A real-time data transmission and feedback method for a remotely controlled automatic charging robot

Abstract

The present invention relates to the field of data transmission and control technology, and discloses a real-time data transmission and feedback method for a remotely controlled automatic charging robot. The method comprises the following steps: S101, collecting sea condition data to generate a sea condition risk index, and performing status detection on the manipulator arm, cable drive, and sensor subsystems; S102, acquiring relative posture data of the power supplying ship and the powered ship, generating posture control instructions, and controlling the manipulator arm subsystem to perform posture compensation; S103, identifying and locating the charging interface, collecting cable tension to determine the connection status, and adjusting the position of the cable subsystem and the power supplying ship; S104, collecting charging status data, combining it with the sea condition risk index to make a judgment, and executing a charging termination response when the termination condition is met; S105, after charging is terminated, disconnecting the connection and returning the charging control system to a standby state. The present invention achieves high efficiency in unmanned equipment charging operations in complex marine environments.

Description

Technical Field

[0001] The present invention belongs to the technical field of data transmission and control, and in particular relates to a real-time data transmission and feedback method for a remotely controlled automatic charging robot. Background Art

[0002] With the widespread use of unmanned marine vessels and underwater robots, dynamic charging technology at sea has become key to ensuring the endurance of equipment. However, traditional offshore charging methods face significant technical challenges. In the marine environment, factors such as waves and wind speed cause ships to move violently relative to each other. Existing charging systems lack real-time sea condition assessment and dynamic compensation mechanisms, making it difficult to achieve stable docking in complex sea conditions. The positioning error of the robotic arm is large, and the charging success rate is low. The transmission delay of multi-source data such as sea condition data, robotic arm posture, and charging status is large, and there is a lack of a unified time synchronization mechanism, which cannot meet the real-time compensation requirements for hull sway. Existing technologies only control charging termination based on the battery charge level, without fully considering the unique sea condition risks and safety hazards such as interface overheating in the marine environment. Equipment failure rates are high in complex sea conditions. Summary of the Invention

[0003] The present invention provides a real-time data transmission and feedback method for a remotely controlled automatic charging robot, which solves the technical problems in related technologies such as insufficient docking accuracy, large multi-source data transmission delay, and single charging safety protection caused by sea condition interference when unmanned equipment is charging in a dynamic marine environment.

[0004] The present invention provides a real-time data transmission and feedback method for a remotely controlled automatic charging robot, comprising the following steps:

[0005] S101, after receiving the remote start command, collect sea condition data, generate a sea condition risk index based on the sea condition data using a weighted method, and perform status detection operations on the manipulator subsystem, cable drive subsystem, and sensor subsystem in the charging control system respectively;

[0006] Among them, sea condition data include: significant wave height, peak period, surface wind speed;

[0007] S102, obtaining relative posture data between the power supplying ship and the powered ship, processing the data through a Kalman filter algorithm, generating posture control instructions, and controlling the manipulator subsystem to perform dynamic posture compensation operations;

[0008] Among them, the relative posture data includes translation and rotation angle;

[0009] S103: Identify and locate the charging port, control the robotic arm subsystem to complete the connector insertion and locking operations, collect cable tension in real time, determine the connection status, and adjust the position of the cable subsystem and the power supply vessel based on the determination result until the connection status is stable;

[0010] S104, controlling the charging process according to a preset charging power strategy, collecting charging status data, and making a judgment based on the sea condition risk index, executing a charging termination response when termination conditions are met; wherein the charging status data includes: charging current, charging voltage, battery level, and interface temperature;

[0011] S105, after charging is terminated, disconnection-related operations are performed in a preset order, and the robot arm and the cable drive subsystem are controlled to coordinately complete homing, so that the charging control system returns to the initial standby state.

[0012] Furthermore, a first intermediate parameter is obtained by calculating the ratio of the effective wave height to the preset maximum safe wave height, a second intermediate parameter is obtained by calculating the ratio of the difference between the preset maximum safe period and the peak period to the span of the preset period safety range, and a third intermediate parameter is obtained by calculating the ratio of the surface wind speed to the preset maximum safe wind speed. The first intermediate parameter, the second intermediate parameter and the third intermediate parameter are weightedly summed based on the preset weights to obtain the sea condition risk index.

[0013] Furthermore, the status detection operation includes:

[0014] Perform self-test on the robotic arm subsystem, including whether the motor current of each joint is within the first preset range;

[0015] Performing a self-test on the cable drive subsystem, including whether the cable retraction and extension speed is stable within a second preset range when no-load, and whether the cable tension in a static state is less than a second preset threshold;

[0016] The sensor subsystem is self-checked, including whether the GPS signal strength is greater than a third preset threshold.

