Three-dimensional motion control methods, devices, equipment, media, and products for underwater flexible robots

Abstract

This application discloses a three-dimensional motion control method, device, equipment, medium, and product for underwater flexible robots, relating to the fields of flexible robot automation technology and nonlinear dynamics modeling and analysis control. The method is applicable to robots with periodic fluctuations and flexible motion characteristics. The method includes: acquiring information data of the target underwater flexible robot; based on the information data and the body wave equation of the target underwater flexible robot, fitting hydrodynamic parameters using physical experiments and fluid dynamics simulations to obtain the hydrodynamic equation; determining a dynamic model based on the hydrodynamic equation using Lagrange theory; and performing closed-loop motion control based on the dynamic model in three-dimensional space to achieve three-dimensional trajectory tracking control of the target underwater flexible robot; the three-dimensional space is determined based on the speed, heading, and depth of the target underwater flexible robot. This application aims to achieve three-dimensional motion control of underwater flexible robots.

Description

Technical Field

[0001] This application relates to the fields of flexible robot automation technology and nonlinear dynamics modeling, analysis and control, and in particular to a three-dimensional motion control method, device, equipment, medium and product for underwater flexible robots. Background Technology

[0002] Currently, most research on underwater robot modeling and control focuses on rigid-body underwater vehicles. Their dynamic modeling generally employs a rigid-body six-degree-of-freedom model, which cannot accurately describe the impact of local deformation caused by flexible structures on overall motion. In particular, it lacks analysis of the characteristics of flexible motion interacting with water flow in an aquatic environment and its impact on motion control. Some studies have attempted to treat flexible bodies as multi-segment rigid bodies or establish linear models based on simplifying assumptions, but these still have shortcomings. For example, there is a lack of a unified flexible robot modeling framework, control methods are highly coupled and have poor adaptability, and there is a lack of a real-time, usable integrated modeling-control mechanism. Summary of the Invention

[0003] The purpose of this application is to provide a method, device, equipment, medium, and product for three-dimensional motion control of an underwater flexible robot, which can realize three-dimensional motion control of the underwater flexible robot.

[0004] To achieve the above objectives, this application provides the following solution:

[0005] In a first aspect, this application provides a three-dimensional motion control method for an underwater flexible robot, which is applicable to robots with periodic fluctuations and flexible motion characteristics; the method includes:

[0006] Acquire information data of the target underwater flexible robot; the information data includes: CAD shape information and fluid information; the fluid information includes: fluid density and flow velocity;

[0007] Based on the information data, and using the body wave equation of the target underwater flexible robot, the hydrodynamic parameters are fitted using physical experiments and fluid dynamics simulations to obtain the hydrodynamic equation.

[0008] Based on Lagrange theory, the dynamic model is determined according to the hydrodynamic equations.

[0009] Based on the dynamic model, closed-loop motion control in three-dimensional space is performed to achieve three-dimensional trajectory tracking control of the target underwater flexible robot; the three-dimensional space is determined based on the speed, heading, and depth of the target underwater flexible robot.

[0010] Secondly, this application provides a three-dimensional motion control device for an underwater flexible robot, comprising:

[0011] An information data acquisition module is used to acquire information data of the target underwater flexible robot; the information data includes: CAD shape information and fluid information; the fluid information includes: fluid density and flow velocity.

[0012] The fitting module is used to fit the hydrodynamic parameters based on the information data and the body wave equation of the target underwater flexible robot, using physical experiments and fluid dynamics simulation methods, to obtain the hydrodynamic equation.

[0013] The dynamic model determination module is used to determine the dynamic model based on the hydrodynamic equations according to Lagrange theory.

[0014] The control module is used to perform closed-loop motion control based on the dynamic model in three-dimensional space to achieve three-dimensional trajectory tracking control of the target underwater flexible robot; the three-dimensional space is determined based on the speed, heading and depth of the target underwater flexible robot.

[0015] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described three-dimensional motion control method for an underwater flexible robot.

[0016] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aforementioned three-dimensional motion control method for an underwater flexible robot.

[0017] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the aforementioned three-dimensional motion control method for an underwater flexible robot.

