A self-moving water depth maintenance robot

Abstract

The present invention relates to the field of navigation technology, and discloses a self-moving water depth maintenance robot. On the basis of the existing sound velocity value, multiple environmental factors such as real-time temperature, real-time salinity and real-time pressure are further introduced to dynamically correct the original sound velocity value, thereby significantly improving the accuracy and reliability of three-dimensional coordinate conversion. By calculating the real-time depth value based on the corrected sound velocity, and combining the current speed, current acceleration, real-time temperature and real-time pressure of the robot, a maximum allowable depth change rate is studied, thereby significantly improving the safety and efficiency of the robot's autonomous navigation in a complex underwater environment.

Description

Technical Field

[0001] The invention relates to the field of navigation technology, and in particular to a self-moving water depth maintenance robot. Background Art

[0002] The traditional way of maintaining the depth of port channels is mainly to use dredgers to clear the silt. As the distance of mud dumping increases to dozens of kilometers, the cost of clearing the silt increases sharply. In addition, there are problems such as low efficiency, high cost, and environmental pollution. The basic idea of ​​the intelligent guarantee technology for the depth of port channels based on natural power is to increase the turbulent energy of the water body through artificial disturbance, compensate for the reduction of the water flow carrying capacity caused by the excavation of the port channel or the water blocking of buildings, and then achieve the goal of maintaining the depth of the water body with "no sedimentation and natural balance". Compared with the traditional "regular dredging" dredging method, it has the following advantages: First, it uses natural water flow instead of long-distance transportation of dredgers, which significantly reduces the cost of water depth maintenance and carbon emissions; second, the disturbance is completed at the bottom of the water, which can achieve zero impact on ship operations; third, normalized disturbance avoids pollutant enrichment caused by sediment sedimentation and consolidation. The economic, social and ecological benefits are significant. In order to achieve the water depth maintenance of the port channel based on natural power and intelligent technology, a highly modular water depth maintenance robot is designed and developed, which has multiple functions such as sediment disturbance, transmission, water depth and obstacle monitoring; advanced waterproof sealing technology is developed and corrosion-resistant materials are selected; a long-distance cable retraction system is developed, combining high-strength cables with intelligent control algorithms to provide a stable power supply system for the equipment. However, the premise of water depth maintenance is the navigation of the water depth maintenance path, and water depth maintenance is achieved based on the navigation system. However, the existing navigation system has the following technical defects:

[0003] First, the sonar system of the traditional navigation system usually uses a fixed sound speed value to calculate the distance between the node and the robot, converts the distance into three-dimensional coordinates, and realizes navigation based on the three-dimensional coordinates. However, the sound speed in the actual ocean environment is affected by many factors, including temperature, salinity, pressure, and dissolved oxygen concentration. Existing systems rarely consider the impact of changes in these environmental variables on the sound speed, resulting in inaccurate sound speed correction, which in turn causes navigation deviation.

[0004] Secondly, traditional path planning algorithms usually rely on pre-built maps and fixed target points. In complex environments, the robot may deviate from the preset path, but due to the lack of a dynamic adjustment mechanism, the system cannot correct this deviation in time, causing the robot to easily get lost. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a self-moving water depth maintenance robot, including a navigation system for guiding the robot to move autonomously; the navigation system is composed of the following modules:

[0006] 3D sonar module: used to transmit and receive sound wave signals to the underwater environment and build a 3D model of the underwater environment based on the sound wave signals;

[0007] Inertial navigation module: It is arranged at the center of gravity of the robot and connected to the 3D sonar module to obtain the real-time position data and real-time attitude data of the robot in the 3D model, and update the real-time position data and real-time attitude data to the 3D model;

[0008] Depth measurement module: It consists of several directional probes evenly arranged at the bottom of the robot and connected to the 3D sonar module to calculate the real-time depth value of the underwater environment and update the real-time depth value to the 3D model.

[0009] It also includes: an autonomous mobile system; the autonomous mobile system is connected to the three-dimensional sonar module to generate a final path; according to the real-time position data, real-time posture data and real-time water depth value in the three-dimensional model, a maximum allowable depth change rate is obtained; the real-time depth value change of the shortest path is obtained, and the shortest path in which all real-time depth value changes are less than or equal to the maximum allowable depth change rate is used as the final path, and the robot moves autonomously on the final path.