[0017] Furthermore, the relative posture data is processed by the Kalman filter algorithm to generate posture control instructions. The specific steps include:

[0018] S201, inputting the relative pose data into the Kalman filter algorithm, performing state prediction and measurement update in sequence, and obtaining the optimal estimated pose, wherein the optimal estimated pose is a state vector including the translation amount and the rotation angle;

[0019] S202, extracting the rotation angle and angular velocity as target posture parameters based on the optimal estimated posture;

[0020] S203, converting the target posture parameters into target angles of each joint of the robotic arm through the robotic arm inverse kinematics algorithm;

[0021] S204: Encapsulate the target angles of the joints of the robotic arm into posture control instructions and send them to the robotic arm subsystem.

[0022] Furthermore, the specific steps of controlling the manipulator subsystem to perform the dynamic posture compensation operation include:

[0023] S301, performing a validity check on the posture control instruction, wherein the validity check includes: angle range check and speed constraint verification;

[0024] S302, driving the coordinated motion of the joints of the manipulator through a distributed control architecture, and offsetting the relative motion of the hull based on a feedforward-feedback composite control strategy;

[0025] S303, obtaining a contact force feedback signal through the force sensor at the end of the robotic arm, and adjusting the translation amount and rotation angle of the actuator at the end of the robotic arm in real time based on the contact force feedback signal, wherein the adjustment includes PID correction of the target angle of each joint.

[0026] Furthermore, the connection status includes: fully connected, critical state and abnormal state;

[0027] Calculating the cable tension change rate; determining that the connection is complete and maintaining charging when the cable tension is within a preset safety range and the cable tension change rate is less than a fourth preset threshold;

[0028] When the cable tension is within the preset safety range and the cable tension change rate is between the fourth preset threshold and the fifth preset threshold, it is determined to be a critical state and dynamic compensation is started;

[0029] When the cable tension exceeds the preset safety range and the cable tension change rate is greater than a fifth preset threshold, it is determined to be an abnormal state and an emergency disconnection operation is performed.

[0030] Furthermore, the preset charging power strategy includes: when the sea condition risk index exceeds a sixth preset threshold, reducing the charging power to a first preset proportion of the preset rated power.

[0031] Furthermore, the termination conditions include:

[0032] The battery level reaches the preset power threshold;

[0033] The charging voltage exceeds the preset voltage threshold;

[0034] The charging current is lower than the preset current threshold;

[0035] The sea condition risk index exceeds the preset risk threshold;

[0036] The interface temperature exceeds the preset temperature threshold.

[0037] The beneficial effects of the present invention are as follows: by introducing a sea condition risk index judgment mechanism, the present invention can quantitatively assess the sea surface environment before charging operations, significantly improving operation safety; secondly, the relative posture data between the two ships is processed in combination with the Kalman filter algorithm, and precise attitude control instructions are generated, and dynamic attitude compensation is achieved in conjunction with the robotic arm subsystem, effectively solving the docking problem caused by the relative movement of ships; in addition, the present invention adopts a multi-dimensional state data monitoring and feedback mechanism, which can monitor key parameters such as cable tension, charging power, interface temperature, etc. in real time, and respond quickly under abnormal circumstances to ensure the safety and reliability of the charging process; the entire charging control system supports remote control and automatic control, reduces manual intervention, is suitable for unmanned operations under complex sea conditions, and has the advantages of high safety, high automation and high environmental adaptability. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 This is a flow chart of a real-time data transmission and feedback method for a remotely controlled automatic charging robot of the present invention. DETAILED DESCRIPTION

[0039] The subject matter described herein will now be discussed with reference to exemplary embodiments. It should be understood that these embodiments are discussed solely to enable those skilled in the art to better understand and implement the subject matter described herein, and that the functions and arrangements of the elements discussed may be varied without departing from the scope of this specification. Various examples may omit, substitute, or add various processes or components as needed. In addition, features described with respect to some examples may also be combined in other examples.

