A method for optimizing the planar development of a soft finger-like gripper

Abstract

The application discloses a soft finger-shaped gripper plane expansion shape optimization method, step 1, an equivalent linear model along the length direction of the finger is established; step 2, a gripper deformation numerical model is calculated and iteration is carried out; step 3, a termination condition judgment is performed, a termination condition is set, and whether the deformation degree of the gripper reaches the set termination condition is judged; if yes, the next step is continued; if no, the step 2 is jumped to; step 4, an ideal width is calculated; the ideal width of the finger for realizing the object of closing and grabbing of the gripper is calculated; step 5, a convergence judgment is performed; a convergence condition is set, and whether the error between the obtained ideal width and the current width satisfies the convergence condition is judged; if yes, the shape optimization of the gripper is completed, the numerical model is output, otherwise, the step 2 is returned until the convergence condition is satisfied; and step 6, a plane geometric model is output. The application improves the reliability and robustness of the soft finger-shaped gripper when the object is grabbed, and can realize simultaneous grabbing of multiple objects without falling.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automated gripper, in particular to a soft finger-shaped gripper plane unfolding shape optimization method. BACKGROUND

[0002] The automated gripper is an execution component carried by a robot to grasp, move and place target objects, thereby achieving the purpose of improving production efficiency and production quality. The current finger-shaped gripper mostly adopts force grasping mode, that is, the contact force is generated by contacting the surface of the target object to achieve grasping of the target object. However, the force grasping mode needs to rely on the selection and design of materials, control and sensing fields to adapt to target objects of different shapes, sizes and weights and to reduce damage to the surface of the target object caused by grasping action, so that the design and manufacturing process of the force grasping mode are relatively complex. For the envelope grasping mode, the object can be basically grasped as long as it is enveloped, so many factors do not need to be considered in the design, and thus the finger-shaped gripper is simpler in design and manufacturing process than the force grasping mode, thereby making the cost lower and the failure rate lower, and being favored by the market. However, the fingers of the existing finger-shaped gripper are discretely distributed when bending to grasp the object.

[0003] A replaceable soft hand claw is disclosed in Chinese patent application No. CN115008495A, which includes a hand claw body including a palm and a plurality of fingers, the plurality of fingers are uniformly and spaced apart arranged on the periphery of the palm, the finger includes a finger bone, a finger tendon and a finger tip, the finger tendon is separated from the middle part of the finger, and the end of the finger tendon away from the palm is connected with the finger, the end of the finger tendon close to the palm is disconnected with the palm, the end of the finger tendon and the finger bone away from the palm is connected with the finger tip, the edge of the palm is provided with a plurality of limiting holes with the same number as the finger tendon, the finger tendon can be inserted into the limiting hole, and the finger tendon can move in the limiting hole. See Figure 3 and Figure 4 The soft hand claw is discretely distributed between the fingers in the grasping state, has a gap, and is difficult to achieve closed envelope grasping of the target object, which may affect the stability of grasping and is difficult to complete simultaneous grasping of multiple objects. SUMMARY

[0004] In view of the defects in the prior art, the purpose of the present application is to provide a soft finger-shaped gripper plane unfolding shape optimization method, which solves the problem that the existing soft finger-shaped gripper is difficult to achieve closed envelope grasping of the target object, which may affect the stability of grasping and is difficult to complete simultaneous grasping of multiple objects.

[0005] In order to achieve the above object, the technical scheme adopted by the present application is as follows: a soft finger-shaped gripper plane unfolding shape optimization method, which satisfies the following assumed conditions:

[0006] 1) The finger can be regarded as a linear object, that is, an object with a dimension much larger in one orthogonal direction than in the other two directions;

[0007] 2) Only in-plane deformation is generated during the gripping process of the finger.