[0010] Furthermore, the three-dimensional sonar module includes the following units:

[0011] The sound wave transmitting unit is arranged at the front end of the robot and covers the angle range of ±60° in front of the robot. The angle range of ±60° in front of the robot includes several nodes, which are used to transmit sound wave signals to each node in the angle range of ±60° in front of the robot;

[0012] Echo receiving unit: arranged at the front end of the robot and installed coaxially with the sound wave transmitting unit, used to receive the sound wave signal reflected to each node;

[0013] Three-dimensional coordinate generation unit: used to construct a three-dimensional reference coordinate system, calculate the distance between each node and the robot according to the sound wave signal reflected to each node, and convert the distance into three-dimensional node coordinates of the three-dimensional reference coordinate system;

[0014] 3D model building unit: used to build a 3D model according to 3D coordinates.

[0015] Furthermore, the three-dimensional coordinate generating unit includes the following subunits:

[0016] The time difference acquisition subunit is used to calculate the time difference of the sound wave signal of each node according to the sound wave signal emitted by each node and the sound wave signal reflected to each node;

[0017] Initial sound velocity presetting subunit: used to preset an initial sound velocity for the sound wave signal;

[0018] Initial temperature preset subunit: used to preset an initial temperature;

[0019] Sound velocity correction subunit: used to obtain the real-time temperature, real-time salinity, and real-time pressure of each node in real time, obtain the temperature influence value according to the real-time temperature and the initial temperature, obtain the salinity influence value according to the real-time salinity, and obtain the pressure influence value according to the real-time pressure; calculate and obtain the corrected sound velocity according to the initial sound velocity, temperature influence value, salinity influence value, and pressure influence value;

[0020] Node distance calculation subunit: used to calculate the distance between each node and the robot according to the time difference and the corrected sound speed, and generate three-dimensional coordinates based on the distance.

[0021] Furthermore, the autonomous mobile system includes the following modules:

[0022] Shortest path generation module: used to exploit The algorithm generates the shortest path, which is formed by connecting several consecutive three-dimensional coordinates;

[0023] Robot real-time speed and real-time acceleration acquisition module: used to obtain the real-time speed and real-time acceleration of the robot;

[0024] Maximum allowable depth change rate calculation module: used to calculate the maximum allowable depth change rate according to the real-time speed, real-time pressure, real-time temperature and real-time acceleration of the robot;

[0025] Adjacent node real-time depth value change calculation module: used to calculate the real-time depth value change between two adjacent nodes in the shortest path;

[0026] Path screening module: used to determine whether all real-time depth value changes in the shortest path are less than or equal to the maximum allowable depth change rate. If so, the shortest path is used as the final path; if not, a new path is regenerated and the real-time depth value changes between two adjacent nodes in the new path are calculated until all real-time depth value changes in the new path are less than or equal to the maximum allowable depth change rate, and the current new path is used as the final path.

[0027] Furthermore, the water depth measurement module includes the following units:

[0028] Real-time water depth value calculation unit: used to obtain the three-dimensional coordinates of the silt to be maintained at the bottom of the water, transmit and receive sound wave signals to the three-dimensional coordinates of the silt to be maintained, obtain the time difference, and calculate the real-time water depth value of each node based on the time difference and the corrected sound speed:

[0029] ;

[0030] In the formula, represents the real-time water depth value of the i-th node, represents the corrected sound speed of the ith node, Represents the time difference of the i-th node.

[0031] Further, for:

[0032] ;

[0033] In the formula, represents the initial sound speed, represents the temperature influence value of the i-th node, represents the salinity impact value of the ith node, Represents the pressure impact value of the i-th node.

[0034] Further, for:

[0035] ;

[0036] In the formula, represents the real-time temperature of the i-th node, represents the initial temperature, Represents the temperature difference between the real-time temperature and the initial temperature of the i-th node, The linear coefficient representing the temperature influence value, The quadratic coefficient representing the temperature effect, The exponential decay coefficient representing the temperature effect, Represents the exponential decay rate coefficient of the temperature effect value.

