Method, device and equipment for measuring water surface sliding speed of water-air cross-medium robot

Abstract

The invention relates to a method, a device and equipment for measuring the water surface sliding speed of a water-air cross-medium robot, which indirectly obtain the sliding speed information through an algorithm by using the existing sensor of the water-air cross-medium robot without adopting a traditional speed sensor, for example, the robot can measure the sliding speed by sensing the position signal of the robot. The data are processed and calculated by using an algorithm, and the sliding speed of the water-air cross-medium robot is obtained in real time, so that additional hardware measurement equipment does not need to be added, the dependence on a traditional sensor is remarkably reduced, and meanwhile, the light weight and the practicability of the system are improved; the design is more suitable for the application scene of a miniaturized water-air cross-medium robot with the size and the weight strictly limited.

Description

Technical Field

[0001] This invention belongs to the field of control and measurement technology, and relates to a method, device and equipment for measuring the water surface gliding speed of a water-air cross-medium robot. Background Technology

[0002] As an emerging research direction, water-air cross-medium robots have achieved some initial results, but their theoretical framework and practical applications are still under development. Current research mainly focuses on the dynamic modeling, control strategies, and structural design of cross-medium motion. For example, biomimetic cross-medium robots achieve switching between air and water by mimicking the movement characteristics of animals in nature, while rotor-type cross-medium robots utilize the vertical take-off and landing capabilities of multi-rotors to complete the transition from water surface to air. However, most of these research results focus on cross-medium switching and motion control in a single medium, and research on water surface gliding control at a constant depth remains insufficient.

[0003] During water gliding, the fluid environment is complex, involving the adjustment of multiple controlled variables and the output of multiple actuators, making it difficult to ensure system stability. Current control methods are mainly designed for stability underwater or in the air, lacking effective technical solutions for the control allocation and dynamic adjustment required for water gliding at a constant depth. In addition, water gliding control algorithms require gliding speed as a key input, but existing sensors are difficult to balance in terms of range, size, and weight, failing to provide a suitable gliding speed measurement solution for small cross-medium robots. Summary of the Invention

[0004] To address the problems existing in the above-mentioned traditional technologies, this invention proposes a method for measuring the water surface gliding speed of a water-air cross-medium robot, a device for measuring the water surface gliding speed of a water-air cross-medium robot, and a computer device, which can provide suitable gliding speed measurement for small cross-medium robots.

[0005] To achieve the above objectives, the embodiments of the present invention adopt the following technical solutions: On the one hand, a method for measuring the gliding speed of a water-air cross-medium robot is provided, including the following steps: Obtain the reference position of the hydrofoil of the water-air cross-medium robot on the water surface; The position of the hydrofoil during gliding is measured using the inherent sensors of the water-air cross-medium robot; The reference position is input into the gliding speed estimation algorithm based on the tracking differentiator. The gliding speed estimation algorithm is used to adjust the error feedback of the hydrofoil's position during gliding and calculate and output the gliding speed of the water-air cross-medium robot. The gliding speed includes two velocity components corresponding to the forward direction of the body and the plane of the body in the constructed body coordinate system, respectively.

[0006] On the other hand, a water surface gliding speed measuring device for a water-air cross-medium robot is also provided, comprising: The reference acquisition module is used to acquire the reference position of the hydrofoil of the water-air cross-medium robot on the water surface; The position measurement module is used to measure the position of the hydrofoil during gliding using the inherent sensors of the water-air cross-medium robot. The gliding estimation module is used to input the reference position into the gliding speed estimation algorithm based on the tracking differentiator. The algorithm adjusts the error feedback of the hydrofoil's position during gliding and calculates and outputs the gliding speed of the water-air cross-medium robot. The gliding speed includes two velocity components corresponding to the forward direction of the body and the plane of the body in the constructed body coordinate system, respectively.

[0007] In another aspect, a computer device is also provided, 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 steps of the above-described method for measuring the water surface gliding speed of a water-air cross-medium robot.

[0008] Furthermore, a computer-readable storage medium is also provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the above-described method for measuring the water surface gliding speed of a water-air cross-medium robot.