[0018] According to the specific embodiments provided in this application, the following technical effects are disclosed:

[0019] This application provides a method, device, equipment, medium, and product for three-dimensional motion control of an underwater flexible robot. The method is applicable to robots with periodic fluctuations and flexible motion characteristics. It involves acquiring information data of the target underwater flexible robot; based on this data and the body wave equation of the target underwater flexible robot, fitting hydrodynamic parameters using physical experiments and fluid dynamics simulations to obtain the hydrodynamic equation; determining a dynamic model based on the hydrodynamic equation using Lagrange theory; and performing closed-loop motion control in three-dimensional space based on the dynamic model to achieve three-dimensional trajectory tracking control of the target underwater flexible robot. This application emphasizes the flexible motion characteristics of the robot, including periodicity and fluctuation, and considers closed-loop control under the influence of flexible deformation and random disturbances during interaction with the external environment. Furthermore, this application determines the dynamic model based on the hydrodynamic equation using Lagrange theory, thereby achieving closed-loop motion control in three-dimensional space encompassing velocity, heading, and depth. Therefore, this application enables three-dimensional motion control of underwater flexible robots. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 A flowchart of a three-dimensional motion control method for an underwater flexible robot;

[0022] Figure 2 A flowchart illustrating the overall process control method for three-dimensional motion control of underwater flexible robots;

[0023] Figure 3 This is a three-dimensional motion control block diagram;

[0024] Figure 4 A schematic diagram of the fitting results for hydrodynamic data;

[0025] Figure 5 This is a schematic diagram illustrating the effect of three-dimensional trajectory tracking control.

[0026] Figure 6 This is a schematic diagram illustrating the speed stabilization effect;

[0027] Figure 7 This is a schematic diagram illustrating the heading stabilization effect.

[0028] Figure 8 This is a schematic diagram illustrating the deep stabilization effect;

[0029] Figure 9 This is a schematic diagram illustrating the pitch angle stabilization effect.

[0030] Figure 10 This is a structural diagram of a three-dimensional motion control device for an underwater flexible robot.

[0031] Figure 11 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0032] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0033] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0034] In one exemplary embodiment, a three-dimensional motion control method for an underwater flexible robot is provided, which is applicable to robots with periodic fluctuations and flexible motion characteristics. For example... Figure 1 As shown, the method includes:

[0035] Step 100: Acquire information data of the target underwater flexible robot. Information data includes: CAD shape information and fluid information; fluid information includes: fluid density and flow velocity.

[0036] Step 200: Based on the information data and the body wave equation of the target underwater flexible robot, the hydrodynamic parameters are fitted using physical experiments and fluid dynamics simulation to obtain the hydrodynamic equation.

[0037] Step 300: Based on Lagrange theory, determine the dynamic model according to the hydrodynamic equations.

[0038] Step 400: Perform closed-loop motion control based on the dynamic model in three-dimensional space to achieve three-dimensional trajectory tracking control of the target underwater flexible robot. The three-dimensional space is determined based on the target underwater flexible robot's velocity, heading, and depth.

[0039] In one embodiment, based on information data and the body wave equation of the target underwater flexible robot, hydrodynamic parameters are fitted using physical experiments and fluid dynamics simulations to obtain the hydrodynamic equation, which specifically includes:

[0040] Based on the information data and the body wave equation of the target underwater flexible robot, the fluid dynamic data is determined by using fluid dynamics simulation. The fluid dynamic data includes forward thrust data and turning torque.

[0041] Using a physical experiment, the target underwater flexible robot was induced to descend at a constant speed by changing the pitch rudder, and the pitch torque was determined based on the measured pitch angular velocity.

[0042] Based on the hydrodynamic data and pitching moment, the hydrodynamic parameters are fitted to the preset hydrodynamic equations to obtain the hydrodynamic equations.

[0043] The expression corresponding to the body wave equation is:

[0044] .

[0045] in, for t The lateral offset of the target underwater flexible robot relative to the body centerline at any given moment; s The volume wave state quantity is the state quantity along the axial direction from the head to the tail tip of the target underwater flexible robot. All are constants; The wave number corresponding to the body's fluctuations; The fluctuation frequency; This is the turning offset.

[0046] The expression for the hydrodynamic equation is:

[0047] .

