Multi-branch spacecraft design evaluation system and method for on-orbit servicing

Abstract

A multi-branch spacecraft design evaluation system and method for on-orbit service, it relates to a multi-branch spacecraft design evaluation system and method. The present invention aims to solve the problem that performance indicators such as single-arm and dual-arm operability are all quantitative measurements of a single aspect of performance, and the design based only on such indicators lacks comprehensive consideration of the overall performance of the spacecraft. The steps of the present invention include step 1, establishing a standard interface D-H parameter model for multi-branch spacecraft; step 2, building a performance evaluation system for multi-branch spacecraft; step 3, through a multi-objective optimization algorithm, with the best performance in the evaluation system as the goal, to complete the design and optimization of the multi-branch spacecraft configuration. The present invention belongs to the field of aerospace technology.

Description

Technical Field

[0001] The invention relates to a multi-branch spacecraft design evaluation system and method, belonging to the field of aerospace technology. Background Art

[0002] With the advancement of technology and the increase in the types and number of space missions, the styles and types of on-orbit services have also diversified. For example, on-orbit assembly, on-orbit refueling, and orbit-assisted transfer are required, which puts higher requirements on on-orbit service spacecraft. In existing missions, on-orbit service spacecraft mainly carry single or double robotic arms on a fixed base, and their working range is limited, making it difficult to perform complex and dexterous manipulation tasks. In order to overcome the above defects, the working boundaries of fixed-base space robotic arms and single- and double-arm spacecraft are extended, and multi-branch spacecraft systems that can independently complete various types of space manipulation with a single arm or with multiple arms in coordination and can move flexibly in large space facilities, such as spider manufacturing robots and space tree web robots, have become the main form and development trend of future on-orbit service spacecraft. At the same time, this type of spacecraft has significant advantages such as variable configuration, low maintenance cost, and diverse functions through modular design. However, the existing spacecraft and robot design theory lacks a unified evaluation standard for this type of multi-branch system, and cannot comprehensively and accurately measure the on-orbit service capabilities of spacecraft, which directly affects the design of spacecraft systems and on-orbit manipulation tasks. Therefore, an evaluation system that can quantify the performance of multi-branch spacecraft is needed to guide the configuration design of multi-branch spacecraft, ensure that the multi-branch spacecraft can meet the corresponding mission requirements when performing various on-orbit missions, and ensure the safe and efficient completion of on-orbit missions.

[0003] For a single robotic arm system, condition number and maneuverability are classic evaluation indicators, where condition number represents the accuracy of the robotic arm's force application, and maneuverability represents the robotic arm's ability to avoid singularities. On this basis, people later proposed dynamic maneuverability and directional maneuverability to measure the robotic arm's ability to generate acceleration under given joint torque and the robotic arm's ability to avoid singularities in a specific direction. The size of the maneuverability of the robotic arm's accessible spatial points can also be used to distinguish the size of the robotic arm's dexterous workspace. With the emergence of dual-arm and multi-arm robots, the evaluation system is also developing in the direction of multi-arms, such as task-oriented maneuverability, which defines the geometric similarity measurement between the actual maneuverability ellipsoid and the required maneuverability ellipsoid as task-oriented maneuverability; dual-arm maneuverability, described as the geometric similarity between the intersection of the maneuverability ellipses of two single arms and the ideal maneuverability ellipsoid; some scholars combined dynamic maneuverability with reconfigurable maneuverability for humanoid bipedal robots, and proposed dynamic reconfigurable maneuverability to measure the degree to which a power system can complete actions in a workspace with normalized input torque, that is, the ability of the robot system to move within the workspace under the condition of unit torque input. In summary, for multi-branch spacecraft, performance indicators such as single-arm and dual-arm maneuverability are quantitative measurements of a single aspect of performance. Designing based solely on such indicators lacks comprehensive consideration of the overall performance of the spacecraft. Summary of the invention

[0004] In order to solve the problem that performance indicators such as single-arm and dual-arm operability are all quantitative measurements of a single aspect of performance, and the design based only on such indicators lacks comprehensive consideration of the overall performance of the spacecraft, the present invention proposes a multi-branch spacecraft design evaluation system and method for on-orbit service.

