A six-degree-of-freedom platform structure optimization method and device

Abstract

A six-degree-of-freedom platform structure optimization method and device described in the present application relates to the field of data processing technology. The present application sets a large number of simulation quantities for simulating the construction of a six-degree-of-freedom platform to form a simulation quantity set. Each time, a target number of simulation quantities are selected from the simulation quantity set and sequentially input into the six-degree-of-freedom model to obtain the result quantity of the model output, forming a simulation group of the target number, and obtaining the local optimal solution in the simulation group of the target number through the optimal solution algorithm. By repeatedly inputting the target number of simulation quantities in the simulation quantity set into the six-degree-of-freedom platform model and executing subsequent steps, multiple local optimal solutions are obtained, a global optimal solution is selected from the local optimal solutions, and a six-degree-of-freedom platform is designed according to the constant parameters of the global optimal solution. In this way, by setting a large number of simulation quantities, multiple local optimal solutions that meet the second constraint condition are obtained, and the global optimal solution is screened from the local optimal solution, and a six-degree-of-freedom platform is designed according to the constant parameters of the global optimal solution.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a six-degree-of-freedom platform structure optimization method and device. Background Art

[0002] In the design and manufacturing process of the six-degree-of-freedom platform, most companies only design the parameters of the six-degree-of-freedom platform based on experience, such as the height of the platform, hinge position data, actuator length, etc. The six-degree-of-freedom platform system designed in this way may not meet the technical index requirements, or even if the technical index requirements are met, the design and use of the entire six-degree-of-freedom platform cannot be optimized. Summary of the invention

[0003] In view of this, an embodiment of the present application provides a six-degree-of-freedom platform structure optimization method and device, aiming to obtain the optimal six-degree-of-freedom platform design parameters under the constraints of the design indicators.

[0004] In a first aspect, an embodiment of the present application provides a six-degree-of-freedom platform structure optimization method, comprising:

[0005] Acquire a target number of analog quantities from an analog quantity set, wherein the analog quantity set includes a plurality of different analog quantities, each of the analog quantities includes a constant parameter and a posture state quantity of at least one degree of freedom; the constant parameter is a parameter that satisfies a first constraint condition and is used to construct a six-degree-of-freedom platform, and the posture state quantity is used to determine a working position of an upper platform in the six-degree-of-freedom platform;

[0006] Inputting a target number of simulation quantities into the six-degree-of-freedom platform model, respectively obtaining result quantities of the simulation output of the six-degree-of-freedom platform model; the six-degree-of-freedom platform is used to simulate and construct the working state of the six-degree-of-freedom platform according to the simulation quantities; the result quantities include the working lengths of the six actuators included in the six-degree-of-freedom platform;

[0007] Generate the target number of simulation groups, the simulation groups including simulation quantities input to the six-degree-of-freedom platform model and result quantities output by the six-degree-of-freedom platform model based on the simulation quantities;

[0008] Inputting the target number of simulation groups into an optimal solution algorithm to obtain a local optimal solution output by the optimal solution algorithm that satisfies a second constraint condition;

[0009] Returning to execute the step of obtaining the target number of analog quantities from the analog quantity set and subsequent steps until a set number of local optimal solutions are obtained, wherein the set number of local optimal solutions are different from each other;

[0010] The best local optimal solution is selected from the set number of local optimal solutions as the global optimal solution, and the constant parameters included in the global optimal solution are used to construct a six-degree-of-freedom platform.

[0011] Optionally, obtaining a target number of analog quantities from the analog quantity set includes:

[0012] Get the target number of analog quantities from the analog quantity set in chronological order according to the set trend.

[0013] Optionally, after obtaining the target number of analog quantities from the analog quantity set, the method further includes:

[0014] The target number of analog quantities is deleted from the analog quantity set.

[0015] Optionally, the constant parameters include the distance between the upper platform and the lower platform in the six-degree-of-freedom platform, the radius of the lower circle formed by multiple Hooke's joints in the lower platform, the radius of the upper circle formed by multiple Hooke's joints in the upper platform, the central angle of the near hinge point in the same platform, and the central angle of the far hinge point in the same platform.

[0016] Optionally, the first constraint condition is that the radius of the upper circle is smaller than the radius of the lower circle and the central angle of the near hinge point in the same platform is smaller than the central angle of the far hinge point in the same platform.

[0017] Optionally, inputting the target number of simulation groups into an optimal solution algorithm to obtain a local optimal solution output by the optimal solution algorithm that satisfies a second constraint condition includes:

[0018] If the target number of simulation groups does not satisfy the second constraint condition of the optimal solution algorithm, then inputting the target number of simulation quantities into the six-degree-of-freedom platform model and performing subsequent operations until the target number of simulation groups satisfying the second constraint condition is obtained;

[0019] If the target number of simulation groups meets the second constraint of the optimal solution algorithm, a local optimal solution in the target number of simulation groups is obtained according to an optimization function, wherein the optimization function is set by combining a first parameter obtained by maximizing the workspace and a second parameter obtained by dexterity.

[0020] Optionally, obtaining the local optimal solution in the target number of simulation groups according to the optimization function includes:

[0021] Calculate an optimized value for each simulation group in the target number of simulation groups, the optimized value being the absolute value of the target difference divided by two, the target difference being the difference obtained by subtracting the first parameter from the second parameter;

[0022] The simulation value with the smallest optimization value in the simulation groups of the target number is determined as the local optimal solution.

