Vector propulsion underwater robot and control method thereof

Abstract

The invention discloses a vector propulsion underwater robot and a control method thereof. The vector propulsion underwater robot comprises an aluminum alloy sealed cabin, a vector propulsion base, symmetrically distributed vector propulsion devices, a short baseline positioning system and an autopilot. The sealed cabin provides waterproof protection for core components; the propelling base is rigidly connected with the sealed cabin; the vector propulsion device generates multidirectional power and feeds back an azimuth angle in real time; the short baseline positioning system obtains an underwater position; and the autopilot integrates positioning, depth and attitude data, plans a navigation path in real time, solves the thrust direction and magnitude of the propulsion device, realizes three-dimensional motion and attitude stability, and dynamically adjusts the propulsion orientation at the same time. The modular vector propulsion design is adopted, the mechanical complexity is remarkably reduced, and the deep sea operation stability and the energy efficiency are improved. And accurate position / attitude control is realized through multi-directional thrust adjustment, and the problem of water flow disturbance is solved. Disturbance compensation and a self-adaptive mechanism are integrated, thrust distribution is dynamically optimized in combination with the battery state, and the operation time is prolonged.

Description

Technical Field

[0001] The present invention belongs to the technical field of underwater robots, and in particular relates to a vector-propelled underwater robot and a control method thereof. Background Art

[0002] With the rapid development of marine engineering technology, underwater robots (AUVs) have become essential core equipment for deep-sea operations. Tasks such as marine environmental monitoring and resource exploration are often handled by AUVs. Their key components, such as propulsion systems, robotic arms, and sensors, are constantly exposed to the complex and volatile deep-sea environment. Common problems such as current disturbances, equipment corrosion, cable entanglement, and sudden changes in seafloor topography can severely impact the safety and reliability of underwater operations, making the AUV's environmental adaptability particularly crucial.

[0003] Currently, vector propulsion technology is widely used in various underwater robotic systems. By adopting advanced vector propulsion solutions, robots can achieve more flexible movement and more precise positioning, providing operators with more reliable operational support. However, traditional underwater robots often use full-drive propulsion systems. When equipped with large operating equipment, this not only increases system complexity but also affects the robot's maneuverability and energy efficiency due to additional water resistance.

[0004] This paper proposes a vector-propulsion underwater robot and its control method, featuring an innovative structural design and control algorithm. These features are simple and responsive. When equipped with a large operating module, the system effectively reduces water resistance interference and significantly improves the robot's motion stability and endurance, providing a more efficient and reliable solution for deep-sea exploration operations. Summary of the Invention

[0005] In response to the above technical problems, the present invention provides a vector-propelled underwater robot and a control method thereof.

[0006] The technical solution adopted by the present invention to solve the technical problem is:

[0007] A vector propulsion underwater robot comprises a sealed cabin, an omnidirectional vector propulsion base, a vector propulsion device, a short baseline positioning system and an autopilot.

[0008] The sealed cabin is made of aluminum alloy, providing waterproof protection for the core components of the robot;

[0009] The omnidirectional vector propulsion base is rigidly connected to the sealed cabin to support and position the modular propulsion system;

[0010] The vector propulsion devices are symmetrically installed on both sides of the omnidirectional vector propulsion base to generate multi-directional propulsion power, control the thrust angle, and monitor the azimuth angle changes in real time;

[0011] Short baseline positioning system, used to obtain the current position of the underwater robot and send it to the autopilot;

[0012] The autopilot is used to integrate short-baseline positioning, depth and attitude sensor data, plan autonomous navigation and obstacle avoidance paths in real time, calculate and control the thrust direction and magnitude of the vector propulsion device, achieve three-dimensional motion and attitude stability; dynamically adjust the orientation of the vector propulsion device based on angle feedback, and perform system status monitoring.

[0013] Preferably, the omnidirectional vector propulsion base is composed of a high-density polyethylene rectangular plate and a footframe, and four vector propulsion devices are installed at the four corners. Each vector propulsion device includes a tilt motor, a propeller, an angle sensor and a connector. The tilt motor is installed on the omnidirectional vector propulsion base, the angle sensor and the tilt motor are installed coaxially, one side of the propeller is connected to the tilt motor through a connector, and the center is connected to the blade through an axle seat; the autopilot drives the propeller to drive the blade to generate thrust, and at the same time drives the tilt motor to operate and obtain angle sensor data, so that the tilt motor drives the propeller to rotate to a specified angle, thereby realizing a change in thrust direction.

[0014] Preferably, the four groups of vector propulsion devices are symmetrically distributed on the center, and are divided into a completely identical first propulsion device, a second vector propulsion device, a third vector propulsion device and a fourth vector propulsion device, the first vector propulsion device and the third vector propulsion device are located on the same diagonal line, and the second vector propulsion device and the fourth vector propulsion device are located on the same diagonal line;

[0015] When the robot moves forward, the four sets of inclination motors of the vector propulsion device drive the propeller to rotate backward through the connector, obtain the angle sensor data, and make the inclination motor rotate to the required angle, so that the robot obtains forward acceleration;

[0016] When the robot moves backward, the inclination motors of the four sets of vector propulsion devices drive the propellers forward through the connecting parts, obtain the angle sensor data, make the inclination motors rotate to the required angle, and the robot obtains backward acceleration.

[0017] When the robot is hovering, the inclination motors of the four sets of vector propulsion devices drive the thrusters to rotate through the connecting parts, obtain the angle sensor data, and make the inclination motors rotate to the vertical upward position. The robot obtains the thrust required for hovering to offset the net buoyancy; if the thrust is greater than the net buoyancy, the robot dives; if the thrust is less than the net buoyancy, the robot floats.

[0018] Preferably, the autopilot includes a power supply, an onboard computer, a network communication module, an RS485 communication module, a power distribution board, an inertial measurement unit, and a power management module;

[0019] The onboard computer is used to run the control program to achieve intelligent control and autonomous decision-making of the robot;

[0020] The network communication module is used to establish a data channel between the underwater robot and the ground control station through a zero-buoyancy cable, and transmit operating status and environmental perception data in real time;

[0021] RS485 communication module is used to control the inclination motor in real time and obtain angle sensor data;

[0022] The inertial measurement unit includes a three-axis gyroscope, a three-axis accelerometer and a three-axis geomagnetic sensor, which are used to detect and measure the robot's three-axis angular velocity, three-axis acceleration and the components of the geomagnetic intensity on the robot's three axes;

[0023] The power management module is equipped with multiple field-effect transistors and high-current fuses, and controls the on-off of the system power supply through an external physical switch on the surface of the sealed cabin.