[0009] One of the above technical solutions has the following advantages and beneficial effects: The aforementioned method, apparatus, and equipment for measuring the gliding speed of the water-air cross-medium robot do not employ traditional speed sensors. Instead, they utilize the existing sensors of the water-air cross-medium robot to indirectly obtain gliding speed information through algorithms. For example, the robot senses its own position signal and uses algorithms to process and calculate this data to obtain the gliding speed of the water-air cross-medium robot in real time. This eliminates the need for additional hardware measurement equipment, significantly reducing reliance on traditional sensors and improving the system's lightweight and practicality. This design is well-suited for applications of miniaturized water-air cross-medium robots where size and weight are strictly limited. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of the present invention or the conventional technology, the drawings used in the description of the embodiments or the conventional technology will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This is a flowchart illustrating a method for measuring the gliding speed of a water-air cross-medium robot in one embodiment. Figure 2 This is a schematic diagram of the body coordinate system in one embodiment; Figure 3 A block diagram of the controller design in one embodiment (TD part); Figure 4 This is a schematic diagram of the module frame of the water surface gliding speed measuring device for a water-air cross-medium robot in one embodiment. Detailed Implementation

[0012] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention.

[0013] It should be noted that, in this document, the reference to "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The presentation of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will understand that the embodiments described herein can be combined with other embodiments. The term "and / or" as used herein refers to any combination of one or more of the associated listed items, and all possible combinations, including such combinations.

[0014] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0015] A water-air cross-medium robot (UAUV) is an unmanned aerial vehicle capable of adaptively transitioning between two different fluid media, underwater and air, and autonomously navigating continuously. It breaks the limitations of previous unmanned aerial vehicles (UAVs), unmanned surface vessels (USVs), and unmanned underwater vehicles (UUVs) that could only navigate in a single specific environment, achieving the goal of simultaneously conducting aerial, surface, and underwater exploration of a specific area using a single unit. Existing water-air cross-medium robots include biomimetic, rotorcraft, fixed-wing, and hybrid UAUV prototypes, which achieve switching between air and water by mimicking the movement characteristics of animals in nature or utilizing the vertical takeoff and landing capabilities of multi-rotors. However, most of these existing research results focus on cross-medium switching and motion control in a single medium, lacking in-depth research on surface gliding control at a constant depth.

[0016] Existing small current meters for underwater robots have insufficient measurement range, failing to meet the practical needs of measuring the gliding speed of water-to-air cross-medium robots. Considering the limitations of current small current meters in terms of measurement speed range—for example, the maximum measurable speed of the DVL-A50 Doppler velocimeter is only 3.75 m / s, while the DVL-A125 Doppler velocimeter, although increasing the maximum measurable speed to 9 m / s, is relatively large and heavy, unsuitable for the hydrofoil gliding scenario of water-to-air cross-medium robots—this specification proposes a gliding speed estimation algorithm based on a tracking differentiator (TD) to accurately estimate the speed of water-to-air cross-medium robots during hydrofoil gliding.

[0017] Among them, the dual-loop PID (Proportional-Integral-Derivative) controller is a commonly used feedback controller that adjusts system deviation in real time through three stages: proportional (P), integral (I), and derivative (D). Proportional control is used for rapid deviation response, integral control is used to eliminate steady-state errors, and derivative control is used to predict deviation trends and prevent overshoot. The dual-loop PID controller is based on a multi-stage PID control structure. The outer loop is mainly used for target control of position or velocity, while the inner loop is responsible for rapid response control of attitude angle or angular velocity.

[0018] Extended State Observer (ESO): An advanced state estimation technique used to estimate system state variables and external disturbances in real time. Compared to traditional state observers, ESO can estimate not only internal system state variables but also unknown external disturbances. Its core design concept is to treat unknown disturbances as an "extended state" and incorporate them into the observer design. By designing appropriate observer gains, ESO can quickly and accurately estimate the system state and disturbances and feed this information back to the controller, thereby improving the robustness and anti-interference capability of the control system. Levenberg-Marquardt (LM) Algorithm: An optimization algorithm for solving nonlinear least squares problems, an improvement on the Gauss-Newton method. The LM algorithm combines the advantages of the steepest descent method and linearization methods (Taylor series expansion), and is suitable for different stages where parameter estimates are far from and close to the optimal value, thus finding the optimal solution faster.

