Space dual-arm robot floating base perturbation minimization optimal path planning method

Abstract

The present application relates to the field of path planning of space floating robot, and discloses a kind of optimal path planning method of space double-arm robot floating base disturbance minimization, which improves the control accuracy and stability of mechanical arm by minimizing base disturbance.The present application first models double-arm space mechanical arm, then solves the final pose of double-arm space mechanical arm near target object using nonlinear programming method, then parameterizes joint trajectory using five-order polynomial, and finally fits joint trajectory and performs collision detection and singularity detection.Adjust the constraint conditions of nonlinear programming, iteratively calculate, and output the joint motion trajectory of the optimal path.The present application has the advantages of minimizing base disturbance while ensuring the positioning accuracy of the end effector, and effectively avoiding collision and singularity.The present application provides technical support for autonomous decision-making and path planning, and provides possibilities for the application of space mechanical arm in various tasks.

Description

Technical Field

[0001] This invention relates to the field of path planning for space-floating robots, specifically to an optimal path planning method that minimizes disturbances to the floating base of a space dual-arm robot. Background Technology

[0002] A space robotic arm is a robot that operates in the space environment and can perform various tasks such as maintenance, assembly, and material handling. A space robotic arm typically consists of a free-floating base and a series of robotic arms composed of one or more links and joints, with a dynamic coupling between them. However, the movement of the space robotic arm in free-floating mode can disturb the position and attitude of the base, affecting the base's control accuracy and stability.

[0003] To minimize the disturbance of the space robotic arm to the base, reasonable path planning is required to reduce the amplitude of base posture changes while satisfying motion constraints. Currently, several methods for path planning of space robotic arms have been proposed, such as parameterizing joint trajectories using sinusoidal polynomial functions and then searching for the optimal trajectory using simulated annealing-particle swarm optimization; optimizing joint trajectory parameters based on Bézier curves using genetic algorithms; and solving optimization problems based on least squares using nonlinear programming methods.

[0004] However, these methods are all for path planning of single-arm space robots. In practical applications, dual-arm space robots offer greater flexibility and efficiency, especially in free-floating mode. Therefore, how to perform path planning with minimal base disturbance for dual-arm space robots is a problem worthy of further research. Summary of the Invention

[0005] This invention aims to provide a path planning method for a dual-arm floating robot in space. It employs a nonlinear programming method to seek the optimal or near-optimal solution, thereby achieving path planning with minimal base disturbance for the dual-arm space robot, improving the control accuracy and stability of the robot, further promoting the application of space robots in various tasks, and providing technical support for autonomous decision-making and path planning.

[0006] The technical solution adopted by the present invention to achieve the above objectives is as follows:

[0007] An optimal path planning method for minimizing the disturbance of a floating base on a space dual-arm robot is disclosed. This method aims to minimize base disturbance, improve the control accuracy and stability of the robotic arm, and effectively avoid collisions and singularities. The method includes the following steps:

[0008] S1. Define the geometric parameters of the robotic arm and establish the kinematic equations of the dual-arm spatial robotic arm using the generalized Jacobian matrix.

[0009] S2. Obtain the initial pose of the base of the dual-arm spatial manipulator system and the initial angle information of each joint; establish the objective function and constraints of the nonlinear programming method; use the nonlinear programming method to solve the final pose of the dual-arm spatial manipulator near the target object;

[0010] S3. Parameterize the joint trajectory of the dual-arm spatial manipulator from the initial pose to the final pose using a fifth-order polynomial.

[0011] S4. Fit the joint trajectory and perform collision detection and singularity detection. If there is a collision or singularity, return to step S2 to adjust the objective function and constraints of the nonlinear programming method, and iterate repeatedly until there is no collision or singularity, then proceed to step S5.

[0012] S5. Outputs the joint motion trajectory of the optimal path for the robotic arm, which is used to control the robotic arm to move along the trajectory.