[0024] A control method for a vector-propelled underwater robot, comprising the following steps:

[0025] S100: using a short baseline positioning system or an inertial measurement unit to obtain a current state of the robot in real time; wherein the state is a position or a posture;

[0026] S200: Compare the current state with the preset target state, calculate the error, and evaluate the current energy consumption state;

[0027] S300: Decomposing the error into error components in specific directions according to the three-dimensional coordinate system, and calculating the energy consumption weight of each direction;

[0028] S400: Based on the decomposed error components, the vector propulsion device is driven to make adjustments so that the robot reaches a preset target state;

[0029] S500: Executes energy optimization strategy, optimizes thrust distribution and motion trajectory, and minimizes system energy consumption.

[0030] Preferably, when the underwater robot performs a target task, S100 includes: using a short baseline positioning system to measure the current position of the underwater robot, constructing a three-dimensional coordinate system with the propeller as the origin to obtain an underwater coordinate system, wherein the Z axis of the underwater coordinate system coincides with the direction of gravity, and the Z axis is perpendicular to the X axis and the Y axis; and simultaneously fusing inertial measurement unit data to improve position estimation accuracy through a complementary filtering algorithm;

[0031] S200 includes: determining a position error based on the current position and a preset target position, and calculating an error change rate;

[0032] S300 includes: decomposing the position error to obtain a first translation error, a second translation error, and a third translation error, where the first translation error is a component of the position error in the X-axis direction, the second translation error is a component of the position error in the Y-axis direction, and the third translation error is a component of the position error in the Z-axis direction; and simultaneously calculating first-order derivatives and second-order derivatives of the errors of each axis;

[0033] S400 includes: controlling a propeller and an inclination motor according to the first translation error, the second translation error, and the third translation error to adjust the robot from a current position to a preset target position;

[0034] S500 includes: establishing an energy consumption model based on the current thruster operating status and remaining battery power; dynamically adjusting control parameters according to mission priority; and optimizing the thrust distribution strategy to minimize the system's energy consumption while meeting control accuracy requirements.

[0035] Preferably, when the underwater robot is in a hovering state, S100 includes: using an inertial measurement unit to monitor a current posture of the underwater robot in the hovering state;

[0036] S200 includes: determining a posture error according to the current posture and a preset target posture;

[0037] S300 includes: using the robot body coordinate system, decomposing the posture error to obtain a first angle error, a second angle error, and a third angle error, wherein the first angle error is a component of the posture error on the XoY plane, the second angle error is a component of the posture error on the YoZ plane, and the third angle error is a component of the posture error on the XoZ plane;

[0038] S400 includes: controlling a propeller according to the first angle error, the second angle error, and the third angle error to adjust the robot from a current posture to a preset target posture;

[0039] S500 includes: establishing an energy consumption model based on the current thruster operating status and remaining battery power; dynamically adjusting control parameters according to mission priority; and optimizing the thrust distribution strategy to minimize the system's energy consumption while meeting control accuracy requirements.

[0040] Preferably, when the underwater robot performs a target task, S400 includes:

[0041] S410: Calculate the velocity errors in the X, Y, and Z axes based on the first, second, and third translation errors; derive the corresponding acceleration errors based on the velocity errors of each axis; establish a system model based on the acceleration errors to determine the required thrust compensation for the propeller and the tilt compensation for the tilt motor; introduce integral and differential terms to enhance control accuracy, and estimate external disturbances using a disturbance observer;

[0042] S420: Based on a preset error convergence strategy, the current translation error, velocity error, and acceleration error are matched with the target dynamic response characteristics to generate velocity error compensation terms and acceleration error compensation terms; a feedforward control term and an adaptive control term are added, and the control coefficient is dynamically adjusted according to the system state;

[0043] S430: Correcting the actual speed using the speed error compensation term and correcting the actual acceleration using the acceleration error compensation term; converting the corrected acceleration error into an inclination control command and a thrust control command using a system mathematical model;

[0044] S440: Iterate the process from S420 to S430 until all the control variables for the X, Y, and Z axes are calculated. The disturbance estimate and control parameters are updated in each iteration to ensure system convergence.

[0045] S450: Drive the corresponding tilt motor according to the generated tilt control instruction, and adjust the thruster output according to the thrust control instruction to achieve the adjustment of the robot from the current position to the preset target position; when the current tilt value or thrust control amount exceeds the preset threshold, control the tilt motor and thruster to stop running.

[0046] Preferably, S420 specifically includes:

[0047] e v =k1e p -v r

[0048] Among them, e v is the target speed error, e p is the target translation, v r is the true speed, k1 is the coefficient;

[0049]

[0050]

[0051] Among them, e a is the target acceleration error, e v is the target speed error, a r is the acceleration, d est is the disturbance estimate, is the acceleration error at the previous moment, is the acceleration error predicted by the model, k2 is the coefficient, k3 is the coefficient, and k4 is the coefficient;

[0052]

[0053] u ff =m·a ref

[0054] u adapt =γ·sign(e a )·|e a | α

[0055] Among them, u is the three-axis control rate, e a is the target acceleration error, a r is the acceleration, u ff is the feedforward control term, u adapt is the adaptive control item, m is the robot mass, a ref is the reference acceleration, γ is the adaptive gain, α is the exponential coefficient, k5 is the coefficient, and k6 is the coefficient;

[0056] S430 specifically:

[0057]

[0058] Among them, θ is the tilt angle control value of the four tilt motors, W is the net buoyancy of the robot in water, u x 、u y 、u z is the three-axis virtual force, and t1, t2, t3, and t4 are the control inputs of the four thrusters.