[0040] It should be noted that, unless otherwise defined, the technical or scientific terms used in one or more embodiments of the present invention should have the usual meanings understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in one or more embodiments of the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprising" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, but do not exclude other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0041] like Figure 1 As shown, a real-time data transmission and feedback method for a remotely controlled automatic charging robot includes the following steps:

[0042] S101, after receiving the remote start command, collect sea condition data, generate a sea condition risk index based on the sea condition data using a weighted method, and perform status detection operations on the manipulator subsystem, cable drive subsystem, and sensor subsystem in the charging control system respectively;

[0043] Among them, sea condition data include: significant wave height, peak period, surface wind speed;

[0044] S102, obtaining relative posture data between the power supplying ship and the powered ship, processing the data through a Kalman filter algorithm, generating posture control instructions, and controlling the manipulator subsystem to perform dynamic posture compensation operations;

[0045] Among them, the relative posture data includes translation and rotation angle;

[0046] S103: Identify and locate the charging port, control the robotic arm subsystem to complete the connector insertion and locking operations, collect cable tension in real time, determine the connection status, and adjust the position of the cable subsystem and the power supply vessel based on the determination result until the connection status is stable;

[0047] S104, controlling the charging process according to a preset charging power strategy, collecting charging status data, and making a judgment based on the sea condition risk index, executing a charging termination response when termination conditions are met; wherein the charging status data includes: charging current, charging voltage, battery level, and interface temperature;

[0048] S105, after charging is terminated, disconnection-related operations are performed in a preset order, and the robot arm and the cable drive subsystem are controlled to coordinately complete homing, so that the charging control system returns to the initial standby state.

[0049] In one embodiment of the present invention, a pressure wave sensor is installed 1.5 m below the waterline of the hull to measure the water pressure caused by the waves. Obtain, among which, represents the effective wave height, represents the standard deviation of water pressure; perform fast Fourier transform on the collected wave height time series, calculate the energy spectral density function, and determine the peak period by determining the spectral peak frequency, where the peak period is the inverse of the spectral peak frequency; install an ultrasonic anemometer on the top of the mast to measure the surface wind speed.

[0050] Furthermore, a GPS clock synchronization module is used to calibrate the clocks of the pressure wave sensor and ultrasonic anemometer to ensure data time consistency; a sliding average filter is applied to the significant wave height and surface wind speed, and a median filter is used for the peak period to reduce high-frequency noise interference.

[0051] In one embodiment of the present invention, a first intermediate parameter is obtained by calculating the ratio of a significant wave height to a preset maximum safe wave height, a second intermediate parameter is obtained by calculating the ratio of a difference between a preset maximum safe period and a peak period to a preset period safety range span, and a third intermediate parameter is obtained by calculating the ratio of a surface wind speed to a preset maximum safe wind speed. The first intermediate parameter, the second intermediate parameter, and the third intermediate parameter are weighted and summed based on preset weights to obtain a sea condition risk index.

[0052] The calculation formula of the sea condition risk index is: , where R represents the sea condition risk index, ranging from 0 to 10. represents the effective wave height, Indicates the preset maximum safe wave height. Indicates the preset maximum safety cycle, represents the peak period, Indicates the preset cycle safety range span, that is, the difference between the preset maximum safety cycle and the preset minimum safety cycle. represents the surface wind speed, Indicates the preset maximum safe wind speed. 、 and Represent the first weight coefficient, the second weight coefficient and the third weight coefficient respectively.

[0053] In one embodiment of the present invention, the charging control system is used to realize dynamic charging operations at sea, and includes: a robotic arm subsystem, a cable drive subsystem, a sensor subsystem and a control unit. The robotic arm subsystem is used to complete the identification, positioning and connection operations of the charging interface, the cable drive subsystem is responsible for the retraction and tension adjustment of the cable, the sensor subsystem collects sea condition data and charging status data in real time, and the control unit is used to coordinate each subsystem to perform corresponding operations.

[0054] In one embodiment of the present invention, the status detection operation includes:

[0055] Perform self-test on the robotic arm subsystem, including whether the motor current of each joint is within the first preset range;

[0056] Performing a self-test on the cable drive subsystem, including whether the cable retraction and extension speed is stable within a second preset range when no-load, and whether the cable tension in a static state is less than a second preset threshold;

[0057] The sensor subsystem is self-checked, including whether the GPS signal strength is greater than a third preset threshold.

[0058] In one embodiment of the present invention, after completing the calculation of the sea condition risk index and the status detection of each subsystem, the charging control system performs a conditional judgment operation: if the sea condition risk index is lower than the preset risk threshold, and the status detection results of the robotic arm subsystem, cable drive subsystem, and sensor subsystem are all passed, the subsequent charging operation process is triggered; on the contrary, if the sea condition risk index exceeds the preset risk threshold, or the status detection result of any subsystem is abnormal, the charging control system immediately terminates the current operation, and sends a warning signal through the sound and light alarm device, and sends a fault code to the remote control terminal.