[0023] Optionally, the optimal solution algorithm is a particle swarm algorithm or a genetic mutation algorithm.

[0024] Optionally, the second constraint condition is that the ratio of the working length of each actuator in the result quantity in each group of the simulation group to the initial length of the actuator does not exceed a preset ratio, the angle between the actuator length direction and the normal vector of the lower platform is between positive and negative forty-five degrees, the working space of the six-degree-of-freedom platform constructed by each simulation group in the target number of simulation groups does not exceed a preset working range, and the dexterity calculated for each simulation group in the target number of simulation groups is not an infinite value.

[0025] Optionally, the six-degree-of-freedom platform model includes:

[0026] An input unit, used for receiving the analog quantity;

[0027] A coordinate conversion unit is used to convert the coordinates of the upper platform in the upper platform dynamic coordinate system into the coordinates of the upper platform in the upper platform static coordinate system according to the analog quantity; the origin of the upper platform dynamic coordinate system is the center of mass of the upper platform in the six-degree-of-freedom platform, the upper platform dynamic coordinate system maintains a fixed relationship with the upper platform, and the upper platform static coordinate system is the coordinate system when the dynamic coordinates are in an initial position; the coordinate conversion unit includes a rotation matrix unit and a translation matrix unit, and the rotation matrix unit is provided with a transformation matrix for converting the upper platform dynamic coordinate system to the upper platform static coordinate system; the translation matrix unit is used to calculate the displacement of the origin of the dynamic coordinate system relative to the static coordinate system;

[0028] An upper platform unit is used to translate the coordinates of the six Hooke's joints in the upper platform in the static coordinate system of the upper platform by a set distance to obtain the coordinate points of the six Hooke's joints in the upper platform in the static coordinate system of the lower platform;

[0029] The lower platform unit is used to obtain the coordinate points of the six Hooke's hinges in the lower platform in the static coordinate system of the lower platform;

[0030] The actuator length calculation module is used to calculate the working lengths of the six actuators according to the coordinate points of the six Hooke's hinges in the upper platform in the static coordinate system of the lower platform and the coordinate points of the six Hooke's hinges in the lower platform in the static coordinate system of the lower platform, through the point-to-point distance formula; each of the six actuators is hinged to the upper platform through a Hooke's hinge, and each of the six actuators is also hinged to the lower platform through a Hooke's hinge.

[0031] In a second aspect, the present application also proposes a six-degree-of-freedom platform structure optimization device, comprising:

[0032] A first acquisition module is used to acquire a target number of analog quantities from an analog quantity set, wherein the analog quantity set includes a plurality of different analog quantities, each of which includes a constant parameter and a posture state quantity of at least one degree of freedom; the constant parameter is a parameter that satisfies a first constraint condition and is used to construct a six-degree-of-freedom platform, and the posture state quantity is used to determine a working position of an upper platform in the six-degree-of-freedom platform;

[0033] A simulation module is used to input a target number of simulation quantities into the six-degree-of-freedom platform model, and obtain the result quantities of the simulation output of the six-degree-of-freedom platform model respectively; the six-degree-of-freedom platform is used to simulate and construct the working state of the six-degree-of-freedom platform according to the simulation quantities; the result quantities include the working lengths of the six actuators included in the six-degree-of-freedom platform;

[0034] A generation module, used for generating the target number of simulation groups, wherein the simulation group includes a simulation quantity input to the six-degree-of-freedom platform model and a result quantity output by the six-degree-of-freedom platform model based on the simulation quantity;

[0035] A calculation module, used for inputting the target number of simulation groups into an optimal solution algorithm to obtain a local optimal solution output by the optimal solution algorithm that satisfies a second constraint condition;

[0036] A second acquisition module is used to return to execute the step of acquiring a target number of analog quantities from the analog quantity set and subsequent steps until a set number of local optimal solutions are acquired, and the set number of local optimal solutions are different from each other;

[0037] A confirmation module is used to select the best local optimal solution from the set number of local optimal solutions as the global optimal solution, and the constant parameters included in the global optimal solution are used to construct a six-degree-of-freedom platform

[0038] The embodiment of the present application provides a method and device for optimizing the structure of a six-degree-of-freedom platform. The present application obtains a target number of simulated quantities from a simulated quantity set, wherein the simulated quantity set includes a plurality of different simulated quantities, each of which includes a constant parameter and a posture state quantity of at least one degree of freedom; inputs the simulated quantities of the target number in the simulated quantity set into a preset six-degree-of-freedom platform model, and respectively uses the six-degree-of-freedom platform to simulate and construct the working state of the six-degree-of-freedom platform according to the simulated quantity, and obtains the result quantity of the simulation output of the six-degree-of-freedom platform model; generates a simulation group of the target number, wherein the simulation group includes the simulated quantity input into the six-degree-of-freedom platform model and the result quantity output based on the simulated quantity of the six-degree-of-freedom platform model; inputs the simulation group of the target number into the optimal solution algorithm, and obtains the local optimal solution output by the optimal solution algorithm that satisfies the second constraint condition; returns to execute the simulated quantity obtained from the simulated quantity set and subsequent steps until a set number of local optimal solutions are obtained, and the set number of local optimal solutions are different from each other; selects the best local optimal solution from the set number of local optimal solutions as the global optimal solution, and the constant parameters included in the global optimal solution are used to construct a six-degree-of-freedom platform. The target number of analog quantities is obtained from the analog quantity set multiple times, and each analog quantity in the analog quantity set can simulate the working state of a six-degree-of-freedom platform. The local optimal solution that meets the second constraint condition in the simulation group of the target number is obtained through the optimal solution algorithm, and the analog quantity set is obtained multiple times to generate multiple local optimal solutions, and the global optimal solution is obtained from the multiple local optimal solutions. Finally, the constant parameters included in the global optimal solution are used to construct the six-degree-of-freedom platform. In this way, the global optimal solution that meets the constraint condition can be obtained by screening the analog quantity set including a large number of analog quantities, and the optimal six-degree-of-freedom platform design parameters in the analog quantity set can be obtained. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in this embodiment or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0040] Figure 1 A schematic diagram of a six-degree-of-freedom platform structure optimization method provided in an embodiment of the present application;

