Autonomous docking wireless charging method for underwater robot

Abstract

The invention relates to an autonomous docking wireless charging method for an underwater robot, and the method comprises the steps: enabling the underwater robot to monitor the state of a battery in real time through a battery management module, and triggering a charging mode when the electric quantity is detected to be lower than a preset low electric quantity threshold value; when the underwater robot moves to a preset to-be-charged area near the charging base station, magnetic field gradient data and motion state data of the underwater robot are collected, and three-dimensional coordinates and attitude angles of the underwater robot relative to the magnetic dipole beacons of the charging base station are calculated; calculating a position deviation between a charging coil of the underwater robot and a charging base station coil according to the three-dimensional coordinate and the attitude angle; after the position of the underwater robot is adjusted, the underwater robot is driven to be in charging butt joint with the charging base station, and a charging program is started; and monitoring the charging process in real time until the electric quantity of the underwater robot reaches the preset charging electric quantity. According to the invention, charging is autonomously triggered through electric quantity monitoring, accurate docking in a complex environment is realized through magnetic field gradient positioning, and efficient charging is ensured.

Description

Technical Field

[0001] The present application relates to the technical field of underwater robot charging, and in particular to a method for autonomous docking and wireless charging of an underwater robot. Background Art

[0002] Autonomous docking and wireless charging of underwater robots means that the underwater robots, without human intervention, automatically find and approach the charging base station through their own sensors and control systems, and perform contactless energy transmission through electromagnetic induction, magnetic resonance coupling, ultrasound, etc. to achieve wireless charging.

[0003] After searching, it can be found that in the prior art, for example, patent CN202210493431.0 discloses an automatic charging method and system for underwater robots, wherein the automatic charging method of underwater robots is specifically that when the underwater robot determines that its own power is insufficient, it will automatically search for a nearby charging base, and according to the driving trajectory planning in the pipeline, it will automatically arrive in front of the charging base for docking. After the docking is completed, the two parties exchange information, and after confirming that there is no abnormality, charging begins; when the underwater robot is fully charged, the charging base stops charging and enters a dormant state, and the underwater robot automatically leaves and continues to complete the received task information. And for example, patent CN202211725438.7 discloses a wireless charging system and method for underwater robots based on visual positioning. The underwater robot wireless charging method mainly includes: an underwater robot wireless charging system based on visual positioning, which guides the robot to dock through Aruco QR code visual recognition, combines mechanical claws, permanent magnets and support frames to achieve physical fixation, and adopts electromagnetic induction charging. The above two prior arts still have the following defects in actual application:

[0004] First, the automatic charging method for underwater robots relies on a magnetic stripe identifier to guide the robot to the charging base. It can only identify the main and branch magnetic stripe lines. It lacks precise positioning means for the precise spatial position of the charging base, such as axial distance, angular deviation and other key information, which can easily lead to large alignment errors of the charging coil, affecting charging efficiency and stability.

[0005] Secondly, the underwater robot wireless charging method based on visual positioning uses Aruco QR code visual recognition to guide the robot to dock. In the underwater environment, QR code recognition has extremely high visibility requirements. Once in turbid waters, such as areas with high sediment content or a lot of suspended matter, the clarity of the image collected by the camera will drop sharply, and may even cause complete failure of recognition, and the positioning error will also increase significantly. Summary of the Invention

[0006] To address the aforementioned issues with the existing technology, the present application aims to provide a method for autonomous wireless docking and charging of underwater robots. This method utilizes power monitoring to autonomously trigger charging and magnetic field gradient positioning to achieve precise docking in complex environments. Furthermore, dynamic power regulation and intelligent charging termination ensure the efficiency, reliability, and safety of underwater wireless charging.

[0007] The present application discloses a method for autonomously docking and wireless charging of an underwater robot, comprising the following steps:

[0008] S1. The underwater robot monitors the battery status in real time through the battery management module. When the battery level is detected to be lower than the preset low-battery threshold, the underwater robot triggers the charging mode and moves towards the charging base station.

[0009] S2. When the underwater robot moves to a preset charging area near the charging base station, magnetic field gradient data and motion state data of the underwater robot are collected, and the three-dimensional coordinates and attitude angle of the underwater robot relative to the magnetic dipole beacon of the charging base station are calculated;

[0010] S3. Calculate the positional deviation between the underwater robot's charging coil and the charging base station coil based on the three-dimensional coordinates and the attitude angle, and dynamically adjust the underwater robot's position;

[0011] S4. After the position of the underwater robot is adjusted, the underwater robot is driven to dock with the charging base station for charging, so that the main receiving coil of the underwater robot and the main transmitting coil of the charging base station are electromagnetically coupled, and the charging process is started;

[0012] S5. Monitor the charging process in real time and dynamically adjust the transmission power of the main transmitting coil until the power of the underwater robot reaches the preset charging power, thus completing the charging.

[0013] Preferably, the step S1 specifically includes:

[0014] The battery management module monitors the battery status in real time and collects the battery voltage, current and temperature. The collection period T is set, and the battery voltage, current and temperature are collected at time intervals Δt1.

[0015] The current value is accumulated and calculated using the ampere-hour integration method to obtain a charge accumulation value, and the remaining state of charge (SOC) of the battery is calculated by combining the pre-established voltage-state of charge characteristic curve;

[0016] If SOC≥SOC L , it is determined that the battery power of the underwater robot meets the operation requirements, and the underwater robot continues to operate in its original state;

[0017] If SOC<SOC L, it is determined that the battery power of the underwater robot does not meet the operation requirements, the underwater robot stops working, and triggers the charging mode;

[0018] Among them, SOC L Indicates the preset low battery threshold; Δt1<T.

[0019] Preferably, the step S1 further includes:

[0020] After the charging mode is triggered, the sonar module of the underwater robot starts multi-beam scanning, sets the ratio of the number of transmitting beams to the number of receiving beams to be 1:2, and transmits an acoustic pulse signal of a fixed frequency;

[0021] By capturing the echo time difference Δt2 and calibrating the water sound speed c in real time according to the pre-established temperature-sound speed compensation model, the first distance d between the underwater robot and the charging base station is calculated:

[0022]

[0023] The phase difference method is used to analyze the received signals of different beams, and combined with the array signal processing algorithm, the azimuth angle θ of the underwater robot relative to the charging base station is obtained;

[0024] Matching the first distance d and the azimuth angle θ with a preset underwater environment map to obtain initial distance and azimuth information between the underwater robot and the charging base station;

[0025] An initial navigation path for the underwater robot to move toward the charging base station is planned based on the initial distance and the orientation information, and the underwater robot is driven to move toward the charging base station along the initial navigation path.