[0059] In one embodiment of the present invention, dual-frequency RTK-GNSS receivers are respectively installed at the center of the decks of the power supplying ship and the powered ship to obtain the three-dimensional coordinates of the two ships in the spatial coordinate system in real time, and the translation between the two ships is calculated by the coordinate difference; at the same time, 3D laser radars are installed on opposite sides of the two ships. The laser radars construct point cloud models of the surrounding environments of the two ships by emitting and receiving laser beams. The iterative closest point algorithm is used to match the point cloud model of the power supplying ship with the point cloud model of the powered ship, and the relative rotation matrix between the two ships is calculated, thereby obtaining the rotation angle, which includes: roll angle, pitch angle and yaw angle.

[0060] In one embodiment of the present invention, relative posture data is processed by a Kalman filter algorithm to generate posture control instructions. The specific steps include:

[0061] S201: Input the relative pose data into the Kalman filter algorithm, perform state prediction and measurement update in sequence, and obtain the optimal estimated pose, where the optimal estimated pose is a state vector containing a translation and a rotation angle. Specifically, the state prediction is used to predict the current position based on the ship's speed and position at the previous moment, and to predict the current rotation angle based on the angular velocity at the previous moment. The measurement update combines the currently input relative pose data, and corrects the predicted state through the gain calculation of the Kalman filter to suppress noise interference. Finally, the optimal estimated pose containing a translation and a rotation angle, i.e., the state vector, is output.

[0062] S202, extracting the rotation angle and angular velocity as target posture parameters based on the optimal estimated posture;

[0063] S203, using the manipulator inverse kinematics algorithm, converting the target posture parameters into target angles for each joint of the manipulator. Specifically, a rotation matrix is ​​constructed based on the target posture parameters, and a homogeneous transformation matrix is ​​formed by combining the translation. The manipulator kinematic model is established using the DH parameter method to solve for the target angles of each joint.

[0064] S204, encapsulate the target angle of each joint of the robotic arm into a posture control instruction and send it to the robotic arm subsystem; specifically, convert the target angle of each joint into a standardized data structure, including parameters such as angle value and control period, and package it into a data packet and send it to the robotic arm controller.

[0065] In one embodiment of the present invention, the specific steps of controlling the manipulator subsystem to perform the dynamic posture compensation operation include:

[0066] S301, performing a validity check on the posture control command, wherein the validity check includes: angle range check and speed constraint verification; specifically, the angle range check is used to verify whether the target angle of each joint is within the safe range, and the speed constraint verification is used to ensure that the joint movement speed does not exceed the safe threshold;

[0067] S302: Drive the coordinated motion of the joints of the manipulator through a distributed control architecture, and offset the relative motion of the hull based on a feedforward-feedback composite control strategy. Specifically, feedforward control refers to precalculating the compensation amount based on the hull motion trend predicted by the Kalman filter. Feedback control obtains the actual joint angle in real time through the joint encoder, compares it with the target angle, generates an error signal, and adjusts it through the PID controller. The calculation formula for the joint angle adjustment is: , represents the adjustment amount of the joint angle at the tth moment, 、 and represent the proportional coefficient, integral coefficient and differential coefficient respectively, represents the deviation between the target angle and the actual joint angle, i represents the joint index;

[0068] S303, obtain the contact force feedback signal through the force sensor at the end of the robotic arm, and adjust the translation and rotation angle of the actuator at the end of the robotic arm in real time based on the contact force feedback signal. The adjustment includes PID correction of the target angle of each joint. Specifically, based on the feedback from the force sensor at the end of the robotic arm, the contact force deviation is mapped to the joint angle correction, and the joint target angle is dynamically adjusted through PID control to achieve smooth control of the translation or rotation of the end effector and eliminate contact rigid impact.

[0069] In one embodiment of the present invention, the step of identifying and locating the charging port includes:

[0070] S401, obtaining spatial feature data of a charging interface, wherein the spatial feature data includes: three-dimensional point cloud data and image data;

[0071] S402: Extracting the translation and rotation angle of the charging interface relative to the actuator at the end of the robotic arm based on the spatial feature data. Specifically, an iterative ICP algorithm is used to match the 3D point cloud data with a pre-stored 3D model of the interface. The translation and rotation angle of the charging interface relative to the actuator at the end of the robotic arm are calculated by minimizing the distance error between corresponding points.