[0048] in, for t The hydrodynamic equations corresponding to the forward thrust data at any given moment; For linear hydrodynamic coefficients that couple inertia and friction; This is the frequency nonlinear term of the average thrust; This represents the nonlinear term for the fluctuation amplitude; For hydrodynamic coefficients; This refers to the frequency nonlinear term of the wave thrust; All are constant coefficients; The fluctuation frequency; For thrust phase delay; for t The hydrodynamic equation corresponding to the turning moment at time ; For control of turning motion; The fluid dynamic coefficient is the fluctuation term of the turning moment. For linear hydrodynamic coefficients; These are second-order nonlinear hydrodynamic coefficients; for tThe hydrodynamic equation corresponding to the pitching moment at time t; For fluid density; The resultant velocity of the three axes of velocity; S The target is the maximum cross-sectional area of ​​the underwater flexible robot body. L The body length of the target underwater flexible robot; The linear hydrodynamic coefficient for pitching moment; Let be the second-order nonlinear hydrodynamic coefficient; This is the pitch angle control variable.

[0049] In one embodiment, the method for determining the dynamic model specifically includes:

[0050] The hydrodynamic equations are input to the corresponding positions of the six degrees of freedom of the preset robot control force vector to determine the robot control force vector.

[0051] Based on Lagrange theory, the dynamic model is determined according to the robot's control force vector; the expression of the dynamic model is:

[0052] .

[0053] in, For the additional mass matrix; For the speed-related damping term; Here is the damping matrix; For the velocity coupling term caused by rotation; The Coriolis force matrix; The six-degree-of-freedom generalized velocity vector of the system includes linear velocity and angular velocity; The time derivative of the velocity vector; This is a coupling term of gravity and buoyancy; The restoring force matrix; The pose in three-dimensional space; Disturbance from external water flow; This is the robot's control force vector.

[0054] As an optional implementation method, closed-loop motion control based on a three-dimensional space is performed according to a dynamic model to achieve three-dimensional trajectory tracking control of the target underwater flexible robot, specifically including:

[0055] Based on the dynamic model, a discrete velocity control law for the target underwater flexible robot is determined; the expression for the discrete velocity control law is:

[0056] .

[0057] Based on the dynamic model, the discrete heading control law for the target underwater flexible robot is determined; the expression of the discrete heading control law is:

[0058] .

[0059] Based on the dynamic model, the pitch angle control law for the target underwater flexible robot at different depths is determined; the expression for the pitch angle control law is:

[0060] .

[0061] in, It is a discrete velocity control law; For discrete-time variables; It is a constant; and All are discrete-time variables The corresponding control parameters; For discrete-time variables The corresponding error between the expected speed and the robot speed; This represents the cumulative error in the robot's speed. For the robot's motion cycle; For time loop variables; For discrete heading control law; This is the heading control value from the previous moment; and All are constants; The angular velocity of the heading at the current moment; For heading error; All are controller parameters; This refers to the pitch angle error; This represents the pitch angle error at the previous moment; To accumulate pitch angle error; For pitch angle control cycle; This is the pitch control law.

[0062] The technical problem this application aims to solve is to provide a three-dimensional dynamic modeling method and hydrodynamic equations for underwater flexible robots. This modeling method is applicable to robots with significant periodic fluctuations and flexible motion characteristics, such as underwater biomimetic robotic fish and underwater biomimetic robotic snakes. The system's dynamics and precise hydrodynamics are obtained through Lagrange equations and data-driven methods, respectively, thus avoiding direct modeling of the complex coupling relationships within the robot's internal mechanisms. Based on the dynamic model, an online, real-time usable three-dimensional motion controller for the flexible robot is designed.

[0063] The technical solution of this application is as follows: First, the flexible motion of the robot is defined; second, the hydrodynamic equations are established and their parameters are fitted based on fluid dynamics data obtained from experiments and Computational Fluid Dynamics (CFD) simulations; then, the hydrodynamic equations are input into a Lagrange dynamics model, and the robot state is solved based on the action of internal and external forces; finally, a three-dimensional closed-loop motion controller for the robot is designed using the designed model, which can support the robot to achieve specific trajectory tracking in underwater space. The flowchart of this application is shown below. Figure 2 As shown, the specific steps are as follows:

[0064] Step 1: Define the body deformation of the flexible robot.

[0065] The motion characteristics of underwater flexible waves in robots are defined using the body wave equation:

[0066] .

[0067] The amplitude envelope of the lateral motion follows a quadratic function. ,in All are constants; body fluctuations are represented by wavenumbers. Description, in which l Multiples of body length (BL) The value of can be set according to the robot's actual wave capability, and is generally within a dynamic range. Different combinations of the above parameters will exhibit different flexible motion modes. Based on this body wave equation, it can be seen that the motion of the target underwater flexible robot has wave-like and periodic characteristics, and the robot's motion period is... Defined as The motion of the flexible robot is defined using the body wave equation, which is then input into step two.