[0059] Preferably, when the underwater robot performs a target task, S500 includes:

[0060] S510: Establishing a propeller energy consumption model to calculate the real-time power consumption of each propeller and the total power consumption of the system;

[0061] S520: Construct a multi-objective optimization function that comprehensively considers control performance and energy consumption, and balances the relationship between control accuracy, response speed, and energy consumption;

[0062] S530: Execute a thrust redistribution optimization algorithm based on the propeller efficiency curve and the current operating point;

[0063] S540: Implement a hierarchical energy management strategy based on the remaining battery power and mission requirements.

[0064] Preferably, S510 specifically includes:

[0065]

[0066] Among them, P i is the i-th thruster power, T i is the thrust, ω i is the speed, c1, c2, c3 are the power coefficients, and P0 is the basic power consumption;

[0067] S520 specifically:

[0068] J opt =w1·||e p || 2 +w2·‖e v ‖ 2 +w3·P total +w4·∑‖ΔT‖ 2

[0069] Among them, w1 to w4 are adjustable weight coefficients, which are dynamically adjusted according to the remaining battery capacity SOC:

[0070] w3=w 3,base (1+k soc ·e -SOC / 30 )

[0071] Among them, w 3,base is the benchmark value of energy consumption weight, k soc is the energy sensitivity coefficient; when the power is reduced, the energy consumption weight w3 is automatically increased, giving priority to energy saving;

[0072] S530 specifically:

[0073] Perform thrust optimization distribution based on thruster efficiency characteristics:

[0074] Establish the propeller efficiency-operating point mapping relationship η i (T i ,ω i ), under the premise of meeting the total thrust demand, solve the thrust distribution scheme that minimizes the total power consumption:

[0075]

[0076] subject to:B·T=τ required

[0077] T min ≤T i ≤T max

[0078] Where B is the thrust distribution matrix, which describes the mapping relationship between the thrust of the propeller and the force / torque of the robot's six degrees of freedom; T = [T1, T2, T3, T4] T is the thrust vector of the four thrusters; τ required is the desired six-degree-of-freedom control force / torque inward; T min and T max are the lower and upper limits of the thruster respectively; η i is the efficiency of the i-th propeller at the current working point;

[0079] When the system is in low thrust demand, select the minimum thruster combination, turn off redundant thrusters to reduce no-load loss;

[0080] Specifically, S540 is as follows:

[0081] Implement a hierarchical energy management strategy:

[0082] When the SOC > 60%, it is in the normal mode and operates at full performance. When 30% < SOC ≤ 60%, it is in the energy-saving mode. In the energy-saving mode, the control gain is reduced to 80% and the thrust limit is 85%. When the SOC ≤ 30%, it is in the emergency mode. In the emergency mode, the control gain is reduced to 60% and the thrust limit is 60%, and non-essential equipment is turned off. When the battery power is lower than the preset safety threshold, it automatically switches to the energy-saving return mode to ensure the robot's safe return first. Dynamically adjust the power budget according to the task priority and the remaining voyage to ensure the completion of critical tasks or a safe return.

[0083] The above-mentioned vector propulsion underwater robot and its control method adopt a modular design. Through the vector propulsion technology, the mechanical complexity of the traditional full drive system is significantly reduced, and at the same time, the stability and energy efficiency of deep-sea operations are improved. By adjusting the thrust from multiple directions through the control method to achieve precise control of the position and attitude, the problem that the underwater robot is easily affected by water flow disturbance during operation, resulting in insufficient positioning accuracy, is solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Figure 1 It is a schematic structural diagram of the vector propulsion underwater robot in an embodiment of the present invention;

[0085] Figure 2 It is a structural diagram of the vector propulsion device in an embodiment of the present invention;

[0086] Figure 3 It is a working principle diagram of the tilt motor for adjusting the thrust direction in an embodiment of the present invention;

[0087] Figure 4 It is a working principle diagram adapted to the vector propulsion underwater robot in an embodiment of the present invention;

[0088] Figure 5 It is a module schematic diagram of the autopilot in an embodiment of the present invention;

[0089] Figure 6 It is a flowchart of the control method of the vector propulsion underwater robot in an embodiment of the present invention;

[0090] Among them, the above-mentioned drawings include the following reference numerals:

[0091] 1. Sealed cabin; 2. Omnidirectional vector propulsion base; 3. First tilt motor; 4. Second tilt motor; 5. Third tilt motor; 6. Fourth tilt motor; 7. First thruster; 8. Second thruster; 9. Third thruster; 10. Fourth thruster; 11. Buoyancy block; 12. Forward-looking camera; 13. Inertial measurement unit; 14. Short baseline positioning system; 15. First angle sensor; 16. Second angle sensor; 17. Third angle sensor; 18. Fourth angle sensor. DETAILED DESCRIPTION

[0092] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention is further described in detail below with reference to the accompanying drawings.

[0093] In the prior art, underwater robots currently use full-drive propulsion systems. Traditional full-drive underwater robots require multiple fixed thrusters for deep-sea operations, resulting in complex mechanical structures, increased water resistance, and significantly increased energy consumption, seriously affecting operational stability and endurance. To address the high mechanical complexity, high water resistance, and low energy efficiency associated with full-drive propulsion systems for underwater robots, the present invention provides a vector-propelled underwater robot and a control method thereof.

[0094] In one embodiment, Figure 1 As shown, a vector propulsion underwater robot includes a sealed cabin 1, an omnidirectional vector propulsion base 2, a vector propulsion device, a short baseline positioning system 14 and an autopilot.

[0095] The sealed cabin 1 is made of high-strength aluminum alloy, providing waterproof protection for the robot's core components and ensuring its reliable operation in high-pressure deep-sea environments;

[0096] The omnidirectional vector propulsion base 2 is rigidly connected to the sealed cabin 1 to absorb the vibration and impact generated by the propeller during operation, while supporting and positioning the modular propulsion system;

[0097] The vector propulsion device is symmetrically installed on both sides of the omnidirectional vector propulsion base 2, which is used to generate multi-directional propulsion power, control the thrust angle and monitor the azimuth angle changes in real time;

[0098] A short baseline positioning system 14 is used to obtain the current position of the underwater robot and send it to the autopilot;

[0099] The autopilot is used to integrate short-baseline positioning, depth and attitude sensor data, plan autonomous navigation and obstacle avoidance paths in real time, calculate and control the thrust direction and magnitude of the vector propulsion device, achieve three-dimensional motion and attitude stability; dynamically adjust the orientation of the vector propulsion device based on angle feedback, and perform system status monitoring.