[0026] Preferably, the step S2 specifically includes:

[0027] When the underwater robot moves along the initial navigation path to a preset charging area near the charging base station, the magnetic gradient tensor measurement module and the inertial measurement module of the underwater robot are started;

[0028] The magnetic gradient tensor measurement module collects underwater magnetic field gradient data in real time through a three-dimensional orthogonal magnetic sensor array, and the inertial measurement module collects the robot's motion state data in real time, and the motion state data includes acceleration data and angular velocity data of the underwater robot;

[0029] The underwater magnetic field gradient data and the motion state data are fused and processed using an extended Kalman filter algorithm to obtain the three-dimensional coordinates and attitude angle of the underwater robot relative to the magnetic dipole beacon of the charging base station.

[0030] Preferably, the step S3 specifically includes:

[0031] The underwater robot is provided with a main receiving coil and an auxiliary alignment coil, and the charging base station is provided with a main transmitting coil and an auxiliary calibration coil. The main receiving coil and the main transmitting coil form a magnetic coupling structure, and the auxiliary alignment coil and the auxiliary calibration coil form a deviation detection unit.

[0032] Calculate, based on the three-dimensional coordinates and the attitude angle, an axial distance deviation ΔD between the center of the main receiving coil and the center of the main transmitting coil, and an angular deviation Δβ between the axis of the main receiving coil and the axis of the main transmitting coil, and collect in real time a mutual inductance coefficient M between the auxiliary alignment coil and the auxiliary calibration coil;

[0033] If ΔD≤ΔD L , Δβ≤Δβ L and M≥M L If both conditions are met, it is determined that the alignment accuracy of the main receiving coil and the main transmitting coil meets the requirements;

[0034] If ΔD≤ΔD L , Δβ≤Δβ L and M≥M L If any one of the conditions is not satisfied, it is determined that the alignment accuracy of the main receiving coil and the main transmitting coil does not meet the requirement, and a position adjustment strategy is executed on the underwater robot;

[0035] Where ΔD L Indicates the preset axial distance deviation threshold; Δβ L Indicates the preset angle deviation threshold; M L represents the theoretical mutual inductance coefficient.

[0036] Preferably, the position adjustment strategy includes:

[0037] If ΔD>ΔD L , it is determined that the axial distance deviation does not meet the requirements, and the thrust size and direction of the underwater robot are adjusted to make the underwater robot move closer to the center of the main transmitting coil until ΔD≤ΔD L ;

[0038] If Δβ>Δβ L , it is determined that the angle deviation does not meet the requirements, and the main body of the underwater robot is rotated to adjust the axis direction of the main receiving coil until Δβ≤Δβ is satisfied. L ;

[0039] If M<M L , it is determined that the adjustment of the current underwater robot is not completed, and the mutual inductance coefficient change rate is calculated according to the mutual inductance coefficient M.

[0040] When M′>0, it means that the underwater robot is currently adjusting the direction correctly, and the original adjustment state is maintained and the adjustment is continued until M≥M is satisfied. L ;

[0041] When M′≤0, it means that the current adjustment direction of the underwater robot deviates, and the adjustment direction is corrected and readjusted until M≥M is satisfied. L .

[0042] Preferably, the step S4 specifically includes:

[0043] The underwater robot is equipped with an electromagnetic adsorption module at the charging docking point with the charging base station. After the alignment accuracy of the main receiving coil and the main transmitting coil meets the requirements, a phased electromagnetic adsorption strategy is executed for docking. The phased electromagnetic adsorption strategy includes a pre-tightening stage, a locking stage, and a stabilization stage.

[0044] A constant current I1 is supplied to the electromagnetic adsorption module for a duration of t1, and the electromagnetic adsorption module generates an initial magnetic field, which causes an initial adsorption force to be generated between the charging docking point of the underwater robot and the docking surface of the charging base station, thus completing the pre-tightening stage;

[0045] After the pre-tightening stage is completed, the electromagnetic adsorption module switches the current to I2 for a duration of t2, adopts current closed-loop control, maintains the current stable at I2, and tightly fits and locks the charging docking point of the underwater robot and the docking surface of the charging base station, completing the locking stage;

[0046] After the locking stage is completed, the proportional-integral-differential control algorithm is used to adjust the current of the electromagnetic adsorption module to I3 to maintain the stable adsorption force. The underwater robot and the charging base station collect the adsorption force of the docking position in real time, and dynamically adjust the current of the electromagnetic adsorption module to maintain the stability of the docking state between the underwater robot and the charging base station, completing the stabilization stage.

[0047] Preferably, the step S4 further includes:

[0048] After the underwater robot completes docking with the charging base station, the main receiving coil of the underwater robot establishes electromagnetic coupling with the main transmitting coil of the charging base station, and the charging process is started. The charging process includes:

[0049] The power supply frequency of the charging transmitter of the charging base station is set to f0, and f0 is aligned with the natural frequency of the dual coils formed by the main transmitting coil and the main receiving coil through a phase-locked loop circuit to maintain the magnetic resonance coupling state of the main transmitting coil and the main receiving coil;

[0050] Calculating a matching capacitance adjustment range based on the coil inductance and operating frequency of the main transmitting coil and the main receiving coil, adjusting the capacitance value sequentially using a binary method and measuring the quality factor Q until Q reaches a preset quality factor threshold, and then stopping capacitance adjustment;

[0051] The charging base station increases the charging transmission power to the rated value, and the charging receiving end of the underwater robot converts the induced alternating current into stable direct current to charge the battery.

[0052] Preferably, the step S5 specifically includes:

[0053] The charging voltage and charging current of the main receiving coil are collected in real time, and the actual active power P is calculated. real , combined with the apparent power P S , calculate the power factor λ and energy transfer efficiency η:

[0054]

[0055] Among them, P trans Indicates the charging transmitter power of the charging base station;

[0056] If λ<λ min and / or η<η min , then increase the transmission power of the charging transmitter of the charging base station until λ=[λ min ,λ max ] and η=[η min , η max ];

[0057] If λ>λ max and / or η>η max , then reduce the transmission power of the charging transmitter of the charging base station until λ=[λ min ,λ max ] and η=[η min , η max ];

[0058] Among them, λ min and λ max Respectively represent the preset power factor lower threshold and power factor upper threshold; η min and η max They represent the preset lower limit threshold of energy transmission efficiency and the upper limit threshold of energy transmission efficiency respectively.

