Reconfiguration planning method for rope-pulled parallel robots for human-robot interaction

Abstract

The present invention discloses a reconfiguration planning method for a rope-pulled parallel robot for human-machine interaction, belonging to the field of rope-pulled parallel robot configuration planning. The method comprises the following steps: Step 1: setting parameters of the rope-pulled parallel robot and establishing a dynamic equation for the moving platform; Step 2: setting an admittance model between the moving platform and the interacting person, and establishing a dynamic relationship between the two; Step 3: setting parameters and dynamic equations according to Step 1, and establishing a mathematical model of a force-feasible workspace; Step 4: dividing the human-machine interaction process into an interactive force phase and a non-interactive force phase according to the magnitude and duration of the force applied by the interacting person on the robot, and setting evaluation indicators for the two phases according to the mathematical model in Step 3; Step 5: using the evaluation indicators in combination with the admittance model, using a reconstruction strategy to solve for the optimal rope indexing point position, thereby completing the reconfiguration planning. The method can solve the rope indexing point position in real time, thereby improving the workspace size and operational freedom during the human-machine interaction process.

Description

Technical Field

[0001] The present invention relates to the technical field of configuration planning of a rope-pulled parallel robot, and in particular to a rope-pulled parallel robot reconfiguration planning method for human-machine interaction. Background Art

[0002] Traditional rigid robots have limited workspaces due to their structure, and safety in the event of collisions between rigid links and humans is difficult to guarantee. However, rope-pulled parallel robots, with their large workspaces, large payloads, inherent flexibility of their rope drive, and modular structure, are easily reconfigurable and well-suited for physical human-robot interaction tasks. Adjusting the rope's release point position not only changes the rope's spatial distribution for obstacle avoidance but also modifies the robot's dynamic characteristics. Therefore, dynamic adjustments to the rope's release point position during human-robot interaction allow for greater freedom of movement and the completion of interactive tasks within a larger workspace. However, evaluating the performance of a set of rope's release point positions is challenging. The evaluation criteria should balance the mechanical properties of the rope-pulled parallel robot with the performance of human-robot interaction, which presents a challenge. Furthermore, since the human's next action in human-robot interaction tasks is difficult to fully predict, the rope's release point needs to be able to adjust rapidly to accommodate real-time changes in human behavior.

[0003] Chinese invention patent CN202210280216.2 discloses a reconstruction strategy for a three-degree-of-freedom rope-pulled parallel robot with four movable rope indexing points. However, this method is only applicable to reconfigurable rope-pulled parallel robots of a specific configuration, and can only plan the rope indexing point trajectory offline for a fixed trajectory. It is not applicable to rope-pulled parallel robots for human-computer interaction tasks.

[0004] In view of this, the present invention is proposed. Summary of the Invention

[0005] The purpose of the present invention is to provide a rope-pulled parallel robot reconstruction planning method for human-machine interaction, which ensures the real-time solution of the rope index output point position through a hierarchical strategy, improves the workspace size and operation freedom during the human-machine interaction process, and thus solves the above-mentioned technical problems existing in the prior art.

[0006] The purpose of the present invention is achieved through the following technical solutions:

[0007] A reconfiguration planning method for a rope-pulled parallel robot for human-robot interaction, comprising:

[0008] Step 1: Set the parameters of the rope-pulled parallel robot and establish the dynamic equation of the moving platform;

[0009] Step 2: Set up an admittance model between the moving platform of the rope-pulled parallel robot and the interacting person, and establish the dynamic relationship between the moving platform motion and the interaction force according to the admittance model;

[0010] Step 3: Based on the parameters of the rope-pulled parallel robot set in step 1 and the established dynamic equations of the moving platform, a mathematical model of the force feasible workspace of the rope-pulled parallel robot is established;

[0011] Step 4: Based on the magnitude and duration of the force applied by the human on the rope-pulled parallel robot, the human-robot interaction process is divided into a phase with interactive force and a phase without interactive force. In the phase without interactive force, the workspace performance of the rope-pulled parallel robot itself is optimized. The evaluation indicators for the phase with interactive force and the phase without interactive force are set according to the mathematical model established in Step 3.

[0012] In step 5, based on the determined interactive force stage and non-interactive force stage and the corresponding evaluation indicators, combined with the admittance model in step 2, the optimal rope index output point position is solved by using the reconstruction strategy with asynchronous control cycle and reconstruction cycle to complete the reconstruction planning of the rope-pulled parallel robot.

[0013] Compared with the prior art, the rope-pulled parallel robot reconfiguration planning method for human-machine interaction provided by the present invention has the following beneficial effects:

[0014] By setting asynchronous control cycles and reconstruction cycles, the computational complexity of solving repetitive optimization problems is reduced, the computational efficiency is improved, and the real-time nature of the solution is guaranteed, making it suitable for rapidly changing human-computer interaction functions. By setting evaluation indicators for the human-computer interaction process of the rope-pulled parallel robot, the evaluation can be targeted at human-computer interaction tasks to evaluate the advantages and disadvantages of the rope indexing point positions, facilitating the selection of a more optimal rope indexing point configuration. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0016] Figure 1 This is a flow chart of a rope-pulled parallel robot reconfiguration planning method suitable for physical human-machine interaction provided by an embodiment of the present invention.

[0017] Figure 2 This is a specific flow chart of a rope-pulled parallel robot reconfiguration planning method suitable for physical human-machine interaction provided by an embodiment of the present invention.

[0018] Figure 3 A schematic structural diagram of a rope-pulled parallel robot suitable for physical human-machine interaction provided by an embodiment of the present invention.

[0019] Figure 4 This is a control block diagram of a rope-pulled parallel robot reconfiguration planning method suitable for physical human-machine interaction provided by an embodiment of the present invention.

[0020] Figure 5 Schematic diagram of the relationship between the rope index exit speed upper limit set in the optimization problem in an embodiment of the present invention and the rope index exit speed upper limit in each control cycle. DETAILED DESCRIPTION

[0021] The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the specific content of the present invention. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments, and do not constitute a limitation of the present invention. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0022] First, the following terms may be used in this article:

[0023] The term “and / or” means that either or both of them can be realized at the same time. For example, X and / or Y includes both “X” or “Y” and “X and Y”.

[0024] The terms "include," "comprises," "contains," "has," or other similar expressions should be interpreted as non-exclusive. For example, "including certain technical features (such as raw materials, components, ingredients, carriers, dosage forms, materials, dimensions, parts, components, mechanisms, devices, steps, procedures, methods, reaction conditions, processing conditions, parameters, algorithms, signals, data, products, or manufactured articles)" should be interpreted as including not only the technical features explicitly listed, but also other technical features known in the art that are not explicitly listed.