[0100] Specifically, the underwater robot adopts a modular design and uses vector propulsion technology to significantly reduce the mechanical complexity of traditional full-drive systems, while improving the stability and energy efficiency of deep-sea operations.

[0101] In one embodiment, Figure 2 As shown, the omnidirectional vector propulsion base 2 is composed of a high-density polyethylene rectangular plate and a foot frame, and four vector propulsion devices are installed at the four corners. Each vector propulsion device includes an inclination motor (corresponding to the attached Figure 2 3-6, propeller (corresponding to the attached Figure 2 7-10), angle sensor (corresponding to the attached Figure 2 15-18) and connectors, the pitch motor is installed on the omnidirectional vector propulsion base 2, the angle sensor and the pitch motor are installed coaxially, one side of the propeller is connected to the pitch motor through a connector, and the center is connected to the blade through a shaft seat; the autopilot drives the propeller to drive the operation of the blade to generate thrust, and at the same time drives the pitch motor to operate and obtain angle sensor data, so that the pitch motor drives the propeller to rotate to a specified angle, thereby realizing a change in thrust direction.

[0102] In one embodiment, the four groups of vector propulsion devices are symmetrically distributed on the center, and are divided into a completely identical first propulsion device, a second vector propulsion device, a third vector propulsion device, and a fourth vector propulsion device. The first vector propulsion device and the third vector propulsion device are located on the same diagonal line, and the second vector propulsion device and the fourth vector propulsion device are located on the same diagonal line.

[0103] When the robot moves forward, the four sets of inclination motors of the vector propulsion device drive the propeller to rotate backward through the connector, obtain the angle sensor data, and make the inclination motor rotate to the required angle, so that the robot obtains forward acceleration;

[0104] When the robot moves backward, the inclination motors of the four sets of vector propulsion devices drive the propellers forward through the connecting parts, obtain the angle sensor data, make the inclination motors rotate to the required angle, and the robot obtains backward acceleration.

[0105] When the robot is hovering, the inclination motors of the four sets of vector propulsion devices drive the thrusters to rotate through the connecting parts, obtain the angle sensor data, and make the inclination motors rotate to the vertical upward position. The robot obtains the thrust required for hovering to offset the net buoyancy; if the thrust is greater than the net buoyancy, the robot dives; if the thrust is less than the net buoyancy, the robot floats.

[0106] Specifically, the principle diagram of the tilt motor for adjusting the thrust direction is as follows: Figure 3 As shown, the working principle of the vector propulsion underwater robot adaptation is as follows Figure 4 shown.

[0107] In one embodiment, Figure 5 As shown, the autopilot includes a power supply, an onboard computer, a network communication module, an RS485 communication module, a power distribution board, an inertial measurement unit 13 and a power management module;

[0108] The onboard computer is used to run the control program to achieve intelligent control and autonomous decision-making of the robot;

[0109] The network communication module is used to establish a data channel between the underwater robot and the ground control station through a zero-buoyancy cable, and transmit operating status and environmental perception data in real time;

[0110] The RS485 communication module is used to control the inclination motor in real time and obtain angle sensor data;

[0111] The inertial measurement unit 13 includes a three-axis gyroscope, a three-axis accelerometer and a three-axis geomagnetic sensor, which are used to detect and measure the robot's three-axis angular velocity, three-axis acceleration and the components of the geomagnetic intensity on the three axes of the robot;

[0112] The power management module is configured with multiple field effect transistors and high-current fuses, and the system power on-off control is achieved through an external physical switch on the surface of the sealed cabin 1.

[0113] In one embodiment, the robot also includes a buoyancy block 11 for adjusting the overall buoyancy to ensure stable suspension of the robot at different water depths. It also includes a forward-looking camera 12 for underwater target recognition and environmental perception, providing visual support for autonomous operation.

[0114] The above-mentioned vector-propelled underwater robot is designed with a vector propulsion system and dynamically adjusts the thrust direction of the propeller through the tilt motor to achieve more efficient multi-degree-of-freedom precision control. In addition, through modular layout and shock-absorbing mechanism, it can perform adaptive adjustment in complex deep-sea flow field environments to ensure operational stability, solving the problems of complex mechanical structure, increased water resistance and low energy efficiency caused by the fixed propeller layout of the fully-driven underwater robot in the existing technology.

[0115] In this embodiment, a vector propulsion control method running on an underwater robot control terminal, a surface control station or a similar computing device is also provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in computing devices such as underwater robot embedded control systems, surface control station computer systems, etc., and although the logical order is shown in the flowchart, in some cases (such as sudden ocean current interference or equipment failure), the control strategy can be dynamically adjusted based on the environmental perception data to execute the steps shown or described in a manner different from the preset order.

[0116] In one embodiment, a control method for a vector-propelled underwater robot is provided, the method comprising the following steps:

[0117] S100: using a short baseline positioning system or an inertial measurement unit to obtain a current state of the robot in real time; wherein the state is a position or a posture;

[0118] S200: Compare the current state with the preset target state and calculate the error;

[0119] S300: Decomposing the error into error components in specific directions according to the three-dimensional coordinate system;

[0120] S400: Based on the decomposed error components, the vector propulsion device is driven to make adjustments so that the robot reaches a preset target state;

[0121] S500: Executes energy optimization strategy, optimizes thrust distribution and motion trajectory, and minimizes system energy consumption.

[0122] In one embodiment, when the underwater robot performs a target task, S100 includes: using a short baseline positioning system to measure the current position of the underwater robot, constructing a three-dimensional coordinate system with the propeller as the origin to obtain an underwater coordinate system, wherein the Z axis of the underwater coordinate system coincides with the direction of gravity, and the Z axis is perpendicular to the X axis and the Y axis; and simultaneously fusing inertial measurement unit data to improve position estimation accuracy through a complementary filtering algorithm.

