pass through the actuators, tendons are common actuators for building continuum robots, such as a multi-joint continuum robot like a nose. A multi-stem continuum robot has one of the backbones considered a primary backbone and the other stems considered secondary backbones. The concentric tube robot is another continuous body robot, which takes a tube as a backbone and has the potential of miniaturization. The length of each part of a continuum robot must be designed appropriately to ensure that the robot meets geometric, anatomical constraints based on the operational task.
Therefore, the research on parameter optimization of the continuum robot has important significance for improving the dexterity of the continuum robot in the operation space.
Disclosure of Invention
The invention aims to provide a method for optimizing the flexibility of a continuum robot so as to improve the flexibility of the continuum robot in a surgery or detection task.
In order to achieve the purpose, the invention adopts the technical scheme that:
a method of optimizing the dexterity of a continuum robot, comprising:
s1: establishing a point cloud map model of the tissue and organ,
s2: establishing a positive kinematics formula of the continuum robot according to the constant curvature model of the continuum robot,
s3: establishing a mathematical model of the reachable space of the continuum robot,
s4: a mathematical model of the dexterity index of the continuum robot is constructed by calculating the occupancy ratio of the reachable space in the task space,
s5: and (2) optimizing the size parameters of the continuum robot by taking the mathematical model of the dexterity index of the continuum robot as an objective function, so that the objective function meets the constraint condition: continuum robot end point (x) end ,y end ) To the target point P target And the minimum distance mindis to the tissue organ edge is larger than a set distance threshold.
Preferably, in S1, a point cloud map model of the tissue and the organ is established using python.
Further preferably, establishing the point cloud map model of the tissue organ comprises: and (3) constructing an stl file of the tissue organ by using three-dimensional reconstruction of the CT file, converting the format of the stl file into a ply format, and generating a tissue organ edge information point cloud map through an open3d library.
Preferably, in S2, the pose of the continuum robot and the position coordinates of the head of the continuum robot are calculated by substituting the parameters of the bending angle of the continuum robot into a positive kinematic formula, and the constant curvature model is:
the positive kinematic model is:
wherein: x is the number of n And y n Is the n-th node end point coordinate, n ∈ (1,N), l 1 Is a first length, θ 1 Is a first bending angle, R m-1 For the rotation transformation matrix of section m-1 to section m,/ m Length of the m-th section, [ theta ] m ' is the bending angle difference between the m-th section and the m-1 st section.
Preferably, in the above technical solution, in S3: the left mathematical model of the reachable space is:
wherein, T 1 ，T 2 And T 3 Respectively, transformation matrices, theta, for the respective joints 1 ，θ 2 ，θ 3 And theta i The bending angles of the corresponding joints are respectively, T is matrix transposition, and a mathematical model of a right space is obtained through symmetry.
Preferably, in S4, the constructing a mathematical model of the dexterity of the continuum robot includes: setting an operation task space in a point cloud map, dividing the reachable space area in the task space by the set operation task space area, and taking the obtained value as the dexterity index of the continuum robot, wherein the dexterity index formula of the continuum robot is as follows:
D T ＝S accessible /S T
S T ＝a×b
wherein: s accessible For the reachable area of the continuum robot in the set surgical task space, S T In order to set the area of the surgical task space, a and b are respectively the length and width of the surgical task space.
Preferably, in S5, the objective function takes each segment length of the continuum robot as a design variable, and the total length and the dexterity index of the continuum robot are multiplied by respective weights and then added to serve as the objective function:
Min F＝1/D T
wherein: d T Is an index of the dexterity of the continuum robot.
Further preferably, the optimal design variables of the objective function are:
L＝(l 1 ，l 2 ，...，l N ) T
wherein: l i The length of the i-th section of the continuum robot, N is the total number of the sections of the continuum robot, T is the matrix transposition, and the optimization design variables determine the purposeNumber of variables in the target function.
Preferably, in S5, the constraint condition is:
wherein: theta i Is the bending angle of the i-th section,/ i Is the length of section i.
Preferably, in S5, the minimum distance detection uses point cloud map data to establish a kd tree, the minimum distance is obtained by a nearest neighbor search method, whether the continuum robot and the tissue and organ are in collision contact or not is judged, and if the distance between the continuum robot and the tissue and organ meets the threshold requirement and the optimization function result meets the requirement, the optimal size parameter is met; if the robot collides with tissues and organs or the result of the optimization function does not meet the requirement, the currently set section number of the continuum robot does not meet the requirement, the section number needs to be increased, and the variable number is correspondingly increased in the objective function.
Due to the application of the technical scheme, compared with the prior art, the invention has the following advantages:
the method uses the positive kinematics of the continuum robot, optimizes the parameters of the continuum robot by establishing the objective function, ensures that the robot meets geometric constraint and anatomical constraint based on operation tasks, improves the dexterity of the continuum robot, avoids collision and contact between the continuum robot and tissues and organs, and reduces the pain of patients.