[0025] The term "consisting of" excludes any technical features not explicitly listed. If used in a claim, this term renders the claim closed, excluding any technical features other than those explicitly listed, except for conventional impurities associated with them. If this term appears only in a clause of a claim, it limits only the elements explicitly listed in that clause; elements listed in other clauses are not excluded from the claim as a whole.

[0026] Unless otherwise specified or limited, the terms "mounted," "connected," "connect," and "fixed" should be interpreted broadly. For example, they can refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediary; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in this document based on specific circumstances.

[0027] When concentration, temperature, pressure, size or other parameters are expressed in the form of a numerical range, the numerical range should be understood to specifically disclose all ranges formed by the pairing of any upper limit, lower limit, or preferred value within the numerical range, regardless of whether the range is explicitly stated. For example, if a numerical range of "2 to 8" is stated, the numerical range should be interpreted as including ranges of "2 to 7," "2 to 6," "5 to 7," "3 to 4 and 6 to 7," "3 to 5 and 7," "2 and 5 to 7," etc. Unless otherwise specified, the numerical ranges stated herein include both their endpoints and all integers and fractions within the numerical range.

[0028] The terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings and are only for the convenience and simplification of description, and do not explicitly or implicitly indicate that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore should not be understood as a limitation to this document.

[0029] The scheme provided by the present invention is described in detail below. The contents not described in detail in the examples of the present invention belong to the prior art known to professionals in this field. If specific conditions are not specified in the examples of the present invention, they are carried out according to conventional conditions in the field or conditions recommended by the manufacturer. If the manufacturer of the reagents or instruments used in the examples of the present invention is not specified, they are all conventional products that can be purchased commercially.

[0030] like Figure 1 As shown, an embodiment of the present invention provides a reconfiguration planning method for a rope-pulled parallel robot for human-machine interaction, which ensures real-time solution of rope index output point positions through a hierarchical strategy, thereby improving the workspace and freedom during the human-machine interaction process, including:

[0031] Step 1: Set the parameters of the rope-pulled parallel robot and establish the dynamic equation of the moving platform;

[0032] Step 2: Set up an admittance model between the moving platform of the rope-pulled parallel robot and the interacting person, and establish the dynamic relationship between the moving platform motion and the interaction force based on the admittance model; this can ensure the stability of the human-machine interaction;

[0033] Step 3: Based on the parameters of the rope-pulled parallel robot set in step 1 and the established dynamic equations of the moving platform, a mathematical model of the force feasible workspace of the rope-pulled parallel robot is established;

[0034] Step 4: Based on the magnitude and duration of the force applied by the human on the rope-pulled parallel robot, the human-robot interaction process is divided into a phase with interaction force and a phase without interaction force. In the phase without interaction force, the workspace performance of the rope-pulled parallel robot is optimized to enable it to cope with interaction forces in any direction. Evaluation indicators for the phase with interaction force and the phase without interaction force are set based on the mathematical model established in Step 3.

[0035] In step 5, based on the determined interactive force stage and non-interactive force stage and the corresponding evaluation indicators, combined with the admittance model in step 2, the optimal rope index output point position is solved by using the reconstruction strategy with asynchronous control cycle and reconstruction cycle to complete the reconstruction planning of the rope-pulled parallel robot.

[0036] like Figure 3 As shown, preferably, in the above method, the reconstructed and planned rope-pulled parallel robot includes:

[0037] A rope indexing device, 12 reels, A rope and a moving platform, is a positive integer, and the rope index point movement uses slide rails, unmanned vehicles or drones according to different installation methods;

[0038] The moving platform adopts a three-degree-of-freedom particle type moving platform or a six-degree-of-freedom rigid body type moving platform;

[0039] A rope is wound around each drum, and each drum is connected to a motor 11, which can be rotated by the motor to retract and release the connected rope; the other end of each rope is successively passed around the guide pulley of the rope index out device above it and is connected to the moving platform, and each rope confines the moving platform to the polyhedron surrounded by each rope index out point 13.

[0040] Preferably, in step 1 of the above method, the parameters of the rope-pulled parallel robot are set and the dynamic equation of the moving platform is established in the following manner, including:

[0041] The origin is the point on the ground where the outer frame of the parallel robot is pulled by the rope. Setting the static coordinate system of the rope-pulled parallel robot , with the center of mass of the moving platform as the origin Set the dynamic coordinate system , the moving coordinate system follows the translation and rotation of the moving platform;

[0042] The dynamic equation of the moving platform of the rope-pulled parallel robot is established according to the set parameters.

[0043] Preferably, in step 1 of the above method, a point on the ground where the outer frame of the rope-pulled parallel robot is located is used as the origin in the following manner: Setting the static coordinate system of the rope-pulled parallel robot , with the center of mass of the moving platform of the parallel robot pulled by the rope as the origin Set the dynamic coordinate system of the rope-pulled parallel robot , the moving coordinate system follows the translation and rotation of the moving platform; according to the set parameters, the dynamic equation of the moving platform of the rope-pulled parallel robot is established, including:

[0044] The reconstructed rope-pulled parallel robot consists of Rope drive with degrees of freedom, and define the rope index exit point of the rope-pulled parallel robot as , each rope index point is expressed in the matrix form in the static coordinate system ,in, i =1,2…m, the superscript T indicates the transpose of the matrix;

[0045] The rope connection point on the moving platform is set as , the coordinates in the moving coordinate system are , where b i is the rope connection point on the moving platform, i =1,2…m, is the driven coordinate system { } to the static coordinate system { }, the position and posture of the moving platform are expressed as , where the center of mass position of the moving platform is expressed as , P x is the x-axis coordinate of the center of mass of the moving platform, P y is the y-axis coordinate of the center of mass of the moving platform, P z is the z-axis coordinate of the center of mass of the moving platform, They are the Euler angles describing the rotation of the rigid body posture around the x-axis, the Euler angles around the y-axis, and the Euler angles around the z-axis, respectively. The rope vector of the i-th rope is obtained from the rope connection point to the rope index point. Expressed as ;

[0046] The dynamic equation of the moving platform of the rope-pulled parallel robot is established as:

[0047] (1);

[0048] In the above formula (1), is the structural matrix corresponding to the rope-pulled parallel robot, The direction of the force and torque provided by the i-th rope, i =1,2…m, is the posture of the moving platform, The matrix of each rope index point in the static coordinate system; is the rope tension vector of the rope-pulled parallel robot is the cable tension of the i-th rope, i =1,2…m; is the mass matrix of the rope-towing parallel robot; Coriolis and centripetal matrices for a rope-pulled parallel robot; is the gravity vector of the rope-pulled parallel robot; and are the velocity and acceleration of the moving platform of the rope-pulled parallel robot, respectively; The interactive force exerted by the interactor on the moving platform during human-computer interaction.