[0123] S200 includes: determining a position error based on the current position and a preset target position, and calculating an error change rate;

[0124] S300 includes: decomposing the position error to obtain a first translation error, a second translation error, and a third translation error, where the first translation error is a component of the position error in the X-axis direction, the second translation error is a component of the position error in the Y-axis direction, and the third translation error is a component of the position error in the Z-axis direction; and simultaneously calculating first-order derivatives and second-order derivatives of the errors of each axis;

[0125] S400 includes: controlling a propeller and an inclination motor according to the first translation error, the second translation error, and the third translation error to adjust the robot from a current position to a preset target position;

[0126] S500 includes: establishing an energy consumption model based on the current thruster operating status and remaining battery power; dynamically adjusting control parameters according to mission priority; and optimizing the thrust distribution strategy to minimize the system's energy consumption while meeting control accuracy requirements.

[0127] Specifically, the above-mentioned target task operation is the preset position of the underwater robot when performing underwater operation tasks in the preset operation plan. The above-mentioned current position is the real-time position obtained by the short baseline positioning system after the underwater robot reaches the operation area. The above-mentioned preset target position is the ideal position and posture of the underwater robot when performing tasks in the above-mentioned operation area; for the convenience of control, the present application establishes a three-dimensional coordinate system with the thruster as the origin; according to the current position and the preset target position, the position deviation amount, that is, the above-mentioned first position error, can be determined in the three-dimensional coordinate system. For the convenience of control, the above-mentioned first position error is decomposed into the X-axis, Y-axis and Z-axis directions respectively, that is, the above-mentioned first translation error, second translation error and third translation error are obtained. Based on the first translation error, the underwater robot's X-axis adjustment is determined, thereby controlling the thrust output of the propeller. Based on the second translation error, the underwater robot's Y-axis adjustment is determined, thereby controlling the inclination motor to adjust the propeller angle. Based on the third translation error, the underwater robot's Z-axis adjustment is determined, thereby controlling the thrust output of the propeller to adjust the underwater robot from its current position to a preset target position. By fusing multi-sensor data and calculating error derivatives, the system can predict motion trends, adjust control parameters in advance, and enhance its ability to suppress external disturbances.

[0128] This method obtains the preset operating position and current position, monitors position error in real time, and decomposes the position error into three directions in a three-dimensional coordinate system. By adjusting the corresponding components based on the thrusters and tilt motors, the thrust can be adjusted in multiple directions to achieve precise control. At the same time, through energy optimization strategies, the robot's operating time is effectively extended while ensuring control accuracy. This method addresses the problem of underwater robots being susceptible to water flow disturbances during operation, resulting in insufficient positioning accuracy, as well as the high energy consumption and insufficient endurance of traditional control methods.

[0129] In one embodiment, when the underwater robot is in a hovering state, S100 includes: using an inertial measurement unit to monitor a current posture of the underwater robot in the hovering state;

[0130] S200 includes: determining a posture error according to the current posture and a preset target posture;

[0131] S300 includes: using the robot body coordinate system, decomposing the posture error to obtain a first angle error, a second angle error, and a third angle error, wherein the first angle error is a component of the posture error on the XoY plane, the second angle error is a component of the posture error on the YoZ plane, and the third angle error is a component of the posture error on the XoZ plane;

[0132] S400 includes: controlling a propeller according to the first angle error, the second angle error, and the third angle error to adjust the robot from a current posture to a preset target posture;

[0133] S500 includes: establishing an energy consumption model based on the current thruster operating status and remaining battery power; dynamically adjusting control parameters according to mission priority; and optimizing the thrust distribution strategy to minimize the system's energy consumption while meeting control accuracy requirements.

[0134] Specifically, before performing an operational task, the underwater robot must first undergo attitude calibration. This involves obtaining the underwater robot's current attitude while in a hovering state, i.e., obtaining the aforementioned current attitude. While the underwater robot is in a horizontally hovering state, it should maintain a stable attitude, i.e., a preset attitude. Based on the current attitude and the preset attitude, the angular deviation, i.e., the aforementioned first attitude error, can be determined in a three-dimensional coordinate system. To facilitate control, the aforementioned first attitude error is decomposed into the XoY plane, YoZ plane, and XoZ plane, respectively, to obtain the aforementioned first angular error, second angular error, and third angular error. In a specific implementation, taking the YoZ plane as an example, if the aforementioned second angular error, i.e., the pitch angle deviation, is greater than 0, the front thruster is controlled to output forward thrust, while the rear thruster is controlled to output reverse thrust. Conversely, if the aforementioned second angular deviation is less than 0, the front thruster is controlled to output reverse thrust, while the rear thruster is controlled to output forward thrust.

[0135] In one embodiment, when the underwater robot performs a target task, S400 includes:

[0136] S410: Calculate the velocity errors in the X, Y, and Z axes based on the first, second, and third translation errors; derive the corresponding acceleration errors based on the velocity errors of each axis; establish a system model based on the acceleration errors to determine the required thrust compensation for the propeller and the tilt compensation for the tilt motor; introduce integral and differential terms to enhance control accuracy, and estimate external disturbances using a disturbance observer;

[0137] S420: Based on a preset error convergence strategy, the current translation error, velocity error, and acceleration error are matched with the target dynamic response characteristics to generate velocity error compensation terms and acceleration error compensation terms; a feedforward control term and an adaptive control term are added, and the control coefficient is dynamically adjusted according to the system state;

[0138] S430: Correcting the actual speed using the speed error compensation term and correcting the actual acceleration using the acceleration error compensation term; converting the corrected acceleration error into an inclination control command and a thrust control command using a system mathematical model;

[0139] S440: Iterate the process from S420 to S430 until all the control variables for the X, Y, and Z axes are calculated. The disturbance estimate and control parameters are updated in each iteration to ensure system convergence.

[0140] S450: driving the corresponding inclination motor according to the generated inclination control instruction, and adjusting the thruster output according to the thrust control instruction to achieve adjustment of the robot from the current position to the preset target position.

[0141] Specifically, according to the calculated inclination control amount and thrust control amount, each inclination motor is controlled to adjust the propeller angle, and each propeller is controlled to output the corresponding thrust, so that the position of the underwater robot reaches the preset target position.