[0059] Preferably, the step S5 further includes:

[0060] The battery management module provides real-time feedback of the underwater robot's battery voltage and current, and uses the ampere-hour integration method and open circuit voltage method to estimate the real-time state of charge (SOC). S ;

[0061] When the real-time state of charge SOC S Reaching the preset state of charge threshold SOC D When the battery is fully charged, the charging mode is switched to constant voltage charging mode, and the real-time current of the battery is continuously monitored until the real-time current of the battery drops to a preset current threshold value, and charging is completed;

[0062] After charging is completed, the battery management module issues a charge termination instruction, and the charging base station linearly reduces the transmission power of the charging transmitter to zero at a fixed slope, cuts off the current of the electromagnetic adsorption module, and passes a reverse current for demagnetization;

[0063] The underwater robot moves in a direction away from the charging base station, and switches to the operation mode after the underwater robot moves outside the area to be charged.

[0064] The advantages of the autonomous docking and wireless charging method for underwater robots described in this application are:

[0065] The present invention provides an autonomous docking wireless charging method for underwater robots. The battery management module monitors the battery level in real time, and automatically triggers the charging mode and moves when the battery level is below the low battery threshold, thereby realizing the autonomy of the charging process and reducing manual intervention. The magnetic field gradient data and motion state data are used to calculate the three-dimensional coordinates and attitude angles, which are suitable for complex underwater environments and have strong positioning and anti-interference capabilities. The method can solve the problem of insufficient magnetic stripe recognition and positioning accuracy in the existing technology. The three-dimensional coordinates and attitude angles are calculated by fusing the magnetic field gradient data with the motion state data, and the key spatial position information such as the axial distance and angular deviation of the underwater robot relative to the charging base station can be accurately obtained, which significantly reduces the alignment error of the charging coil, improves the charging efficiency and stability, and solves the problem of visual positioning being interfered with by turbid waters. No visual recognition technology is used throughout the process, but a non-visual magnetic field gradient positioning method is used, which avoids the influence of underwater visibility on positioning accuracy. The deviation is calculated and the position is adjusted based on the coordinates and attitude angle to ensure the precise alignment of the charging coil, improve the magnetic coupling efficiency, and reduce the energy transmission loss. The charging process is monitored in real time and the transmission power is adjusted to optimize the charging efficiency. The underwater robot's autonomous docking and wireless charging method achieves precise docking in complex environments through power monitoring, autonomously triggering charging, and magnetic field gradient positioning. It also ensures the efficiency, reliability, and safety of underwater wireless charging through dynamic power regulation and intelligent charging termination. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 This is a flow chart of a method for autonomous docking and wireless charging of an underwater robot described in this application. DETAILED DESCRIPTION

[0067] like Figure 1 As shown, the method for autonomous docking and wireless charging of an underwater robot described in this application includes the following steps:

[0068] S1. The underwater robot monitors the battery status in real time through the battery management module. When the battery level is detected to be lower than the preset low-battery threshold, the underwater robot triggers the charging mode and moves towards the charging base station.

[0069] S2. When the underwater robot moves to a preset charging area near the charging base station, magnetic field gradient data and motion state data of the underwater robot are collected, and the three-dimensional coordinates and attitude angle of the underwater robot relative to the magnetic dipole beacon of the charging base station are calculated;

[0070] S3. Calculate the positional deviation between the underwater robot's charging coil and the charging base station coil based on the three-dimensional coordinates and attitude angle, and dynamically adjust the underwater robot's position;

[0071] S4. After the position of the underwater robot is adjusted, the underwater robot is driven to dock with the charging base station for charging, so that the main receiving coil of the underwater robot and the main transmitting coil of the charging base station are electromagnetically coupled, and the charging process is started;

[0072] S5. Monitor the charging process in real time and dynamically adjust the transmission power of the main transmitting coil until the power of the underwater robot reaches the preset charging power and the charging is completed.

[0073] Furthermore, in this embodiment, step S1 specifically includes:

[0074] The battery management module monitors the battery status in real time and collects the battery voltage, current and temperature. It sets the collection period T and collects the battery voltage, current and temperature at time intervals Δt1.

[0075] The current value is accumulated using the ampere-hour integration method to calculate the cumulative charge value. Combined with the pre-established voltage-state-of-charge characteristic curve, the battery's residual state of charge (SOC) is calculated. The voltage-state-of-charge characteristic curve is established through historical experiments, and multiple charge and discharge cycle experiments are performed on the underwater robot's battery. At the steady state of each charge and discharge stage, the corresponding open-circuit voltage and residual state of charge data are recorded. This process is repeated under different temperature environments to obtain comprehensive data. The above data is processed using mathematical methods (such as the least squares method) to fit the voltage-state-of-charge functional relationship and obtain the voltage-state-of-charge characteristic curve.

[0076] If SOC≥SOC L , it is determined that the battery power of the underwater robot meets the operation requirements, and the underwater robot continues to operate in its original state;

[0077] If SOC<SOC L , it is determined that the battery power of the underwater robot does not meet the operation requirements, the underwater robot stops working, and triggers the charging mode;

[0078] Among them, SOC L Indicates the preset low battery threshold; Δt1<T.

[0079] Furthermore, in this embodiment, step S1 further includes:

[0080] After the charging mode is triggered, the underwater robot's sonar module starts multi-beam scanning, sets the ratio of the number of transmitting beams to the number of receiving beams to 1:2, and emits a fixed-frequency acoustic pulse signal;

[0081] By capturing the echo time difference Δt2 and calibrating the water sound speed c in real time according to the pre-established temperature-sound speed compensation model, the first distance d between the underwater robot and the charging base station is calculated:

[0082]

[0083] The phase difference method is used to analyze the received signals of different beams, and combined with the array signal processing algorithm, the azimuth angle θ of the underwater robot relative to the charging base station is obtained;

[0084] Matching the first distance d and azimuth angle θ with a preset underwater environment map to obtain initial distance and azimuth information between the underwater robot and the charging base station;

[0085] Based on the initial distance and orientation information, the underwater robot is planned to move along an initial navigation path toward the charging base station, and the underwater robot is driven to move along the initial navigation path toward the charging base station.

[0086] The initial navigation path is planned using an improved A* algorithm. This algorithm is based on a preset underwater environment map and divides the underwater environment map into multiple grid cells. Each cell corresponds to different environmental attributes (such as obstacle areas and traversable areas) and is assigned a corresponding cost weight.