[0008] A soft finger-shaped gripper plane unfolding shape optimization method comprises the following steps:

[0009] Step 1. Establishing an equivalent linear model: according to the initial plane geometric model of the soft gripper, analyzing the functional characteristics of each part of the gripper and establishing an equivalent linear model along the length direction of the finger;

[0010] Step 2. Calculating the deformation numerical model of the gripper and iterating: according to the driving and constraint conditions of the gripper under actual conditions, the deformation process of the gripper is calculated numerically to simulate the gripping process of the gripper;

[0011] Step 3. Termination condition judgment: set the termination condition, judge whether the deformation degree of the gripper reaches the set termination condition; if yes, continue to the next step; if no, jump to step 2;

[0012] Step 4. Calculating the ideal width: according to the numerical model obtained under the termination condition and the geometric relationship, the ideal width of the finger to achieve the goal of closing gripping is calculated;

[0013] Step 5. Convergence judgment: set the convergence condition, judge whether the error between the ideal width obtained and the current width (the existing soft finger-shaped gripper finger width) meets the convergence condition, if yes, complete the shape optimization of the gripper, output the numerical model, otherwise return to step 2 until the convergence condition is met;

[0014] Step 6. Outputting the plane geometric model: according to the optimized numerical model, the width of any point of the gripper finger meeting the closing gripping goal is obtained, and the plane geometric model is designed.

[0015] On the basis of the above technical scheme, in step 2, the equivalent linear model obtained in step 1 is divided into finite elements to establish a finite element model, and the node parameters are initialized. (Because it is a finite element method, there will be nodes and elements, which is equivalent to dividing the long finger into small segments for calculation, and the connection point between segments is the node.)

[0016] On the basis of the above technical scheme, the node initialization process specifically comprises the following steps:

[0017] 1) Initialize the node width coefficient (R i) to represent the bending section modulus at node i; wherein i = 1, 2,..., n, n is the total number of nodes;

[0018] 2) initialize the arc length (s i ) and tangent orientation angle (θ i ) of the nodes.

[0019] On the basis of the above technical solutions, in step 2, the tangent orientation angle (θ i ) of the key node is constrained as a boundary condition, and a driving feature is introduced as a constraint condition and an iteration start and end condition.

[0020] On the basis of the above technical solutions, in step 2, according to the principle that the internal energy of the linear object reaches a minimum value in its stable deformation state, any state in the deformation process of the gripper can be statically modeled. The internal energy V is calculated according to expression (1);

[0021] V = U - ∑ i W i (1)

[0022] Wherein W i is the work done by the external force at node i, U is the potential energy of the linear object, and the potential energy U is calculated according to expression (2);

[0023] U = U flex + U ext + U grav (2)

[0024] Wherein U flex , U ext , U grav respectively represent the bending potential energy, the stretching potential energy and the gravity potential energy of the object, the bending potential energy U flex , the stretching potential energy U ext can be calculated according to expressions (3) and (4) respectively, and the gravity potential energy U grav can be calculated according to expression (5) assuming that the gravity acts along the x-axis:

[0025]

[0026]

[0027]

[0028] Wherein R f represents the bending stiffness of the object, R e represents the tensile stiffness of the object, D represents the weight per unit length of the object, K represents the curvature at any point on the object, and ε represents the tensile strain of any point on the linear object along the central axis;

[0029] On the basis of the above technical solution, in step 6, the interpolation method can be used to obtain the finger width of any point between two nodes, and then the coordinates of any point on the optimized finger boundary are obtained, and then the finger boundary curve can be obtained through the curve fitting method, so as to output the gripper plane geometric model.

[0030] The technical solution of the present application has the following advantages:

[0031] The soft finger-shaped gripper plane unfolding shape optimization method provided by the present application takes the original soft finger-shaped gripper plane geometric model as the basis, takes the finger width as the optimization target, performs effective linear modeling on the finger, simulates the gripping state of the gripper, calculates the ideal width of the finger under the condition of meeting the termination condition, sets the convergence condition, outputs the numerical model when the ideal width of the finger and the current finger width error meet the convergence condition, and designs the optimized finger plane geometric model, so as to realize the purpose of forming closed gripping of the target object after the discretely distributed finger is curved, improve the reliability and robustness of the object when being gripped, and also realize the simultaneous gripping of multiple objects without falling. BRIEF DESCRIPTION OF DRAWINGS

[0032] In order to more clearly illustrate the technical solution in the specific embodiments of the present application or the prior art, the drawings needed in the specific embodiments or the prior art description will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present application, and those skilled in the art can also obtain other drawings according to these drawings without creative labor.