[0041] Figure 2 A schematic diagram of the structure of a six-degree-of-freedom platform structure optimization method device for a data acquisition device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0042] The lower platform in the six-degree-of-freedom platform remains fixed, and the upper platform is pushed to move to a suitable working position under the joint action of six actuators. One end of each actuator is hinged to the upper platform through a Hooke's hinge, and the other end is hinged to the lower platform through a Hooke's hinge.

[0043] In the design and manufacturing process of the six-degree-of-freedom platform, most companies only design the parameters of the six-degree-of-freedom platform based on experience, such as the height of the platform, hinge position data, actuator length, etc. The six-degree-of-freedom platform system designed in this way may not meet the technical index requirements, or even if the technical index requirements are met, the design and use of the entire six-degree-of-freedom platform cannot be optimized.

[0044] The present application sets constant parameters for constructing a six-degree-of-freedom platform and simulates the simulation of the posture state of the upper platform in the six-degree-of-freedom platform. The simulation is set multiple times without repetition to form a simulation set. Each time, the target number of simulations is selected from the simulation set and sequentially input into the six-degree-of-freedom model, the six-degree-of-freedom platform is simulated and constructed, and the working length of the six actuators in the six-degree-of-freedom platform is simulated and output as the result. The simulation and the result of the simulation form a set of simulation groups, and the simulation of the target number of simulations obtains the simulation group of the target number. The local optimal solution in the simulation group of the target number is obtained by the optimal solution algorithm. By repeatedly inputting the simulation of the target number of simulations in the simulation set into the six-degree-of-freedom platform model and executing subsequent steps, multiple local optimal solutions are obtained, the global optimal solution is selected from the local optimal solution, and the six-degree-of-freedom platform is designed according to the constant parameters of the global optimal solution. By setting a large number of simulations, multiple local optimal solutions that meet the second constraint condition are obtained, and the global optimal solution is screened from the local optimal solution to obtain the optimal six-degree-of-freedom platform design parameters in the simulation set.

[0045] Obviously, the described embodiments are only a 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 ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0046] Figure 1 A schematic diagram of a six-degree-of-freedom platform structure optimization method provided in an embodiment of the present application, see Figure 1 , a six-degree-of-freedom platform structure optimization method provided in an embodiment of the present application includes:

[0047] S101. Obtain a target number of analog quantities from a set of analog quantities, wherein the set of analog quantities includes a plurality of different analog quantities, each of which includes a constant parameter and a posture state quantity of at least one degree of freedom; the constant parameter is a parameter that satisfies a first constraint condition and is used to construct a six-degree-of-freedom platform, and the posture state quantity is used to determine a working position of an upper platform in the six-degree-of-freedom platform.

[0048] The constant parameters may include the distance between the upper platform and the lower platform in the six-degree-of-freedom platform, the radius of the lower circle formed by the multiple Hooke's joints in the lower platform, the radius of the upper circle formed by the multiple Hooke's joints in the upper platform, the central angle of the near hinge point in the same platform, and the central angle of the far hinge point in the same platform. The sum of the central angle of the near hinge point in the same platform and the central angle of the far hinge point in the platform is 120 degrees. The various parameter values ​​in the constant parameters can be set arbitrarily under the condition of satisfying the first constraint.

[0049] The first constraint condition may be that the radius of the upper circle is smaller than the radius of the lower circle and the central angle of the near hinge point in the same platform is smaller than the central angle of the far hinge point in the same platform.

[0050] The posture state quantity can be one or more of the six degrees of freedom of the moving coordinate axis fixed to the upper platform (displacement in the X-axis direction, rotation angle in the X-axis direction, displacement in the Y-axis direction, rotation angle in the Y-axis direction, displacement in the Z-axis direction, rotation angle in the Z-axis direction).

[0051] S102. Input a target number of simulation quantities into the six-degree-of-freedom platform model to obtain result quantities of the simulation output of the six-degree-of-freedom platform model; the six-degree-of-freedom platform is used to simulate and construct the working state of the six-degree-of-freedom platform according to the simulation quantities; the result quantities include the working lengths of the six actuators included in the six-degree-of-freedom platform.

[0052] The target quantity can be one hundred thousand or can be set as required.

[0053] The six-degree-of-freedom platform model is used to simulate and build a six-degree-of-freedom platform according to the simulation quantity, and can be established based on the software GCKontro l.