[0005] The technical solution adopted by the present invention to solve the above problems is: the specific steps of the present invention include:

[0006] Step 1: Establish a standard interface DH parameter model for multi-branch spacecraft;

[0007] Step 2: Build a performance evaluation system for multi-branch spacecraft;

[0008] Step 3: Through the multi-objective optimization algorithm, with the best performance in the evaluation system as the goal, complete the design and optimization of the multi-branch spacecraft configuration.

[0009] Furthermore, in step 1, the DH parameter method is used to establish the mathematical model of each module, and a standardized DH coordinate system is established at the module connection, interface a and interface b.

[0010] Furthermore, building a performance evaluation system for multi-branch spacecraft in step 2 specifically includes establishing single-arm evaluation indicators and establishing multi-branch spacecraft system performance indicators.

[0011] Furthermore, the single-arm evaluation indicators include operability, speed global performance indicators, and flexible workspace indicators.

[0012] Furthermore, maneuverability specifically refers to selecting the maximum maneuverability within the manipulator's workspace as an indicator for measuring the manipulator's motion performance. Maneuverability μ is defined as:

[0013]

[0014] In formula (1), J represents the Jacobian matrix of the robot arm;

[0015] Speed ​​global performance index η J Defined as:

[0016]

[0017] In formula (2), ||·|| represents the second-order matrix norm of the matrix, which is the Frobenius norm; σ max and σ min are the maximum and minimum singular values ​​of the Jacobi matrix; k rec =1 / k J ;W indicates the workspace that the robot arm can reach;

[0018] The flexible workspace index is based on the manipulatability of the robot arm. If the robot arm can reach the manipulatability μ at point y in the workspace, y Satisfy μ y ≥0.8μ max , then point y is considered to be located in the flexible workspace of the robot, where μ max is the global maximum operability; flexible workspace index W f It indicates the proportion of points with operability greater than 0.8 times the maximum operability in the entire workspace.

[0019]

[0020] Furthermore, the performance indicators of the multi-branch spacecraft system include stiffness indicators, dexterity indicators, workspace indicators and energy consumption indicators.

[0021] Furthermore, the stiffness index is measured by the stiffness of the multi-arm system, and the single-arm stiffness matrix It is expressed as:

[0022] K=C -1 =J -T K q J -1 (4)

[0023] In formula (4), K q=diag(k q1 ,k q2 ,...,k qi ,...,k qn ),i=1,2,...,n, n is the number of joints of the robot arm, k qi represents the spring coefficient of joint i, and C represents the flexibility matrix of the robot;

[0024] The stiffness of a single arm of a multi-arm system based on joint flexibility is defined as:

[0025]

[0026] In formula (5), I represents the unit matrix; J i represents the Jacobian matrix of arm i; P Ci represents the vector from the end of arm i to the observation point, S(P Ci ) represents the position vector P from the grasping point to the observation point Ci The antisymmetric matrix, R represents the coordinate transformation matrix, the coordinate system {O} is located at the geometric center of the base, and the coordinate system E i Located at the geometric center of the end gripper, the observation point C is located at the center of gravity of the object being gripped;

[0027] Multi-arm system stiffness matrix K Σ is the sum of the stiffness of each single arm that makes up the multi-arm system:

[0028]

[0029] The dexterity index is a multi-branch kinematic dexterity index measured by the relative Jacobian matrix of the two arms. Its physical meaning is to evaluate the relative motion ability of the end points of the two manipulators:

[0030]

[0031] In formula (7), J PA ,J PB are the Jacobian matrices of branch A and branch B, θ A and θ B Represents the joint angle vector of branch A and branch B;

[0032] make:

[0033] J R =[- 2 Ψ3 2 Ω1J A 2 Ω4J B ](8),

[0034] in,

[0035]

[0036] According to the definition of relative Jacobian matrix, the motor dexterity index is:

[0037]

[0038] The final multi-branch dynamic dexterity index w is calculated based on the kinematic and dynamic constraints brought by the contact model. G for:

[0039]

[0040] The workspace index refers to the intersection of the collaborative workspace and the dual-arm workspace, which is used to measure the size of the dual-arm collaboration range. The collaborative workspace W coop It can be expressed as the intersection of the reachable spaces of the two robotic arms when they are holding the object:

[0041] W coop =W A ∩W B (12)

[0042] In formula (12), W A , W B represents the accessible workspace of robot arms A and B;

[0043] The energy consumption index is used to measure the endurance performance of multi-branch spacecraft. The motion energy consumption is calculated by integrating the torque path of each joint:

[0044]

[0045] In formula (13), t0 represents the starting time, τ i represents the joint torque of joint i.