[0087] Taking the current position of the underwater robot as the starting point and the charging base station as the end point, the cost function F = G + H is calculated for each adjacent grid cell, where G is the actual cost from the starting point to the current grid, and H is the estimated cost from the current grid to the end point. During the search process, the grid with the smallest cost function F is preferentially selected as the next travel node, and the path is continuously expanded until the shortest path from the current position of the robot to the charging base station is found. The motion characteristics of the underwater robot, including the maximum steering angle and the maximum travel speed, are combined to smooth the planned path to avoid unfeasible motion instructions (such as sharp turns) in the path, and finally an initial navigation path that the underwater robot can execute is generated;

[0088] Among them, the temperature-sound speed compensation model is based on historical experiments. The sound speed in water is measured multiple times using a sound velocity meter under different temperature environments, and the corresponding temperature and sound speed data are recorded. Then, a mathematical fitting method is used to determine the functional relationship between temperature and sound speed, and a temperature-sound speed compensation model is established. For example, the functional relationship formula between temperature and sound speed is c=c0+α(W-W0), where c represents the sound speed in water, W0 represents the reference temperature, W represents the real-time temperature in water, c0 represents the sound speed at the reference temperature W0, and α represents the temperature coefficient;

[0089] An example of step S1 is as follows:

[0090] Set the acquisition cycle T = 10 seconds, the time interval Δt1 = 2 seconds, and the preset low power threshold SOC L =30%;

[0091] The battery management module collects data every 2 seconds at a voltage of 18V, a current of 2A, and a temperature of 25°C. It accumulates the charge through real-time integration and calculates the remaining state of charge (SOC) of the battery based on the pre-established voltage-state of charge characteristic curve (e.g., 24V→100% SOC, 15V→0% SOC). L =30%, trigger charging mode;

[0092] After the charging mode is triggered, the sonar module starts multi-beam scanning, sets the transmit beam: receive beam = 1:2, transmits 50kHz sound pulses, captures the echo time difference Δt2 = 0.01 seconds, and calculates the real-time underwater sound speed c = 1490 m / s through the temperature-sound speed compensation model (for example, W0 = 20°C, c0 = 1490 m / s, α = 2 m / s·°C). The first distance between the underwater robot and the charging base station is calculated as d = 1490*0.01 / 2 = 7.45 meters;

[0093] The multi-beam signal is analyzed by the phase difference method, and the azimuth angle relative to the base station is obtained as θ = 30°;

[0094] The underwater environment map is divided into 1m*1m grids (the obstacle grid cost weight is set to 100 and the feasible area is set to 1). The robot's current position is used as the starting point and the base station is used as the end point. The improved A* algorithm is used to calculate the cost function F=G+H. Combined with the robot's maximum steering angle of 45° and maximum speed of 1m / s, the path is smoothed to finally generate an initial navigation path (for example, "first go straight in the current direction for 1 meter, then turn 15° and go 2 meters" to avoid sharp turns) to drive the underwater robot to move towards the charging base station.

[0095] Furthermore, in this embodiment, step S2 specifically includes:

[0096] When the underwater robot moves along the initial navigation path to the preset charging area near the charging base station, the magnetic gradient tensor measurement module and inertial measurement module of the underwater robot are activated;

[0097] The magnetic gradient tensor measurement module collects underwater magnetic field gradient data in real time through a three-dimensional orthogonal magnetic sensor array. The inertial measurement module collects the robot's motion state data in real time, including acceleration and angular velocity data. The magnetic gradient tensor measurement module is a three-dimensional orthogonal magnetic sensor array composed of three mutually perpendicular magnetic sensors. The underwater magnetic field gradient data is a 3×3 gradient tensor matrix composed of the partial derivatives of the magnetic field components with respect to the spatial coordinates.

[0098] The extended Kalman filter algorithm is used to fuse the underwater magnetic field gradient data and motion state data to obtain the three-dimensional coordinates and attitude angle of the underwater robot relative to the magnetic dipole beacon of the charging base station. Specifically, the fusion processing of the underwater magnetic field gradient data and motion state data includes nonlinear state estimation using the extended Kalman filter algorithm. The process is divided into a state prediction phase and an observation update phase.

[0099] During the state prediction phase, the extended Kalman filter algorithm uses the previous state estimate, including the underwater robot's three-dimensional coordinates, attitude angle, velocity, and angular velocity relative to the charging base station's magnetic dipole beacon, combined with the motion state data collected by the inertial measurement module, to calculate the current state prior value and error covariance matrix through a kinematic model. The kinematic model is constructed based on Newton's laws of motion and rigid body rotation equations, taking into account underwater environmental factors. Underwater environmental factors include the influence of water flow resistance on the robot's motion, and the corresponding resistance coefficient is introduced to improve the kinematic model.

[0100] During the observation update phase, the magnetic field gradient data is introduced into the magnetic dipole magnetic field model, and a functional relationship between the magnetic field gradient tensor, the beacon position, and the robot posture is established. The theoretical magnetic field gradient value is calculated and the observation equation is constructed with the measured value. The state prior value is corrected by the Kalman gain to obtain the state posterior value at the current moment and the updated error covariance matrix. The magnetic dipole magnetic field model is constructed based on classical electromagnetic theory. For the magnetic dipole beacon of the charging base station, the magnetic field distribution it generates in space satisfies the basic formula of the magnetic dipole magnetic field:

[0101]

[0102] in, The position vector of the magnetic dipole beacon in space is The magnetic field vector generated at ; μ0 represents the magnetic permeability of vacuum; represents the position vector of the underwater robot relative to the magnetic dipole beacon; represents the magnetic moment of the magnetic dipole beacon; for The unit vector of the direction;

[0103] By introducing the oscillation frequency of the alternating magnetic field generated by the magnetic dipole beacon of the charging base station and the attenuation coefficient related to the conductivity of seawater, the basic formula of the magnetic dipole magnetic field is modified to construct a magnetic dipole magnetic field model;

[0104] After nonlinear state estimation, the three-dimensional coordinates and attitude angles of the underwater robot relative to the magnetic dipole beacon of the charging base station are output; the three-dimensional coordinates are expressed as P = (x, y, z), and the attitude angle is expressed as β = (φ1, φ2, φ3);

[0105] x represents the horizontal coordinate of the underwater robot, y represents the horizontal coordinate of the underwater robot, and z represents the height coordinate of the underwater robot in the vertical direction;

[0106] φ1 is the roll angle, which represents the rotation angle of the robot around its own forward direction axis;

[0107] φ2 is the pitch angle, which represents the rotation angle of the robot around the horizontal;

[0108] φ3 is the yaw angle, which represents the rotation angle of the robot around the vertical direction;

[0109] An example of step S2 is as follows:

[0110] The charging area is set to within a 2-meter radius of the charging base station. The A* algorithm is improved to plan the path (taking into account underwater obstacles, such as reef areas in the middle, which require detours). The robot is driven at a maximum speed of 1m / s toward the charging base station. After entering the charging area, the underwater robot's magnetic gradient tensor measurement module and inertial measurement module are activated.