[0019] In one embodiment, such as Figure 1 As shown, a method for measuring the gliding speed of a water-to-air cross-medium robot is provided, which may include the following steps S12 to S16: S12, Obtain the reference position of the hydrofoil of the water-air cross-medium robot on the water surface; S14, the position of the hydrofoil during gliding is measured by the inherent sensors of the water-air cross-medium robot; S16, input the reference position into the gliding speed estimation algorithm based on the tracking differentiator, adjust the error feedback of the hydrofoil's position during gliding through the gliding speed estimation algorithm, and calculate and output the gliding speed of the water-air cross-medium robot; the gliding speed includes two velocity components corresponding to the forward direction of the body and the plane of the body in the constructed body coordinate system, respectively.

[0020] Understandably, for clarity in the subsequent description, a body coordinate system has been defined, such as... Figure 2 As shown. This coordinate system has its origin at the center of gravity of the "system" of the water-air transmedia robot. O b . x b The axis runs along the direction of the fuselage's movement, from the tail to the nose; y b The shaft lies in the plane of the machine body and is perpendicular to it. x b The axis points to the right wing; z b The axis runs perpendicular to the plane of the fuselage and... x b shaft and y b The axes form a right-handed coordinate system.

[0021] The gliding speed estimation process is as follows: a set of differential equations is used to track the reference position and dynamically estimate the gliding speed. The gliding speed estimation algorithm uses the reference position of the water-air transmedia robot during the hydrofoil gliding process. The input is used as the input, and adjustments are made based on error feedback regarding the hydrofoil's position during gliding. The final output consists of two velocity components representing the gliding velocity of the water-air transmedia robot. These two components correspond to respectively as x b The estimated velocity along the axial direction and y b Estimated velocity along the axial direction.

[0022] Furthermore, the taxiing speed estimation algorithm uses the following differential equation (state-space model of a second-order linear time-invariant system) to estimate the taxiing speed:

[0023] In the body coordinate system, This is the reference position of the hydrofoil on the water surface. For the estimated respectively xb Axial direction and y b Position along the axis. u and The estimated water-air transmedia robot is in x b The estimated velocity along the axial direction and y b Estimated velocity along the axial direction. These are control parameters (which can be set according to the position tracking error requirements in specific application scenarios) used to adjust the system's tracking speed for position errors.

[0024] The gliding speed estimation algorithm is based on the input water surface reference position. By dynamically adjusting the system state through a set of differential equations, the two components of the gliding velocity of the water-air transmedia robot are ultimately output. Compared to traditional flowmeter measurement methods, the above-mentioned method for measuring the surface gliding speed of a water-air transmedia robot can accurately estimate the hydrofoil gliding speed of the robot without additional hardware burden, and has high real-time performance and adaptability.

[0025] like Figure 3 The red box in the controller of the water-air cross-medium robot shows the location of the tracking differentiator TD, indicating its position information. First, the data is processed by a tracking differentiator TD, which outputs an estimate of the hydrofoil's current gliding speed. Next, the estimated current gliding speed of the hydrofoil is... With the expected speed of the hydrofoil The deviation between the input and output parameters is input into the PID controller, which can then calculate and output the desired result based on this deviation. x b Desired force in the axial direction f xbd . f zbd For linearization processing along z b Desired force in the axial direction, h d For the desired depth, To represent the actual measured depth, The desired angle for pitch. The actual pitch angle measured in real time by the inertial measurement unit (IMU). This is the estimated value of the disturbance in the depth direction. The pitch angle deviation is processed by a single-stage PID controller to obtain the desired Euler angular velocity. This is the Euler angular velocity transformation matrix. Let ω be the desired angular velocity in the body coordinate system, and FF be the feedforward control unit. For the expected roll angle, Indicates roll angle The derivative with respect to time, Indicates roll angle The measured value, The measured value representing the roll rate. p d This is the expected value of the roll rate. Roll angle The expected value of the perturbation, The measured value representing the pitch rate. Let the pitch angle be the expected value of the disturbance. m d This represents the output value of the pitch controller. This is the measured value of the torque in the pitch direction. l d This indicates the output value of the roll angle controller. This indicates the measured torque value in the roll direction. T 1c This indicates the desired thrust of the left thruster. T 2c This represents the desired thrust of the right-side thruster. This indicates the desired angle of the left hydrofoil. This indicates the desired angle of the right hydrofoil. Indicates the desired horizontal tail angle.