[0046] Furthermore, the optimization process of the multi-branch spacecraft configuration in step 3 includes single-arm optimization and installation matrix optimization.

[0047] Furthermore, single-arm optimization specifically includes:

[0048] Design variables: The coding rules for each module are as follows:

[0049]

[0050] The kinematic parameters of each configuration are read through binary coding and the corresponding standardized DH parameters;

[0051] Objective function: objective function f for single-arm optimization s Selected as operability μ, flexible workspace index W f , speed global performance index η J Function:

[0052] f s (x) = [μW f η J ](15),

[0053] In formula (15), f s (x) represents a vector consisting of three objective functions, x = (x1, x2, ..., x m ), x represents the module binary code sequence, and m represents the number of modules;

[0054] Constraints:

[0055] The constraints in single-arm optimization are joint constraints, including joint angle θ, joint angular velocity ω and joint torque τ:

[0056]

[0057] The specific optimization process is as follows: select the configuration component modules and quantity from the basic modules, sort the modules, automatically generate the binary configuration code and kinematic parameters for the configuration that meets the constraints, calculate the corresponding indicators, obtain the individual objective function value, iterate the optimization, and finally obtain the Pareto optimal solution set. From the optimal solution set, select single-arm configurations with different emphases based on prior knowledge and build a corresponding configuration library.

[0058] Furthermore, the installation matrix optimization specifically includes:

[0059] System stiffness index: The manipulator and the object form a closed chain system Σ A , the support arm and the truss form a closed chain systemΣ B , multi-branch system stiffness objective function f c1 for:

[0060]

[0061] In formula (17), The stiffness matrices of the multi-arm system are The smallest singular value of ;

[0062] Dexterity index: Dexterity index is divided into kinematic dexterity and dynamic dexterity. The kinematic dexterity objective function f is established. c2 for:

[0063] f c2 =c(q)(18),

[0064] Multi-branch dynamics dexterity objective function f c3 Select as:

[0065] f c3 =w G (19)

[0066] In formula (19), w G is the multi-branch dynamics dexterity index;

[0067] Workspace indicator: Workspace objective function f c4 Take it as:

[0068] f c4 =W coop (Σ A )(20),

[0069] In formula (20), W coop For the double-arm system Σ A Collaboration space volume;

[0070] Base accuracy index: The base accuracy index is defined as the corresponding operating arm system Σ A Support arm system for maximum kinematic dexterityΣ B The minimum singular value of the stiffness matrix is:

[0071]

[0072] Select the objective function value: Configuration design optimization problem f c (x) is:

[0073] f c (x)=[max{f c1i ,f c2i ,f c3i},f c4 ,f c5 ],i=1,2,...,6(22).

[0074] The beneficial effects of the present invention are:

[0075] 1. The present invention can quickly establish a robot arm DH model by standardizing the DH interface parameters of each module joint;

[0076] 2. The present invention sorts out the performance indicators of multi-branch systems and builds a multi-branch spacecraft performance quantification system, which can more comprehensively and accurately describe the working performance of multi-branch spacecraft in various aspects;

[0077] 3. The present invention solves the multi-branch spacecraft configuration optimization problem through a multi-objective optimization algorithm, which has a faster convergence speed and a higher quality Pareto frontier than the traditional multi-objective algorithm. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 It is a schematic diagram of the standardized interface coordinate system;

[0079] Figure 2It is a schematic diagram of the stiffness model of a multi-branch system;

[0080] Figure 3 It is a schematic diagram of the relative Jacobian matrix model;

[0081] Figure 4 is a schematic diagram of the end effector and the clamped object;