[0068] Step 2: Design the hydrodynamic equations of the flexible robot in an aquatic environment, and provide a method for determining its constant coefficients through data-driven approaches.

[0069] In the computational fluid dynamics (CFD) simulation software, input the volume wave equation from step one. Additionally, import the CAD shape of the robot to be modeled, set the fluid density and velocity, and change the wave frequency accordingly. f and turning offset Records CFD output hydrodynamic data for linear and turning motions in a two-dimensional plane, including forward thrust data at different frequencies. and turning torque .

[0070] An experiment was conducted in the physical world. By changing the pitch control, the robot was made to perform a uniform descent motion, and the pitch angular velocity measured by an IMU was recorded under different pitch control conditions. r The pitching moment can be obtained from the data and calculations. ,in, It is the moment of inertia along the pitch axis.

[0071] Two-dimensional plane data obtained from simulation and experiment and Input the designed hydrodynamic equations respectively. The constant coefficients of the equation are obtained by fitting. The hydrodynamic equations designed in this application are as follows:

[0072] .

[0073] in, The wave state of the flexible robot is determined in step one (L is the body length of the target underwater flexible robot). It reflects the nonlinear relationship between average thrust, frequency, and amplitude.

[0074] It is in step one The result, converted to angular units, is also the control quantity for turning motion.

[0075] Input the hydrodynamic equations with determined coefficients into step three.

[0076] Step 3: Design a six-degree-of-freedom dynamic model for the robot.

[0077] definition This is the robot control force vector. The hydrodynamic equations obtained in step two are input into the corresponding positions of the six degrees of freedom of the control force vector to obtain... Define the linear velocity and angular velocity in the robot's body coordinate system as follows: The displacement and attitude in the world coordinate system are The coordinate system transformation relationship is as follows: ,in, These are forward thrust, yaw control torque, and pitch control torque, respectively. These are forward velocity, lateral velocity, longitudinal velocity, roll rate, yaw rate, and pitch rate, respectively. These are forward displacement, lateral displacement, longitudinal displacement, and roll angle, yaw angle, and pitch angle, respectively. Let be the derivative of the six-free generalized position vector with respect to time; For coordinate system rotation transformation of the position vector, where All are Euler angle transformation matrices. For Jacobian matrices, The direct relationship between linear velocity and the rate of change of position is expressed in the following form:

[0078] .

[0079] definition Based on Lagrange theory, the following dynamic model is established:

[0080] .

[0081] Define angle of attack as The sideslip angle is Define gravity With buoyancy difference for The coordinate components of the center of gravity in the volume coordinate system . It is the disturbance of external water flow, among which These are forward disturbance, lateral disturbance, longitudinal disturbance, roll disturbance, heading disturbance, and pitch disturbance. Except for the variables defined in steps one through three, all other parameters are constants. The expanded form of the correlation matrix is ​​as follows:

[0082] .

[0083] Additional mass matrix All parameters in the table are fixed constants, and their values ​​are shown in Table 3. m represents the robot's mass. All are additional quality coefficients. Let these be the coordinates of the center of mass in the volume coordinate system. Both are the robot's inherent rotational inertia.

[0084] .

[0085] exist In this context, variables include those other than linear velocity and angular velocity, such as... The remaining parameters are all fixed constants, and their values ​​are shown in Table 3. All are linear damping coefficients. All are nonlinear damping coefficients.

[0086] .

[0087] exist In this context, the variables include linear velocity and angular velocity variables, such as... Angle of attack Sideslip angle Combined speed The remaining parameters are all fixed constants, and their values ​​are shown in Table 3. For fluid density, S The target is the maximum cross-sectional area of ​​the underwater flexible robot body. L The body length of the target underwater flexible robot; All are hydrodynamic coefficients in the x-direction. All are hydrodynamic coefficients in the y-direction. All are hydrodynamic coefficients in the z-direction. All are torque coefficients about the x-axis. All are moment coefficients about the z-axis. All are torque coefficients about the y-axis.

[0088] .

[0089] In the restoring force matrix In this context, variables include attitude variables, such as... The remaining parameters are all fixed constants, and their values ​​are shown in Table 3. For gravity, It is the difference between gravity and buoyancy.

[0090] Step 4: Design a model-based closed-loop motion control system for the robot in three-dimensional space.