[0054] S103, generating the target number of simulation groups, wherein the simulation group includes a simulation quantity input into the six-degree-of-freedom platform model and a result quantity output by the six-degree-of-freedom platform model based on the simulation quantity.

[0055] Each simulation quantity and the result quantity obtained by the six-degree-of-freedom model form a simulation group, and the target number of simulation quantities can obtain the target number of result simulation groups.

[0056] S104: Input the target number of simulation groups into an optimal solution algorithm to obtain a local optimal solution output by the optimal solution algorithm that satisfies a second constraint condition.

[0057] The optimal solution algorithm can be a particle swarm algorithm or a genetic mutation algorithm.

[0058] The second constraint algorithm can be that the ratio of the working length of each actuator in the result quantity in each group of the simulation group to the initial length of the actuator does not exceed a preset ratio, the angle between the actuator length direction and the normal vector of the lower platform is between positive and negative forty-five degrees, the working space of the six-degree-of-freedom platform constructed by each simulation group in the target number of simulation groups does not exceed a preset working range, and the dexterity calculated for each simulation group in the target number of simulation groups is not an infinite value.

[0059] The actuator may be a direct-connected electric cylinder, a reciprocating electric cylinder or a hydraulic cylinder. When the above preset ratio is set, for a direct-connected electric cylinder, the preset ratio may be 1.2; for a reciprocating electric cylinder, the preset ratio may be 1.5; for a hydraulic cylinder, the preset ratio may be 1.7.

[0060] The infinite value of the non-infinite value of dexterity can be set to 10 to the power of 10.

[0061] The preset working range can be set according to user needs.

[0062] S105, returning to execute the step of obtaining a target number of analog quantities from the analog quantity set and subsequent steps until a set number of local optimal solutions are obtained, and the set number of local optimal solutions are different from each other.

[0063] In a possible implementation, the target number of analog quantities is obtained from the analog quantity set, which can be obtained from the analog quantity set in chronological order according to a set trend. The set trend can be obtained by analyzing the trend of the optimal solution from the local optimal solutions obtained multiple times in advance, or the trend can be determined based on human experience.

[0064] In another possible implementation, the analog quantity of the target quantity is obtained from the analog quantity set, and the analog quantity of the target quantity can be any analog quantity of the target quantity selected from the analog quantity set.

[0065] S106. Selecting the best local optimal solution from the set number of local optimal solutions as the global optimal solution, wherein the constant parameters included in the global optimal solution are used to construct a six-degree-of-freedom platform.

[0066] According to the above steps S101-S106, the constant parameters of the six-degree-of-freedom platform and the simulated values ​​of the posture state of the upper platform in the six-degree-of-freedom platform are constructed. The simulated value set includes multiple simulated values. Each time, the simulated values ​​of the target number are selected from the simulated value set and sequentially input into the six-degree-of-freedom model to obtain the result value. The simulated value and the result value of the simulated value form a set of simulation groups. The simulated values ​​of the target number obtain the simulation groups of the target number, and the local optimal solution in the simulation group of the target number is obtained by the optimal solution algorithm. By repeatedly inputting the simulated values ​​of the target number in the simulated value set into the six-degree-of-freedom platform model and executing subsequent steps, multiple local optimal solutions are obtained, and the global optimal solution is selected from the local optimal solutions. The six-degree-of-freedom platform is designed according to the constant parameters of the global optimal solution. By repeatedly obtaining the simulated values ​​of the target number, multiple local optimal solutions that meet the second constraint condition are obtained through the six-degree-of-freedom platform model and the optimal solution algorithm, and the global optimal solution is screened from the local optimal solution to obtain the optimal six-degree-of-freedom platform design parameters in the simulated value set.

[0067] In the present application embodiment, the above Figure 1 There are multiple possible implementations of step S104, which are described below. It should be noted that the implementations described below are only exemplary and do not represent all implementations of the embodiments of the present application.

[0068] In a possible implementation, inputting the target number of simulation groups into an optimal solution algorithm to obtain a local optimal solution output by the optimal solution algorithm that satisfies the second constraint condition includes:

[0069] A1. If the simulation group of the target number does not satisfy the second constraint condition of the optimal solution algorithm, then the simulation quantity of the target number is input into the six-degree-of-freedom platform model, and subsequent operations are performed until the simulation group of the target number that satisfies the second constraint condition is obtained.

[0070] A2. If the target number of simulation groups meets the second constraint of the optimal solution algorithm, then according to the optimization function, a local optimal solution in the target number of simulation groups is obtained, and the optimization function is set by combining the first parameter obtained by maximizing the workspace and the second parameter obtained by dexterity.

[0071] The optimization function is to calculate the optimization value of each simulation group in the target number of simulation groups, the optimization value is the absolute value of the target difference divided by two, and the target difference is the difference obtained by subtracting the first parameter from two and then subtracting the second parameter. The simulation value with the smallest optimization value in the target number of simulation groups is determined as the local optimal solution.

[0072] The computer programming language Python application programming interface (API) can be used to obtain the target number of simulation groups, and the local optimal solution can be obtained through the optimal solution algorithm set in the computer programming language Python.

[0073] The local optimal solution algorithm may be a particle swarm algorithm, or a genetic mutation algorithm, or of course, other algorithms for obtaining the optimal solution.