[0111] The magnetic gradient tensor measurement module collects magnetic field gradient data (3×3 tensor matrix, reflecting the near-field magnetic field changes of the base station magnetic dipole), and the inertial measurement module collects the motion state. At this time, the underwater robot acceleration a=[0.05, 0.03, -0.01]m / s 2 , angular velocity ω=[0.005,-0.01,0.015]rad / s;

[0112] Through the extended Kalman filter, the positioning result three-dimensional coordinates P = (1.2, 0.9, 0.8) and attitude angle β = (4°, 2°, 3°) are output.

[0113] Furthermore, in this embodiment, step S3 specifically includes:

[0114] The underwater robot is equipped with a main receiving coil and an auxiliary alignment coil, and the charging base station is equipped with a main transmitting coil and an auxiliary calibration coil. The main receiving coil and the main transmitting coil form a magnetic coupling structure, and the auxiliary alignment coil and the auxiliary calibration coil form a deviation detection unit. The outer diameters of the main receiving coil and the main transmitting coil are consistent to ensure that the magnetic fields generated by the two can be coupled to each other to the greatest extent possible, meeting the requirements of the magnetic resonance coupling principle for coil size matching. According to the theory of electromagnetic induction, when high-frequency alternating current is passed through the main transmitting coil, an alternating magnetic field is generated. The main receiving coil generates an induced electromotive force in this magnetic field through electromagnetic induction, realizing the transmission of electrical energy from the charging base station to the underwater robot. The number of turns of the main receiving coil and the main transmitting coil are also consistent to ensure that their natural frequencies are consistent, achieving a magnetic resonance state, significantly improving magnetic coupling efficiency, and reducing energy transmission loss.

[0115] The auxiliary alignment coil and the auxiliary calibration coil have the same outer diameter and number of turns. The ratio of the outer diameter of the auxiliary alignment coil to the outer diameter of the main receiving coil is 1:2. The smaller size makes the magnetic field generated by the auxiliary coil more concentrated and more sensitive to small position changes. When the axial distance or angular offset between the underwater robot and the charging base station changes, the magnetic field coupling between the auxiliary coils will change significantly, resulting in a significant change in the mutual inductance coefficient. The number of turns of the auxiliary alignment coil is 2 to 5 times that of the main receiving coil, with 5 times being the optimal choice. According to Faraday's law of electromagnetic induction, the induced electromotive force is proportional to the rate of change of magnetic flux. Therefore, the more turns there are, the more significant the change in the induced electromotive force, which can improve the detection accuracy of position deviation.

[0116] According to the three-dimensional coordinates and the attitude angle, the axial distance deviation ΔD between the center of the main receiving coil and the center of the main transmitting coil in the axial direction and the angular deviation Δβ between the axis of the main receiving coil and the axis of the main transmitting coil are calculated, and the mutual inductance coefficient M between the auxiliary alignment coil and the auxiliary calibration coil is collected in real time. Specifically, according to the three-dimensional coordinates P = (x, y, z) and the attitude angle β = (φ1, φ2, φ3) obtained in step S2, the axial distance deviation ΔD and the angular deviation Δβ are calculated by the formula:

[0117] ΔD=|z-z0|

[0118]

[0119] Where z0 represents the vertical coordinate of the main transmitting coil; The unit vector representing the axis of the main receiving coil is in the direction of the axis of the main receiving coil in the current posture, and its modulus is 1. Represents the unit vector of the main transmitting coil axis, the direction is along the axis of the main transmitting coil, and the modulus is 1;

[0120] If ΔD≤ΔDL , Δβ≤Δβ L and M≥M L If all of the above conditions are met, it is determined that the alignment accuracy of the main receiving coil and the main transmitting coil meets the requirements;

[0121] If ΔD≤ΔD L , Δβ≤Δβ L and M≥M L If any of the conditions are not met, it is determined that the alignment accuracy of the main receiving coil and the main transmitting coil does not meet the requirements, and a position adjustment strategy is executed for the underwater robot;

[0122] Where ΔD L Indicates the preset axial distance deviation threshold; Δβ L Indicates the preset angle deviation threshold; M L represents the theoretical mutual inductance coefficient.

[0123] Furthermore, in this embodiment, the position adjustment strategy includes:

[0124] If ΔD>ΔD L , it is determined that the axial distance deviation does not meet the requirements, and the thrust size and direction of the underwater robot are adjusted to make the underwater robot move closer to the center of the main transmitting coil until ΔD≤ΔD L ;

[0125] If Δβ>Δβ L , it is determined that the angle deviation does not meet the requirements, and the main body of the underwater robot is rotated to adjust the axis direction of the main receiving coil until Δβ≤Δβ is satisfied. L ;

[0126] If M<M L , it is determined that the adjustment of the current underwater robot is not completed, and the mutual inductance coefficient change rate is calculated according to the mutual inductance coefficient M.

[0127] When M′>0, it means that the underwater robot is currently adjusting the direction correctly, and the original adjustment state is maintained and the adjustment is continued until M≥M is satisfied. L ;

[0128] When M′≤0, it means that the current adjustment direction of the underwater robot deviates, and the adjustment direction is corrected and readjusted until M≥M is satisfied. L ;

[0129] An example of step S3 is as follows:

[0130] According to the three-dimensional coordinates P = (1.2, 0.9, 0.8) and attitude angle β = (4°, 2°, 3°) obtained in step S2, the outer diameters of the main receiving coil and the main transmitting coil are set to 0.5 meters, the number of turns is set to 100, and the outer diameters of the auxiliary alignment coil and the auxiliary calibration coil are set to 0.25 meters, and the number of turns is set to 500.

[0131] Set the axial distance deviation threshold ΔD L =0.2 m, angle deviation threshold Δβ L =5°; Theoretical mutual inductance coefficient M L =0.1mH;

[0132] The vertical coordinate z0 of the main transmitting coil is 0.5. The calculated axial distance deviation ΔD is 0.3 meters and the angular deviation Δβ is 6 degrees. The mutual inductance of the auxiliary alignment coil is collected in real time, and M is measured to be 0.08mH. Since ΔD = 0.3 > 0.2, ΔD does not meet the requirement. Δβ = 6 degrees > 5 degrees, which means Δβ does not meet the requirement. M = 0.08mH < 0.1mH, which means M does not meet the requirement. The position adjustment strategy is executed:

[0133] Adjust the direction (along the negative z-axis) and magnitude of the robot's thrust, and translate it toward the center of the main transmitting coil, with a target ΔD ≤ 0.2 meters.