[0049] Preferably, in step 2 of the above method, the admittance model set between the moving platform of the rope-pulled parallel robot and the interacting person is:

[0050] (2);

[0051] In the above formula (2), and are the inertia term and damping term in the admittance model respectively; It is the interaction force exerted by the interactor on the moving platform during the human-computer interaction process; 、 are the expected acceleration and expected velocity of the moving platform of the rope-pulled parallel robot, respectively.

[0052] Preferably, in step 2 of the above method, the dynamic relationship between the motion of the moving platform and the interaction force is established according to the admittance model in the following manner, including:

[0053] The interaction force is measured by sensors installed on the dynamic platform Finally, the admittance model described in Equation (2) is solved to obtain a reference trajectory that conforms to the admittance model. The reference trajectory is input as the desired trajectory into the PD controller of the rope-pulled parallel robot for tracking, thus achieving a follow-up control effect. Since the dynamic platform must maintain its current position when the interaction force is removed during the follow-up process, the stiffness term in the model is ignored.

[0054] Preferably, in step 3 of the above method, a mathematical model of the force feasible workspace of the rope-pulled parallel robot is established according to the parameters of the rope-pulled parallel robot set in step 1 and the dynamic equation of the moving platform established in the following manner, including:

[0055] The mathematical model of the force feasible workspace of the rope-pulled parallel robot is established as follows:

[0056] (3);

[0057] In the above formula (3), is the structural matrix corresponding to the rope-pulled parallel robot, , is the posture of the moving platform, The matrix of each rope index point in the static coordinate system; is the rope tension vector of the rope-pulled parallel robot; is the resultant force of the rope tension on the moving platform of the parallel robot; is the lower limit of the rope tension vector, and its components are all set to 10N; is the upper limit of the rope tension vector, and its components are all set to 50N;

[0058] The mathematical model of the above formula (3) is expressed by the following inequality using the hyperplane moving method:

[0059] (4);

[0060] In the above formula (4), the matrix and vector According to the structure matrix corresponding to the rope-pulled parallel robot, the hyperplane movement method is used , the lower limit of the rope tension vector , the upper limit of the rope tension vector get.

[0061] Preferably, in step 4 of the above method, the evaluation indexes for the interactive stage and the evaluation indexes for the non-interactive stage are set respectively according to the mathematical model established in step 3 in the following manner, including:

[0062] According to the mathematical model expressed by the inequality of formula (4), the evaluation index of the non-interaction stage of formula (5) is set, that is, the capacity margin for:

[0063] (5);

[0064] In the above formula (5), For along the The normal vector of the hyperplane, the margin of the resultant force that the rope can provide, , is the number of hyperplanes of the rope-pulled parallel robot. Each hyperplane has two normal vectors in opposite directions. Normal vectors; is a vector No. Quantity is a matrix No. Quantity is the resultant force of the rope tension on the moving platform of the parallel robot;

[0065] The evaluation index of the interactive stage of formula (6) is for:

[0066] (6);

[0067] In the above formula (6), is the set of all hyperplane normal vector subscripts that have acute angles with the interaction force vector; is the hyperplane normal vector The angle between it and the interaction force vector; For along the The normal vector of the hyperplane, the margin of the resultant force that the rope can provide, , is the number of hyperplanes possessed by the rope-pulled parallel robot; 、 are vectors The jth component of Quantity 、 The matrices The jth component of Quantity is the resultant force of the rope tension on the moving platform of the parallel robot; is the normalized weight coefficient set according to the angle between the interaction force and the normal vector, and the superscript T represents the transpose of the matrix;

[0068] Set the optimization problem objective function of formula (7) for: (7);

[0069] Taking the force feasibility condition of formula (8) and the position and velocity of the rope index point satisfying the upper and lower limit constraints as the constraint conditions, formula (8) is:

[0070] (8);

[0071] In the above formula (8), the matrix and vector According to the structure matrix corresponding to the rope-pulled parallel robot, the hyperplane movement method is used , the lower limit of the rope tension vector , the upper limit of the rope tension vector get; is the resultant force of the rope tension on the moving platform of the parallel robot; Point location for the rope index constraint, The lower limit of the position constraint of the rope index point is set. The upper limit of the rope index point position constraint is set. In the x-axis and y-axis directions, the position constraint is centered at the initial position and extends 0.5m in the positive and negative directions. The lower limit of the z-axis is 0m and the upper limit is 2.4m. This position constraint is adjusted according to the configuration of the rope-pulled parallel robot to ensure that the suspension configuration or the pulling configuration is always established. Index point velocity for the rope constraint, The lower limit of the velocity constraint of the rope index point is The upper limit of the speed constraint of the rope index exit point is set to 0.05m / s along the single axis direction.

[0072] The above-mentioned evaluation index set for the rope-pulled parallel robot in the human-machine interaction process combines the margin of the feasible force set along the direction of the interaction force and the projection of the vector of the desired force to each boundary of the feasible force set to the interaction force. This allows the evaluation to be targeted at the human-machine interaction task, and can evaluate the advantages and disadvantages of the rope index release point position, facilitating the selection of a better rope index release point configuration.

[0073] like Figure 2 、 Figures 4 and 5 As shown, preferably, in step 5 of the above method, the optimal rope index exit point position is obtained by using a reconstruction strategy with asynchronous control period and reconstruction period in the following manner, including:

[0074] Step 51: At the start of the human-machine interaction task, asynchronous control cycles and reconstruction cycles are set in the external computing device that controls the robot. A real-time control thread running in the control cycle and a reconstruction optimization thread running in the reconstruction cycle are set in parallel. The real-time control thread is responsible for collecting sensor data, updating state variables in real time, and tracking the desired trajectory obtained by the admittance model and the reconstruction optimization thread.

[0075] Setting the control period , set the reconstruction cycle , the reconstruction period is an integer multiple of the control period, that is, ,in ; and initialize the following variables: Control cycle count variable , reconstruct the cycle count variable , count the number of control cycles in which the interaction force amplitude is greater than the threshold within the reconstruction cycle , the initial time is ;

[0076] Step 52: Set up the execution flow of the real-time control thread: measure the interaction force in real time through the force sensor , according to the rope index point position Different installation methods use corresponding methods to measure the rope length through the encoder , perform kinematic forward calculation based on the measured rope length or use external measuring equipment to obtain the position of the moving platform ;

[0077] Calculate interaction force -norm and set the threshold In contrast, if , then the number of control cycles that makes the interaction force amplitude greater than the threshold within the reconstruction cycle is Add 1 to update the control cycle number, that is, ;like , then the number of control cycles in which the interaction force amplitude is kept greater than the threshold within the reconstruction cycle is Same as the previous cycle, that is ;

