An underwater motion control system for a bionic fish robot

Abstract

The present invention discloses an underwater motion control system for a bionic fish robot. The present invention relates to the technical field of underwater robot motion control, and solves the technical problems of incomplete perception, inflexible control, and non-optimized energy efficiency of existing underwater robots in complex environments. The present invention realizes the synchronous measurement of the flow velocity vector and turbulence intensity in the underwater environment, establishes a quantization classification standard based on the flow velocity amplitude and turbulence intensity, realizes the accurate identification of complex flow fields, provides a clear input for subsequent control strategies, adjusts the propulsion efficiency in real time according to the environmental state, combines power integration and real-time efficiency calculation, triggers parameter optimization or mode switching, and avoids control lag caused by fixed thresholds. Through the dual-threshold judgment of the obstacle distance and the preset distance, the intelligent switching of the obstacle avoidance strategy is realized. The close-range threat triggers the repulsive force enhancement algorithm, and the medium and long distances adopt the inertial navigation correction algorithm. The turbulence intensity and relative flow velocity are incorporated into the obstacle avoidance model to improve the overall obstacle avoidance probability.

Description

Technical Field

[0001] The present invention relates to the technical field of underwater motion control of robots, and specifically to an underwater motion control system for a bionic fish robot. Background Art

[0002] Currently, autonomous underwater robots are usually designed as near-buoyancy neutral bodies with low speeds. However, with the demands in aspects such as maritime search and rescue, rapid underwater environment assessment, response to major emergencies such as major marine environmental pollution, and deep-sea resource development.

[0003] According to the patent application with the publication number CN118112918A, a method for controlling the motion of an autonomous underwater robot is disclosed, including the following steps: First, collect the depth, pitch angle, and rudder angle of a variable-speed variable-load autonomous underwater robot through different sensors, and use the pitch angle error signal, the differential signal of the pitch angle error, and the desired rudder angle signal output by the depth-pitch cascade controller to construct an improved Hebb learning rule; Second, design a depth-pitch cascade control method to achieve closed-loop control of depth and pitch angle, and calculate the required rudder force for closed-loop motion control; Finally, complete the motion control of the autonomous underwater robot by calculating the action effect of the bow and stern horizontal rudders and performing rudder angle allocation on them.

[0004] However, when the existing underwater robot motion control system is in use, traditional single sensors are difficult to obtain the three-dimensional flow velocity field and turbulence intensity in real time and accurately, resulting in the inability to accurately identify the environmental state, and the lack of a propulsion parameter adjustment mechanism linked to environmental parameters, causing low energy utilization efficiency of the fixed-frequency drive mode in different flow fields. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the present invention provides an underwater motion control system for a bionic fish robot, which solves the problems of incomplete perception, inflexible control, and non-optimized energy efficiency of existing underwater robots in complex environments.

[0006] To achieve the above objectives, the present invention is realized through the following technical solutions: An underwater motion control system for a bionic fish robot, including:

[0007] An underwater environmental state recognition unit, which analyzes the obtained underwater environmental parameters, calculates the corresponding environmental flow velocity and turbulence intensity, generates environmental state information according to the environmental state classification standard, and transmits it to the robot propulsion efficiency analysis unit at the same time;

[0008] A robot propulsion efficiency analysis unit, which is used to obtain environmental state information and determine the propulsion efficiency threshold, calculate the real-time propulsion efficiency of the robot, compare the two, generate propulsion efficiency optimization information or motion control information, and transmit them respectively at the same time;

[0009] A robot motion control unit is used to analyze the acquired motion control information, identify obstacles on the motion route, generate obstacle avoidance signals, and then compare the distance between the obstacle and the preset distance to generate a repulsive force increase signal or an inertial navigation correction signal;

[0010] Analyze the inertial navigation correction signal, determine the tangent angle and the original angle between the robot and the obstacle, sum the two to obtain the correction angle, generate angle correction information, analyze the repulsive force increase signal, calculate and increase the repulsive force to generate repulsive force increase information, and transmit it to the robot control information display unit;

[0011] A propulsion efficiency optimization control unit is used to analyze the acquired propulsion efficiency optimization information, calculate the relative flow velocity and further obtain the Reynolds number, correct the drag coefficient of the robot at the same time, calculate the corresponding drag, calculate the increased drag and thrust compensation in combination with the turbulence intensity, calculate the adjusted power at the same time, generate propulsion efficiency optimization information, and transmit it to the robot control information display unit.