[0142] In one embodiment, S420 specifically includes:

[0143] e v =k1e p -v r

[0144] Among them, e v is the target speed error, e p is the target translation, v r is the true speed, k1 is the coefficient;

[0145]

[0146]

[0147] Among them, e a is the target acceleration error, e v is the target speed error, a r is the acceleration, d est is the disturbance estimate, is the acceleration error at the previous moment, is the acceleration error predicted by the model, k2 is the coefficient, k3 is the coefficient, and k4 is the coefficient;

[0148]

[0149] u ff =m·a ref

[0150] u adapt =γ·sign(e a )·|e a | α

[0151] Among them, u is the three-axis control rate, e a is the target acceleration error, a r is the acceleration, uff is the feedforward control term, u adapt is the adaptive control item, m is the robot mass, a ref is the reference acceleration, γ is the adaptive gain, α is the exponential coefficient (0<α<1), k5 is the coefficient, and k6 is the coefficient;

[0152] S430 specifically:

[0153]

[0154] Among them, θ is the tilt angle control value of the four tilt motors, W is the net buoyancy of the robot in water, u x 、u y 、u z is the three-axis virtual force, and t1, t2, t3, and t4 are the control inputs of the four thrusters.

[0155] In order to prevent the above-mentioned underwater robot from being damaged, in one embodiment, S400 further includes:

[0156] When the current pitch angle value or thrust control amount exceeds the preset threshold, the pitch motor and thruster are controlled to stop running.

[0157] Specifically, the control system monitors the thrust of each propeller and the angle of the pitch motor in real time. When the thrust or angle exceeds a safety threshold, the pitch motor and the propeller are controlled to stop suddenly to prevent equipment damage.

[0158] In one embodiment, when the underwater robot performs a target task, S500 includes:

[0159] S510: Establishing a propeller energy consumption model to calculate the real-time power consumption of each propeller and the total power consumption of the system;

[0160] S520: Construct a multi-objective optimization function that comprehensively considers control performance and energy consumption, and balances the relationship between control accuracy, response speed, and energy consumption;

[0161] S530: Execute a thrust redistribution optimization algorithm based on the propeller efficiency curve and the current operating point;

[0162] S540: Implement a hierarchical energy management strategy based on the remaining battery power and mission requirements.

[0163] Specifically, by establishing a thruster power consumption model, monitoring the system energy consumption status in real time, constructing a multi-objective optimization function to balance control performance and energy efficiency, and optimizing thrust distribution according to the thruster efficiency characteristics, while implementing hierarchical energy management according to the battery status to ensure that the robot minimizes energy consumption while performing tasks.

[0164] In one embodiment, S510 specifically includes:

[0165]

[0166] Among them, P i is the i-th thruster power, T i is the thrust, ω i is the speed, c1, c2, c3 are the power coefficients, and P0 is the basic power consumption;

[0167] S520 specifically:

[0168] J opt =w1·||e p ‖ 2 +w2·‖e v ‖ 2 +w3·P total +w4·∑‖ΔT‖ 2

[0169] Among them, w1 to w4 are adjustable weight coefficients, which are dynamically adjusted according to the remaining battery capacity SOC:

[0170] w3=w 3,base (1+k soc ·e -SOC / 30 )

[0171] Among them, w 3,base is the benchmark value of energy consumption weight, k soc is the energy sensitivity coefficient; when the power is reduced, the energy consumption weight w3 is automatically increased, giving priority to energy saving;

[0172] S530 specifically:

[0173] Perform thrust optimization distribution based on thruster efficiency characteristics:

[0174] Establish the propeller efficiency-operating point mapping relationship η i (T i ,ω i ), under the premise of meeting the total thrust demand, solve the thrust distribution scheme that minimizes the total power consumption:

[0175]

[0176] subject to:B·T=τ required

[0177] T min ≤T i ≤T max

[0178] Among them, B is the thrust distribution matrix, which describes the mapping relationship from the thruster thrust to the six-degree-of-freedom force / moment of the robot; T = [T1, T2, T3, T4] T is the thrust vector of the four thrusters; τ required is the desired six-degree-of-freedom control force / moment vector; T min and T max are the lower and upper limits of the thruster thrust respectively; η i is the efficiency of the i-th thruster at the current operating point;

[0179] When the system is in low thrust demand, select the minimum thruster combination and turn off redundant thrusters to reduce no-load loss;

[0180] Specifically, S540 is as follows:

[0181] Implement a hierarchical energy management strategy:

[0182] When SOC > 60%, it is the normal mode, and it operates at full performance in the normal mode; when 30% < SOC ≤ 60%, it is the energy-saving mode, and the control gain is reduced to 80% and the thrust is limited to 85% in the energy-saving mode; when SOC ≤ 30%, it is the emergency mode, and the control gain is reduced to 60% and the thrust is limited to 60% in the emergency mode, and non-essential equipment is turned off; when the battery power is lower than the preset safety threshold, it automatically switches to the energy-saving return mode to ensure the safe return of the robot first; dynamically adjust the power budget according to the task priority and the remaining voyage to ensure the completion of key tasks or a safe return.

[0183] Specifically, the system continuously monitors the remaining battery power. When it detects that the power is lower than the safety threshold, it automatically reduces the power output of the thrusters and turns off non-essential equipment to ensure that the robot can safely return to the base.

[0184] Through vector propulsion design, this robot dynamically adjusts the thrust direction of the thrusters using tilt motors, and achieves multi-degree-of-freedom precise control in cooperation with the closed-loop feedback of the inertial measurement unit. By introducing a disturbance observer and an adaptive control strategy, it enhances the system's ability to suppress external disturbances such as ocean currents, significantly reduces the mechanical complexity and water resistance of the traditional fully driven system, and at the same time improves the stability and energy efficiency of deep-sea operations through modular layout and shock-absorbing mechanisms, solving the problems of poor mobility and weak anti-current interference ability of existing underwater robots due to the fixed thruster layout.

[0185] In one embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and it is characterized in that when the processor executes the computer program, the steps of the control method of the vector propulsion underwater robot are implemented. <In one embodiment, a computer-readable storage medium is further provided, on which a computer program is stored, characterized in that when the computer program is executed by a processor, the steps of the control method of the vector propulsion underwater robot are implemented.