[0082] Figure 5 It is a schematic diagram of the performance evaluation index system of a multi-branch system;

[0083] Figure 6 It is a single-arm optimization flow chart;

[0084] Figure 7 It is the installation matrix optimization flow chart. DETAILED DESCRIPTION

[0085] Specific implementation method 1: Figures 1 to 7 As shown in the figure, the multi-branch spacecraft design evaluation system and method for on-orbit service includes the following specific steps:

[0086] Step 1: Establish a mathematical model of a multi-branch spacecraft;

[0087] Step 2: Build a performance evaluation system for multi-branch spacecraft;

[0088] Step 3: Through the multi-objective optimization algorithm, with the best performance in the evaluation system as the goal, complete the design and optimization of the multi-branch spacecraft configuration.

[0089] Specific implementation method 2: Figures 1 to 7 As shown, in step 1, the DH parameter method is used to establish the mathematical model of each module, and a standardized DH coordinate system is established at the module connection, interface a and interface b.

[0090] Specific implementation method three: Figures 1 to 7 As shown, building a performance evaluation system for multi-branch spacecraft in step 2 specifically includes establishing single-arm evaluation indicators and establishing multi-branch spacecraft system performance indicators.

[0091] Specific implementation method four: Figures 1 to 7 As shown, the single-arm evaluation indicators include operability, speed global performance indicators, and flexible workspace indicators.

[0092] Specific implementation method five: Figures 1 to 7 As shown in the figure, maneuverability specifically refers to selecting the maximum maneuverability in the manipulator workspace as an indicator to measure the manipulator's motion performance. Maneuverability μ is defined as:

[0093]

[0094] In formula (1), J represents the Jacobian matrix of the robot arm;

[0095] Speed ​​global performance index η J Defined as:

[0096]

[0097] In formula (2), ||·|| represents the second-order matrix norm of the matrix, which is the Frobenius norm; σ max and σ min are the maximum and minimum singular values ​​of the Jacobi matrix; k rec =1 / k J ;W indicates the workspace that the robot arm can reach;

[0098] The flexible workspace index is based on the manipulatability of the robot arm. If the robot arm can reach the manipulatability μ at point y in the workspace, y Satisfy μ y ≥0.8μ max , then point y is considered to be located in the flexible workspace of the robot, where μ max is the global maximum operability; flexible workspace index W f It indicates the proportion of points with operability greater than 0.8 times the maximum operability in the entire workspace.

[0099]

[0100] Specific implementation method six: Figures 1 to 7 As shown, the performance indicators of the multi-branch spacecraft system include stiffness index, dexterity index, workspace index and energy consumption index.

[0101] Specific implementation method seven: Figures 1 to 7 As shown, the stiffness index is measured by the stiffness of the multi-arm system, and the single-arm stiffness matrix It is expressed as:

[0102] K=C -1 =J -T K q J -1 (4)

[0103] In formula (4), K q =diag(k q1 ,k q2 ,...,k qi ,...,k qn ),i=1,2,...,n, n is the number of joints of the robot arm, k qi represents the spring coefficient of joint i, and C represents the flexibility matrix of the robot;

[0104] The stiffness of a single arm of a multi-arm system based on joint flexibility is defined as:

[0105]

[0106] In formula (5), I represents the unit matrix; J i represents the Jacobian matrix of arm i; P Ci represents the vector from the end of arm i to the observation point, S(P Ci ) represents the position vector P from the grasping point to the observation point Ci The antisymmetric matrix of R represents the coordinate transformation matrix. The coordinate system {O} is located at the geometric center of the base. The coordinate system E i Located at the geometric center of the end gripper, the observation point C is located at the center of gravity of the object being gripped;

[0107] Multi-arm system stiffness matrix K Σ is the sum of the stiffness of each single arm that makes up the multi-arm system:

[0108]

[0109] The dexterity index is a multi-branch kinematic dexterity index measured by the relative Jacobian matrix of the two arms. Its physical meaning is to evaluate the relative motion ability of the end points of the two manipulators:

[0110]

[0111] In formula (7), J PA ,J PB are the Jacobian matrices of branch A and branch B, θ A and θ B Represents the joint angle vector of branch A and branch B;