[0078] According to the known interaction and the parameters of the admittance model and , by solving the differential equation to obtain the expected acceleration of the moving platform and expected speed , combined with the position of the dynamic platform Get the desired position of the moving platform , obtain the expected position of the rope index out point from the calculation results of the reconstruction optimization thread, set the PD controller to track the expected position according to the known expected position of the moving platform and the expected position of the rope index out point, and drive the servo motor to adjust the rope length and the position of the rope index out point;

[0079] Each time a control cycle is completed, the control cycle count variable Add 1 to update the control cycle count variable ,Right now ; When the control cycle count variable When it indicates that a reconstruction cycle has ended, reset the control cycle count variable , and trigger the reconstruction optimization thread to solve the rope index exit point position of the next reconstruction cycle;

[0080] Step 53: Set the execution flow of the reconstruction optimization thread: In the first reconstruction cycle, keep the rope index exit position the same as the initial position, set the speed and acceleration to 0, and do not perform optimization;

[0081] Then reconstruct the cycle count variable Add 1 to update the reconstruction cycle count variable ,Right now , indicating that the rope index point position obtained by the upcoming nonlinear optimization solution is The position of the rope index point within the reconstruction cycle;

[0082] Reset the count variable after updating the number of control cycles in which the interaction force amplitude is greater than the threshold within the reconstruction cycle , the reconstruction optimization thread waits for one tenth of the reconstruction cycle, that is, ,total Control cycles, during which the interaction force amplitude is greater than the threshold value. , if the interaction force amplitude is greater than the threshold value in more than half of the control cycles within the statistical time, that is, the number of control cycles , then this reconstruction cycle is considered to be an interactive stage, and the evaluation index capacity margin of the interactive stage of formula (6) and the optimization problem objective function of formula (7) are used as the objective function of the optimization problem, and the constraint condition of formula (8) is used as the constraint of the optimization problem. The sequential quadratic programming method is used to solve the nonlinear optimization problem and obtain the first The rope index output point position at the end of the reconstruction cycle; otherwise, if , then this reconstruction cycle is considered to be the non-interaction force stage, and the evaluation index of the non-interaction force stage of formula (5) and the optimization problem objective function of formula (7) are used as the objective function of the optimization problem, and the constraint condition of formula (8) is used as the constraint of the optimization problem. The sequential quadratic programming method is used to solve the nonlinear optimization problem and obtain the first The position of the rope index output point at the end of each reconstruction cycle;

[0083] According to the current rope index point position ,speed , acceleration And the rope index point position at the end of the reconstruction cycle obtained by solving the optimization problem , set the rope index exit speed at the end of the reconstruction cycle to , the acceleration is 0, based on which the S-type trajectory planning method is used to generate the The position, velocity and acceleration of the rope index point in each control cycle within a reconstruction cycle. Due to the large number of constraints in the S-type trajectory planning, it is impossible to ensure that the rope index point velocity strictly meets the velocity constraint in formula (8) , but can be set according to the speed constraint and reconstruction cycle in the constraint condition of formula (8) Obtain the upper speed limit of the rope index output point in each control cycle and speed limit ;

[0084] Finally, the rope index exit point position of each control cycle after trajectory planning is passed to the real-time control thread;

[0085] Step 54: Set an external trigger signal to stop the real-time control thread and the reconstruction optimization thread when the human-computer interaction task ends, and terminate the trajectory tracking control and nonlinear optimization.

[0086] Preferably, in step 5 of the above method, when the reconstruction strategy starts and the interactor does not start physical human-computer interaction, the rope index exit point is automatically adjusted according to the no-interaction-force stage to a position suitable for interaction forces of any possible incoming direction;

[0087] In step 5, when the sequential quadratic programming method is used to solve the nonlinear optimization problem, the maximum number of iterations is set to 50; the parameters of the PD controller of the rope-pulled parallel robot are set to 、 、 and ,in, and are the proportional coefficient matrix and differential coefficient matrix controlling the rope length, and They are the proportional coefficient matrix and differential coefficient matrix of the control rope index point position respectively.

[0088] In summary, it can be seen that the embodiment method of the present invention reduces the computational complexity of solving repetitive optimization problems by setting asynchronous control cycles and reconstruction cycles, improves computing efficiency, and ensures real-time solution, making it suitable for rapidly changing human-computer interaction functions; by designing an evaluation index for the rope-traction parallel robot used in the human-computer interaction process that combines the margin of the feasible force set along the direction of the interaction force and the projection of the vector of the desired force to each boundary of the feasible force set to the interaction force, the evaluation index can be used for the human-computer interaction task to evaluate the advantages and disadvantages of the rope index output point position, so as to facilitate the selection of a better rope index output point configuration.

[0089] In order to more clearly demonstrate the technical solution and technical effects provided by the present invention, the solution provided by the embodiment of the present invention is described in detail with reference to specific embodiments below.

[0090] Example 1

[0091] This embodiment provides a method for reconfiguration planning of a rope-pulled parallel robot for human-machine interaction. The method is performed in the following steps (see Figure 1 ):

[0092] Step 1: Introduce a virtual rope index point based on the positional relationship between the rope and the guide pulley of the rope-pulled parallel robot, construct a robot kinematic model, and obtain the closed-chain constraint equation based on the closed-chain structure of the robot: The ground center of the fixed frame of the rope-pulled parallel robot is used as the global coordinate system of the rope-pulled parallel robot. Origin ;

[0093] use ( ) indicates the virtual rope index point, which is the intersection of two rope extension lines, one is the extension line of the rope before entering the guide pulley, and the other is the extension line of the rope connecting the moving platform after leaving the guide pulley. The position vector is ,in and is a known constant, For variables; use Indicates the virtual rope index out point Dynamic Platform The virtual rope length vector between is the virtual rope length vector The model, Denoted as the virtual rope length vector exist Projection of the plane and Positive direction angle, is the virtual rope length vector and Angle of the negative axis (see Figure 3 ); The robot's dynamic platform position vector is used Indicates that the rope-pulling parallel robot has The motion branches are connected to the same moving platform. The equation of one of the branches is subtracted from the equation of the remaining branches to get constraint equations;

[0094] According to the manifold generated by the closed-chain constraint equation, the tangent space is used to locally approximate the manifold, and the orthogonal basis for establishing the tangent space is obtained: Considering that the constraint equation reduces the dimension of the joint space to a low-dimensional manifold, since the manifold is difficult to be represented globally by independent variables, the tangent space is used to locally approximate the manifold in a small neighborhood, and the Jacobian matrix of the constraint equation is derived. Through the null space step 1 of the Jacobian matrix, the static coordinate system of the rope-pulled parallel robot is set. The origin is the point on the ground where the outer frame of the parallel robot is pulled by the rope. , moving coordinate system The origin is the center of mass of the moving platform , and the moving coordinate system follows the translation and rotation of the moving platform. Assume that the rope-pulled parallel robot has degrees of freedom and is driven by ropes. Define the rope index point as , each rope index point can be expressed as a matrix in the static coordinate system, and the rope connection point on the moving platform is , the coordinates in the moving coordinate system are , is the driven coordinate system { } to the static coordinate system { }, the position of the moving platform can be expressed as p z , α , β , γ ] T , where the center of mass position of the moving platform can be expressed as p z ] T , from this we can get The rope vector of the root rope pointing from the rope connection point to the rope index exit point can be expressed as ; The robot structure is as follows Figure 2 As shown; establish the dynamic equation of the moving platform of the rope-pulled parallel robot;