[0074] According to the above steps A1-A2, when the target number of simulation groups meets the second constraint, the optimal simulation group among the target number of simulation groups is obtained as the local optimal solution by comprehensively considering the optimization function of the two factors of workspace maximization and dexterity, ensuring that the six-degree-of-freedom platform can achieve good usage quality while meeting the second constraint required by the design indicators.

[0075] In the present application embodiment, the above Figure 1 After obtaining the target number of analog quantities from the analog quantity set in step S101 or step S105, there are possible implementations, which are introduced below. It should be noted that the implementations given in the following introduction are only exemplary and do not represent all implementations of the embodiments of the present application.

[0076] In a possible implementation manner, the target number of analog quantities is deleted from the analog quantity set.

[0077] In another possible implementation, a mark is set for the analog quantity of the target quantity in the analog quantity set. In addition to obtaining the analog quantity of the target quantity from the analog quantity set for the first time, the analog quantity of the target quantity obtained from the analog quantity set subsequently may include analog quantities with marks and analog quantities without marks.

[0078] In the present application embodiment, the above Figure 1 The six-degree-of-freedom platform model in step S102 has possible implementations, which are described in detail below. It should be noted that the implementations described below are only exemplary and do not represent all implementations of the embodiments of the present application.

[0079] In a possible implementation, the six-degree-of-freedom platform model includes:

[0080] An input unit, used for receiving the analog quantity;

[0081] The simulation includes constant parameters and at least one degree of freedom attitude state quantity. Six posture curves are obtained, and according to the change of time, the attitude state quantity of the upper platform in the simulation at any time on the six degrees of freedom can be obtained.

[0082] The constant parameters include the distance between the upper platform and the lower platform in the six-degree-of-freedom platform, the radius of the lower circle formed by the multiple Hooke's joints in the lower platform, the radius of the upper circle formed by the multiple Hooke's joints in the upper platform, the central angle of the near hinge point in the same platform, and the central angle of the far hinge point in the same platform.

[0083] A coordinate conversion unit is used to convert the coordinates of the upper platform in the upper platform dynamic coordinate system into the coordinates of the upper platform in the upper platform static coordinate system according to the analog quantity; the origin of the upper platform dynamic coordinate system is the center of mass of the upper platform in the six-degree-of-freedom platform, the upper platform dynamic coordinate system maintains a fixed relationship with the upper platform, and the upper platform static coordinate system is the coordinate system when the dynamic coordinates are in an initial position; the coordinate conversion unit includes a rotation matrix unit and a translation matrix unit, and the rotation matrix unit is provided with a transformation matrix for converting the upper platform dynamic coordinate system to the upper platform static coordinate system; the translation matrix unit is used to calculate the displacement of the origin of the dynamic coordinate system relative to the static coordinate system;

[0084] The upper platform unit is used to translate the coordinates of the six Hooke's joints in the upper platform in the static coordinate system of the upper platform by a set distance to obtain the coordinate points of the six Hooke's joints in the upper platform in the static coordinate system of the lower platform.

[0085] The hinge point coordinates of the six Hooke's hinges on the upper platform are obtained by the central angle formed by the center of the upper circle and the connecting lines of the two Hooke's hinges that are close to each other in the upper platform and the radius of the upper circle, and are represented by a 3X6 matrix.

[0086] The lower platform unit is used to obtain the coordinate points of the six Hooke's hinges in the lower platform in the static coordinate system of the lower platform.

[0087] The hinge point coordinates of the six Hooke's hinges of the lower platform are obtained by the central angle formed by the center of the lower circle and the connecting lines of the two Hooke's hinges that are close to each other in the lower platform and the radius of the lower circle, and are represented by a 3X6 matrix.

[0088] The actuator length calculation module is used to calculate the working lengths of the six actuators according to the coordinate points of the six Hooke's hinges in the upper platform in the static coordinate system of the lower platform and the coordinate points of the six Hooke's hinges in the lower platform in the static coordinate system of the lower platform, through the point-to-point distance formula; each of the six actuators is hinged to the upper platform through a Hooke's hinge, and each of the six actuators is also hinged to the lower platform through a Hooke's hinge.

[0089] By subtracting matrix 1 from matrix 2, the vectors of the six actuators are obtained, and the working length of the actuator is obtained by modular calculation. The working length of the actuator is subtracted from the initial length of the actuator to obtain the stroke of the actuator.

[0090] According to the above-mentioned six-degree-of-freedom platform model, the working state of the six-degree-of-freedom platform and the upper platform can be simulated, the positions of the upper platform Hooke's joint and the lower platform Hooke's joint relative to the static coordinates of the lower platform can be obtained, and then the working lengths of the six actuators can be calculated.

[0091] The velocity and acceleration of the actuator can be obtained by differentiating the change of the actuator working length over time.

[0092] The above are some specific implementations of a six-degree-of-freedom platform structure optimization method provided by the embodiment of the present application. Based on this, the present application also provides a corresponding device. The device provided by the embodiment of the present application will be introduced from the perspective of functional modularization.