[0187] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0188] The above is a detailed introduction to a vector propulsion underwater robot and its control method provided by the present invention. This article uses specific examples to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the core ideas of the present invention. It should be pointed out that for ordinary technicians in this technical field, without departing from the principles of the present invention, several improvements and modifications can be made to the present invention, and these improvements and modifications also fall within the scope of protection of the claims of the present invention.

Claims

1. A vector propulsion underwater robot, characterized in that: It includes a sealed cabin, an omnidirectional vector propulsion base, a vector propulsion device, a short baseline positioning system and an autopilot. The sealed cabin is made of aluminum alloy, providing waterproof protection for the core components of the robot; The omnidirectional vector propulsion base is rigidly connected to the sealed cabin to support and position the modular propulsion system; The vector propulsion devices are symmetrically installed on both sides of the omnidirectional vector propulsion base to generate multi-directional propulsion power, control the thrust angle, and monitor the azimuth angle changes in real time; Short baseline positioning system, used to obtain the current position of the underwater robot and send it to the autopilot; The autopilot is used to integrate short-baseline positioning, depth and attitude sensor data, plan autonomous navigation and obstacle avoidance paths in real time, calculate and control the thrust direction and magnitude of the vector propulsion device, achieve three-dimensional motion and attitude stability; dynamically adjust the orientation of the vector propulsion device based on angle feedback, and perform system status monitoring.

2. The method according to claim 1, characterized in that The omnidirectional vector propulsion base is composed of a high-density polyethylene rectangular plate and a footframe, with four vector propulsion devices installed at the four corners. Each vector propulsion device includes a tilt motor, a thruster, an angle sensor and a connector. The tilt motor is installed on the omnidirectional vector propulsion base, and the angle sensor is installed coaxially with the tilt motor. One side of the thruster is connected to the tilt motor through a connector, and the center is connected to the blade through a shaft seat; the autopilot drives the thruster to drive the blade to generate thrust, and at the same time drives the tilt motor to operate and obtain angle sensor data, so that the tilt motor drives the thruster to rotate to the specified angle, thereby realizing a change in thrust direction.

3. The method according to claim 2, characterized in that The four groups of vector propulsion devices are symmetrically distributed on the center, and are divided into a first propulsion device, a second vector propulsion device, a third vector propulsion device, and a fourth vector propulsion device that are completely identical. The first vector propulsion device and the third vector propulsion device are located on the same diagonal line, and the second vector propulsion device and the fourth vector propulsion device are located on the same diagonal line; When the robot moves forward, the four sets of inclination motors of the vector propulsion device drive the propeller to rotate backward through the connector, obtain the angle sensor data, and make the inclination motor rotate to the required angle, so that the robot obtains forward acceleration; When the robot moves backward, the inclination motors of the four sets of vector propulsion devices drive the propellers forward through the connecting parts, obtain the angle sensor data, make the inclination motors rotate to the required angle, and the robot obtains backward acceleration. When the robot is hovering, the inclination motors of the four sets of vector propulsion devices drive the thrusters to rotate through the connecting parts, obtain the angle sensor data, and make the inclination motors rotate to the vertical upward position. The robot obtains the thrust required for hovering to offset the net buoyancy; if the thrust is greater than the net buoyancy, the robot dives; if the thrust is less than the net buoyancy, the robot floats.

4. The method according to claim 3, characterized in that The autopilot includes a power supply, an onboard computer, a network communication module, an RS485 communication module, a power distribution board, an inertial measurement unit, and a power management module; The onboard computer is used to run the control program to achieve intelligent control and autonomous decision-making of the robot; The network communication module is used to establish a data channel between the underwater robot and the ground control station through a zero-buoyancy cable, and transmit operating status and environmental perception data in real time; RS485 communication module is used to control the inclination motor in real time and obtain angle sensor data; The inertial measurement unit includes a three-axis gyroscope, a three-axis accelerometer and a three-axis geomagnetic sensor, which are used to detect and measure the robot's three-axis angular velocity, three-axis acceleration and the components of the geomagnetic intensity on the robot's three axes; The power management module is equipped with multiple field-effect transistors and high-current fuses, and controls the on-off of the system power supply through an external physical switch on the surface of the sealed cabin.

5. A control method for a vector-propelled underwater robot according to any one of claims 1 to 4, characterized in that: The method comprises the following steps: S100: using a short baseline positioning system or an inertial measurement unit to obtain a current state of the robot in real time; wherein the state is a position or a posture; S200: Compare the current state with the preset target state and calculate the error; S300: Decomposing the error into error components in specific directions according to the three-dimensional coordinate system; S400: Based on the decomposed error components, the vector propulsion device is driven to make adjustments so that the robot reaches a preset target state; S500: Executes energy optimization strategy, optimizes thrust distribution and motion trajectory, and minimizes system energy consumption.

6. The method according to claim 5, characterized in that When the underwater robot performs a target task, S100 includes: using a short baseline positioning system to measure the underwater robot's current position, constructing a three-dimensional coordinate system with the thruster as the origin, and obtaining an underwater coordinate system in which the Z axis coincides with the direction of gravity and the Z axis is perpendicular to the X axis and the Y axis; simultaneously fusing inertial measurement unit data and improving position estimation accuracy through a complementary filtering algorithm; S200 includes: determining a position error based on the current position and a preset target position, and calculating an error change rate; S300 includes: decomposing the position error to obtain a first translation error, a second translation error, and a third translation error, where the first translation error is a component of the position error in the X-axis direction, the second translation error is a component of the position error in the Y-axis direction, and the third translation error is a component of the position error in the Z-axis direction; and simultaneously calculating first-order derivatives and second-order derivatives of the errors of each axis; S400 includes: controlling a propeller and an inclination motor according to the first translation error, the second translation error, and the third translation error to adjust the robot from a current position to a preset target position; S500 includes: establishing an energy consumption model based on the current thruster operating status and remaining battery power; dynamically adjusting control parameters according to mission priority; and optimizing the thrust distribution strategy to minimize the system's energy consumption while meeting control accuracy requirements.