[0091] Based on the dynamic model from step three, the controllable degrees of freedom have been determined to be thrust, yaw, and pitch. Position and depth control require indirect control through yaw and pitch motions. The world coordinates of the desired trajectory in space are defined as follows: The expected speed is .

[0092] Design separate control systems for speed, heading, and depth.

[0093] According to fluctuation frequency Simplify the first line of the dynamic model in step three to obtain the simplified model. ,in This is the average velocity over a single period T, which more accurately reflects the actual motion state of the flexible robot when calculating control errors. The constant term is... The perturbation is unknown but bounded. The input is... At that time, the error between the control output of the simplified model and the actual control output of the robot is... The control parameters are adaptively adjusted using the output error between the model and the actual system. Design a discrete speed control law for a speed controller. as follows:

[0094] .

[0095] .

[0096] All are constants.

[0097] For discrete-time variables; For the robot's motion cycle; For time loop variables; and All are discrete-time variables The corresponding control parameters have the following update law for the discrete-time variable k+1: ; This represents the cumulative error in the robot's speed. For discrete-time variables The corresponding error between the expected speed and the robot speed; For the desired speed, The average velocity over the period; For discrete-time variables The corresponding model error at that time; For discrete-time variables The corresponding model error at that time.

[0098] The heading controller frequency is consistent with the speed controller frequency. During the design process, the heading angular velocity updated in the fifth row of the model in step three is used for each update. q The input controller is used as an estimate of the actual system's heading angular velocity. This yields the discrete heading control law. as follows:

[0099] .

[0100] in, All are constants. This is the heading control value from the previous moment; The angular velocity of the heading at the current moment; For the heading error, where These are all reference positions on the desired trajectory. All are discrete-time variables k The corresponding actual position of the robot at that time This is the actual course.

[0101] The model obtained in step three is transformed into a pitch angle tracking control problem. An online pitch angle generation method based on a combination of error feedback and inverse kinematics is designed. The robot's longitudinal kinematic model is obtained from the sixth row of the model in step three. The robot's current depth error is... In this state, a generator for the expected depth change rate with a proportional-integral-differential structure is introduced. .Will Input cost function Solving a single-variable optimization problem Obtain the desired pitch angle control target Therefore, the pitch angle control law for:

[0102] .

[0103] The depth control cycle is as follows: , For deep control frequency, controller parameters , all of which are constants. This refers to the pitch angle error; This represents the pitch angle error at the previous moment; To accumulate pitch angle error; For discrete-time variables k The corresponding expected pitch angle, This is the actual pitch angle.

[0104] Integrated control flowchart as follows Figure 3 Under this control framework, model-based three-dimensional trajectory tracking control of flexible robots can be realized.

[0105] The modeling method proposed in this application breaks through the limitations of traditional rigid body modeling and can be applied to underwater robots with non-rigid bodies, multiple joints, strong internal mechanism coupling, and highly flexible structures. It has the advantages of structural versatility and high modeling accuracy, and is particularly suitable for flexible underwater systems with complex topologies and large deformations.

[0106] Based on the data-driven approach, this application directly fits the parameters of the constructed hydrodynamic equations to experimental and CFD simulation data without requiring explicit analytical expression of complex fluid fields. This enhances the model's representation of phenomena such as flexible body deformation and periodic oscillation, effectively reducing the complexity and error sensitivity of traditional mechanistic model derivation.

[0107] Based on the dynamic modeling framework, a real-time deployable closed-loop controller was further designed to support stable pose adjustment of the flexible robot in an underwater environment. The controller fully integrates the dynamic model and inverse kinematics, exhibiting good real-time performance, stability, and physical consistency.

[0108] The integrated modeling and control solution proposed in this application has strong versatility and scalability, and can effectively support underwater flexible robots to achieve stable trajectory tracking control in three-dimensional space in practical applications.

[0109] In one embodiment, an approximately “S”-shaped flexible wave was simulated, and the specific parameter settings are shown in Table 1. The body wave equation from step one was input into step two.

[0110] Step 2: Using computational fluid dynamics (CFD) simulation software, input the body wave equations defined in Step 1, import the CAD shape of the robot to be modeled (in this example, import an underwater robot with a tuna-like shape), and set the fluid density. When the flow velocity is 0 (still water), the fluctuation frequency is changed. and turning offset Records CFD output hydrodynamic data results for linear and turning motions in a two-dimensional plane, including forward thrust data at different frequencies. and turning torque The CFD simulation is set to output 1000 data points per second, therefore the thrust and turning torque are assumed to be continuous.