[0012] As a further solution of the present invention, it further includes a robot control information display unit, which is used to transmit the acquired angle correction information, repulsive force increase information, and propulsion efficiency optimization information to the corresponding control terminal, and generate a control instruction through the control terminal to control the robot.

[0013] As a further solution of the present invention, the specific way for the underwater environment state recognition unit to generate environment state information is:

[0014] The robot obtains the underwater environment flow velocity Ue through a Doppler current meter, collects the instantaneous flow velocity signal u(t) using a hot wire probe, and calculates the average flow velocity and the root mean square of the pulsating velocity , where T is the sampling time, and calculates the turbulence intensity I of the underwater environment according to the formula ;

[0015] Determine the obtained environmental flow velocity Ue and turbulence intensity I according to the comprehensive environmental state classification standard, and generate environmental state information.

[0016] As a further solution of the present invention, the specific way for the robot propulsion efficiency analysis unit to generate propulsion efficiency optimization information or motion control information is:

[0017] Real-time monitor the voltage U 电 and current I 电 of the drive motor through a wattmeter, and calculate the total power P according to the formula 电 = U 电 × I 电, integrate the battery discharge curve or the change in capacitance energy to obtain the total input energy within time t, denoted as E 总 , according to the formula P 总 = E 总 / t to calculate the total input efficiency P of the robot 总 , where t is the discharge time, and then according to the formula calculate the real-time propulsion efficiency, determine the propulsion efficiency threshold based on the environmental state information, and compare it with the total input efficiency P 总 ;

[0018] If < the propulsion efficiency threshold, generate propulsion efficiency optimization information and transmit it to the propulsion efficiency optimization control unit. If > the propulsion efficiency threshold, generate motion control information and transmit it to the robot motion control unit.

[0019] As a further solution of the present invention, the specific manner in which the robot motion control unit analyzes the obtained motion control information is as follows:

[0020] The robot obtains the motion route, identifies it with the help of an underwater high-definition camera and lidar, and determines whether there are obstacles on the route. If there are, generate an obstacle avoidance signal. If not, generate normal monitoring information and transmit it to the display unit;

[0021] Analyze the obstacle avoidance signal, obtain the obstacle distance D1, and compare it with the preset distance Dy set by the operator. If D1 < Dy, generate a repulsive force increase signal. If D1 > Dy, generate an inertial navigation correction signal.

[0022] As a further solution of the present invention, the specific manner in which the robot motion control unit analyzes the inertial navigation correction signal is as follows:

[0023] Obtain the obstacle position and establish a spatial coordinate system, determine its coordinates, draw a line connecting the robot as the starting point and the obstacle as the ending point, calculate the original angle between the line and the coordinate system, and the tangent angle between the robot and the obstacle. The sum of the two is used as the correction angle, and accordingly, perform navigation correction and generate angle correction information and transmit it to the display unit.

[0024] As a further solution of the present invention, the specific manner in which the robot motion control unit analyzes the repulsive force increase signal is as follows:

[0025] According to the formula calculate the increased repulsive force F rep , where F rep is the repulsive force coefficient, is the vector of D1. Based on the calculated increased repulsive force as the standard, generate repulsive force increase information and transmit it to the robot control information display unit.

[0026] As a further solution of the present invention, the specific manner in which the propulsion efficiency optimization control unit analyzes the obtained propulsion efficiency optimization information is as follows:

[0027] Obtain the environmental flow velocity Ue, the turbulence intensity I, and the fluid density , and at the same time obtain the robot parameters, specifically including the flow-facing area A, the propulsion velocity V, the drag coefficient Cd, the propulsion coefficient C T and the input power P in , the transmission efficiency and the motor efficiency . Then, according to the formula calculate the relative flow velocity U rel . At the same time, according to the formula calculate the Reynolds number, where is the fluid dynamic viscosity and L is the characteristic length of the robot.