[0013] The geometric parameters of the robotic arm are DH parameters and inertial characteristic parameters.

[0014] The nonlinear programming method uses the angles of each joint of both arms as optimization variables, and its objective function is defined as the sum of the end effector pose error term, collision risk term, and joint limit term.

[0015] The objective function of the nonlinear programming method includes the following three terms:

[0016] 1) End-effector pose error: This term represents the error between the pose of each end-effector of the dual-arm space robot and the pose of the target point. The calculation formula is as follows:

[0017]

[0018] Where (p) i ,R i ) represents the position and orientation of the i-th robotic arm end effector relative to the base coordinate system. It is the position and orientation of its corresponding target point, α i and β i This is the weighting coefficient. The smaller the value of this item, the smaller the pose error of the end effector.

[0019] 2) Joint Limits: This item represents the risk of exceeding the joint limits during the movement of the dual-arm spatial robotic arm. The calculation formula is as follows:

[0020]

[0021] Where θ k (t) is the k-th joint variable, g k (θ k(t) is a value about θ k The term (t) is a monotonically increasing function, indicating that the joint limit risk increases as the joint variable approaches its upper and lower limits. The smaller the value of this term, the lower the joint limit risk.

[0022] 3) Collision Detection Penalty: This item represents the penalty for whether a collision occurs during the movement of the dual-arm spatial robotic arm. The calculation formula is as follows:

[0023]

[0024] Where d j (t) is the minimum distance in the j-th collision scenario, which is one of the following: the minimum distance between the dual-arm spatial manipulator and the target object, the minimum distance between the links of the two arms, or the minimum distance between the two arms and the base. j (d j (t) is a concept about d j The term (t) is a monotonically increasing function, indicating that the collision penalty increases as the distance decreases. The larger the value of this term, the greater the collision penalty.

[0025] The constraints of the nonlinear programming method include linear or nonlinear constraints: each joint angle is within its limit range, the end effector is within a certain range near the target object, the end effector maintains a set angle with the target object, and the base disturbance is less than a set threshold. These include:

[0026] 1) Joint Angle Constraints: This constraint states that each joint variable of the dual-arm spatial robotic arm must be within its allowable range to avoid exceeding the physical limits of the joint space. Its mathematical expression is:

[0027] θ k,min ≤θ k (t)≤θ k,max

[0028] Where θ k (t) is the k-th joint variable, θ k,min and θ k,max These are its upper and lower limits, and k = 1, 2, ..., 12 are the joint numbers.

[0029] 2) End-effector pose range: This constraint states that the pose of each end-effector of the dual-arm space robot must be within a certain error range of the predetermined target pose to ensure the accuracy and reliability of the task. Its mathematical expression is:

[0030]

[0031] Where (p) i ,R i) represents the position and orientation of the i-th robotic arm end effector relative to the base coordinate system. It is the position and orientation of its corresponding target point, ∈ p and ∈ R These are the allowable position and attitude errors, where i = 1 and 2 are the robot arm numbers.

[0032] 3) End-effector angle constraint: This constraint indicates that, given the orientation of each end-effector of both arms, there is a certain geometric relationship between the angles of these two end-effectors and the joint angles and base angles of both arms, to ensure the consistency of the kinematic equations. Specifically:

[0033] R1=R0R 01 (θ1,θ2,...,θ6)

[0034] R2=R0R 02 (θ7,θ8,...,θ 12 )

[0035] Where R0 is the attitude matrix of the base coordinate system relative to the inertial coordinate system, R 01 and R 02 It is the attitude matrix of the two robotic arm end effectors relative to the base coordinate system, θ1,θ2,...,θ 12 These are the twelve joint variables of the dual-arm spatial robotic arm system.