[0033] Figure 1 It is a soft finger-shaped gripper plane unfolding geometric model schematic diagram in the prior art;

[0034] Figure 2 It is a three-dimensional diagram of a soft finger-shaped gripper in the prior art;

[0035] Figure 3 It is a three-dimensional diagram of a soft finger-shaped gripper with a driving member in the prior art (inter-finger distance is large);

[0036] Figure 4 It is a three-dimensional diagram of a soft finger-shaped gripper with a driving member in the prior art (inter-finger distance is small);

[0037] Figure 5 It is a flowchart of a soft finger-shaped gripper plane unfolding shape optimization method provided by the specific embodiments of the present application;

[0038] Figure 6 It is an equivalent process schematic diagram of a soft finger-shaped gripper provided by the specific embodiments of the present application;

[0039] Figure 7 A software finger-shaped gripper equivalent linear model result and parameter diagram provided for the specific embodiment of the present application;

[0040] Figure 8 A soft finger-shaped gripper shape numerical model visualization diagram provided for the specific embodiment of the present application;

[0041] Figure 9 A soft finger-shaped gripper planar unfolded shape geometric relationship diagram;

[0042] Figure 10 A soft finger-shaped gripper planar unfolded shape optimized model provided for the specific embodiment of the present application;

[0043] Figure 11 A soft finger-shaped gripper planar unfolded shape optimized three-dimensional perspective view provided for the specific embodiment of the present application; DETAILED DESCRIPTION

[0044] The technical solutions of the present application will be described clearly and completely below in conjunction with the drawings. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0045] Referring to Figure 5 The embodiment of the present application provides a soft finger-shaped gripper planar unfolded shape optimization method, which comprises the following steps:

[0046] Step 1. Establishing an equivalent linear model: according to the initial planar geometric model of the soft gripper, analyzing the functional characteristics of each part of the gripper and establishing an equivalent linear model along the length direction of the finger.

[0047] In the optimization method, the numerical model of the gripper in the gripping deformation needs to be calculated, so the key features of the gripper are extracted and the initial model is simplified through reasonable assumptions, which can reduce the difficulty of deformation calculation. In the equivalent linear model, in addition to the finger part, the equivalent representation of the constraint and driving part is also needed.

[0048] Referring to Figure 1 The prior art soft finger-shaped gripper planar geometric model is shown in the figure: the material of the gripper is paper, the palm diameter d b = 45mm, the diameter of the limiting hole d c = 35mm; the number of fingers is 3, which are evenly distributed on the circumference of the palm, the finger length l f = 105mm, the width W f = 30mm, the finger muscle length l p = 90mm, the width W p=10mm, fingertip length l t =15mm. The finger tendons near the palm are disconnected from the palm, while the finger tendons near the fingertips are connected to the fingertips. The finger tendons pass through the limiting holes and pull the fingertips to achieve the finger grasping action.

[0049] See Figure 6 , Figure 7 As shown, since only in-plane deformation occurs during the deformation process, the gripper can be characterized by a midline with the same width as the finger width boundary. The palm AB segment is 22.5 mm long and is divided into AE and EB segments by the limiting hole E. The AE segment is 17.5 mm long. The finger BCD segment is 105 mm long and is divided into phalanges BC and fins CD by the finger tendon C segment. The finger tendon FEC segment is 90 mm long and is divided into outer segment (FB segment) and inner segment (EC segment) by the limiting hole E.

[0050] Step 2. Calculate and iterate the numerical model of gripper deformation: Based on the actual driving and constraint conditions of the gripper, perform numerical calculations on the gripper deformation process to simulate the gripper's grasping process;