[0072] S403, dynamically track the relative position of the charging interface through a target tracking algorithm; specifically, use a Kalman filter algorithm to update the translation and rotation angle. When the charging interface moves, the Kalman filter algorithm can respond quickly, reduce update delays, and provide reliable position information for precise docking of the robotic arm.

[0073] In one embodiment of the present invention, the connection status includes: full connection, critical state and abnormal state.

[0074] Furthermore, the cable tension change rate is obtained by calculating the ratio of the difference between the cable tensions at adjacent moments to the sampling interval; when the cable tension is within the preset safety range and the cable tension change rate is less than the fourth preset threshold, it is determined to be fully connected, and the charging control system maintains normal charging operation at this time; when the cable tension is within the preset safety range and the cable tension change rate is between the fourth preset threshold and the fifth preset threshold, it is determined to be a critical state, and the charging control system immediately starts dynamic compensation, and offsets external force interference by adjusting the translation amount and rotation angle of the robotic arm to avoid deterioration of the connection state; when the cable tension exceeds the preset safety range and the cable tension change rate is greater than the fifth preset threshold, it is determined to be an abnormal state, and the charging control system performs an emergency disconnection operation, cuts off the charging circuit, and controls the robotic arm to evacuate to prevent cable breakage or equipment damage.

[0075] In one embodiment of the present invention, when the sea condition risk index exceeds the sixth preset threshold, the charging power is reduced to a first preset ratio of the preset rated power to avoid equipment overload when the cable is pulled due to hull shaking; preferably, the sixth preset threshold is set to 8 and the first preset ratio is 60%.

[0076] In one embodiment of the present invention, the termination condition of the charging operation is achieved through real-time monitoring of multi-dimensional sensor data and threshold judgment, specifically including:

[0077] When the battery power reaches the preset power threshold, the charging control system determines that charging is complete and terminates the charging operation;

[0078] When the charging voltage exceeds the preset voltage threshold during charging, the overvoltage protection mechanism is triggered, and a hard shutdown is achieved by disconnecting the charging circuit relay to prevent thermal runaway of the battery.

[0079] When the charging current is continuously lower than the preset current threshold for more than a first preset time period, the charging is determined to be abnormal and terminated;

[0080] When the sea condition risk index exceeds the preset risk threshold, the charging operation is terminated;

[0081] When the interface temperature is detected to exceed the preset temperature threshold, the charging operation is terminated to prevent interface burning.

[0082] The above-mentioned termination conditions realize the safety protection of the charging operation throughout its life cycle. They not only meet the battery safety specifications, but also add unique protection dimensions such as sea condition risks and interface temperature for the dynamic marine environment, forming a complete safety protection system.

[0083] In one embodiment of the present invention, after the charging operation is terminated, the charging control system executes the disconnection and homing process according to the preset logic to ensure the safety of the equipment and restore the standby state; specifically, the charging controller sends a power-off command, the robotic arm subsystem performs a combined evacuation-lifting action, and the cable drive subsystem recycles the cable.

[0084] It should be noted that the intervals and thresholds are set for ease of comparison. The threshold size depends on the amount of sample data and the cardinality set by those skilled in the art for each set of sample data, as long as it does not affect the proportional relationship between the parameter and the quantized value. Furthermore, the above formulas are all dimensionless numerical calculations. These formulas are derived from software simulations of the most recent real-world conditions using large amounts of data. The preset parameters in these formulas are set by those skilled in the art based on actual conditions.

[0085] The above describes the embodiments of the present invention, but the present invention is not limited to the above specific implementation methods. The above specific implementation methods are merely illustrative and not restrictive. Ordinary technicians in this field can also make many forms based on the inspiration of this embodiment, all of which are protected by this embodiment.

Claims

1. A remote-controlled automatic charging robot real-time data transmission and feedback method, characterized in that: The following steps are involved: S101, after receiving the remote start command, collect sea condition data, generate a sea condition risk index based on the sea condition data using a weighted method, and perform status detection operations on the manipulator subsystem, cable drive subsystem, and sensor subsystem in the charging control system respectively; Among them, sea condition data include: significant wave height, peak period, surface wind speed; S102, obtaining relative posture data between the power supplying ship and the powered ship, processing the data through a Kalman filter algorithm, generating posture control instructions, and controlling the manipulator subsystem to perform dynamic posture compensation operations; Among them, the relative posture data includes translation and rotation angle; S103: Identify and locate the charging port, control the robotic arm subsystem to complete the connector insertion and locking operations, collect cable tension in real time, determine the connection status, and adjust the position of the cable subsystem and the power supply vessel based on the determination result; S104, controlling the charging process according to a preset charging power strategy, collecting charging status data, and making a judgment based on the sea condition risk index, executing a charging termination response when termination conditions are met; wherein the charging status data includes: charging current, charging voltage, battery level, and interface temperature; S105, after charging is terminated, disconnection-related operations are performed in a preset order, and the robot arm and the cable drive subsystem are controlled to coordinately complete homing, so that the charging control system returns to the initial standby state.