Drawings
FIG. 1 is a schematic flow chart of the method in this embodiment,
figure 2 is an image of the intestinal tract stl in this example,
fig. 3 is a point cloud map image of the intestinal tract obtained by python processing in this embodiment,
figure 4 is a schematic diagram of the tendon driven continuum robot in this embodiment (not curved),
figure 5 is a schematic view (S-shaped curve) of the tendon-driven continuum robot in this embodiment,
fig. 6 is a schematic diagram of the reachable space of the continuum robot in this embodiment.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it is to be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 shows a method for optimizing the dexterity of a continuum robot, in which the tissue organ is an intestinal tract, the method includes the following steps:
first, a point cloud map model of the intestinal tract (anal canal, rectum, sigmoid colon, and descending colon) is built from CT files. The method comprises the steps of establishing an intestinal tract point cloud map, using python, using a CT file to reconstruct and construct an intestinal tract stl file in a three-dimensional mode, firstly converting the stl file format into a ply format, and generating an intestinal tract edge information point cloud map through an open3d library, as shown in fig. 2 and 3.
Then, establishing a continuum robot positive kinematics formula according to the continuum robot constant curvature model, wherein: the constant curvature model of the continuum robot is that each section of the robot is regarded as a continuously curved circular arc, and coordinates of each section are calculated through a rotation transformation matrix. The pose of the continuum robot and the position coordinates of the head of the continuum robot are calculated by substituting the parameters of the bending angle of the continuum robot into a positive kinematics formula, as shown in fig. 4 and 5. Wherein:
the constant curvature model is:
the positive kinematic model is:
wherein: x is the number of n And y n Is the n-th node end point coordinate, n ∈ (1,N), l 1 Is a first length, θ 1 Is a first bending angle, R m-1 For the rotation transformation matrix of section m-1 to section m,/ m Is the m-th length, θ m ' is the bending angle difference between the m-th section and the m-1 st section.
Then, a mathematical model of the reachable space of the continuum robot is established, the mathematical model of the reachable space of the continuum robot is calculated through a positive kinematics formula of the continuum robot, and the mathematical model on the left side of the reachable space is as follows:
the right space can be derived from symmetry, where T 1 ，T 2 And T 3 Respectively, transformation matrices, theta, for the respective joints 1 ，θ 2 ，θ 3 And theta i Respectively, the bending angles of the corresponding joints, and T is matrix transposition.
Next, a mathematical model of the dexterity index of the continuum robot is constructed by calculating the occupancy ratio of the reachable space in the task space. The method specifically comprises the following steps: setting an operation task space in a point cloud map, dividing an accessible space area in the task space by the set operation task space area, and taking an obtained value as a dexterity index of the continuum robot, wherein the formula of the dexterity index of the continuum robot is as follows:
D T ＝S accessible /S T
wherein: s accessible For the area reachable by the continuum robot in the set surgical task space, S accessible Calculated by an accessible space calculation formula, calculated by S T To set the area of the surgical task space, the surgeon sets it in the image, which is cylindrical and displayed in the imageIs rectangular.
S T ＝a×b
Wherein, a and b are respectively the length and width of the operation task space.
And finally, taking the mathematical model of the dexterity index of the continuum robot as an objective function, and enabling the objective function to meet the constraint condition: continuum robot end point (x) end ，y end ) To the target point P target And the minimum distance mindis to the intestinal edge is larger than a set distance threshold. The method comprises the steps of establishing a kd tree by using point cloud map data for minimum distance detection, obtaining a minimum distance through a nearest neighbor search method, judging whether a continuum robot is in collision contact with an intestinal tract, and if the distance between the continuum robot and the intestinal tract meets the threshold requirement and the optimization function result meets the requirement, meeting the optimal size parameter; if the robot collides with the intestinal tract or the result of the optimization function does not meet the requirement, the number of the currently set nodes of the continuum robot does not meet the requirement, the number of the nodes needs to be increased, and the number of the variables is correspondingly increased in the objective function.
Specifically, the method comprises the following steps: the target function takes the length of each section of the continuum robot as a design variable, the total length and the dexterity index of the continuum robot are multiplied by respective weights respectively and then added to be used as the target function, and the maximum dexterity is required to be obtained:
Min F＝1/D T
wherein: d T Is an index of the dexterity of the continuum robot.
The optimization design variables of the objective function determine the variable quantity in the objective function, and the variables are as follows:
L＝(l 1 ，l 2 ，...，l N ) T
wherein: l i The length of the i-th section of the continuum robot, N is the total number of the sections of the continuum robot, and T is the matrix transposition.
The following is a constraint:
wherein: theta i Is the bending angle of section i,/ i Is the length of section i.