[0051] See Figure 6 and Figure 7 As shown: To calculate the deformation of the entire finger, in addition to the calculation formula, some constraints need to be set to ensure that the calculation result meets some real-world constraints. Segment BCD represents the finger, and point B is a key node because it is the connection point between the finger and the palm, while the palm remains fixed. Therefore, the position and angle of point B remain unchanged throughout the deformation process. Similarly, point C is also a key point because it is the connection point between the finger and the tendon. The finger can be divided into 21 units by 22 nodes. Let P be a node at a distance s from the starting point B, and let ζ(s) = (cosθ(s), sinθ(s)) be the unit vector of point P along the object direction. Then, the deformation of the entire object can be represented by a series of object directions θ(s) at each object point. Therefore, the position of node P at a distance s from the starting point B can be represented as: The curvature at each point on the object is: k(s) = dθ(s) / ds. Ignoring its own weight and finite tensile deformation, the internal energy of the deformed object is: R(s) is the bending stiffness at the node, which is related to the width of the finger and is expressed by a dimensionless number. The constraints are: 1) the tangent direction angle θ1 of the starting point B = 0°; 2) driving characteristics: the relationship between the position of the finger tendon and the finger connection point C and the inner segment (EC segment), i.e. Based on the principle that the internal energy of a linear object reaches its minimum value under stable deformation, the deformation numerical model is a constrained optimization problem: the design variable is the nodal tangent azimuth angle (θ). i The design goal is to reduce the bending energy (U) of the linear model. flexThe minimum value can be represented as:

[0052] Minimize:U flex =U(θ1, θ2, ..., θ) n )

[0053] subject to: θ1=0

[0054]

[0055] design: θ1, θ2, ..., θ n .

[0056] See Figure 8 As shown, by setting a dimensionless number To determine the start and end conditions of the iteration, and to simulate the iterative process of pulling the finger tendons (FBC) to achieve gripping, in the example, under the initial condition D... constrain =0.9, D under termination condition constrain =0.6, set the number of iterations to 10.

[0057] Step 3. Termination Condition Judgment: Set a termination condition and determine whether the degree of deformation of the gripper reaches the set termination condition; if it does, continue to the next step; if not, jump to step 2.

[0058] By determining the dimensionless number D constrain The system determines whether the set termination conditions have been met. If met, the rational width of the node is calculated; otherwise, it proceeds to step 2 to continue model calculation and iteration.

[0059] Step 4. Calculate the ideal width: Based on the numerical model and geometric relationship obtained under the termination conditions, calculate the ideal finger width for achieving the gripper's closure and grasping.

[0060] See Figure 9 As shown, the fingers are spaced 120° apart; according to assumption 2), the fingers only undergo in-plane deformation during the gripping process (we conventionally consider the screen as the plane containing the component). Figure 7 As shown, in addition to the x and y directions constructed on the screen, a z coordinate pointing outside the screen can be added. In-plane deformation can be understood as follows: for any point A on the finger, the coordinates before deformation are A(x0, y0, z), and the coordinates after deformation are A(x1, y1, z). Only the x and y coordinates change, meaning the finger deformation only occurs in the x and y planes. Clearly, in the linear model, the tangent plane of any node p and its corresponding node p′ of its adjacent finger must intersect at a point on a plane 60° away from both fingers. Therefore, the ideal width W of any node p... di =L pM =L Opx tan 60°, while L Op = x p The starting closing node can be set according to actual conditions, and the embodiment starts closing from node 2.

[0061] Step 5. Convergence judgment: set the convergence condition, judge whether the error of the obtained ideal width and the current width (the existing soft finger-shaped gripper finger width) meets the convergence condition, if it meets, complete the gripper shape optimization, output the numerical model, otherwise return to step 2, until the convergence condition is met;

[0062] The embodiment sets the convergence condition as: ∑ i (|W i -W di |)≤1mm, and the final node coordinates and rational width of the embodiment are shown in the following table, and the unit is mm:

[0063]

[0064]

[0065]

[0066] Step 6. Output the planar geometric model: according to the optimized numerical model, the finger width of any point of the gripper finger meeting the closed grasping target is obtained, and the planar geometric model is designed.

[0067] The interpolation method can be used to obtain the finger width of any point between two nodes, and then the coordinates of any point on the optimized finger boundary are obtained, and then the curve fitting method can be used to obtain the finger boundary curve. If the coordinates of the two end points A and C of any continuous line segment AC in space are known, as well as the distance of any point p on AC to A and the distance to C, the coordinates of p can be calculated by interpolation method. The width here is equivalent to the z-direction coordinate value. Thus the gripper planar geometric model is output, and the optimized gripper planar geometric model is shown in Figure 10 .