[0026] RC_setpoint is an important concept in the control of water-air cross-medium robots. It is usually used to set parameters such as position, velocity, acceleration, resultant force, yaw angle, and yaw rate of the water-air cross-medium robot. These control instructions can be issued by using the existing mavros library's mavros / setpoint_raw / local command.

[0027] The above-mentioned method for measuring the gliding speed of the water-air cross-medium robot does not use traditional speed sensors. Instead, it utilizes the existing sensors of the water-air cross-medium robot to indirectly obtain gliding speed information through algorithms. For example, the robot senses its own position signal, and the algorithm processes and calculates this data to obtain the gliding speed of the water-air cross-medium robot in real time. This eliminates the need for additional hardware measurement equipment, significantly reducing reliance on traditional sensors and improving the system's lightweight and practicality. This design is more suitable for application scenarios of miniaturized water-air cross-medium robots where size and weight are strictly limited.

[0028] Compared to traditional technologies, this embodiment provides an effective gliding speed measurement scheme for UAUVs (Unmanned Aquanautical Marine Vehicles). The gliding speed estimation algorithm boasts high real-time performance and adaptability, enabling it to operate accurately in complex fluid environments, which is crucial for improving the robot's operational efficiency. Under the existing hardware conditions of UAUVs, the algorithm's advantages are fully utilized to solve the bottleneck problem of speed measurement, demonstrating broad application prospects in various navigation application fields. For example, UAUVs can perform underwater reconnaissance, surveillance, and strike missions, while possessing rapid deployment and aerial maneuverability capabilities. In marine scientific research, UAUVs can conduct marine data collection, environmental monitoring, and seabed exploration, providing more efficient and economical solutions. In maritime search and rescue operations, UAUVs can quickly respond to maritime emergencies, conduct large-scale searches and rescues, and improve search and rescue efficiency and success rates. In resource development, UAUVs provide precise data support and operational assistance in offshore oil and gas exploration and seabed mineral development. In environmental monitoring, UAUVs can be used to monitor the impact of marine pollution and climate change on marine ecosystems, providing scientific evidence for environmental protection.

[0029] In one embodiment, a Kalman filter algorithm or a particle filter algorithm can also be used to estimate the hydrofoil gliding speed based on the sensor data output by the position sensor of the water-air transmedia robot.

[0030] It is understandable that the gliding speed estimation algorithm is primarily a better solution to the current limitations of sensors in water-to-air cross-medium robots, which cannot simultaneously achieve small size, light weight, and large measurement range. The problem of estimating the gliding speed of water-to-air cross-medium robots can be solved through both algorithmic and hardware alternatives. In this embodiment, regarding algorithmic alternatives, classic signal processing methods such as Kalman filtering or particle filtering can be used to achieve accurate gliding speed estimation even when sensor data contains noise or uncertainty. The specific speed estimation process can be understood by referring to the existing calculation processes of these two classic signal processing methods, and will not be elaborated further in this embodiment.

[0031] Regarding hardware solutions, while there is currently no instrument that can simultaneously achieve small size, light weight, and large measurement range for flow velocity, this challenge can be overcome through advancements in hardware technology. For example, higher precision and lighter flow velocity sensors, such as improved laser Doppler current meters or ultrasonic velocimeters, can be developed. These devices may be able to further optimize their size and weight while maintaining a large measurement range, thereby supporting their application in small water-air cross-medium robots to achieve accurate estimation of the hydrofoil gliding speed of these robots.