[0095] The dynamic equation of the moving platform is:

[0096] (1);

[0097] In the formula (1), The structural matrix corresponding to the rope-pulled parallel robot; is the rope tension vector of the rope-pulling parallel robot; 、 、 are the mass matrix, Coriolis and centripetal matrices, and gravity vector of the rope-pulled parallel robot, respectively; and are the velocity and acceleration of the moving platform of the rope-pulled parallel robot respectively; The interactive force exerted by the interactor on the moving platform during human-computer interaction.

[0098] Step 2: To achieve the effect of the moving platform following the operator in human-computer interaction, an admittance model is set between the moving platform and the interacting person to establish the dynamic relationship between the moving platform motion and the interaction force, which can ensure the stability of human-computer interaction.

[0099] The admittance model is: (2);

[0100] In the formula (2), and are the inertia term and damping term in the admittance model respectively; It is the interaction force exerted by the interactor on the moving platform during the human-computer interaction process; 、 are the expected acceleration and expected velocity of the moving platform of the rope-pulled parallel robot respectively; the interaction force is measured by the sensor installed on the moving platform The reference trajectory that conforms to the admittance model can then be obtained by solving Equation (2). This trajectory is then input into the PD controller as the desired trajectory for tracking, achieving a servo control effect. Since the platform remains at its current position when the interaction force is removed during servo control, the stiffness term in the model is ignored.

[0101] Step 3, establishing a mathematical model of the force-feasible workspace: Based on the parameters of the rope-pulled parallel robot set in step 1, the force-feasible workspace of the rope-pulled parallel robot is established as the following mathematical model:

[0102] (3);

[0103] In the formula (3), The structural matrix corresponding to the rope-pulled parallel robot; is the rope tension vector of the rope-pulling parallel robot; is the resultant force of the rope tension that the moving platform of the parallel robot is expected to receive; is the lower limit of the rope tension vector, and its components are all set to 10N; is the upper limit of the rope tension vector, and its components are all set to 50N; the formula (3) can be expressed by the following inequality using the hyperplane moving method:

[0104] (4);

[0105] In the formula (4), the matrix and vector The hyperplane moving method is used to calculate the structural matrix corresponding to the rope-pulling parallel robot. , the lower limit of the rope tension vector , the upper limit of the rope tension vector get;

[0106] Step 4: Establish an optimization problem with the position of the rope index point as a variable: divide the human-machine interaction process into an interactive force stage and a non-interactive force stage according to the magnitude and duration of the force exerted by the interacting person on the robot. In the non-interactive force stage, optimize the workspace performance of the rope-pulled parallel robot itself so that it can cope with the interactive force in any direction that may come. Therefore, according to the formula (4), the evaluation index capacity margin of the non-interactive force stage is proposed:

[0107] (5);

[0108] In the formula (5), For along the The normal vector of the hyperplane, the margin of the resultant force that the rope can provide, , is the number of hyperplanes of the rope-pulled parallel robot. Since each hyperplane has two normal vectors in opposite directions, there are Normal vectors; is a vector No. Quantity is a matrix No. Quantity is the resultant force of the rope tension that the moving platform of the parallel robot is expected to receive;

[0109] The evaluation indicators for the interactive stage are set as:

[0110] (6);

[0111] In the formula (6), is the set of all hyperplane normal vector subscripts that have acute angles with the interaction force vector; is the hyperplane normal vector The angle between it and the interaction force vector; For along the The normal vector of the hyperplane, the margin of the resultant force that the rope can provide, , is the number of hyperplanes possessed by the rope-pulled parallel robot; 、 is a vector The Components and Quantity 、 is a matrix The Components and Quantity is the resultant force of the rope tension that the moving platform of the parallel robot is expected to receive; is the normalized weight coefficient set according to the angle between the interaction force and the normal vector, and the superscript T represents the transpose of the matrix;

[0112] Set the optimization problem objective function as: (7);

[0113] The constraints take into account the feasibility of the force and the position and speed of the rope index point to meet the upper and lower limit constraints:

[0114] (8);

[0115] In the formula (8), the matrix and vector The hyperplane moving method is used to calculate the structural matrix corresponding to the rope-pulling parallel robot. , the lower limit of the rope tension vector , the upper limit of the rope tension vector get; is the resultant force of the rope tension that the moving platform of the parallel robot is expected to receive; Position constraints are set for the rope index points. In the x- and y-axis directions, the position constraints extend 0.5 m in both the positive and negative directions, centered on the initial position. In the z-axis, the upper and lower limits are 0 m and the upper limit is 2.4 m. Furthermore, the position constraints need to be adjusted based on the configuration of the reconfigurable rope-pulled parallel robot, for example, ensuring that the suspension or pulling configuration always holds. The rope index point velocity constraint is set, and the upper limit of the absolute value of the velocity of the rope index point along the single axis direction is set to 0.05m / s.

[0116] like Figure 2 、 Figures 3 to 5 As shown, in step 5, the optimal rope index exit point position is solved using the reconstruction strategy:

[0117] Step 51: Open up parallel real-time control threads and reconstruction optimization threads: The real-time control thread is responsible for collecting sensor data, updating state variables in real time, and tracking the desired trajectory obtained by the admittance model and reconstruction optimization thread; the control block diagram is as follows Figure 3 As shown; set the control cycle , set the reconstruction cycle , the reconstruction period is an integer multiple of the control period, that is, ,in ; and initialize variables: control cycle counter , reconstruct the cycle counter , count the number of control cycles in which the interaction force amplitude is greater than the threshold within the reconstruction cycle , the initial time is ;

[0118] Step 52: Set up real-time control thread execution process: measure interaction force in real time through force sensor , measuring the rope length by encoder , the rope index point position Depending on the installation method, such as installation on a slide rail, unmanned vehicle or drone, different methods can be used to measure the position of the moving platform. The kinematic solution can be calculated based on the rope length or obtained using external measurement equipment;

[0119] Calculate interaction force -norm and set the threshold In contrast, if , then update the number of control cycles in which the interaction force amplitude is greater than the threshold within the reconstruction cycle ;if , the counting variable remains the same as the previous cycle ;