[0093] Figure 2 A schematic diagram of a six-degree-of-freedom platform structure optimization device provided in an embodiment of the present application is shown in FIG. Figure 2 , a six-degree-of-freedom platform structure optimization device 200 provided in an embodiment of the present application includes:

[0094] A first acquisition module 201 is used to acquire a target number of analog quantities from an analog quantity set, wherein the analog quantity set includes a plurality of different analog quantities, each of which includes a constant parameter and a posture state quantity of at least one degree of freedom; the constant parameter is a parameter that satisfies a first constraint condition and is used to construct a six-degree-of-freedom platform, and the posture state quantity is used to determine a working position of an upper platform in the six-degree-of-freedom platform;

[0095] The simulation module 202 is used to input the target number of simulation quantities into the six-degree-of-freedom platform model, and obtain the result quantities of the simulation output of the six-degree-of-freedom platform model respectively; the six-degree-of-freedom platform is used to simulate and construct the working state of the six-degree-of-freedom platform according to the simulation quantities; the result quantities include the working lengths of the six actuators included in the six-degree-of-freedom platform;

[0096] A generation module 203 is used to generate the target number of simulation groups, wherein the simulation group includes a simulation quantity input to the six-degree-of-freedom platform model and a result quantity output by the six-degree-of-freedom platform model based on the simulation quantity;

[0097] A calculation module 204, configured to input the target number of simulation groups into an optimal solution algorithm, and obtain a local optimal solution output by the optimal solution algorithm that satisfies a second constraint condition;

[0098] The second acquisition module 205 is used to return to execute the step of acquiring the target number of analog quantities from the analog quantity set and subsequent steps until a set number of local optimal solutions are acquired, and the set number of local optimal solutions are different from each other.

[0099] The confirmation module 206 is used to select the best local optimal solution from the set number of local optimal solutions as the global optimal solution, and the constant parameters included in the global optimal solution are used to construct a six-degree-of-freedom platform.

[0100] According to the above-mentioned six-degree-of-freedom platform structure optimization device, the target number of analog quantities are obtained multiple times through the first acquisition module 201 and the second acquisition module 205, and multiple different local optimal solutions are calculated by the calculation module 204. The global optimal solution is screened from the local optimal solution through the confirmation module 206, and finally, the optimal six-degree-of-freedom platform design parameters in the analog quantity set are obtained. Under the condition of meeting the design requirements, the optimized structure of the six-degree-of-freedom platform is designed through the simulation screening of a large number of analog quantities.

[0101] In a possible implementation, the first acquisition module 201 and the second acquisition module 205 are both used to delete the target number of analog quantities from the analog quantity set.

[0102] In another possible implementation, the second acquisition module 205 is further configured to acquire a target number of analog quantities from the analog quantity set in chronological order according to a set trend.

[0103] In one possible implementation, the constant parameters include the distance between the upper platform and the lower platform in the six-degree-of-freedom platform, the radius of the lower circle formed by multiple Hooke's joints in the lower platform, the radius of the upper circle formed by multiple Hooke's joints in the upper platform, the central angle of the near hinge point in the same platform, and the central angle of the far hinge point in the same platform.

[0104] The central angle of the circle near the hinge point in the same platform can be the central angle of the circle near the hinge point in the Hooke's hinge in the upper platform, or the central angle of the circle near the hinge point in the Hooke's hinge in the lower platform.

[0105] The central angle of the far hinge point in the same platform can be the central angle of the far hinge point in the Hooke's hinge in the upper platform, or the central angle of the far hinge point in the Hooke's hinge in the lower platform.

[0106] The first constraint condition is that the radius of the upper circle is smaller than the radius of the lower circle and the central angle of the near hinge point in the same platform is smaller than the central angle of the far hinge point in the same platform.

[0107] The central angle of the near hinge point in the same platform is smaller than the central angle of the far hinge point in the same platform. The central angle of the near hinge point in the upper platform can be smaller than the central angle of the far hinge point in the upper platform, or the central angle of the near hinge point in the lower platform can be smaller than the central angle of the far hinge point in the lower platform.

[0108] In another possible implementation, the calculation module 204 is also used for, if the simulation group of the target number does not meet the second constraint of the optimal solution algorithm, then executing the input of the target number of simulations into the six-degree-of-freedom platform model, and performing subsequent operations until the simulation group of the target number that meets the second constraint is obtained; if the simulation group of the target number meets the second constraint of the optimal solution algorithm, then obtaining the local optimal solution in the simulation group of the target number according to the optimization function, the optimization function is set by combining the first parameter obtained by maximizing the workspace and the second parameter obtained by dexterity. The optimization function is used to calculate the optimization value of each simulation group in the simulation group of the target number, the optimization value is the absolute value of the target difference divided by two, and the target difference is the difference obtained by subtracting the first parameter from the second parameter; the simulation value with the smallest optimization value in the simulation group of the target number is determined as the local optimal solution. The optimal solution algorithm is a particle swarm algorithm or a genetic mutation algorithm. The second constraint condition is that the ratio of the working length of each actuator in the result quantity in each group of the simulation group to the initial length of the actuator does not exceed a preset ratio, the angle between the actuator length direction and the normal vector of the lower platform is between positive and negative forty-five degrees, the working space of the six-degree-of-freedom platform constructed by each simulation group in the target number of simulation groups does not exceed a preset working range, and the dexterity calculated for each simulation group in the target number of simulation groups is not an infinite value.