[0036] Since R1 and R2 are the attitude matrices of the two robotic arm end effectors relative to the inertial coordinate system, and are known, we can combine the above two equations to obtain a mathematical expression for the linear constraint condition:

[0037]

[0038] 4) Base Disturbance Constraint: This constraint limits the disturbance to the base, requiring it to remain within a certain angular range during movement to ensure the stability and safety of the space station. Its mathematical expression is:

[0039]

[0040] Where R1 is the attitude matrix of the end effector of arm 1 relative to the inertial coordinate system, R 01 R is the attitude matrix of the end effector of arm 1 relative to the base coordinate system. max It is the maximum range of attitudes that the base can be disturbed.

[0041] The method utilizes a fifth-order polynomial to parameterize the joint trajectory of the dual-arm spatial manipulator from its initial pose to its final pose, namely:

[0042] θ i (t)=ai0 +a i1 t+a i2 t 2 +a i3 t 3 +a i4 t 4 +a i5 t 5

[0043] Where, θ i (t) is a function of the change of the angle of the i-th joint with time t, a ij Let i be the polynomial parameters to be solved, i = 1, 2, ..., 12, j = 0, 1, ..., 5. The corresponding joint angular velocities and joint acceleration curves can be expressed as:

[0044]

[0045]

[0046] Further, the constraint θ i (0)=θ i0 , Substitute θ i (t), The expression yields:

[0047]

[0048]

[0049]

[0050] Ultimately, a i5 This is the only parameter that needs to be determined in the joint curve.

[0051] The collision detection method based on gap vectors is used to perform collision detection on the fitted joint trajectory.

[0052] The collision detection method based on gap vectors includes:

[0053] S41. Abstract and simplify the spatial robotic arm and obstacles using the smallest cuboid;

[0054] S42. Determine the relative positions and orientations of each pair of cuboids;

[0055] S43. Calculate the minimum distance and direction between two cuboids;

[0056] S44. Compare the length of the gap vector with the preset safety distance. If the length of the gap vector is less than the safety distance, then a collision is considered to exist; otherwise, a collision is considered not to exist.

[0057] The relative position and orientation between any two cuboids are determined by the vector between the center points of the two cuboids and the angle between the orientations of the two cuboids:

[0058] v AB =c B -c A

[0059]

[0060]

[0061]

[0062] Where v AB It is the vector between the center points of the two cuboids, c A and c B These are the center points of objects A and B, respectively, u A v A and w A These are the three orientation vectors of object A, u B v B and w B These are the three orientation vectors of object B, α AB β AB and γ AB These are the included angles between the orientations of the two cuboids.

[0063] The calculation of the minimum distance and direction between two cuboids is a vector pointing from any point on the surface of one cuboid to the nearest point on the surface of the other cuboid:

[0064] G AB =d AB n AB

[0065] d AB =‖v AB ||-l A cos(α AB )-l B cos(α BA )-w A cos(β AB )-w B cos(β BA )-h A cos(γ AB )-h B cos(γ BA )

[0066]

[0067] Among them G AB d is the gap vector between two cuboids. AB It is the minimum distance between two cuboids, n AB It is the direction of the minimum distance between two cuboids, l A w A and h A These are the length, width, and height of object A, l B w B and h B These are the length, width, and height of object B, respectively.

[0068] The singularity detection refers to the reachable workspace of the dual-arm robot in its initial pose. If a trajectory point is outside the reachable workspace, it is determined to be a singularity.

[0069] Compared with the prior art, the present invention has the following advantages:

[0070] 1. This invention uses a dual-arm spatial robotic arm, which can improve task execution efficiency and flexibility, while reducing the requirements for base attitude control;

[0071] 2. This invention employs a path planning method that combines nonlinear programming and quintic curve fitting, which can effectively optimize multiple objective functions such as base disturbance, collision risk, and joint limits, and can adapt to complex and changing environments;

[0072] 3. This invention uses a quintic curve to fit the joint trajectory, which can ensure the continuity and smoothness of the trajectory, while reducing the number of parameters and the amount of computation. Attached Figure Description

[0073] Figure 1 This is a flowchart of the method of the present invention;