[0037] Further, for:

[0038] ;

[0039] In the formula, represents the real-time salinity of the ith node, The square root coefficient representing the salinity impact value, The periodic term coefficient representing the salinity impact value, The frequency coefficient of the periodic term representing the salinity impact value, The saturation effect coefficient representing the salinity impact value, The threshold coefficient of the saturation effect term representing the salinity impact value.

[0040] Further, for:

[0041] ;

[0042] In the formula, represents the real-time pressure of the ith node, The logarithmic coefficient representing the pressure influence value, The fractional coefficient representing the pressure influence value, The fractional threshold coefficient representing the pressure impact value, Represents the cube root coefficient of the pressure effect value.

[0043] Furthermore, the maximum allowable depth change rate is calculated as:

[0044] ;

[0045] In the formula, represents the maximum allowable depth change rate, Represents the current speed of the robot, Represents the current acceleration of the robot, represents the real-time pressure of the ith node, represents the real-time temperature of the i-th node, n represents the total number of nodes, i represents the number of nodes, represents the speed influence coefficient, represents the acceleration influence coefficient, represents the pressure index term coefficient, represents the pressure exponential decay rate coefficient, Represents the squared temperature coefficient.

[0046] The embodiments of the present invention have the following technical effects:

[0047] The present invention studies the selection and arrangement of a three-dimensional sonar module, an inertial navigation module, a water depth measurement module, and an autonomous mobile system to obtain an underwater high-precision autonomous navigation system to achieve route navigation for water depth maintenance.

[0048] The present invention further introduces multiple environmental factors such as real-time temperature, real-time salinity and real-time pressure on the basis of the existing sound speed value, and dynamically corrects the original sound speed value, thereby significantly improving the accuracy and reliability of three-dimensional coordinate conversion. Traditional sonar systems usually use fixed sound speed values ​​to calculate the distance between nodes and robots. This method is prone to large measurement errors in complex and changeable actual environments. In contrast, the correction method proposed in the present invention can adjust the sound speed parameters in real time according to changes in actual environmental conditions to ensure the high accuracy of the conversion results. Specifically, by obtaining the environmental parameters of each node and calculating the accurate corrected sound speed. In addition, based on these real-time data, the sound speed value of each node is dynamically adjusted, and then the distance between each node and the robot is calculated according to the time difference and the corrected sound speed, and converted into three-dimensional coordinates according to the distance. The navigation accuracy is improved, the measurement error is greatly reduced, and the robot can operate stably in a complex marine environment and accurately complete the water depth maintenance task. At the same time, the robot can plan the path more efficiently, avoid task failures caused by misjudgment of the terrain, thereby significantly improving the performance and reliability of the entire system.

[0049] The present invention calculates the real-time depth value based on the corrected sound velocity, and combines the robot's current speed, current acceleration, real-time temperature and real-time pressure to develop a maximum allowable depth change rate, thereby significantly improving the safety and efficiency of the robot's autonomous navigation in a complex underwater environment. Compared with the prior art, the maximum allowable depth change rate proposed by the present invention can dynamically calculate the maximum depth change rate that the robot can withstand under different conditions based on the robot's current speed and acceleration, combined with the temperature and pressure data acquired in real time. Specifically, by evaluating the real-time depth value of each node, it is determined whether it is within the maximum allowable depth change rate range, thereby ensuring that the robot will not cause task interruptions due to too rapid depth changes during the execution of the task. The risks caused by too rapid depth changes are greatly reduced, ensuring that the robot can operate stably in a complex and changeable marine environment and efficiently complete water depth maintenance tasks. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0051] Figure 1 It is a structural diagram of a self-moving deep water maintenance robot provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0053] Figure 1 is a structural diagram of a self-propelled water depth maintenance robot provided by an embodiment of the present invention. Figure 1 , specifically including a navigation system for guiding the robot to move autonomously; the navigation system is composed of the following modules:

[0054] 3D sonar module: used to transmit and receive sound wave signals to the underwater environment, and build a 3D model of the underwater environment based on the sound wave signals.