This embodiment has obtained better motion performance through optimizing the structural parameter to continuum robot, can carry out human intestinal detection and operation task better, has avoided the collision contact of continuum robot with the intestinal.
The above embodiments are only for illustrating the technical idea and features of the present invention, and the purpose of the present invention is to enable those skilled in the art to understand the content of the present invention and implement the present invention, and not to limit the protection scope of the present invention by this means. All equivalent changes and modifications made according to the spirit of the present invention should be covered within the protection scope of the present invention.
Claims (10)
1. A method for optimizing the dexterity of a continuum robot is characterized by comprising the following steps: the method comprises the following steps:
s1: establishing a point cloud map model of the tissue and organ,
s2: establishing a positive kinematics formula of the continuum robot according to the constant curvature model of the continuum robot,
s3: establishing a mathematical model of the reachable space of the continuum robot,
s4: a mathematical model of the dexterity index of the continuum robot is constructed by calculating the occupancy ratio of the reachable space in the task space,
s5: and (2) optimizing the size parameters of the continuum robot by taking the mathematical model of the dexterity index of the continuum robot as an objective function, so that the objective function meets the constraint condition: continuum robot end point (x) end ,y end ) To the target point P target And the minimum distance mindis to the tissue organ edge is larger than a set distance threshold.
2. The method of claim 1 for optimizing continuum robot dexterity, wherein: in S1, a point cloud map model of the tissue organ is established by python.
3. The method of optimizing continuum robot dexterity of claim 2, wherein: the method for establishing the point cloud map model of the tissue organ comprises the following steps: the method comprises the steps of using CT file three-dimensional reconstruction to construct an stl file of a tissue organ, firstly converting the format of the stl file into a ply format, and generating a tissue organ edge information point cloud map through an open3d library.
4. The method of optimizing continuum robot dexterity of claim 1, wherein: in S2, the pose of the continuum robot and the position coordinates of the head of the continuum robot are calculated by substituting the bending angle parameters of the continuum robot into a positive kinematic formula, and a constant curvature model is as follows:
the positive kinematic model is:
wherein: x is a radical of a fluorine atom n And y n Is the n-th node end point coordinate, n ∈ (1,N), l 1 Is a first length, θ 1 Is a first bending angle, R m-1 For the rotation transformation matrix of section m-1 to section m,/ m Is the m-th length, θ m ' is the bending angle difference between the m-th section and the m-1 st section.
5. The method of claim 1 for optimizing continuum robot dexterity, wherein: in S3: the left mathematical model of the reachable space is:
wherein, T 1 ,T 2 And T 3 Respectively, transformation matrices, theta, for the respective joints 1 ,θ 2 ,θ 3 And theta i The bending angles of the corresponding joints are respectively, T is matrix transposition, and a mathematical model of a right space is obtained through symmetry.
6. The method of optimizing continuum robot dexterity of claim 1, wherein: in S4, constructing a mathematical model of the continuum robot dexterity comprises: setting an operation task space in a point cloud map, dividing the reachable space area in the task space by the set operation task space area, and taking the obtained value as the dexterity index of the continuum robot, wherein the dexterity index formula of the continuum robot is as follows:
D T ＝S accessible /S T
S T ＝a×b
wherein: s accessible For the area reachable by the continuum robot in the set surgical task space, S T In order to set the area of the surgical task space, a and b are respectively the length and width of the surgical task space.
7. The method of optimizing continuum robot dexterity of claim 1, wherein: in S5, the objective function takes the length of each section of the continuum robot as a design variable, and the total length and the flexibility index of the continuum robot are multiplied by respective weights and then added to be used as the objective function:
Min F＝1/D T
wherein: d T Is an index of the dexterity of the continuum robot.
8. The method of optimizing continuum robot dexterity of claim 7, wherein: the optimal design variables of the objective function determine the number of variables in the objective function, which are:
L＝(l 1 ,l 2 ,...,l N ) T
wherein: l i The length of the i-th section of the continuum robot, N is the total number of the sections of the continuum robot, and T is the matrix transposition.
9. The method of optimizing continuum robot dexterity of claim 1, wherein: in S5, the constraint conditions are:
wherein: theta i Is the bending angle of section i,/ i Is the length of section i.
10. The method of optimizing continuum robot dexterity of claim 1, wherein: in S5, the minimum distance detection uses point cloud map data to establish a kd tree, the minimum distance is obtained through a nearest neighbor search method, whether the continuum robot and the tissue organ are in collision contact or not is judged, and if the distance between the continuum robot and the tissue organ meets the threshold requirement and the optimization function result meets the requirement, the optimal size parameter is met; if the robot collides with tissues and organs or the result of the optimization function does not meet the requirement, the currently set section number of the continuum robot does not meet the requirement, the section number needs to be increased, and the variable number is correspondingly increased in the objective function.
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