[0112] make:

[0113] J R =[- 2 Ψ3 2 Ω1J A 2 Ω4J B ] (8),

[0114] in,

[0115]

[0116] According to the definition of relative Jacobian matrix, the motor dexterity index is:

[0117]

[0118] The final multi-branch dynamic dexterity index w is calculated based on the kinematic and dynamic constraints brought by the contact model. G for:

[0119]

[0120] The workspace index refers to the intersection of the collaborative workspace and the dual-arm workspace, which is used to measure the size of the dual-arm collaboration range. The collaborative workspace W coop It can be expressed as the intersection of the reachable spaces of the two robotic arms when they are holding the object:

[0121] W coop =W A ∩W B (12)

[0122] In formula (12), W A , W B represents the accessible workspace of robot arms A and B;

[0123] The energy consumption index is used to measure the endurance performance of multi-branch spacecraft. The motion energy consumption is calculated by integrating the torque path of each joint:

[0124]

[0125] In formula (13), t0 represents the starting time, τ i represents the joint torque of joint i.

[0126] Specific implementation method eight: Figures 1 to 7 As shown, the optimization process of the multi-branch spacecraft configuration in step 3 includes single-arm optimization and installation matrix optimization.

[0127] Specific implementation method nine: Figures 1 to 7 As shown in the figure, single-arm optimization specifically includes:

[0128] Design variables: The coding rules for each module are as follows:

[0129]

[0130] The kinematic parameters of each configuration are read through binary coding and the corresponding standardized DH parameters;

[0131] Objective function: objective function f for single-arm optimization s Selected as operability μ, flexible workspace index W f , speed global performance index η J Function:

[0132] f s (x) = [μW f η J ](15),

[0133] In formula (15), f s(x) represents a vector consisting of three objective functions, x = (x1, x2, ..., x m ), x represents the module binary code sequence, and m represents the number of modules;

[0134] Constraints:

[0135] The constraints in single-arm optimization are joint constraints, including joint angle θ, joint angular velocity ω, and joint torque τ:

[0136]

[0137] The specific optimization process is as follows: select the configuration component modules and quantity from the basic modules, sort the modules, automatically generate the binary configuration code and kinematic parameters for the configuration that meets the constraints, calculate the corresponding indicators, obtain the individual objective function value, iterate the optimization, and finally obtain the Pareto optimal solution set. From the optimal solution set, select single-arm configurations with different emphases based on prior knowledge and build a corresponding configuration library.

[0138] Among them, the optimal solution of multi-objective optimization is defined as follows:

[0139] Suppose a multi-objective optimization problem has n (n ≥ 2) objective functions, where f i (x) is the i-th objective function, and the set Ω is the set of all feasible solutions. If there is no x∈Ω such that for any i, f i (x)≥f i (x * ),i=1,2,…,n, then x * is an optimal solution for the set Ω, all x * The set of becomes the optimal solution set, that is, the Pareto optimal solution;

[0140] The optimization goal of multi-objective optimization problem is to find a solution x, and there is no solution x * , so that x * All objective functions of are better than solution x, that is, x may not be optimal in all objective functions, but there must be no other solution x * Better than x in all aspects.

[0141] Specific implementation method ten: Figures 1 to 7 As shown, the installation matrix optimization specifically includes:

[0142] System stiffness index: The manipulator and the object form a closed chain system Σ A , the support arm and the truss form a closed chain systemΣ B , the stiffness objective function of the multi-branch system f c1 for:

[0143]

[0144] In formula (17), The stiffness matrices of the multi-arm system are The smallest singular value of ;

[0145] Dexterity index: Dexterity index is divided into kinematic dexterity and dynamic dexterity. The kinematic dexterity objective function f is established. c2 for:

[0146] f c2 =c(q)(18),

[0147] Multi-branch dynamics dexterity objective function f c3 Select as:

[0148] f c3 =w G (19)

[0149] In formula (19), w G is the multi-branch dynamics dexterity index;

[0150] Workspace indicator: Workspace objective function f c4 Take it as:

[0151] f c4 =W coop (Σ A )(20),

[0152] In formula (20), W coop For the double-arm system Σ A Collaboration space volume;

[0153] Base accuracy index: In order to further consider the stability and anti-interference performance of the base supporting the operating arm during the assembly operation, the support arm system Σ B The stiffness is used as the base accuracy index. At this time, because the flexibility of the operating arm in the assembly state is the primary optimization target, the stability of the base is the auxiliary optimization index;

[0154] The base accuracy index is defined as the corresponding manipulator system Σ A Support arm system for maximum kinematic dexterityΣ B The minimum singular value of the stiffness matrix is:

[0155]

[0156] Select the objective function value: Configuration design optimization problem f c (x) is:

[0157] f c (x)=[max{f c1i ,fc2i ,f c3i},f c4 ,f c5 ],i=1,2,...,6(22).

[0158] Among them, in the four-arm system, there are 6 different combinations of manipulator arms / support arms, and the support arms and manipulator arms can be converted into each other. Therefore, for the same solution, the three types of index function values ​​of kinematic dexterity, dynamic dexterity and system stiffness all take the maximum value among the 6 groups of values, while the base accuracy and workspace indicators depend on the kinematic dexterity index, so there is no need to consider the maximum value.

[0159] The above is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technician familiar with this profession can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent replacement and improvement made to the above embodiments without departing from the content of the technical solution of the present invention, based on the technical essence of the present invention, within the spirit and principles of the present invention, still fall within the protection scope of the technical solution of the present invention.

Claims

1. A multi-branch spacecraft design evaluation system and method for on-orbit servicing, characterized by: The specific steps include: Step 1: Establish a standard interface DH parameter model for multi-branch spacecraft; Step 2: Build a performance evaluation system for multi-branch spacecraft; specifically, establish single-arm evaluation indicators and multi-branch spacecraft system performance indicators; single-arm evaluation indicators include operability, speed full-domain performance indicators, and flexible workspace indicators; multi-branch spacecraft system performance indicators include stiffness indicators, dexterity indicators, workspace indicators, and energy consumption indicators; The stiffness index is measured by the stiffness of the multi-arm system, and the single-arm stiffness matrix It is expressed as: K=C -1 =J -T K q J -1 (4), In formula (4), K q =diag(k q1 ,k q2 ,...,k qi ,...,k qn ),i=1,2,...,n, n is the number of joints of the robot arm, k qi represents the spring coefficient of joint i, and C represents the flexibility matrix of the robot; The stiffness of a single arm of a multi-arm system based on joint flexibility is defined as: In formula (5), I represents the unit matrix; J i represents the Jacobian matrix of arm i; P Ci represents the vector from the end of arm i to the observation point, S(P Ci ) represents the position vector P from the grasping point to the observation point Ci The antisymmetric matrix, R represents the coordinate transformation matrix, the coordinate system {O} is located at the geometric center of the base, and the coordinate system E i Located at the geometric center of the end gripper, the observation point C is located at the center of gravity of the object being gripped; Multi-arm system stiffness matrix K Σ is the sum of the stiffness of each single arm that makes up the multi-arm system: The dexterity index is a multi-branch kinematic dexterity index measured by the relative Jacobian matrix of the two arms. Its physical meaning is to evaluate the relative motion ability of the end points of the two manipulators: In formula (7), J PA ,J PB are the Jacobian matrices of branch A and branch B, θ A and θ B Represents the joint angle vector of branch A and branch B; make: J R =[- 2 P3 2 Ω1J A 2 Ω4J B ](8), in, According to the definition of relative Jacobian matrix, the motor dexterity index is: The final multi-branch dynamic dexterity index w is calculated based on the kinematic and dynamic constraints brought by the contact model. G for: The workspace index refers to the intersection of the collaborative workspace and the dual-arm workspace, which is used to measure the size of the dual-arm collaboration range. The collaborative workspace W coop It is expressed as the intersection of the reachable spaces of the two manipulators when they are holding the object: IN coop =In A ∩In B (12), In formula (12), W A , W B represents the accessible workspace of robot arms A and B; The energy consumption index is used to measure the endurance performance of multi-branch spacecraft. The motion energy consumption is calculated by integrating the torque path of each joint: In formula (13), t0 represents the starting time, τ i represents the joint torque of joint i; Step 3: Through the multi-objective optimization algorithm, with the best performance in the evaluation system as the goal, complete the design and optimization of the multi-branch spacecraft configuration.