[0134] Rotate the underwater robot body and adjust the axis direction of the main receiving coil (for example, reduce the pitch angle to 1° and the yaw angle to 2°), with the target Δβ ≤ 5°;

[0135] Calculate the rate of change of mutual inductance (M increases over time during the adjustment process), indicating that the current adjustment direction is correct. Maintain the current "axial translation + angular rotation" control strategy and continue to adjust;

[0136] After continuous control, the underwater robot status is updated as follows:

[0137] ΔD=0.15m<0.2m, Δβ=4°<5°, M=0.12mH≥0.1mH. If all three are satisfied, it is determined that the alignment accuracy of the main receiving coil and the main transmitting coil meets the requirements.

[0138] Furthermore, in this embodiment, step S4 specifically includes:

[0139] The underwater robot is equipped with an electromagnetic adsorption module at the charging docking point with the charging base station. After the alignment accuracy of the main receiving coil and the main transmitting coil meets the requirements, the underwater robot executes a phased electromagnetic adsorption strategy for docking. The phased electromagnetic adsorption strategy includes a pre-tightening stage, a locking stage, and a stabilization stage.

[0140] A constant current I1 is passed through the electromagnetic adsorption module for a duration of t1. The electromagnetic adsorption module generates an initial magnetic field, which creates an initial adsorption force between the charging docking point of the underwater robot and the docking surface of the charging base station, completing the pre-tightening stage. The pre-tightening stage adopts open-loop control. The generation of the initial adsorption force can gradually eliminate the assembly gap and positioning error between the two, providing a stable foundation for the subsequent locking stage.

[0141] After the pre-tightening phase is completed, the electromagnetic adsorption module switches the current to I2 for a duration of t2, and uses current closed-loop control to maintain a stable current of I2, tightly fitting and locking the charging docking point of the underwater robot with the docking surface of the charging base station, completing the locking phase; where I2>I1, t2>t1;

[0142] After the locking stage is completed, the proportional-integral-differential control algorithm is used to adjust the current of the electromagnetic adsorption module to I3 to maintain the stable adsorption force. The underwater robot and the charging base station collect the adsorption force at the docking position in real time, and dynamically adjust the current of the electromagnetic adsorption module to maintain the stability of the docking state between the underwater robot and the charging base station, completing the stabilization stage; where I3 is less than I2, and I3 is determined according to the adsorption force required for actual use, that is, the adsorption force required for the underwater robot used to charge the charging base station.

[0143] Furthermore, in this embodiment, step S4 further includes:

[0144] After the underwater robot completes docking with the charging base station, the main receiving coil of the underwater robot establishes electromagnetic coupling with the main transmitting coil of the charging base station, and the charging process is started. The charging process includes:

[0145] The power supply frequency of the charging transmitter of the charging base station is set to f0, and f0 is aligned with the natural frequency of the dual coils consisting of the main transmitting coil and the main receiving coil through a phase-locked loop circuit to maintain the magnetic resonance coupling state of the main transmitting coil and the main receiving coil;

[0146] Based on the coil inductance and operating frequency of the main transmitting coil and the main receiving coil, the matching capacitor adjustment range is calculated. The capacitance value is adjusted step by step using the binary method and the quality factor Q is measured. The capacitance adjustment is stopped when Q reaches the preset quality factor threshold. After each capacitance adjustment, the system quality factor Q is measured using an impedance analyzer.

[0147] The charging base station increases the charging transmission power to the rated value, and the underwater robot's charging receiving end converts the induced alternating current into stable direct current to charge the battery. The underwater robot's charging receiving end has a rectifier and filter circuit that converts the induced alternating current into stable direct current, which charges the underwater robot's battery.

[0148] An example of step S4 is as follows:

[0149] According to step S3, the alignment accuracy of the main receiving coil and the main transmitting coil meets the requirements, and ΔD = 0.15 meters, Δβ = 4 degrees, and M = 0.12mH are obtained. A phased electromagnetic adsorption strategy is implemented for docking;

[0150] In the pre-tightening stage, a constant current I1 = 2A is applied to the electromagnetic adsorption module for a duration of t1 = 3 seconds. Within 3 seconds, the coil is gradually "pulled together" to eliminate the assembly gap and prepare for the locking stage.

[0151] During the locking phase, the electromagnetic adsorption module switches the current to I2 = 5A for a duration of t2 = 5 seconds, and within 5 seconds, the pressure on the mating surface reaches 50N, completing the mechanical locking.

[0152] During the stabilization phase, the current of the electromagnetic adsorption module is adjusted to I3=3A to maintain a stable adsorption force and maintain stable docking;

[0153] Charging procedure starts:

[0154] The power frequency of the charging transmitter of the charging base station is set to f0 = 100kHz. Through the phase-locked loop, f0 is made consistent with the natural frequency of the dual coils consisting of the main transmitting coil and the main receiving coil. The coil inductance between the main transmitting coil and the main receiving coil is 100μH, and the matching capacitor is calculated to be 25nF.

[0155] The capacitance was adjusted using the binary method (range 20nF to 30nF), with each adjustment of 2.5nF. The quality factor Q was measured, and the quality factor threshold was set to 100. When Q ≥ 100, the final capacitance was measured to be 25nF, and the actual Q = 102, which met the resonance condition.

[0156] The charging base station's transmission power is increased to a rated value of 500W. The main transmitting coil passes high-frequency current, and the main receiving coil senses alternating current. The full-bridge rectifier + capacitor filter circuit at the receiving end of the robot converts the alternating current into a stable 24V direct current to charge the battery with a current SOC of 25%.

[0157] Furthermore, in this embodiment, step S5 specifically includes:

[0158] The charging voltage and charging current of the main receiving coil are collected in real time, and the actual active power P is calculated. real , combined with the apparent power P S , calculate the power factor λ and energy transfer efficiency η:

[0159]

[0160] Among them, P trans Indicates the charging transmitter power of the charging base station;

[0161] If λ<λ minand / or η<η min , then increase the transmission power of the charging transmitter of the charging base station until λ=[λ min ,λ max ] and η=[η min , η max ];

[0162] If λ>λ max and / or η>η max , then reduce the transmission power of the charging transmitter of the charging base station until λ=[λ min ,λ max ] and η=[η min , η max ];

[0163] Among them, λ min and λ max Respectively represent the preset power factor lower threshold and power factor upper threshold; η min and η max They represent the preset lower limit threshold of energy transmission efficiency and the upper limit threshold of energy transmission efficiency respectively.