[0111] An experiment was conducted in the physical world. By changing the pitch control, the robot was made to perform a uniform descent motion, and the pitch angular velocity measured by an IMU was recorded under different pitch control conditions. r The pitching moment can be obtained from the data and calculations. ,in It is the moment of inertia along the pitch axis, and the values ​​are shown in Table 3.

[0112] Two-dimensional plane data obtained from simulation and experiment and Input the hydrodynamic equations respectively Using the curve fitter in MATLAB, the constant coefficients of the equation are obtained. The hydrodynamic equations designed in this application are as follows:

[0113] .

[0114] The wave state of the flexible robot is determined from step one (L=0.55m is the length of the robot body).

[0115] In this embodiment, the robot's single active joint is positioned at L / 2, therefore the conversion relationship is: . This refers to the fluid density; the robot's inherent parameters are shown in Table 3.

[0116] The fitting results of the hydrodynamic equations are shown in Table 2. Figure 4 This is a schematic diagram showing the matching results of partial hydrodynamic data and the fitting of hydrodynamic equations, demonstrating the adaptability of the fitting accuracy across various frequency bands. The hydrodynamic equations with determined coefficients are then input into step three.

[0117] Step 3:

[0118] definition The robot's initial state is: , See Table 3 for specific settings. It is an external water flow disturbance, set in the simulation. Follow the interval The uniform distribution on the surface, in addition The correlation matrix expansion is shown below, and the inherent parameters in the dynamic model are shown in Table 3. Note that, except for the variables defined in steps one through three, all other parameters are constants.

[0119] Step 4: Import the model from Step 3 into MATLAB for simulation. Set the simulation time to 100 seconds and define the world coordinates of the desired trajectory in space as follows:

[0120]

[0121] Next, the control laws for speed, heading, and depth are calculated separately.

[0122] Set the robot's motion frequency f = 2.5Hz, simplify the first line of the dynamic model in step three, and obtain the simplified model. ,in This is the average velocity over a single period T, which more accurately reflects the actual motion state of the flexible robot when calculating control errors. The constant term is... The perturbation is unknown but bounded. The input is... At that time, the error between the control output of the simplified model and the actual control output of the robot is... The control parameters are adaptively adjusted using the output error between the model and the actual system. Design a discrete speed control law for a speed controller. .

[0123] It is a constant coefficient.

[0124] The heading controller frequency is consistent with that of the speed controller. During the design process, the heading angular velocity q updated in the fifth row of the model in step three is input into the controller as an estimate of the actual system's heading angular velocity. This yields the discrete heading control law. . It is a constant coefficient.

[0125] The robot's depth control problem is transformed into a pitch angle tracking control problem using the model obtained in step three. An online pitch angle generation method based on a combination of error feedback and inverse kinematics is designed. The robot's longitudinal kinematic model is obtained from the sixth row of the model in step three. The robot's current depth error is... In this state, a generator for the expected depth change rate with a proportional-integral-differential structure is introduced. ,in This expression can be viewed as a "feedforward + feedback" estimator for the depth tracker, suppressing steady-state bias and enhancing response capability. Input cost function Solving a single-variable optimization problem Obtain the desired pitch angle control target Therefore, the pitch angle control law for:

[0126] .

[0127] in, Depth control frequency Controller parameters .

[0128] Overall control block diagram as follows Figure 3 Within this control framework, model-based 3D trajectory tracking control of flexible robots can be achieved, and the robot's 3D trajectory tracking motion control effect in space is as follows: Figure 5 As shown, this effect demonstrates the effectiveness of the 3D motion control framework; the robot's speed, heading, depth, and pitch angle stabilization effects are respectively as follows: Figures 6 to 9 As shown, the results demonstrate the stability and convergence of each control law.

[0129] Table 1. Robot Flexible Motion Parameter Setting Table

[0130]

[0131] Table 2. Parameter Fitting Results of Hydrodynamic Equations

[0132]

[0133] Table 3 Robot Inherent Parameter Setting Table

[0134]

[0135] The significant difference between this application and existing methods lies in its emphasis on the flexible motion characteristics of the robot, including periodicity and fluctuation, and its consideration of a closed-loop control system that undergoes flexible deformation and is affected by random disturbances when interacting with the external environment.