[0120] In the interactive force and the parameters of the admittance model (2) and Under known conditions, the expected motion of the moving platform can be obtained by solving the differential equation and , combined with the position of the dynamic platform The desired moving platform position can be obtained The expected position of the rope index exit point can be obtained from the calculation results of the reconstruction optimization thread. Under the condition that the expected motion of the dynamic platform and the expected motion of the rope index exit point are known, a PD controller is designed to track the expected motion and drive the servo motor to adjust the rope length and the position of the rope index exit point;

[0121] Every time a control cycle is completed, the control cycle count variable is updated ;when When a reconstruction cycle is completed, reset , and trigger the reconstruction optimization thread to solve the rope index exit point position of the next reconstruction cycle;

[0122] Step 53: Set the reconstruction optimization thread execution process: In the first reconstruction cycle, keep the rope index exit position the same as the initial position, set the speed and acceleration to 0, and do not optimize;

[0123] Then update the reconstruction cycle count variable , indicating that the rope index point position obtained by the upcoming nonlinear optimization solution is The position of the rope index point within the reconstruction cycle;

[0124] Reset the count variable after updating it , refactoring and optimizing thread waiting , which is one tenth of the reconstruction cycle, a total of Control cycles, during which the interaction force amplitude is greater than the threshold value. , if the interaction force amplitude is greater than the threshold value in more than half of the control cycles within the statistical time, that is , then this reconstruction cycle is considered to be an interactive force stage, and the above formulas (5) and (7) are used as the objective function of the optimization problem, and the above formula (8) is used as the constraint of the optimization problem. The sequential quadratic programming method is used to solve the nonlinear optimization problem and obtain the first The rope index output point position at the end of the reconstruction cycle; otherwise, if , then this reconstruction cycle is considered to be a stage without interaction force, and the above formulas (6) and (7) are used as the objective function of the optimization problem, and the above formula (8) is used as the constraint of the optimization problem. The sequential quadratic programming method is used to solve the nonlinear optimization problem, and the first The position of the rope index output point at the end of each reconstruction cycle;

[0125] According to the current rope index point position ,speed , acceleration And the optimization problem solution , set the rope index exit speed at the end of the reconstruction cycle to , the acceleration is 0, based on which the S-type trajectory planning method is used to generate the The position, velocity, and acceleration of the rope index point in each control cycle within a reconstruction cycle. Due to the large number of constraints in the S-type trajectory planning, it is impossible to ensure that the rope index point velocity strictly meets the velocity constraint in formula (8) , but can be set according to the speed constraint and reconstruction period set in formula (8) Obtain the upper speed limit of the rope index output point in each control cycle and speed limit ; Finally, the rope index exit point motion of each control cycle after trajectory planning is passed to the real-time control thread; the relationship between the rope index exit point speed upper limit set in the optimization problem and the rope index exit point speed upper limit in each control cycle is as follows Figure 4 As shown;

[0126] Step 54: Set an external trigger signal to stop the real-time control thread and the reconstruction optimization thread at the end of the interactive task, and terminate the trajectory tracking control and nonlinear optimization.

[0127] In summary, the reconstruction planning method according to the embodiment of the present invention has at least the following advantages compared with the prior art:

[0128] (1) By introducing an admittance model that does not include stiffness terms, the relationship between the interacting person and the robot is established, and the moving platform can stop at any position in space to achieve the following task, ensuring smooth and flexible physical human-robot interaction.

[0129] (2) By designing an interaction index that combines the interaction force direction and the workspace of the rope-pulled parallel robot as the objective function of the optimization problem, the performance of human-robot interaction on the rope-pulled parallel robot was quantitatively evaluated.

[0130] (3) By designing asynchronous control cycles and reconstruction cycles and limiting the number of iterations when solving nonlinear problems, it is ensured that the solution of the nonlinear optimization problem can be completed within each reconstruction cycle, so that the rope index point can change in real time during the physical human-computer interaction process.

[0131] (4) By using S-type trajectory planning, the rope index point can achieve smooth movement while ensuring that the constraints are met as much as possible.

[0132] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing related hardware through a program. The program can be stored in a computer-readable storage medium. When executed, the program can include the processes in the above-described method embodiments. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0133] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by any person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims. The information disclosed in the background technology section of this article is only intended to deepen the understanding of the overall background technology of the present invention, and should not be regarded as an admission or any form of implication that the information constitutes prior art already known to those skilled in the art.

Claims

1. A rope-pulled parallel robot reconfiguration planning method for human-machine interaction, characterized in that: include: Step 1: Set the parameters of the rope-pulled parallel robot and establish the dynamic equation of the moving platform; Step 2: Set up an admittance model between the moving platform of the rope-pulled parallel robot and the interacting person, and establish the dynamic relationship between the moving platform motion and the interaction force according to the admittance model; Step 3: Based on the parameters of the rope-pulled parallel robot set in step 1 and the established dynamic equations of the moving platform, a mathematical model of the force feasible workspace of the rope-pulled parallel robot is established; Step 4: Based on the magnitude and duration of the force applied by the human on the rope-pulled parallel robot, the human-robot interaction process is divided into a phase with interactive force and a phase without interactive force. In the phase without interactive force, the workspace performance of the rope-pulled parallel robot itself is optimized. The evaluation indicators for the phase with interactive force and the phase without interactive force are set according to the mathematical model established in Step 3. In step 5, based on the determined interactive force stage and non-interactive force stage and the corresponding evaluation indicators, combined with the admittance model in step 2, the optimal rope index output point position is solved by using the reconstruction strategy with asynchronous control cycle and reconstruction cycle to complete the reconstruction planning of the rope-pulled parallel robot.

2. The method for reconfiguration planning of a rope-pulled parallel robot for human-machine interaction according to claim 1, characterized in that: In the method, the reconstructed and planned rope-pulled parallel robot includes: m rope indexing devices, m drums, m ropes and a moving platform, where m is a positive integer and the rope indexing points are installed using slide rails; The moving platform adopts a three-degree-of-freedom particle type moving platform or a six-degree-of-freedom rigid body type moving platform; A rope is wound around each drum, and each drum is connected to a motor, which can rotate under the drive of the motor to retract and release the connected rope; the other end of each rope is sequentially passed around the guide pulley of the rope index outgoing device above it and then connected to the moving platform, and each rope confines the moving platform to the polyhedron surrounded by each rope index outgoing point.

3. The method for reconfiguration planning of a rope-pulled parallel robot for human-machine interaction according to claim 1 or 2, characterized in that: In step 1, the parameters of the rope-pulled parallel robot are set and the dynamic equation of the moving platform is established in the following manner, including: The static coordinate system O-xyz of the rope-pulled parallel robot is set with a point on the ground where the outer frame of the rope-pulled parallel robot is located as the origin O, and the dynamic coordinate system Px of the rope-pulled parallel robot is set with the center of mass of the moving platform of the rope-pulled parallel robot as the origin P. p y p z p , the moving coordinate system follows the translation and rotation of the moving platform; The dynamic equation of the moving platform of the rope-pulled parallel robot is established according to the set parameters.