[0074] Figure 2 This is the motion trajectory of the planar dual-arm spatial robotic arm embodiment of the present invention;

[0075] Figure 3(a) shows the position change curve of the space robotic arm base;

[0076] Figure 3(b) shows the attitude change curve of the space robotic arm base; Detailed Implementation

[0077] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of the invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0078] like Figure 1 The diagram shown is a flowchart of the method of this invention. This invention proposes an optimal path planning method for minimizing the disturbance of a floating base for a space dual-arm robot, comprising the following steps:

[0079] (1) Model the dual-arm spatial manipulator and establish its kinematic equations.

[0080] (2) Obtain the initial pose information of the space robotic arm system and the target pose of the dual-arm end effectors at the target to be captured.

[0081] (3) Design the objective function and constraints of the nonlinear programming method.

[0082] (4) Use nonlinear programming to find the optimal solution that satisfies the constraints.

[0083] (5) Parameterize the joint trajectory of the dual-arm spatial robot and perform curve fitting.

[0084] (6) Perform collision detection and singularity detection on the fitted joint trajectory. If a collision or singularity exists, adjust the constraints of the nonlinear programming method and repeat steps (3) to (6); if no collision or singularity exists, proceed to step (7).

[0085] (7) Output the joint motion trajectory of the robotic arm.

[0086] Example:

[0087] Here, a planar dual-arm spatial robotic arm is used as an example to provide a detailed implementation method and specific operation process, but the scope of protection of this invention is not limited to the following embodiments. The specific implementation steps are as follows:

[0088] (1) Define the DH parameters of the space robotic arm system as shown in Table 1 and the system inertial characteristic parameters as shown in Table 2.

[0089] Table 1 DH parameters of the system

[0090]

[0091] Table 2 Inertial Characteristic Parameters of the System

[0092]

[0093]

[0094] Where m is the mass of the base and the connecting rod. Let i be the inertia tensor of the i-th link. For the i-th joint hinge J i To its connecting rod i, center of mass C i position vector, Let C be the center of mass of connecting rod i. i To the next joint hinge J i+1 The position vector.

[0095] Based on the above parameters, a model of a dual-arm spatial robotic arm is constructed, and the kinematic equations are established using the generalized Jacobian matrix:

[0096]

[0097]

[0098] in J is the generalized velocity term of the end effector of the space robotic arm. B J is the Jacobian matrix of the base. M Let Jacobian matrix be the value of the robotic arm. J is the joint angular velocity term of the robotic arm. G H is the generalized Jacobian matrix. MC The equations for the motion coupling between the robotic arm and the base in free-floating mode; For the generalized velocity term of the base, H B H is the inertia matrix of the matrix. BM This is the coupling matrix between the base and the robotic arm.

[0099] (2) Obtain the initial pose of the planar spatial robotic arm system and the position information of the target to be captured. [x0 y0 θ0 θ1 θ2 θ3 θ4 θ5 θ6] T The coordinate information of the dual-arm spatial robotic arm system is represented by [x1, y1, x2, y2, θ]. Here, (x0, y0) represents the base position, θ0 is the base attitude angle, θ1–θ3 are the three joint angles of arm 1, and θ4–θ6 are the three joint angles of arm 2. The coordinates are [x1, y1, x2, y2, θ]. e1 θ e2 ] T Let θ represent the coordinate information of the target position to be captured by the planar dual-arm spatial robotic arm, where (x1, y1) is the position of the end effector of arm 1, and θ is the coordinate information of the target position to be captured. e1 Let θ be the attitude angle of the end effector of arm 1, (x2, y2) be the position of the end effector of arm 2, and θ be the position of the end effector of arm 2. e2 The attitude angle of the end effector of arm 2.