7. The method according to claim 5, characterized in that When the underwater robot is in a hovering state, S100 includes: using an inertial measurement unit to monitor a current posture of the underwater robot in the hovering state; S200 includes: determining a posture error according to the current posture and a preset target posture; S300 includes: using the robot body coordinate system, decomposing the posture error to obtain a first angle error, a second angle error, and a third angle error, wherein the first angle error is a component of the posture error on the XoY plane, the second angle error is a component of the posture error on the YoZ plane, and the third angle error is a component of the posture error on the XoZ plane; S400 includes: controlling a thruster according to the first angle error, the second angle error, and the third angle error to adjust the robot from a current posture to a preset target posture; S500 includes: establishing an energy consumption model based on the current thruster operating status and remaining battery power; dynamically adjusting control parameters according to mission priority; and optimizing the thrust distribution strategy to minimize the system's energy consumption while meeting control accuracy requirements.

8. The method according to claim 6, characterized in that When the underwater robot performs a target task, S400 includes: S410: Calculate the velocity errors in the X, Y, and Z axes based on the first, second, and third translation errors; derive the corresponding acceleration errors based on the velocity errors of each axis; establish a system model based on the acceleration errors to determine the required thrust compensation for the propeller and the tilt compensation for the tilt motor; introduce integral and differential terms to enhance control accuracy, and estimate external disturbances using a disturbance observer; S420: Based on a preset error convergence strategy, the current translation error, velocity error, and acceleration error are matched with the target dynamic response characteristics to generate velocity error compensation terms and acceleration error compensation terms; a feedforward control term and an adaptive control term are added, and the control coefficient is dynamically adjusted according to the system state; S430: Correcting the actual speed using the speed error compensation term and correcting the actual acceleration using the acceleration error compensation term; converting the corrected acceleration error into an inclination control command and a thrust control command using a system mathematical model; S440: Iterate the process from S420 to S430 until all the control variables for the X, Y, and Z axes are calculated. The disturbance estimate and control parameters are updated in each iteration to ensure system convergence. S450: Drive the corresponding tilt motor according to the generated tilt control instruction, and adjust the thruster output according to the thrust control instruction to achieve the adjustment of the robot from the current position to the preset target position; when the current tilt value or thrust control amount exceeds the preset threshold, control the tilt motor and thruster to stop running.

9. The method according to claim 8, characterized in that S420 specifically: yes v =k1e p -v r Among them, e v is the target speed error, e p is the target translation, v r is the true speed, k1 is the coefficient; e a =k2e v +k3∫0 t e v d(t)-a r +d est Among them, e a is the target acceleration error, e v is the target speed error, a r is the acceleration, d est is the disturbance estimate, is the acceleration error at the previous moment, is the acceleration error predicted by the model, k2 is the coefficient, k3 is the coefficient, and k4 is the coefficient; u ff =m·a ref u adapt =γ·sign(e a )·|and a | α Among them, u is the three-axis control rate, e a is the target acceleration error, a r is the acceleration, u ff is the feedforward control term, u adapt is the adaptive control item, m is the robot mass, a ref is the reference acceleration, γ is the adaptive gain, α is the exponential coefficient, k5 is the coefficient, and k6 is the coefficient; S430 specifically: Among them, θ is the tilt angle control value of the four tilt motors, W is the net buoyancy of the robot in water, u x 、u y 、u z is the three-axis virtual force, and t1, t2, t3, and t4 are the control inputs of the four thrusters.

10. The method according to claim 9, characterized in that When the underwater robot performs a target mission, S500 includes: S510: Establishing a propeller energy consumption model to calculate the real-time power consumption of each propeller and the total power consumption of the system; S520: Construct a multi-objective optimization function that comprehensively considers control performance and energy consumption, and balances the relationship between control accuracy, response speed, and energy consumption; S530: Execute a thrust redistribution optimization algorithm based on the propeller efficiency curve and the current operating point; S540: Implement a hierarchical energy management strategy based on the remaining battery power and mission requirements.

11. The method according to claim 10, characterized in that S510 specifically: Among them, P i is the i-th thruster power, T i is the thrust, ω i is the speed, c1, c2, c3 are the power coefficients, and P0 is the basic power consumption; S520 specifically: J opt =w1·||e p || 2 +w2·‖e v ‖ 2 +w3·P total +w4·∑‖ΔT‖ 2 Among them, w1 to w4 are adjustable weight coefficients, which are dynamically adjusted according to the remaining battery capacity SOC: w3=w 3,base ·(1+k soc ·e -SOC / 30 ) Among them, w 3,base is the benchmark value of energy consumption weight, k soc is the energy sensitivity coefficient; when the power is reduced, the energy consumption weight w3 is automatically increased, giving priority to energy saving; S530 specifically: Perform thrust optimization based on thruster efficiency characteristics: Establish the propeller efficiency-operating point mapping relationship η i (T i ,ω i ), under the premise of meeting the total thrust demand, solve the thrust distribution scheme that minimizes the total power consumption: subject to:B·T=τ required T min ≤T i ≤T max Where B is the thrust distribution matrix, which describes the mapping relationship between the thrust of the propeller and the force / torque of the robot's six degrees of freedom; T = [T1, T2, T3, T4] T is the thrust vector of the four thrusters; τ required is the desired six-degree-of-freedom control force / torque inward; T min and T max are the lower and upper limits of the thruster respectively; η i is the efficiency of the i-th propeller at the current working point; When the system is in low thrust demand, the minimum thruster combination is selected and redundant thrusters are turned off to reduce no-load loss; S540 specifically: Implement a hierarchical energy management strategy: When the SOC > 60%, it is in the normal mode and operates at full performance. When 30% < SOC ≤ 60%, it is in the energy-saving mode, and in this mode, the control gain is reduced to 80% and the thrust is limited to 85%. When SOC ≤ 30%, it is in the emergency mode, and in this mode, the control gain is reduced to 60% and the thrust is limited to 60%, and non-essential devices are turned off. When the battery power is lower than the preset safety threshold, it automatically switches to the energy-saving return mode to ensure the robot's safe return first. The power budget is dynamically adjusted according to the task priority and the remaining flight distance to ensure the completion of critical tasks or a safe return.

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