[0032] It should be understood that, although the above process Figure 1The steps in the diagram are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order in which these steps are executed; they can be performed in other orders. Furthermore, the above process... Figure 1 At least some of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0033] In one embodiment, such as Figure 4 As shown, a water surface gliding speed measurement device for an air-to-water cross-medium robot is also provided, including a reference acquisition module 11, a position measurement module 13, and a gliding estimation module 15. The reference acquisition module 11 is used to acquire the reference position of the hydrofoil of the air-to-water cross-medium robot on the water surface. The position measurement module 13 is used to measure the position of the hydrofoil during gliding using the inherent sensors of the air-to-water cross-medium robot. The gliding estimation module 15 is used to input the reference position into a gliding speed estimation algorithm based on a tracking differentiator, adjust the error feedback of the hydrofoil's position during gliding using the gliding speed estimation algorithm, and calculate and output the gliding speed of the air-to-water cross-medium robot; the gliding speed includes two velocity components corresponding to the forward direction of the robot body and the plane of the robot body in the constructed body coordinate system, respectively.

[0034] The aforementioned water surface gliding speed measurement device for the water-air cross-medium robot does not use traditional speed sensors. Instead, it utilizes the existing sensors of the water-air cross-medium robot to indirectly obtain gliding speed information through algorithms. For example, the robot senses its own position signal, and the algorithm processes and calculates this data to obtain the gliding speed of the water-air cross-medium robot in real time. This eliminates the need for additional hardware measurement equipment, significantly reducing reliance on traditional sensors and improving the system's lightweight and practicality. This design is more suitable for application scenarios of miniaturized water-air cross-medium robots where size and weight are strictly limited.

[0035] In one embodiment, the gliding speed estimation algorithm includes a state-space model of a second-order linear time-invariant system, a Kalman filter algorithm, or a particle filter algorithm.

[0036] In one embodiment, the state-space model of a second-order linear time-invariant system is:

[0037] in, This is the reference position of the hydrofoil on the water surface. For the estimated respectivelyx b Axial direction and y b Position in the axial direction u and They are estimated respectively x b Axial direction and y b Velocity in the axial direction, For control parameters, for x b The rate of change of position in the axial direction for x b Rate of change of axial velocity for y b The rate of change of position in the axial direction for y b Rate of change of velocity in the axial direction.

[0038] It is understood that the explanations of the features in the above-mentioned water surface gliding speed measuring device 100 for the water-air cross-medium robot can be understood by referring to the corresponding explanations in the various embodiments of the water surface gliding speed measuring method for the water-air cross-medium robot. Each module in the above-mentioned water surface gliding speed measuring device 100 for the water-air cross-medium robot can be implemented entirely or partially through software, hardware, or a combination thereof. The above-mentioned components can be embedded in hardware or independently of a device with data processing capabilities, or stored in software in the memory of the aforementioned device, so that the processor can call and execute the operations corresponding to each module. The aforementioned device can be, but is not limited to, various types of computers already existing in the art.

[0039] In one embodiment, a computer device is also provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to perform the following processing steps: acquiring a reference position of the hydrofoil of the water-air cross-medium robot on the water surface; measuring the position of the hydrofoil during gliding using the inherent sensors of the water-air cross-medium robot; inputting the reference position into a gliding speed estimation algorithm based on a tracking differentiator; adjusting the error feedback of the position of the hydrofoil during gliding using the gliding speed estimation algorithm; and calculating and outputting the gliding speed of the water-air cross-medium robot; the gliding speed includes two velocity components corresponding to the forward direction of the robot body and the plane of the robot body in the constructed body coordinate system, respectively.

[0040] In one embodiment, when the processor executes the computer program, it can also implement the steps or sub-steps added in the various embodiments of the above-described method for measuring the water surface gliding speed of a water-air cross-medium robot.