4. The method for reconfiguration planning of a rope-pulled parallel robot for human-machine interaction according to claim 3, characterized in that: In step 1, the static coordinate system O-xyz of the rope-pulled parallel robot is set with a point on the ground where the outer frame of the rope-pulled parallel robot is located as the origin O, and the dynamic coordinate system Px of the rope-pulled parallel robot is set with the center of mass of the moving platform of the rope-pulled parallel robot as the origin P. p y p z p , the moving coordinate system follows the translation and rotation of the moving platform; according to the set parameters, the dynamic equation of the moving platform of the rope-pulled parallel robot is established, including: The reconstructed rope-pulled parallel robot is driven by m ropes and has n degrees of freedom. The rope index output point of the rope-pulled parallel robot is defined as U i , each rope index point is expressed in the static coordinate system as a matrix form U=[u1,u2,...,u i ,...,u m ] T , where i = 1, 2…m, and the superscript T represents the transpose of the matrix; The rope connection point on the moving platform is set as B i , the coordinates in the moving coordinate system are B=[b1,b2,...,b i ,...,b m ] T , where b i is the rope connection point on the moving platform, i=1,2…m, is the rotation matrix from the moving coordinate system {P} to the static coordinate system {O}, and the position of the moving platform is expressed as x = [p x ,p y ,p z ,α,β,γ] T , where the center of mass position of the moving platform is expressed as p = [p x ,p y ,p z ] T , P x is the x-axis coordinate of the center of mass of the moving platform, P y is the y-axis coordinate of the center of mass of the moving platform, P z is the z-axis coordinate of the center of mass of the moving platform, α, β, and γ are the Euler angles describing the rotation of the rigid body around the x-axis, the y-axis, and the z-axis, respectively. The rope vector l of the i-th rope is obtained from the rope connection point to the rope index point. i Expressed as The dynamic equation of the moving platform of the rope-pulled parallel robot is established as: In the above formula (1), W(x,U)=[w1,w2,...,w i ,...,w m ] T is the structural matrix corresponding to the rope-pulled parallel robot, w i is the direction of the force and torque provided by the i-th rope, i = 1, 2…m, x is the position of the dynamic platform, U is the matrix of the rope index points in the static coordinate system; T = [T1, T2, ..., T i ...,T m ] T is the rope tension vector of the rope-pulled parallel robot, T i is the cable force of the i-th rope, i = 1, 2…m; M(x) is the mass matrix of the rope-pulled parallel robot; are the Coriolis and centripetal matrices of the rope-pulled parallel robot; G(x) is the gravity vector of the rope-pulled parallel robot; and are the velocity and acceleration of the moving platform of the rope-pulled parallel robot respectively; f h The interactive force exerted by the interactor on the moving platform during the human-computer interaction process.

5. The method for reconfiguration planning of a rope-pulled parallel robot for human-machine interaction according to claim 1 or 2, characterized in that: In step 2, the admittance model set between the moving platform of the rope-pulled parallel robot and the interacting person is: In the above formula (2), M a and C a are the inertia term and damping term in the admittance model respectively; f h It is the interaction force exerted by the interactor on the moving platform during the human-computer interaction process; are the expected acceleration and expected velocity of the moving platform of the rope-pulled parallel robot, respectively.

6. The method for reconfiguration planning of a rope-pulled parallel robot for human-machine interaction according to claim 5, characterized in that: In step 2, a dynamic relationship between the motion of the moving platform and the interaction force is established according to the admittance model in the following manner, including: The interaction force f is measured by the sensor installed on the dynamic platform h After that, the reference trajectory that conforms to the admittance model is obtained by solving the admittance model described in formula (2). The reference trajectory is input as the desired trajectory into the PD controller of the rope-pulled parallel robot for tracking to achieve the follow-up control effect.

7. The method for reconfiguration planning of a rope-pulled parallel robot for human-machine interaction according to claim 4, characterized in that: In step 3, a mathematical model of the force feasible workspace of the rope-pulled parallel robot is established according to the parameters of the rope-pulled parallel robot set in step 1 and the dynamic equations of the moving platform established in the following manner, including: The mathematical model of the force feasible workspace of the rope-pulled parallel robot is established as follows: In the above formula (3), W is the structure matrix corresponding to the rope-pulled parallel robot, W(x,U)=[w1,w2,...,w i ,...,w m ] T , x is the position of the moving platform, U is the matrix of each rope index point in the static coordinate system; T=[T1,T2,...,T i ...,T m ] T is the rope tension vector of the rope-pulled parallel robot; w e is the resultant force of the rope pulling force on the moving platform of the parallel robot; T min is the lower limit of the rope tension vector, and its components are all set to 10N; T max is the upper limit of the rope tension vector, and its components are all set to 50N; The mathematical model of the above formula (3) is expressed by the following inequality using the hyperplane moving method: Cw e ≤d (4); In the above formula (4), the matrix C and the vector d are calculated by the hyperplane moving method according to the structure matrix W corresponding to the rope-pulled parallel robot and the lower limit T of the rope tension vector. min , the upper limit of the rope tension vector T max get.

8. The method for reconfiguration planning of a rope-pulled parallel robot for human-machine interaction according to claim 7, characterized in that: In step 4, the evaluation indexes for the interactive stage and the non-interactive stage are respectively set according to the mathematical model established in step 3 in the following manner, including: According to the mathematical model expressed by the inequality of formula (4), the evaluation index of the non-interaction stage of formula (5) is set, that is, the capacity margin η w for: In the above formula (5), is the margin of the resultant force that the rope can provide along the normal vector of the jth hyperplane, j = 1, 2, ..., 2n s , n s is the number of hyperplanes of the rope-pulled parallel robot. Each hyperplane has two normal vectors in opposite directions, and there are 2n in total. s Normal vector; d j is the jth component of vector d; c j is the j-th component of matrix C; The evaluation index η of the interactive stage in formula (6) is set as i for: In the above formula (6), is the set of all hyperplane normal vector subscripts that have acute angles with the interaction force vector; is the hyperplane normal vector c σ The angle between the interaction force vector and the interaction force vector; d σ is the σth component of vector d; c σ is the σth component of the matrix C; is the normalized weight coefficient set according to the angle between the interaction force and the normal vector, and the superscript T represents the transpose of the matrix; The objective function f of the optimization problem of formula (7) is set to: f = -η i (7); Taking the force feasibility condition of formula (8) and the position and velocity of the rope index point satisfying the upper and lower limit constraints as the constraint conditions, formula (8) is: In the above formula (8), Index the point position U constraint for the rope. U The lower limit of the position constraint of the rope index point is set. The upper limit of the rope index point position constraint is set. In the x-axis and y-axis directions, the position constraint is centered at the initial position and extends 0.5m in the positive and negative directions. The lower limit of the z-axis is 0m and the upper limit is 2.4m. This position constraint is adjusted according to the configuration of the rope-pulled parallel robot to ensure that the suspension configuration or the pulling configuration is always established. Index point velocity for the rope constraint, The lower limit of the velocity constraint of the rope index point is The upper limit of the speed constraint of the rope index exit point is set to 0.05m / s along the single axis direction.