[0136] Existing modeling methods are designed for multi-link flexible robots, using recursive relationships of joint kinematics to obtain the pose information of the robot's end effector. However, this application does not consider the joint motion of the flexible robot. Specifically, it does not use the approximation of joint links to handle flexible motion, but instead obtains hydrodynamic forces directly through a data-driven approach and substitutes them into the dynamic model to solve for pose information. The methods are significantly different.

[0137] Furthermore, this application provides a modeling method for underwater flexible robots and a closed-loop controller design method that includes speed, heading, and depth.

[0138] In one exemplary embodiment, such as Figure 10 As shown, a three-dimensional motion control device for an underwater flexible robot is provided, comprising:

[0139] The information data acquisition module is used to acquire information data of the target underwater flexible robot; the information data includes: CAD shape information and fluid information; the fluid information includes: fluid density and flow velocity.

[0140] The fitting module is used to fit the hydrodynamic parameters based on the information data and the body wave equation of the target underwater flexible robot, using physical experiments and fluid dynamics simulation methods to obtain the hydrodynamic equation.

[0141] The dynamic model determination module is used to determine the dynamic model based on Lagrange theory and hydrodynamic equations.

[0142] The control module is used to perform closed-loop motion control based on three-dimensional space according to the dynamic model, so as to realize the three-dimensional trajectory tracking control of the target underwater flexible robot; the three-dimensional space is determined based on the speed, heading and depth of the target underwater flexible robot.

[0143] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 11 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The database stores three-dimensional motion control data for the underwater flexible robot. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a three-dimensional motion control method for the underwater flexible robot.

[0144] Those skilled in the art will understand that Figure 11 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0145] In one exemplary embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0146] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0147] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0148] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0149] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0150] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0151] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0152] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A three-dimensional motion control method for an underwater flexible robot, characterized in that, The aforementioned three-dimensional motion control method for underwater flexible robots is applicable to robots with periodic fluctuations and flexible motion characteristics. The method includes: Acquire information data of the target underwater flexible robot; the information data includes: CAD shape information and fluid information; the fluid information includes: fluid density and flow velocity; Based on the information data, and using the body wave equation of the target underwater flexible robot, the hydrodynamic parameters are fitted using physical experiments and fluid dynamics simulations to obtain the hydrodynamic equation. Based on Lagrange theory, the dynamic model is determined according to the hydrodynamic equations. Based on the aforementioned dynamic model, closed-loop motion control in three-dimensional space is performed to achieve three-dimensional trajectory tracking control of the target underwater flexible robot; the three-dimensional space is determined based on the target underwater flexible robot's velocity, heading, and depth. Based on the aforementioned information data, and using the body wave equation of the target underwater flexible robot, hydrodynamic parameters are fitted using physical experiments and fluid dynamics simulations to obtain the hydrodynamic equation, which specifically includes: Based on the aforementioned information data, and using the body wave equations of the target underwater flexible robot, the fluid dynamic data are determined using a fluid dynamics simulation method. The fluid dynamic data includes forward thrust data and turning torque. Using physical experiments, the target underwater flexible robot was made to dive at a constant speed by changing the pitch rudder, and the pitch torque was determined based on the measured pitch angular velocity. Based on the fluid dynamics data and the pitching moment, the preset hydrodynamic equations are fitted with hydrodynamic parameters to obtain the hydrodynamic equations.

2. The three-dimensional motion control method for an underwater flexible robot according to claim 1, characterized in that, The expression corresponding to the volume wave equation is: ； in, for t The lateral offset of the target underwater flexible robot relative to the body centerline at any given moment; s The volume wave state quantity is defined along the axial direction from the head to the tail tip of the target underwater flexible robot. All are constants; The wave number corresponding to the body's fluctuations; The fluctuation frequency; This is the turning offset.

3. The three-dimensional motion control method for an underwater flexible robot according to claim 1, characterized in that, The expression for the hydrodynamic equation is: ； in, for t The hydrodynamic equations corresponding to the forward thrust data at any given moment; For linear hydrodynamic coefficients that couple inertia and friction; This is the frequency nonlinear term of the average thrust; This is a nonlinear term representing the fluctuation amplitude; For hydrodynamic coefficients; This refers to the frequency nonlinear term of the wave thrust; All are constant coefficients; The fluctuation frequency; For thrust phase delay; for t The hydrodynamic equation corresponding to the turning moment at time ; For control of turning motion; The fluid dynamic coefficient is the fluctuation term of the turning moment. For linear hydrodynamic coefficients; These are second-order nonlinear hydrodynamic coefficients; for t The hydrodynamic equation corresponding to the pitching moment at time t; For fluid density; The resultant velocity of the three axes of velocity; S The target is the maximum cross-sectional area of ​​the underwater flexible robot body. L The body length of the target underwater flexible robot; The linear hydrodynamic coefficient for pitching moment; These are second-order nonlinear hydrodynamic coefficients; This is the pitch angle control variable.