[0164] Furthermore, in this embodiment, step S5 further includes:

[0165] The battery management module provides real-time feedback of the underwater robot's battery voltage and current, and uses the ampere-hour integration method and open circuit voltage method to estimate the real-time state of charge (SOC). S ;

[0166] When the real-time state of charge SOC S Reaching the preset state of charge threshold SOC D When the battery is fully charged, it switches to constant voltage charging mode and continuously monitors the real-time current of the battery until the real-time current of the battery drops to the preset current threshold, and charging is completed.

[0167] After charging is completed, the battery management module issues a charge termination instruction. The charging base station linearly reduces the transmission power of the charging transmitter to zero at a fixed slope, cuts off the current of the electromagnetic adsorption module, and passes a reverse current for demagnetization.

[0168] The underwater robot moves away from the charging base station and switches to the operation mode after moving outside the charging area;

[0169] An example of step S5 is as follows:

[0170] Setting λ min =0.8,λ max =0.95,η min =80%,η max =92%;

[0171] The charging voltage of the main receiving coil is collected in real time, which is 24V and the charging current is 15A. The phase difference is obtained through the phase detection circuit. (correspond ), calculate the apparent power P S =360W, actual active power P real =270W, then the power factor λ=0.75<0.8;

[0172] Charging transmitter power P of the charging base station trans =500W, then the energy transmission efficiency η=54%<80%;

[0173] Then determine λ<λ min ,η<η min , then increase the transmission power of the charging transmitter of the charging base station to 400W. After retesting, we get λ = 0.82, η = 82%, which meets the requirements;

[0174] Battery management module estimates SOC S =90%, set the charging state of charge threshold SOC D =90%, then switch to constant voltage mode, the current threshold is 0.5A, reduce the charging current to 0.5A, and determine that charging is complete;

[0175] The transmitting power is linearly returned to zero, the electromagnetic adsorption module is reversely demagnetized, and the underwater robot switches to the operating mode after moving away from the charging base station.

[0176] In the description of this application, it should be understood that the directions or positional relationships indicated by directional words such as "front, back, up, down, left, right", "horizontal, vertical, horizontal" and "top, bottom" are usually based on the directions or positional relationships shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description. Unless otherwise specified, these directional words do not indicate or imply that the device or element referred to must have a specific direction or be constructed and operated in a specific direction. Therefore, they cannot be understood as limiting the scope of protection of this application.

[0177] Those skilled in the art can make various other corresponding changes and deformations based on the technical solutions and concepts described above, and all of these changes and deformations should fall within the scope of protection of the claims of this application.

Claims

1. A method for autonomous docking and wireless charging of an underwater robot, characterized in that: The following steps are involved: S1. The underwater robot monitors the battery status in real time through the battery management module. When the battery level is detected to be lower than the preset low-battery threshold, the underwater robot triggers the charging mode and moves towards the charging base station. S2. When the underwater robot moves to a preset charging area near the charging base station, magnetic field gradient data and motion state data of the underwater robot are collected, and the three-dimensional coordinates and attitude angle of the underwater robot relative to the magnetic dipole beacon of the charging base station are calculated; S3. Calculate the positional deviation between the underwater robot's charging coil and the charging base station coil based on the three-dimensional coordinates and the attitude angle, and dynamically adjust the underwater robot's position; S4. After the position of the underwater robot is adjusted, the underwater robot is driven to dock with the charging base station for charging, so that the main receiving coil of the underwater robot and the main transmitting coil of the charging base station are electromagnetically coupled, and the charging process is started; S5. Monitor the charging process in real time and dynamically adjust the transmission power of the main transmitting coil until the power of the underwater robot reaches the preset charging power, thus completing the charging.

2. The underwater robot autonomous docking wireless charging method according to claim 1, characterized in that: The step S1 specifically includes: The battery management module monitors the battery status in real time and collects the battery voltage, current and temperature. The collection period T is set, and the battery voltage, current and temperature are collected at time intervals Δt1. The current value is accumulated and calculated using the ampere-hour integration method to obtain a charge accumulation value, and the remaining state of charge (SOC) of the battery is calculated by combining the pre-established voltage-state of charge characteristic curve; If SOC≥SOC L , it is determined that the battery power of the underwater robot meets the operation requirements, and the underwater robot continues to operate in its original state; If SOC<SOC L , it is determined that the battery power of the underwater robot does not meet the operation requirements, the underwater robot stops working, and triggers the charging mode; Among them, SOC L Indicates the preset low battery threshold; Δt1<T.

3. The underwater robot autonomous docking wireless charging method according to claim 2, characterized in that: The step S1 further includes: After the charging mode is triggered, the sonar module of the underwater robot starts multi-beam scanning, sets the ratio of the number of transmitting beams to the number of receiving beams to be 1:2, and transmits an acoustic pulse signal of a fixed frequency; By capturing the echo time difference Δt2 and calibrating the water sound speed c in real time according to the pre-established temperature-sound speed compensation model, the first distance d between the underwater robot and the charging base station is calculated: The phase difference method is used to analyze the received signals of different beams, and combined with the array signal processing algorithm, the azimuth angle θ of the underwater robot relative to the charging base station is obtained; Matching the first distance d and the azimuth angle θ with a preset underwater environment map to obtain initial distance and azimuth information between the underwater robot and the charging base station; An initial navigation path for the underwater robot to move toward the charging base station is planned based on the initial distance and the orientation information, and the underwater robot is driven to move toward the charging base station along the initial navigation path.

4. The underwater robot autonomous docking wireless charging method according to claim 3, characterized in that: The step S2 specifically includes: When the underwater robot moves along the initial navigation path to a preset charging area near the charging base station, the magnetic gradient tensor measurement module and the inertial measurement module of the underwater robot are started; The magnetic gradient tensor measurement module collects underwater magnetic field gradient data in real time through a three-dimensional orthogonal magnetic sensor array, and the inertial measurement module collects the robot's motion state data in real time, and the motion state data includes acceleration data and angular velocity data of the underwater robot; The underwater magnetic field gradient data and the motion state data are fused and processed using an extended Kalman filter algorithm to obtain the three-dimensional coordinates and attitude angle of the underwater robot relative to the magnetic dipole beacon of the charging base station.