2. The method for real-time data transmission and feedback of a remotely controlled automatic charging robot according to claim 1, characterized in that: The first intermediate parameter is obtained by calculating the ratio of the effective wave height to the preset maximum safe wave height, the second intermediate parameter is obtained by calculating the ratio of the difference between the preset maximum safe period and the peak period to the span of the preset period safety range, and the third intermediate parameter is obtained by calculating the ratio of the surface wind speed to the preset maximum safe wind speed. The first intermediate parameter, the second intermediate parameter and the third intermediate parameter are weightedly summed based on the preset weights to obtain the sea condition risk index.

3. The method for real-time data transmission and feedback of a remotely controlled automatic charging robot according to claim 1, characterized in that: The state detection operation includes: Perform self-test on the robotic arm subsystem, including whether the motor current of each joint is within the first preset range; Performing a self-test on the cable drive subsystem, including whether the cable retraction and extension speed is stable within a second preset range when no-load, and whether the cable tension in a static state is less than a second preset threshold; The sensor subsystem is self-checked, including whether the GPS signal strength is greater than a third preset threshold.

4. The method for real-time data transmission and feedback of a remotely controlled automatic charging robot according to claim 1, characterized in that: The relative posture data is processed by the Kalman filter algorithm to generate posture control instructions. The specific steps include: S201, inputting the relative pose data into the Kalman filter algorithm, performing state prediction and measurement update in sequence, and obtaining the optimal estimated pose, wherein the optimal estimated pose is a state vector including the translation amount and the rotation angle; S202, extracting the rotation angle and angular velocity as target posture parameters based on the optimal estimated posture; S203, converting the target posture parameters into target angles of each joint of the robotic arm through the robotic arm inverse kinematics algorithm; S204: Encapsulate the target angles of the joints of the robotic arm into posture control instructions and send them to the robotic arm subsystem.

5. The method for real-time data transmission and feedback of a remotely controlled automatic charging robot according to claim 1, characterized in that: The specific steps of controlling the robotic arm subsystem to perform dynamic posture compensation operations include: S301, performing a validity check on the posture control instruction, wherein the validity check includes: angle range check and speed constraint verification; S302, driving the coordinated motion of the joints of the manipulator through a distributed control architecture, and offsetting the relative motion of the hull based on a feedforward-feedback composite control strategy; S303, obtaining a contact force feedback signal through the force sensor at the end of the robotic arm, and adjusting the translation amount and rotation angle of the actuator at the end of the robotic arm in real time based on the contact force feedback signal, wherein the adjustment includes PID correction of the target angle of each joint.

6. The method for real-time data transmission and feedback of a remotely controlled automatic charging robot according to claim 1, characterized in that: The connection status includes: fully connected, critical state and abnormal state; Calculating the cable tension change rate; determining that the connection is complete and maintaining charging when the cable tension is within a preset safety range and the cable tension change rate is less than a fourth preset threshold; When the cable tension is within the preset safety range and the cable tension change rate is between the fourth preset threshold and the fifth preset threshold, it is determined to be a critical state and dynamic compensation is started; When the cable tension exceeds the preset safety range and the cable tension change rate is greater than a fifth preset threshold, it is determined to be an abnormal state and an emergency disconnection operation is performed.

7. The method for real-time data transmission and feedback of a remotely controlled automatic charging robot according to claim 1, characterized in that: The preset charging power strategy includes: when the sea condition risk index exceeds a sixth preset threshold, reducing the charging power to a first preset proportion of the preset rated power.

8. The method for real-time data transmission and feedback of a remotely controlled automatic charging robot according to claim 1, characterized in that: The termination conditions include: The battery level reaches the preset power threshold; The charging voltage exceeds the preset voltage threshold; The charging current is lower than the preset current threshold; The sea condition risk index exceeds the preset risk threshold; The interface temperature exceeds the preset temperature threshold.

Images