[0109] The six-degree-of-freedom platform model includes an input unit for receiving the analog quantity; a coordinate conversion unit for converting the coordinates of the upper platform in the upper platform dynamic coordinate system into the coordinates of the upper platform in the upper platform static coordinate system according to the analog quantity; the origin of the upper platform dynamic coordinate system is the center of mass of the upper platform in the six-degree-of-freedom platform, the upper platform dynamic coordinate system maintains a fixed relationship with the upper platform, and the upper platform static coordinate system is the coordinate system when the dynamic coordinate is in an initial position; the coordinate conversion unit includes a rotation matrix unit and a translation matrix unit, and the rotation matrix unit is provided with a transformation matrix for converting the upper platform dynamic coordinate system to the upper platform static coordinate system; the translation matrix unit is used to calculate the displacement of the origin of the dynamic coordinate system relative to the static coordinate system. ; An upper platform unit, used to translate the coordinates of the six Hooke's hinges in the upper platform in the static coordinate system of the upper platform by a set distance to obtain the coordinate points of the six Hooke's hinges in the upper platform in the static coordinate system of the lower platform; a lower platform unit, used to obtain the coordinate points of the six Hooke's hinges in the lower platform in the static coordinate system of the lower platform; an actuator length calculation module, used to calculate the working lengths of the six actuators according to the coordinate points of the six Hooke's hinges in the upper platform in the static coordinate system of the lower platform and the coordinate points of the six Hooke's hinges in the lower platform in the static coordinate system of the lower platform, through a point-to-point distance formula; each of the six actuators is hinged to the upper platform through a Hooke's hinge, and each of the six actuators is also hinged to the lower platform through a Hooke's hinge.

[0110] The embodiments of the present application also provide corresponding devices and computer storage media for implementing the solutions provided by the embodiments of the present application.

[0111] The device includes a memory and a processor, the memory is used to store instructions or codes, and the processor is used to execute the instructions or codes so that the device executes a six-degree-of-freedom platform structure optimization method described in any embodiment of the present application.

[0112] The computer storage medium stores codes, and when the codes are executed, the device executing the codes implements a six-degree-of-freedom platform structure optimization method as described in any embodiment of the present application.

[0113] The "first" and "second" in the names such as "first" and "second" (if any) mentioned in the embodiments of the present application are only used as name identifiers and do not represent the first or second in order.

[0114] Through the description of the above implementation methods, it can be known that those skilled in the art can clearly understand that all or part of the steps in the above-mentioned embodiment method can be implemented by means of software plus a general hardware platform. Based on such an understanding, the technical solution of the present application can be embodied in the form of a software product, and the computer software product can be stored in a storage medium, such as a read-only memory (ROM) / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network communication device such as a router) to execute the methods described in each embodiment of the present application or some parts of the embodiments.

[0115] Each embodiment in this specification is described in a progressive manner, and the same and similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative work.

[0116] The above description is merely an exemplary embodiment of the present application and is not intended to limit the protection scope of the present application.

Claims

1. A six-degree-of-freedom platform structure optimization method, characterized in that: include: Acquire a target number of analog quantities from an analog quantity set, wherein the analog quantity set includes a plurality of different analog quantities, each of the analog quantities includes a constant parameter and a posture state quantity of at least one degree of freedom; the constant parameter is a parameter that satisfies a first constraint condition and is used to construct a six-degree-of-freedom platform, and the posture state quantity is used to determine a working position of an upper platform in the six-degree-of-freedom platform; Inputting a target number of simulation quantities into the six-degree-of-freedom platform model, respectively obtaining result quantities of the simulation output of the six-degree-of-freedom platform model; the six-degree-of-freedom platform is used to simulate and construct the working state of the six-degree-of-freedom platform according to the simulation quantities; the result quantities include the working lengths of the six actuators included in the six-degree-of-freedom platform; Generate the target number of simulation groups, the simulation groups including simulation quantities input to the six-degree-of-freedom platform model and result quantities output by the six-degree-of-freedom platform model based on the simulation quantities; Inputting the simulation group of the target number into the optimal solution algorithm to obtain a local optimal solution output by the optimal solution algorithm that satisfies the second constraint condition, including if the simulation group of the target number does not satisfy the second constraint condition of the optimal solution algorithm, then inputting the simulation quantity of the target number into the six-degree-of-freedom platform model, and performing subsequent operations until the simulation group of the target number that satisfies the second constraint condition is obtained; if the simulation group of the target number satisfies the second constraint condition of the optimal solution algorithm, then obtaining a local optimal solution in the simulation group of the target number according to an optimization function, wherein the optimization function is set by combining a first parameter obtained by maximizing the workspace and a second parameter obtained by dexterity; Returning to execute the step of obtaining the target number of analog quantities from the analog quantity set and subsequent steps until a set number of local optimal solutions are obtained, wherein the set number of local optimal solutions are different from each other; The best local optimal solution is selected from the set number of local optimal solutions as the global optimal solution, and the constant parameters included in the global optimal solution are used to construct a six-degree-of-freedom platform.

2. The method according to claim 1, characterized in that The step of obtaining a target number of analog quantities from the analog quantity set includes: Get the target number of analog quantities from the analog quantity set in chronological order according to the set trend.

3. The method according to claim 1, characterized in that After obtaining the target number of analog quantities from the analog quantity set, the method further includes: The target number of analog quantities is deleted from the analog quantity set.