[0100] (3) Design the objective function and constraints of the nonlinear programming method. Specifically, firstly, the angles of each joint of the two arms corresponding to the final pose of the planar spatial robotic arm near the object to be captured are defined as optimization variables. Then, the objective function is defined as the sum of the end effector pose error term, the collision risk term, and the joint limit term:

[0101] 1) End-effector pose error term: This term represents the error between the pose of each end-effector of the planar dual-arm spatial robot and the pose of the target point. The calculation formula is as follows:

[0102]

[0103] Where (p) i ,R i ) represents the position and orientation of the i-th robotic arm end effector relative to the base coordinate system. It is the position and orientation of its corresponding target point, α i and β i This is the weighting coefficient. The smaller the value of this item, the smaller the pose error of the end effector.

[0104] 2) Joint Limits: This term represents the risk of exceeding the joint limits during the movement of the planar dual-arm spatial robotic arm. Its calculation formula is as follows:

[0105]

[0106] Where θ k (t) is the k-th joint variable, g k (θ k (t) is a value about θ k The term (t) is a monotonically increasing function, indicating that the joint limit risk increases as the joint variable approaches its upper and lower limits. The smaller the value of this term, the lower the joint limit risk.

[0107] 3) Collision Detection Penalty: This item represents the penalty for whether a collision occurs during the movement of the planar dual-arm spatial robotic arm. Its calculation formula is as follows:

[0108]

[0109] Where d j (t) is the minimum distance in the j-th collision scenario, which is one of the following: the minimum distance between the dual-arm spatial manipulator and the object to be captured, the minimum distance between the links of the two arms, and the minimum distance between the two arms and the base. j (d j (t) is a concept about d j The term (t) is a monotonically increasing function, indicating that the collision penalty increases as the distance decreases. The larger the value of this term, the greater the collision penalty.

[0110] Finally, some linear or nonlinear constraints are designed for the nonlinear programming method, including:

[0111] 1) Joint Angle Constraints: This constraint states that each joint variable of the planar dual-arm spatial robot must be within its allowable range to avoid exceeding the physical limits of the joint space. Its mathematical expression is:

[0112] θ k,min ≤θ k (t)≤θ k,max

[0113] Where θ k (t) is the k-th joint variable, θ k,min and θ k,max These are its upper and lower limits, and k = 1, 2, ..., 6 are the joint numbers.

[0114] 2) End-effector pose range: This constraint states that the pose of each end-effector of the planar dual-arm spatial manipulator must be within a certain error range of the predetermined target pose to ensure the accuracy and reliability of the task. Its mathematical expression is:

[0115]

[0116] Where (p) i ,R i ) represents the position and orientation of the i-th robotic arm end effector relative to the base coordinate system. It is the position and orientation of its corresponding target point, ∈ p and ∈ R These are the allowable position and attitude errors, where i = 1 and 2 are the robot arm numbers.

[0117] 3) End-effector angle constraint: This constraint indicates that, given the orientation of the end-effectors of each arm, there is a certain geometric relationship between the angles of these two end-effectors and the joint angles and base angles of the arms, to ensure the consistency of the kinematic equations:

[0118]

[0119] Where R1 and R2 are the attitude matrices of the two robotic arm end effectors relative to the inertial coordinate system, R 01 and R 02 θ1, θ2, ..., θ6 are the attitude matrices of the two end effectors of the robotic arms relative to the base coordinate system, and θ1, θ2, ..., θ6 are the six joint variables of the planar dual-arm spatial robotic arm system.

[0120] 4) Base Disturbance Constraint: This constraint limits the disturbance to the base, requiring it to remain within a certain angular range during movement to ensure the stability and safety of the space station. Its mathematical expression is:

[0121]

[0122] Where R1 is the attitude matrix of the end effector of arm 1 relative to the inertial coordinate system, R 01 R is the attitude matrix of the end effector of arm 1 relative to the base coordinate system. max It is the maximum range of attitudes that the base can be disturbed.

[0123] (4) Use nonlinear programming to find the optimal solution that satisfies the constraints.