[0041] In one embodiment, a computer-readable storage medium is also provided, on which a computer program is stored. When the computer program is executed by a processor, it performs the following processing steps: obtaining the reference position of the hydrofoil of the water-air cross-medium robot on the water surface; measuring the position of the hydrofoil during gliding using the inherent sensors of the water-air cross-medium robot; inputting the reference position into a gliding speed estimation algorithm based on a tracking differentiator; adjusting the error feedback of the position of the hydrofoil during gliding using the gliding speed estimation algorithm; and calculating and outputting the gliding speed of the water-air cross-medium robot; the gliding speed includes two velocity components corresponding to the forward direction of the robot body and the plane of the robot body in the constructed body coordinate system, respectively.

[0042] In one embodiment, when the computer program is executed by the processor, it can also implement the steps or sub-steps added to the various embodiments of the above-described method for measuring the water surface gliding speed of a water-air cross-medium robot.

[0043] 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. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), memory bus DRAM (RDRAM), and interface DRAM (DRDRAM), etc.

[0044] 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.

[0045] The above embodiments merely illustrate several implementation methods of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of protection of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and all such modifications and improvements fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the appended claims.

Claims

1. A method for measuring the gliding speed of a water-to-air transmedia robot, characterized in that, Including the following steps: Obtain the reference position of the hydrofoil of the water-air cross-medium robot on the water surface; The position of the hydrofoil during gliding is measured using the inherent sensors of the water-air cross-medium robot; The reference position is input into the gliding speed estimation algorithm based on the tracking differentiator. The gliding speed estimation algorithm is used to adjust the error feedback of the hydrofoil's position during gliding and calculate and output the gliding speed of the water-air cross-medium robot. The gliding speed includes two velocity components corresponding to the forward direction of the body and the plane of the body in the constructed body coordinate system, respectively.

2. The method for measuring the water surface gliding speed of a water-air cross-medium robot according to claim 1, characterized in that, Gliding speed estimation algorithms include state-space models of second-order linear time-invariant systems, Kalman filtering algorithms, or particle filtering algorithms.

3. The method for measuring the water surface gliding speed of a water-air cross-medium robot according to claim 2, characterized in that, The state-space model of a second-order linear time-invariant system is: in, This is the reference position of the hydrofoil on the water surface. For the estimated respectively x b Axial direction and y b Position in the axial direction u and They are estimated respectively x b Axial direction and y b Velocity in the axial direction, For control parameters, for x b The rate of change of position in the axial direction for x b Rate of change of axial velocity for y b The rate of change of position in the axial direction for y b Rate of change of velocity in the axial direction.

4. A device for measuring the gliding speed of a water-to-air cross-medium robot, characterized in that, include: The reference acquisition module is used to acquire the reference position of the hydrofoil of the water-air cross-medium robot on the water surface; The position measurement module is used to measure the position of the hydrofoil during gliding using the inherent sensors of the water-air cross-medium robot. The gliding estimation module is used to input the reference position into the gliding speed estimation algorithm based on the tracking differentiator. The algorithm adjusts the error feedback of the hydrofoil's position during gliding and calculates and outputs the gliding speed of the water-air cross-medium robot. The gliding speed includes two velocity components corresponding to the forward direction of the body and the plane of the body in the constructed body coordinate system, respectively.

5. The water surface gliding speed measuring device for a water-air cross-medium robot according to claim 4, characterized in that, Gliding speed estimation algorithms include state-space models of second-order linear time-invariant systems, Kalman filtering algorithms, or particle filtering algorithms.

6. The water surface gliding speed measuring device for a water-air cross-medium robot according to claim 5, characterized in that, The state-space model of a second-order linear time-invariant system is: in, This is the reference position of the hydrofoil on the water surface. For the estimated respectively x b Axial direction and y b Position in the axial direction u and They are estimated respectively x b Axial direction and y b Velocity in the axial direction, For control parameters, for x b The rate of change of position in the axial direction for x b Rate of change of axial velocity for y b The rate of change of position in the axial direction for y b Rate of change of velocity in the axial direction.

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, When the processor executes the computer program, it implements the steps of the water surface gliding speed measurement method for a water-air transmedia robot as described in any one of claims 1 to 3.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the water surface gliding speed measurement method for the water-air transmedia robot according to any one of claims 1 to 3.

Images