2. The multi-branch spacecraft design evaluation system and method for on-orbit servicing according to claim 1 is characterized in that: In step 1, the DH parameter method is used to establish the mathematical model of each module, and a standardized DH coordinate system is established at the module connection, interface a and interface b.

3. The multi-branch spacecraft design evaluation system and method for on-orbit servicing according to claim 1 is characterized in that: Maneuverability specifically refers to selecting the maximum maneuverability within the robot's workspace as an indicator to measure the robot's motion performance. Maneuverability μ is defined as: In formula (1), J represents the Jacobian matrix of the robot arm; Speed ​​global performance index η J Defined as: In formula (2), ||·|| represents the second-order matrix norm of the matrix, which is the Frobenius norm; σ max and σ min are the maximum and minimum singular values ​​of the Jacobi matrix; k rec =1 / k J ;W indicates the workspace that the robot arm can reach; The flexible workspace index is based on the manipulatability of the robot arm. If the robot arm can reach the manipulatability μ at point y in the workspace, y Satisfy μ y ≥0.8μ max , then point y is considered to be located in the flexible workspace of the robot, where μ max is the global maximum operability; flexible workspace index W f It indicates the proportion of points with operability greater than 0.8 times the maximum operability in the entire workspace.

4. The multi-branch spacecraft design evaluation system and method for on-orbit servicing according to claim 1 is characterized in that: The optimization process of the multi-branch spacecraft configuration in step 3 includes single-arm optimization and installation matrix optimization.

5. The multi-branch spacecraft design evaluation system and method for on-orbit servicing according to claim 4 is characterized in that: Single-arm optimization specifically includes: Design variables: The coding rules for each module are as follows: The kinematic parameters of each configuration are read through binary coding and the corresponding standardized DH parameters; Objective function: objective function f for single-arm optimization s Selected as operability μ, flexible workspace index W f , speed global performance index η J Function: f s (x)=[μW f or J ](15), In formula (15), f s (x) represents a vector consisting of three objective functions, x = (x1, x2, ..., x m ), x represents the module binary code sequence, and m represents the number of modules; Constraints: The constraints in single-arm optimization are joint constraints, including joint angle θ, joint angular velocity ω, and joint torque τ: The specific optimization process is as follows: select configuration component modules and their quantity from the basic modules, sort the modules, automatically generate binary configuration codes and kinematic parameters for configurations that meet the constraints, calculate corresponding indicators, obtain individual objective function values, iterate and optimize, and finally obtain the Pareto optimal solution set. From the optimal solution set, select single-arm configurations with different emphases based on prior knowledge and build a corresponding configuration library.

6. The multi-branch spacecraft design evaluation system and method for on-orbit servicing according to claim 4 is characterized in that: Installation matrix optimization specifically includes: System stiffness index: The manipulator and the object form a closed chain system Σ A , the support arm and the truss form a closed chain systemΣ B , multi-branch system stiffness objective function f c1 for: In formula (17), The stiffness matrices of the multi-arm system are The smallest singular value of ; Dexterity index: Dexterity index is divided into kinematic dexterity and dynamic dexterity. The kinematic dexterity objective function f is established. c2 for: f c2 =c(q)(18), Multi-branch dynamics dexterity objective function f c3 Select as: f c3 =w G (19), In formula (19), w G is the multi-branch dynamics dexterity index; Workspace indicator: Workspace objective function f c4 Take it as: f c4 =W coop (S A )(20), In formula (20), W coop For the double-arm system Σ A Collaboration space volume; Base accuracy index: The base accuracy index is defined as the corresponding operating arm system Σ A Support arm system for maximum kinematic dexterityΣ B The minimum singular value of the stiffness matrix is: Select the objective function value: Configuration design optimization problem f c (x) is: f c (x)=[max{f c1i ,f c2i ,f c3i },f c4 ,f c5 ],i=1,2,...,6(22)。

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