4. The method according to claim 1, characterized in that: The constant parameters include the distance between the upper platform and the lower platform in the six-degree-of-freedom platform, the radius of the lower circle formed by the multiple Hooke's joints in the lower platform, the radius of the upper circle formed by the multiple Hooke's joints in the upper platform, the central angle of the near hinge point in the same platform, and the central angle of the far hinge point in the same platform.

5. The method according to claim 4, characterized in that The first constraint condition is that the radius of the upper circle is smaller than the radius of the lower circle and the central angle of the near hinge point in the same platform is smaller than the central angle of the far hinge point in the same platform.

6. The method according to claim 1, characterized in that The step of obtaining the local optimal solution in the target number of simulation groups according to the optimization function comprises: Calculate an optimized value for each simulation group in the target number of simulation groups, the optimized value being the absolute value of the target difference divided by two, the target difference being the difference obtained by subtracting the first parameter from the second parameter; The simulation value with the smallest optimization value in the simulation groups of the target number is determined as the local optimal solution.

7. The method according to claim 1, characterized in that The optimal solution algorithm is a particle swarm algorithm or a genetic mutation algorithm.

8. The method according to claim 1, characterized in that The second constraint condition is that the ratio of the working length of each actuator in the result quantity in each group of the simulation group to the initial length of the actuator does not exceed a preset ratio, the angle between the actuator length direction and the normal vector of the lower platform is between positive and negative forty-five degrees, the working space of the six-degree-of-freedom platform constructed by each simulation group in the target number of simulation groups does not exceed a preset working range, and the dexterity calculated for each simulation group in the target number of simulation groups is not an infinite value.

9. The method according to claim 1, characterized in that: The six-degree-of-freedom platform model includes: An input unit, used for receiving the analog quantity; A coordinate conversion unit is used to convert the coordinates of the upper platform in the upper platform dynamic coordinate system into the coordinates of the upper platform in the upper platform static coordinate system according to the analog quantity; the origin of the upper platform dynamic coordinate system is the center of mass of the upper platform in the six-degree-of-freedom platform, the upper platform dynamic coordinate system maintains a fixed relationship with the upper platform, and the upper platform static coordinate system is the coordinate system when the dynamic coordinates are in an initial position; the coordinate conversion unit includes a rotation matrix unit and a translation matrix unit, and the rotation matrix unit is provided with a transformation matrix for converting the upper platform dynamic coordinate system to the upper platform static coordinate system; the translation matrix unit is used to calculate the displacement of the origin of the dynamic coordinate system relative to the static coordinate system; An upper platform unit is used to translate the coordinates of the six Hooke's joints in the upper platform in the static coordinate system of the upper platform by a set distance to obtain the coordinate points of the six Hooke's joints in the upper platform in the static coordinate system of the lower platform; The lower platform unit is used to obtain the coordinate points of the six Hooke's hinges in the lower platform in the static coordinate system of the lower platform; The actuator length calculation module is used to calculate the working lengths of the six actuators according to the coordinate points of the six Hooke's hinges in the upper platform in the static coordinate system of the lower platform and the coordinate points of the six Hooke's hinges in the lower platform in the static coordinate system of the lower platform, through the point-to-point distance formula; each of the six actuators is hinged to the upper platform through a Hooke's hinge, and each of the six actuators is also hinged to the lower platform through a Hooke's hinge.

10. A six-degree-of-freedom platform structure optimization device, characterized in that: include: A first acquisition module is used to acquire a target number of analog quantities from an analog quantity set, wherein the analog quantity set includes a plurality of different analog quantities, each of which includes a constant parameter and a posture state quantity of at least one degree of freedom; the constant parameter is a parameter that satisfies a first constraint condition and is used to construct a six-degree-of-freedom platform, and the posture state quantity is used to determine a working position of an upper platform in the six-degree-of-freedom platform; A simulation module is used to input a target number of simulation quantities into the six-degree-of-freedom platform model, and obtain the result quantities of the simulation output of the six-degree-of-freedom platform model respectively; the six-degree-of-freedom platform is used to simulate and construct the working state of the six-degree-of-freedom platform according to the simulation quantities; the result quantities include the working lengths of the six actuators included in the six-degree-of-freedom platform; A generation module, used for generating the target number of simulation groups, wherein the simulation group includes a simulation quantity input to the six-degree-of-freedom platform model and a result quantity output by the six-degree-of-freedom platform model based on the simulation quantity; A calculation module, used for inputting the simulation group of the target number into the optimal solution algorithm, and obtaining the local optimal solution outputted by the optimal solution algorithm and satisfying the second constraint condition, including if the simulation group of the target number does not satisfy the second constraint condition of the optimal solution algorithm, then executing the step of inputting the simulation quantity of the target number into the six-degree-of-freedom platform model, and executing subsequent operations until the simulation group of the target number satisfying the second constraint condition is obtained; if the simulation group of the target number satisfies the second constraint condition of the optimal solution algorithm, then obtaining the local optimal solution in the simulation group of the target number according to the optimization function, wherein the optimization function is set by combining the first parameter obtained by maximizing the workspace and the second parameter obtained by dexterity; A second acquisition module is used to return to execute the step of acquiring a target number of analog quantities from the analog quantity set and subsequent steps until a set number of local optimal solutions are acquired, and the set number of local optimal solutions are different from each other; A confirmation module is used to select the best local optimal solution from the set number of local optimal solutions as the global optimal solution, and the constant parameters included in the global optimal solution are used to construct a six-degree-of-freedom platform.

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