[0068] Obviously, the above embodiment is only an example for clear illustration, and is not a limitation on the implementation. For ordinary skilled persons in the art, other different forms of changes or variations can be made on the basis of the above description. Here, all the implementations do not need to be exhausted, and the obvious changes or variations derived therefrom are still within the protection scope of the present application.

Claims

1. A method for optimizing the planar unfolded shape of a soft, finger-like gripper, characterized in that, The finger width of the original soft gripper is optimized to achieve the purpose of forming a closed grip on the target object after bending the discretely distributed fingers. The optimization method meets the following assumptions: 1) The finger is regarded as a linear object, i.e. an object with a size much larger in one orthogonal direction than in the other two directions; 2) Only in-plane deformation occurs during the finger gripping process; The optimization method includes the following steps: Step 1. Establish an equivalent linear model: according to the existing soft gripper planar unfolded geometric model, analyze the functional characteristics of each part of the gripper and establish an equivalent linear model along the length direction of the finger; Step 2. Calculate the deformation numerical model of the gripper and iterate: according to the actual situation of the gripper being driven and constrained, the deformation process of the gripper is calculated numerically to simulate the gripping process of the gripper; Step 3. Termination condition judgment: set the termination condition to judge whether the deformation degree of the gripper reaches the set termination condition; if yes, go to the next step; if not, jump to step 2; Step 4. Calculate the ideal width: according to the numerical model obtained under the termination condition and the geometric relationship, calculate the ideal width of the finger to achieve the goal of closed gripping of the gripper; Step 5. Convergence judgment: set the convergence condition to judge whether the error between the ideal width obtained and the current width (the existing soft finger-shaped gripper finger width) meets the convergence condition; if yes, complete the shape optimization of the gripper, output the numerical model, otherwise return to step 2 until the convergence condition is met; Step 6. Output the planar geometric unfolded model: according to the optimized numerical model, get the width of any point of the gripper finger that meets the closed gripping goal, and design the planar unfolded geometric model.

2. A method for shape optimization of a planar deployment of a soft robotic finger gripper as claimed in claim 1, wherein: In step 2, the equivalent linear model obtained in step 1 is divided by finite elements to establish a finite element model, and the node parameters are initialized.

3. A method for shape optimization of a planar deployment of a soft robotic finger gripper as claimed in claim 2, wherein: The node initialization process includes the following steps: 1) initializing a node width coefficient (R i ) to represent a bending resistance cross-sectional coefficient at node i; wherein i = 1, 2,..., n, n is the total number of nodes; 2) Initialize the arc length (s i ) and tangent azimuth angle (θ i ) of the node.

4. A method for shape optimization of a planar deployment of a soft robotic finger gripper as claimed in claim 1, wherein: In Step 2, the tangent orientation angle (θ i ) of the key node is constrained as a boundary condition, and the driving feature is introduced as a constraint condition and iteration start and end conditions.

5. A method for shape optimization of a planar deployment of a soft robotic finger gripper as recited in claim 1, wherein: In step 2, according to the principle that the internal energy of a linear object reaches a minimum value in its stable deformation state, any state during the deformation process of the gripper can be modeled statically, and the internal energy V is calculated according to expression (1); V = U -∑ i W i (1) where W i is the work done by external forces on node i, and U is the potential energy of the linear object, which is calculated according to expression (2). U = U flex + U ext + U grav (2) where U flwx , U ext , and U grav represent the bending potential energy, the stretching potential energy, and the gravitational potential energy of the object, respectively, and the bending potential energy U flex , the stretching potential energy U ext may be calculated according to expressions (3), (4), respectively, and the gravitational potential energy U grav may be calculated according to expression (5), assuming that the gravitational force acts along the x-axis. where R f represents the bending stiffness of the object, R e represents the tensile stiffness of the object, D represents the weight per unit length of the object, K represents the curvature at an arbitrary point on the object, and ε represents the tensile strain of an arbitrary point on the linear object along its central axis.

6. A method for shape optimization of a planar deployment of a soft robotic finger gripper as recited in claim 1, wherein: In step 6, the interpolation method is used to get the finger width of any point between two nodes, and then the coordinates of any point on the boundary of the optimized finger are obtained, and then the curve fitting method is used to get the finger boundary curve, so as to output the planar unfolded geometric model of the gripper.

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