[0028] As a further solution of the present invention, the specific manner in which the propulsion efficiency optimization control unit generates the propulsion efficiency optimization information is as follows:

[0029] According to the formula correct the drag coefficient, where C d0 is the drag coefficient under no turbulence or low turbulence intensity, and k is an empirical constant related to the object shape and flow regime. And according to the formula calculate the drag force F of the water flow on the robot d , and this drag force is opposite to the movement direction of the robot. Then calculate the increased drag force caused by the turbulence intensity I, and calculate the increased drag force according to the formula , where is the compensation coefficient. Further, according to the obtained increased drag force calculate the thrust compensation, and calculate the thrust compensation according to the formula . At the same time, according to the formula calculate the adjusted power ;

[0030] Generate the propulsion efficiency optimization information based on the thrust compensation and the adjusted power, and transmit it to the robot control information display unit.

[0031] The present invention provides an underwater motion control system for a bionic fish robot. Compared with the prior art, it has the following beneficial effects:

[0032] ​​The present invention realizes the synchronous measurement of the velocity vector and the turbulence intensity in the underwater environment by using an acoustic Doppler velocimeter (ADV) and a hot-wire probe in cooperation, improves the overall measurement accuracy, establishes a quantitative classification standard based on the velocity amplitude and the turbulence intensity, realizes the accurate identification of complex flow fields, provides clear inputs for subsequent control strategies, adjusts the propulsion efficiency target in real time according to the environmental state, combines power integration and real-time efficiency calculation, triggers parameter optimization or mode switching, and avoids control lag caused by fixed thresholds.

[0033] The present invention realizes the intelligent switching of the obstacle avoidance strategy through the dual-threshold judgment of the obstacle distance and the preset distance. The close-range threat triggers the repulsive force enhancement algorithm, and the medium and long distances adopt the inertial navigation correction algorithm. The turbulence intensity and the relative velocity are incorporated into the obstacle avoidance model to improve the overall obstacle avoidance probability. Brief Description of the Drawings

[0034] Figure 1 It is a block diagram of the control system principle of the present invention. Detailed Embodiments

[0035] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention. Embodiment 1

[0036] Please refer to Figure 1 , this application provides an underwater motion control system for a bionic fish robot, including an underwater environmental state recognition unit, a robot propulsion efficiency analysis unit, a propulsion efficiency optimization control unit, a robot operation control unit, and a robot control information display unit, and in combination with Figure 1 It can be known that the above functional units are unidirectionally electrically connected.

[0037] The underwater environmental state recognition unit is used to obtain underwater environmental parameters, identify the current underwater environmental state according to the underwater environmental parameters, generate environmental state information, and transmit it to the robot propulsion efficiency analysis unit at the same time. The specific recognition method is as follows:

[0038] A compact three-dimensional acoustic Doppler velocimeter (such as Nortek Vectrino+) is installed in the streamlined fairing of the robot head, with a measurement range of 0 to 5 m / s and an accuracy of ±1% reading + 1 mm / s, and can output the environmental velocity vector Ue in real time ;

[0039] Select a micro constant temperature hot wire probe (such as TSI1261 type, probe diameter 50μm), integrated on the surface of the robot's flank (0.3L from the head, L is the body length), to avoid the influence of body flow disturbance. At the same time, determine the sampling strategy, where the sampling strategy includes sampling frequency and sampling time, and the sampling frequency f s = 1000Hz, and the sampling time T = 10s;

[0040] Then, perform denoising processing on the instantaneous flow velocity signal u(t) collected by the hot wire, including low-pass filtering and trend term removal, as follows:

[0041] Low-pass filtering: Use a Butterworth filter with a cut-off frequency f c = 400Hz to eliminate high-frequency electronic noise;

[0042] Trend term removal: Eliminate the DC drift through polynomial fitting (such as a 5th-degree polynomial) to obtain the pulsating signal , where is the average flow velocity, and the specific calculation formula ;

[0043] Then, calculate the turbulence characteristic parameters, as follows:

[0044] ;

[0045] And is not equal to 0. At the same time, when < 0.01m / s, the turbulence intensity is calculated with the denominator of 0.01;

[0046] Establish a two-dimensional classification system based on the flow velocity amplitude |Ue| and the turbulence intensity I, as shown in the following table:

[0047] ;

[0048] And compare the calculated environmental flow velocity and turbulence intensity with it to determine the environmental state, and generate environmental state information. Then, transmit it to the robot propulsion efficiency analysis unit.