4. The three-dimensional motion control method for an underwater flexible robot according to claim 1, characterized in that, The method for determining the dynamic model specifically includes: The hydrodynamic equations are input to the corresponding positions of the six degrees of freedom of the preset robot control force vector to determine the robot control force vector; Based on Lagrange theory, a dynamic model is determined according to the robot's control force vector; the expression of the dynamic model is: ； in, For the additional mass matrix; For the speed-related damping term; Here is the damping matrix; For the velocity coupling term caused by rotation; The Coriolis force matrix; The six-degree-of-freedom generalized velocity vector of the system includes linear velocity and angular velocity; The time derivative of the velocity vector; This is a coupling term of gravity and buoyancy; The restoring force matrix; The pose in three-dimensional space; Disturbance from external water flow; This is the robot control force vector.

5. The three-dimensional motion control method for an underwater flexible robot according to claim 1, characterized in that, Based on the aforementioned dynamic model, closed-loop motion control in three-dimensional space is performed to achieve three-dimensional trajectory tracking control of the target underwater flexible robot, specifically including: Based on the aforementioned dynamic model, a discrete velocity control law is determined for the velocity of the target underwater flexible robot; the expression for the discrete velocity control law is: ； Based on the aforementioned dynamic model, a discrete heading control law is determined for the heading of the target underwater flexible robot; the expression for the discrete heading control law is: ； Based on the aforementioned dynamic model, the pitch angle control law for the target underwater flexible robot at its depth is determined; the expression for the pitch angle control law is: ； in, It is a discrete velocity control law; For discrete-time variables; It is a constant; and All are discrete-time variables The corresponding control parameters; For discrete-time variables The error between the expected speed and the robot speed; This represents the cumulative error in the robot's speed. For the robot's motion cycle; For time loop variables; For discrete heading control law; This is the heading control value from the previous moment; and All are constants; The angular velocity of the heading at the current moment; For heading error; All are controller parameters; This refers to the pitch angle error; This represents the pitch angle error at the previous moment; To accumulate pitch angle error; For pitch angle control cycle; This is the pitch control law.

6. A three-dimensional motion control device for an underwater flexible robot, characterized in that, include: The information data acquisition module is used to acquire information data of the target underwater flexible robot; The information data includes: CAD shape information and fluid information; the fluid information includes: fluid density and flow velocity; The fitting module is used to fit the hydrodynamic parameters based on the information data and the body wave equation of the target underwater flexible robot, using physical experiments and fluid dynamics simulation methods, to obtain the hydrodynamic equation. The dynamic model determination module is used to determine the dynamic model based on the hydrodynamic equations according to Lagrange theory. The control module is used to perform closed-loop motion control based on three-dimensional space according to the dynamic model, so as to realize the three-dimensional trajectory tracking control of the target underwater flexible robot; the three-dimensional space is determined based on the speed, heading and depth of the target underwater flexible robot. Based on the aforementioned information data, and using the body wave equation of the target underwater flexible robot, hydrodynamic parameters are fitted using physical experiments and fluid dynamics simulations to obtain the hydrodynamic equation, which specifically includes: Based on the aforementioned information data, and using the body wave equations of the target underwater flexible robot, the fluid dynamic data are determined using a fluid dynamics simulation method. The fluid dynamic data includes forward thrust data and turning torque. Using physical experiments, the target underwater flexible robot was made to dive at a constant speed by changing the pitch rudder, and the pitch torque was determined based on the measured pitch angular velocity. Based on the fluid dynamics data and the pitching moment, the preset hydrodynamic equations are fitted with hydrodynamic parameters to obtain the hydrodynamic equations.

7. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the three-dimensional motion control method for an underwater flexible robot according to any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the three-dimensional motion control method for an underwater flexible robot as described in any one of claims 1-5.

9. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the three-dimensional motion control method for an underwater flexible robot as described in any one of claims 1-5.

Images