[0124] (5) The joint trajectories of the dual-arm spatial manipulator are parameterized using a fifth-order polynomial, and curve fitting is performed:

[0125] θ i (t)=a i0 +a i1 t+a i2 t 2 +a i3 t 3 +a i4 t 4 +a i5 t 5

[0126] Where, θ i (t) is a function of the change of the angle of the i-th joint with time t, a ij Let i be the polynomial parameters to be solved, i = 1, 2, ..., 6, j = 0, 1, ..., 5. The corresponding joint angular velocities and joint acceleration curves can be expressed as:

[0127]

[0128]

[0129] Further, the constraint θ i (0)=θ i0 , Substitute θ i (t), The expression yields:

[0130]

[0131]

[0132]

[0133] Ultimately, a i5 This is the only parameter that needs to be determined in the joint curve.

[0134] (6) Perform collision detection and singularity detection on the fitted joint trajectory. If a collision or singularity exists, adjust the constraints of the nonlinear programming method and repeat steps (3) to (6); if no collision or singularity exists, proceed to step (7).

[0135] The collision detection process employs a gap vector-based collision detection method. This includes:

[0136] 1) The spatial robotic arm and obstacles are abstracted and simplified using the smallest cuboid.

[0137] 2) It is necessary to determine the relative positions and orientations of each pair of cuboids, that is, the vector between the center points of the two cuboids and the angle between their orientations. Specifically, the following formula applies:

[0138] v AB =c B -c A

[0139]

[0140]

[0141]

[0142] Where v AB It is the vector between the center points of the two cuboids, c A and c B These are the center points of objects A and B, respectively, u A v A and w A These are the three orientation vectors of object A, u B v B and w B These are the three orientation vectors of object B, α AB β AB and γ AB These are the included angles between the orientations of the two cuboids.

[0143] 3) Calculate the minimum distance and direction between two cuboids, that is, the vector from any point on the surface of one cuboid to the nearest point on the surface of the other cuboid. Specifically, the following formula applies:

[0144] G AB =d AB n AB

[0145] d AB =‖v AB ||-l A cos(α AB )-l B cos(α BA )-w A cos(β AB )-w B cos(β BA )-h A cos(γ AB )-h B cos(γ BA )

[0146]

[0147] Among them G AB d is the gap vector between two cuboids. AB It is the minimum distance between two cuboids, n AB It is the direction of the minimum distance between two cuboids, l A w A and h A These are the length, width, and height of object A, l B w B and h B These are the length, width, and height of object B, respectively.

[0148] 4) Compare the length of the gap vector with the preset safety distance. If the length of the gap vector is less than the safety distance, then a collision is considered to exist; otherwise, a collision is considered not to exist.

[0149] Singularity detection refers to the reachable workspace of the dual-arm robot in its initial pose. If a trajectory point is outside the reachable workspace, it is determined to be a singularity.

[0150] (7) Output the joint motion trajectory of the robotic arm.

[0151] The initial pose of the planar spatial robotic arm system is defined as [0.24 0.8 0 90-45-60-90 45 60]. T The target position coordinates to be captured are [2.0 1.0 2.2781 0.8494 -10.0 80.0]. Finally, the joint angles are solved using a nonlinear programming algorithm, and the parameter 'a' is obtained by parameterizing the joint trajectory using a fifth-order polynomial. i5 = [-0.0016813-0.0055534-0.0075047-0.0036091-0.00071903-0.00097995] T .

[0152] The motion trajectory of the planar dual-arm spatial robotic arm embodiment obtained using the method of the present invention is as follows: Figure 2 As shown in Figures 3(a) and 3(b), the pose change curves of the base are illustrated. It can be seen that the optimal path planning method for minimizing disturbances of the floating base of a spatial dual-arm robot provided by this invention can achieve path planning for both arms under conditions of small perturbations in the base's pose.