[0049] The robot propulsion efficiency analysis unit is used to set the propulsion efficiency threshold according to the obtained environmental state information, and at the same time compare the real-time propulsion efficiency of the robot with it and transmit it to the robot motion control unit. The specific analysis method is as follows:

[0050] The voltage U of the motor is monitored in real time by a power meter 电 and the current I 电 , and calculate the instantaneous power P 电 = U 电 × I 电, integrate the battery discharge curve or the change in capacitance energy to obtain the cumulative input energy within a period of time T. , and at the same time, according to the formula P 总 = E_total / t to calculate the total input efficiency;

[0051] It is defined as the ratio of the useful power of the propulsion system (the power to overcome resistance) to the total input power: , calculate the real-time propulsion efficiency according to the formula , where F 推 is the robot propulsion force, V is the robot speed. Specifically, the calculation method of the propulsion force is , where is the density of water, A jet is the wake jet area, V 2 jet is the water flow velocity. Based on the environmental state (such as flow velocity, turbulence intensity), preset the target efficiency value (for example, static water environment threshold = 60%, turbulent environment threshold = 45%), and compare the two;

[0052] If the real-time propulsion efficiency is greater than the propulsion efficiency threshold, generate propulsion efficiency optimization information, otherwise generate motion control information.

[0053] The robot motion control unit first deeply analyzes the obtained motion control information. By integrating the data of the underwater high-definition camera and the lidar, accurately obtain the motion route of the robot. These two sensors cooperate with each other. The underwater high-definition camera is responsible for obtaining visual image information, and the lidar uses the principle of laser ranging to provide accurate distance data.

[0054] During the process of identifying the motion route, the system will judge whether there are obstacles on this route. If an obstacle is detected, the motion control unit will immediately generate an obstacle avoidance signal; if no obstacle is detected, it will generate normal monitoring information and transmit it to the robot control information display unit so that the operator can understand the running state of the robot in real time.

[0055] After generating the obstacle avoidance signal, the motion control unit further analyzes and processes it to obtain detailed obstacle information. This information covers key parameters such as the position, shape, and distance of the obstacle. Among them, the obstacle position is determined by sensor data fusion and spatial positioning algorithms; the shape can be identified by using image processing and point cloud data processing technologies; the distance is directly measured by ranging sensors such as lidar.

[0056] After obtaining the obstacle distance D1, the system compares it with the preset distance Dy set by the operator. If D1 < Dy, it indicates that the obstacle is relatively close and there is a risk of collision. At this time, the motion control unit generates a repulsive force increase signal. If D1 > Dy, an inertial navigation correction signal is generated. Next, these two signals will be analyzed in depth respectively.

[0057] When receiving the inertial navigation correction signal, the motion control unit first extracts the position information of the obstacle and establishes a corresponding spatial coordinate system based on this. Through precise coordinate calculation methods, the position coordinates of the obstacle in this coordinate system are determined.

[0058] Subsequently, a connection line is determined with the current position of the robot as the starting point and the position of the obstacle as the end point. Through geometric calculation methods such as trigonometric functions, the angles between this connection line and the coordinate axes of the spatial coordinate system are obtained, denoted as the original angles. At the same time, the tangent angle between the robot and the obstacle is calculated. The sum of the tangent angle and the original angle is denoted as the correction angle.

[0059] Based on the correction angle, the motion control unit corrects the navigation of the robot and generates angle correction information, which is finally transmitted to the robot control information display unit to provide relevant data for navigation correction to the operator.

[0060] When analyzing the repulsive force increase signal, the motion control unit calculates the increased repulsive force F according to a specific repulsive force calculation formula where F rep is the repulsive force coefficient, rep is the vector of D1, which represents the rate of change and the direction of change of the distance D1 in space. The direction is from the robot to the obstacle, used to determine the direction of the repulsive force. At the same time, taking the calculated increased repulsive force as the standard, repulsive force increase information is generated and transmitted to the robot control information display unit. The robot control information display unit is used to perform corresponding control on the robot according to the obtained angle correction information and repulsive force increase information.