5. The underwater robot autonomous docking wireless charging method according to claim 4, characterized in that: The step S3 specifically includes: The underwater robot is provided with a main receiving coil and an auxiliary alignment coil, and the charging base station is provided with a main transmitting coil and an auxiliary calibration coil. The main receiving coil and the main transmitting coil form a magnetic coupling structure, and the auxiliary alignment coil and the auxiliary calibration coil form a deviation detection unit. Calculate, based on the three-dimensional coordinates and the attitude angle, an axial distance deviation ΔD between the center of the main receiving coil and the center of the main transmitting coil, and an angular deviation Δβ between the axis of the main receiving coil and the axis of the main transmitting coil, and collect in real time a mutual inductance coefficient M between the auxiliary alignment coil and the auxiliary calibration coil; If ΔD≤ΔD L , Δβ≤Δβ L and M≥M L If both conditions are met, it is determined that the alignment accuracy of the main receiving coil and the main transmitting coil meets the requirements; If ΔD≤ΔD L , Δβ≤Δβ L and M≥M L If any one of the conditions is not satisfied, it is determined that the alignment accuracy of the main receiving coil and the main transmitting coil does not meet the requirement, and a position adjustment strategy is executed on the underwater robot; Where ΔD L Indicates the preset axial distance deviation threshold; Δβ L Indicates the preset angle deviation threshold; M L represents the theoretical mutual inductance coefficient.

6. The underwater robot autonomous docking wireless charging method according to claim 5, characterized in that: The position adjustment strategy includes: If ΔD>ΔD L , it is determined that the axial distance deviation does not meet the requirements, and the thrust size and direction of the underwater robot are adjusted to make the underwater robot move closer to the center of the main transmitting coil until ΔD≤ΔD L ; If Δβ>Δβ L , it is determined that the angle deviation does not meet the requirements, and the main body of the underwater robot is rotated to adjust the axis direction of the main receiving coil until Δβ≤Δβ is satisfied. L ; If M<M L , it is determined that the adjustment of the current underwater robot is not completed, and the mutual inductance coefficient change rate is calculated according to the mutual inductance coefficient M. When M′>0, it means that the underwater robot is currently adjusting the direction correctly, and the original adjustment state is maintained and the adjustment is continued until M≥M is satisfied. L ; When M′≤0, it means that the current adjustment direction of the underwater robot deviates, and the adjustment direction is corrected and readjusted until M≥M is satisfied. L .

7. The underwater robot autonomous docking wireless charging method according to claim 6, characterized in that: The step S4 specifically includes: The underwater robot is equipped with an electromagnetic adsorption module at the charging docking point with the charging base station. After the alignment accuracy of the main receiving coil and the main transmitting coil meets the requirements, a phased electromagnetic adsorption strategy is executed for docking. The phased electromagnetic adsorption strategy includes a pre-tightening stage, a locking stage, and a stabilization stage. A constant current I1 is supplied to the electromagnetic adsorption module for a duration of t1, and the electromagnetic adsorption module generates an initial magnetic field, which causes an initial adsorption force to be generated between the charging docking point of the underwater robot and the docking surface of the charging base station, thus completing the pre-tightening stage; After the pre-tightening stage is completed, the electromagnetic adsorption module switches the current to I2 for a duration of t2, adopts current closed-loop control, maintains the current stable at I2, and tightly fits and locks the charging docking point of the underwater robot and the docking surface of the charging base station, completing the locking stage; After the locking stage is completed, the proportional-integral-differential control algorithm is used to adjust the current of the electromagnetic adsorption module to I3 to maintain the stable adsorption force. The underwater robot and the charging base station collect the adsorption force of the docking position in real time, and dynamically adjust the current of the electromagnetic adsorption module to maintain the stability of the docking state between the underwater robot and the charging base station, completing the stabilization stage.

8. The underwater robot autonomous docking wireless charging method according to claim 7, characterized in that: The step S4 further includes: After the underwater robot completes docking with the charging base station, the main receiving coil of the underwater robot establishes electromagnetic coupling with the main transmitting coil of the charging base station, and the charging process is started. The charging process includes: The power supply frequency of the charging transmitter of the charging base station is set to f0, and f0 is aligned with the natural frequency of the dual coils formed by the main transmitting coil and the main receiving coil through a phase-locked loop circuit to maintain the magnetic resonance coupling state of the main transmitting coil and the main receiving coil; Calculating a matching capacitance adjustment range based on the coil inductance and operating frequency of the main transmitting coil and the main receiving coil, adjusting the capacitance value sequentially using a binary method and measuring the quality factor Q until Q reaches a preset quality factor threshold, and then stopping capacitance adjustment; The charging base station increases the charging transmission power to the rated value, and the charging receiving end of the underwater robot converts the induced alternating current into stable direct current to charge the battery.

9. The underwater robot autonomous docking wireless charging method according to claim 8, characterized in that: The step S5 specifically includes: The charging voltage and charging current of the main receiving coil are collected in real time, and the actual active power P is calculated. real , combined with the apparent power P S , calculate the power factor λ and energy transfer efficiency η: Among them, P trans Indicates the charging transmitter power of the charging base station; If λ<λ min and / or η<η min , then increase the transmission power of the charging transmitter of the charging base station until λ=[λ min ,λ max ] and η=[η min , η max ]; If λ>λ max and / or η>η max , then reduce the transmission power of the charging transmitter of the charging base station until λ=[λ min ,λ max ] and η=[η min , η max ]; Among them, λ min and λ max Respectively represent the preset power factor lower threshold and power factor upper threshold; η min and η max They represent the preset lower limit threshold of energy transmission efficiency and the upper limit threshold of energy transmission efficiency respectively.

10. The underwater robot autonomous docking wireless charging method according to claim 9, characterized in that: The step S5 further includes: The battery management module provides real-time feedback of the underwater robot's battery voltage and current, and uses the ampere-hour integration method and open circuit voltage method to estimate the real-time state of charge (SOC). S ; When the real-time state of charge SOC S Reaching the preset state of charge threshold SOC D When the battery is fully charged, the charging mode is switched to constant voltage charging mode, and the real-time current of the battery is continuously monitored until the real-time current of the battery drops to a preset current threshold value, and charging is completed; After charging is completed, the battery management module issues a charge termination instruction, and the charging base station linearly reduces the transmission power of the charging transmitter to zero at a fixed slope, cuts off the current of the electromagnetic adsorption module, and passes a reverse current for demagnetization; The underwater robot moves in a direction away from the charging base station, and switches to the operation mode after the underwater robot moves outside the area to be charged.

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