[0153] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. An optimal path planning method for minimizing disturbance to the floating base of a space dual-arm robot, characterized in that, This method is used to minimize base disturbances, improve the control accuracy and stability of the robotic arm, and effectively avoid collisions and singularities; it includes the following steps: S1. Define the geometric parameters of the robotic arm and establish the kinematic equations of the dual-arm spatial robotic arm using the generalized Jacobian matrix. S2. Obtain the initial pose of the base of the dual-arm spatial robotic arm system and the initial angle information of each joint; Establish the objective function and constraints for the nonlinear programming method; The final pose of the dual-arm spatial manipulator near the target object is solved using a nonlinear programming method. The nonlinear programming method uses the angles of each joint of the two arms as optimization variables, and its objective function is defined as the sum of the end effector pose error term, the collision risk term, and the joint limit term. The constraints of the nonlinear programming method include linear or nonlinear constraints: the joint angles are within their limit ranges, the end effector is within a certain range near the target object, the end effector maintains a set angle with the target object, and the base disturbance is less than a set threshold. S3. Parameterize the joint trajectory of the dual-arm spatial manipulator from the initial pose to the final pose using a fifth-order polynomial. S4. Fit the joint trajectory and perform collision detection and singularity detection. If there is a collision or singularity, return to step S2 to adjust the objective function and constraints of the nonlinear programming method, and iterate repeatedly until there is no collision or singularity, then proceed to step S5. S5. Outputs the joint motion trajectory of the optimal path for the robotic arm, which is used to control the robotic arm to move along the trajectory.

2. The optimal path planning method for minimizing disturbance of a floating base for a space dual-arm robot according to claim 1, characterized in that, The geometric parameters of the robotic arm are DH parameters and inertial characteristic parameters.

3. The optimal path planning method for minimizing disturbance of a floating base for a space dual-arm robot according to claim 1, characterized in that: The fifth-order polynomial function is: ； in, It is the first The angle of each joint changes over time The function of change, These are the polynomial parameters to be solved. , .

4. The optimal path planning method for minimizing disturbance of a floating base for a space dual-arm robot according to claim 1, characterized in that, The collision detection method based on gap vectors is used to perform collision detection on the fitted joint trajectory.

5. The optimal path planning method for minimizing disturbance of a floating base for a space dual-arm robot according to claim 4, characterized in that, The collision detection method based on gap vectors includes: S41. Abstract and simplify the spatial robotic arm and obstacles using the smallest cuboid; S42. Determine the relative positions and orientations of each pair of cuboids; S43. Calculate the minimum distance and direction between two cuboids; S44. Compare the length of the gap vector with the preset safety distance. If the length of the gap vector is less than the safety distance, then a collision is considered to exist; otherwise, a collision is considered not to exist.

6. The optimal path planning method for minimizing disturbance of a floating base for a space dual-arm robot according to claim 5, characterized in that, The relative position and orientation between any two cuboids are determined by the vector between the center points of the two cuboids and the angle between the orientations of the two cuboids: ； ； ； ； in It is the vector between the center points of the two cuboids. and These are the center points of objects A and B, respectively. , and These are the three orientation vectors of object A. , and These are the three orientation vectors of object B. , and These are the included angles between the orientations of the two cuboids.

7. The optimal path planning method for minimizing disturbance of a floating base for a space dual-arm robot according to claim 5, characterized in that, The calculation of the minimum distance and direction between two cuboids is a vector pointing from any point on the surface of one cuboid to the nearest point on the surface of the other cuboid: ； ； ； in It is the gap vector between the two cuboids. It is the minimum distance between two cuboids. It is the direction of the minimum distance between two cuboids. , and These are the length, width, and height of object A, respectively. , and These are the length, width, and height of object B, respectively.

8. The optimal path planning method for minimizing disturbance of a floating base for a space dual-arm robot according to claim 1, characterized in that, The singularity detection refers to the reachable workspace of the dual-arm robot in its initial pose. If a trajectory point is outside the reachable workspace, it is determined to be a singularity.

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