9. The method for reconfiguration planning of a rope-pulled parallel robot for human-machine interaction according to claim 8, characterized in that: In step 5, the optimal rope index exit point position is obtained by using a reconstruction strategy with asynchronous control period and reconstruction period in the following manner, including: Step 51: At the start of the human-machine interaction task, asynchronous control cycles and reconstruction cycles are set in the external computing device that controls the robot. A real-time control thread running in the control cycle and a reconstruction optimization thread running in the reconstruction cycle are also set up in parallel. The real-time control thread is responsible for collecting sensor data, updating state variables in real time, and tracking the desired trajectory obtained by the admittance model and the reconstruction optimization thread. Set the control period t c =5ms, set the reconstruction period t r =1s, the reconstruction period is an integer multiple of the control period, that is, t r =n r t c , where n r =200; and initialize the following variables: Control cycle count variable k c =0, reconstruct cycle count variable k r = 0, count the number of control cycles m in which the interaction force amplitude is greater than the threshold within the reconstruction cycle c =0, the initial time is t0; Step 52: Set up the execution flow of the real-time control thread: measure the interaction force f in real time through the force sensor h , according to the different installation methods of the rope index point position U, the rope length q is measured by the encoder in a corresponding manner, and the kinematic forward solution is calculated based on the measured rope length or the position x of the moving platform is obtained using an external measuring device; Calculate the L2 norm of the interaction force ||f h ||2 and set the threshold f t In contrast, if || f h ||2>f t , then the number of control cycles m that makes the interaction force amplitude greater than the threshold within the reconstruction cycle is c Add 1 to update the control cycle number, that is, m c =m c +1; if ||f h ||2≤f t , then the number of control cycles m in which the interaction force amplitude is kept greater than the threshold value within the reconstruction cycle is c Same as the previous cycle, that is, m c =m c ; According to the known interaction force f h and the parameter M of the admittance model a and C a , by solving the differential equation to obtain the expected acceleration of the moving platform and expected acceleration Combined with the moving platform position x, the expected position x of the moving platform is obtained d , obtain the expected position of the rope index out point from the calculation results of the reconstruction optimization thread, set the PD controller to track the expected position according to the known expected position of the moving platform and the expected position of the rope index out point, and drive the servo motor to adjust the rope length and the position of the rope index out point; Each time a control cycle is completed, the control cycle counting variable k c Add 1 to update the control cycle count variable k c , that is, k c =k c +1; when the control cycle count variable k c =n r When it indicates that a reconstruction cycle has ended, reset the control cycle count variable k c = 0, and trigger the reconstruction optimization thread to solve the rope index point position of the next reconstruction cycle; Step 53: Set the execution flow of the reconstruction optimization thread: In the first reconstruction cycle, keep the rope index exit position the same as the initial position, set the speed and acceleration to 0, and do not perform optimization; Then let the reconstruction cycle count variable k r Add 1 to update the reconstruction cycle count variable k r , that is, k r =k r +1, indicating that the rope index point position obtained by the upcoming nonlinear optimization solution is the kth r The position of the rope index point within the reconstruction cycle; Reset the count variable m after updating the number of control cycles in which the interaction force amplitude is greater than the threshold within the reconstruction cycle c =0, the reconstruction optimization thread waits for one tenth of the reconstruction cycle, that is, total control cycles, and the number of control cycles during which the interaction force amplitude is greater than the threshold is counted m c , if the interaction force amplitude is greater than the threshold value in more than half of the control cycles within the statistical time, that is, the number of control cycles This reconstruction cycle is considered as the interactive force stage. The evaluation index capacity margin of the interactive force stage in formula (6) and the optimization problem objective function in formula (7) are used as the objective function of the optimization problem. The constraint condition in formula (8) is used as the constraint of the optimization problem. The sequential quadratic programming method is used to solve the nonlinear optimization problem and obtain the kth r The rope index output point position at the end of the reconstruction cycle; otherwise, if This reconstruction cycle is considered as the non-interaction force stage. The evaluation index of the non-interaction force stage of formula (5) and the optimization problem objective function of formula (7) are used as the objective function of the optimization problem. The constraint condition of formula (8) is used as the constraint of the optimization problem. The sequential quadratic programming method is used to solve the nonlinear optimization problem and obtain the kth r The position of the rope index output point at the end of each reconstruction cycle; According to the current rope index point position U d (t0+k r t r ),speed acceleration And the rope index point position U at the end of the reconstruction cycle obtained by solving the optimization problem d (t0+(k r +1)t r ), set the rope index exit speed at the end of the reconstruction cycle to The acceleration is 0, and the S-type trajectory planning method is used to generate the kth r The position, velocity and acceleration of the rope index point of each control cycle in the reconstruction cycle are calculated according to the velocity constraint set in the constraint condition of formula (8) and the reconstruction cycle t r Obtain the upper speed limit of the rope index output point in each control cycle and speed limit Ensure that the speed of the rope index point strictly meets the speed constraint in formula (8) Finally, the rope index exit point position of each control cycle after trajectory planning is passed to the real-time control thread; Step 54: Set an external trigger signal to stop the real-time control thread and the reconstruction optimization thread when the human-computer interaction task ends, and terminate the trajectory tracking control and nonlinear optimization.

10. The method for reconfiguration planning of a rope-pulled parallel robot for human-machine interaction according to claim 9, characterized in that: In step 5, when the reconstruction strategy starts and the interactor does not start physical human-computer interaction, the rope index exit point is automatically adjusted according to the no-interaction-force stage to a position suitable for interaction forces of any possible incoming direction; In step 5, when solving the nonlinear optimization problem using the sequential quadratic programming method, the maximum number of iterations is set to 50; the parameters of the PD controller of the rope-pulled parallel robot are set to K Pq =0.08I,K Dq =0.0005I,K PU =0.1I and K DU =0.01I, where K Pq and K Dq are the proportional coefficient matrix and differential coefficient matrix for controlling the rope length, K PU and K DU They are the proportional coefficient matrix and differential coefficient matrix of the control rope index point position respectively.

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