[0061] The robot control information display unit is used to perform corresponding control on the robot according to the obtained angle correction information and repulsive force increase information. Embodiment 2

[0062] As Embodiment 2 of the present invention, it is implemented on the basis of Embodiment 1, and the differences from Embodiment 1 are as follows:

[0063] The propulsion efficiency optimization control unit is used to analyze the obtained propulsion efficiency optimization information. By analyzing the current underwater environmental state and combining with the current real-time propulsion efficiency of the robot for comprehensive analysis and adjustment, and the specific adjustment method is as follows:

[0064] Obtain the environmental flow velocity Ue, the turbulence intensity I, and the fluid density , while obtaining the robot parameters, specifically including the flow area A, the propulsion speed V, the drag coefficient Cd, and the propulsion coefficient C T and the input power P in , the transmission efficiency and the motor efficiency . Then, according to the formula calculate the relative flow velocity U rel , and here it represents the calculation method when the directions of the two are the same. If the directions are opposite, the relative flow velocity . If there is an included angle , vector synthesis is required, . At the same time, according to the formula calculate the Reynolds number, where is the hydrodynamic viscosity of the fluid, and L is the characteristic length of the robot;

[0065] Then, according to the formula correct the drag coefficient, where C d0 is the drag coefficient under no turbulence or low turbulence intensity, and k is an empirical constant related to the shape of the object and the flow regime. And according to the formula calculate the drag force F of the water flow on the robot d , and this drag force is opposite to the movement direction of the robot. Then calculate the additional drag force caused by the turbulence intensity I. According to the formula calculate the additional drag force , where is the compensation coefficient, and the specific value is set according to the actual situation. Further, according to the obtained additional drag force calculate the thrust compensation. According to the formula calculate the thrust compensation . At the same time, according to the formula calculate the adjusted power ;

[0066] Generate propulsion efficiency optimization information based on the thrust compensation and the adjusted power, and transmit it to the robot control information display unit.

[0067] The robot control information display unit is used to adjust the robot according to the obtained propulsion efficiency optimization information.

[0068] Example 3. As the third example of the present invention, the key lies in combining the implementation processes of Example 1 and Example 2.

[0069] For some data in the above formulas, only their numerical values are taken for calculation, and the parameter units are not substituted for calculation. At the same time, the content not described in detail in this specification belongs to the prior art well-known to those skilled in the art.

[0070] The above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An underwater motion control system for a bionic fish robot, characterized in that, Including: An underwater environment state recognition unit, which analyzes the acquired underwater environment parameters, calculates the corresponding environmental flow velocity and turbulence intensity, generates environmental state information according to the environmental state classification standard, and transmits it to the robot propulsion efficiency analysis unit at the same time; A robot propulsion efficiency analysis unit, which is used to obtain environmental state information and determine the propulsion efficiency threshold, calculate the real-time propulsion efficiency of the robot, compare the two, generate propulsion efficiency optimization information or motion control information, and transmit the two respectively; A robot motion control unit, which analyzes the acquired motion control information, identifies obstacles on the motion route, generates an obstacle avoidance signal, and then compares the distance between the obstacle and the preset distance to generate a repulsive force increase signal or an inertial navigation correction signal; Analyze the inertial navigation correction signal, determine the tangent angle and the original angle between the robot and the obstacle, sum the two to obtain the correction angle, generate angle correction information, analyze the repulsive force increase signal, calculate the increased repulsive force to generate repulsive force increase information, and transmit it to the robot control information display unit; A propulsion efficiency optimization control unit, which analyzes the acquired propulsion efficiency optimization information, calculates the relative flow velocity and further obtains the Reynolds number, corrects the drag coefficient of the robot at the same time, calculates the corresponding drag, calculates the increased drag and thrust compensation in combination with the turbulence intensity, calculates the adjusted power at the same time, generates propulsion efficiency optimization information, and transmits it to the robot control information display unit.

2. The underwater motion control system of a bionic fish robot according to claim 1, characterized in that, It also includes a robot control information display unit, which is used to transmit the acquired angle correction information, repulsive force increase information and propulsion efficiency optimization information to the corresponding control terminal, and generate a control instruction through the control terminal to control the robot.

3. The underwater motion control system of a bionic fish robot according to claim 1, characterized in that The specific way for the underwater environment state recognition unit to generate environmental state information is: The robot obtains the underwater environmental flow velocity Ue through a Doppler current meter, uses a hot-wire probe to collect the instantaneous flow velocity signal u(t), and calculates the average flow velocity and the root mean square of the pulsating velocity , where T is the sampling time, and calculates the turbulence intensity I of the underwater environment according to the formula ; Determine the obtained environmental flow velocity Ue and turbulence intensity I according to the comprehensive environmental state classification standard, and generate environmental state information.

4. The underwater motion control system of a bionic fish robot according to claim 1, characterized in that, The specific way for the robot propulsion efficiency analysis unit to generate propulsion efficiency optimization information or motion control information is: Monitor the voltage U of the drive motor in real time through a power meter 电 and current I 电 , and calculate the total power P according to the formula 电 =U 电 ×I 电 , integrate the battery discharge curve or the change in capacitor energy to obtain the total input energy within time t, denoted as E 总 , according to the formula P 总 =E 总 / t to calculate the total input efficiency P of the robot 总 , where t is the discharge time, and then calculate the real-time propulsion efficiency according to the formula , F 推 is the propulsion force of the robot, V is the speed of the robot, determine the propulsion efficiency threshold based on the environmental state information, and compare it with the total input efficiency P 总 ; If < the propulsion efficiency threshold, propulsion efficiency optimization information is generated and transmitted to the propulsion efficiency optimization control unit. If > the propulsion efficiency threshold, motion control information is generated and transmitted to the robot motion control unit.

5. The underwater motion control system of a bionic fish robot according to claim 1, characterized in that, The specific way for the robot motion control unit to analyze the acquired motion control information is: The robot obtains the motion route, identifies it with the help of an underwater high-definition camera and lidar, judges whether there are obstacles on the route. If there are, it generates an obstacle avoidance signal. If not, it generates normal monitoring information and transmits it to the display unit; Analyze the obstacle avoidance signal, obtain the obstacle distance D1, compare it with the preset distance Dy set by the operator. If D1 < Dy, generate a repulsive force increase signal. If D1 > Dy, generate an inertial navigation correction signal.

6. The underwater motion control system of a bionic fish robot according to claim 1, characterized in that The specific way for the robot motion control unit to analyze the inertial navigation correction signal is: Obtain the obstacle position and establish a spatial coordinate system, determine its coordinates, draw a line connecting the robot as the starting point and the obstacle as the ending point, calculate the original angle between the line and the coordinate system, and the tangent angle between the robot and the obstacle. The sum of the two is used as the correction angle, and the navigation is corrected accordingly and the angle correction information is generated and transmitted to the display unit.

7. The underwater motion control system of a bionic fish robot according to claim 5, characterized in that, The specific way for the robot motion control unit to analyze the repulsive force increasing signal is as follows: According to the formula the increased repulsive force F is calculated rep , where F rep is the repulsive force coefficient, is the vector of D1. Taking the calculated increased repulsive force as the standard, repulsive force increase information is generated and transmitted to the robot control information display unit.

8. The underwater motion control system of a bionic fish robot according to claim 1, characterized in that, The specific way for the propulsion efficiency optimization control unit to analyze the obtained propulsion efficiency optimization information is as follows: Obtain the environmental flow velocity Ue, the turbulence intensity I, and the fluid density , and at the same time obtain the robot parameters, specifically including the cross-sectional area A facing the flow, the propulsion velocity V, the drag coefficient Cd, the propulsion coefficient C T , and the input power P in , the transmission efficiency , and the motor efficiency . Then, according to the formula , calculate the relative flow velocity U rel . At the same time, according to the formula , calculate the Reynolds number, where is the dynamic viscosity of the fluid, and L is the characteristic length of the robot 9. The underwater motion control system of a bionic fish robot according to claim 8, characterized in that, The specific way for the propulsion efficiency optimization control unit to generate the propulsion efficiency optimization information is as follows: According to the formula correct the drag coefficient, where C d0 is the drag coefficient under no turbulence or low turbulence intensity, k is an empirical constant related to the shape of the object and the flow regime, and according to the formula calculate the drag force F of the water flow on the robot d , and this drag force is opposite to the moving direction of the robot. Then calculate the additional drag force caused by the turbulence intensity I. According to the formula calculate the obtained additional drag force , where is the compensation coefficient. Further, according to the obtained additional drag force calculate the thrust compensation. According to the formula calculate the obtained thrust compensation , and at the same time, according to the formula calculate the adjusted power ; Generate the propulsion efficiency optimization information based on thrust compensation and adjusted power, and transmit it to the robot control information display unit.

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