[0055] 3D sonar module, including the following units:

[0056] Sound wave transmitting unit: It is arranged at the front end of the robot and covers the angle range of ±60° in front. The angle range of ±60° in front of the robot includes several nodes, which are used to transmit sound wave signals to each node within the angle range of ±60° in front of the robot.

[0057] The sound wave transmitting unit is composed of multiple ultrasonic transducers, which can be distributed at the front end of the robot, and each transducer is responsible for the sound wave emission within a specific angle range. For example:

[0058] Ultrasonic transducer: It uses highly sensitive piezoelectric ceramic materials (such as PZT) and has high transmission power and frequency stability.

[0059] Array arrangement: Multiple transducers are arranged at a certain pitch to form an array to cover the front angle range of ±60°. Common arrangements include linear arrays or circular arrays.

[0060] Covering the angle range of ±60° in front, specifically means that the sound wave transmitting unit can cover the range from -60° to +60° in the horizontal direction in front of the robot. In other words, the sound wave can transmit sound wave signals 60 degrees to the left and 60 degrees to the right, forming a 120-degree fan-shaped area. This design can provide a wider field of view, ensuring that the robot can detect a wider range of environmental information during movement.

[0061] Echo receiving unit: arranged at the front end of the robot and installed coaxially with the sound wave transmitting unit, used to receive the sound wave signal reflected to each node.

[0062] The echo receiving unit is also composed of a plurality of ultrasonic transducers and is used for receiving the sound wave signal reflected to each node.

[0063] Three-dimensional coordinate generation unit: used to construct a three-dimensional reference coordinate system, calculate the distance between each node and the robot based on the sound wave signal reflected to each node, and convert the distance into three-dimensional node coordinates (x, y, z) of the three-dimensional reference coordinate system.

[0064] This embodiment generates the three-dimensional coordinates of each node by processing the reflected sound wave signal. The received echo signal is pre-processed by filtering, amplifying and other pre-processing operations to remove noise interference. The distance between each node and the robot is calculated based on the time difference between the transmitted and received signals. The above distance information is converted into a point in three-dimensional space to form a three-dimensional coordinate and updated to the three-dimensional reference coordinate system.

[0065] Furthermore, the distance between each node and the robot is calculated by the time difference and the speed of sound. Usually, the speed of sound is a fixed value: 1500 m / s. In this embodiment, the speed of sound is corrected to obtain a corrected speed of sound, and a more accurate three-dimensional coordinate is obtained based on the corrected speed of sound. Specifically:

[0066] The three-dimensional coordinate generation unit includes the following subunits:

[0067] The time difference acquisition subunit is used to calculate the time difference of the sound wave signal of each node according to the sound wave signal emitted by each node and the sound wave signal reflected to each node.

[0068] Initial sound velocity preset subunit: used to preset an initial sound velocity for the sound wave signal.

[0069] The initial sound velocity is 1500 m / s.

[0070] Initial temperature preset subunit: used to preset an initial temperature.

[0071] The temperature under standard seawater conditions is taken as the initial temperature.

[0072] Sound velocity correction subunit: used to obtain the real-time temperature, real-time salinity and real-time pressure of each node in real time, obtain the temperature influence value according to the real-time temperature and the initial temperature, obtain the salinity influence value according to the real-time salinity, and obtain the pressure influence value according to the real-time pressure; calculate and obtain the corrected sound velocity according to the initial sound velocity, temperature influence value, salinity influence value and pressure influence value.

[0073] ;

[0074] ;

[0075] ;

[0076] ;

[0077] In the formula, represents the initial sound speed, represents the temperature influence value of the i-th node, represents the salinity impact value of the ith node, represents the pressure impact value of the i-th node, represents the real-time temperature of the i-th node, represents the initial temperature, Represents the temperature difference between the real-time temperature and the initial temperature of the i-th node, The linear coefficient representing the temperature influence value, The quadratic coefficient representing the temperature effect, The exponential decay coefficient representing the temperature effect, represents the exponential decay rate coefficient of the temperature effect value, represents the real-time salinity of the ith node, The square root coefficient representing the salinity impact value, The periodic coefficient representing the salinity influence value, The frequency coefficient of the periodic term representing the salinity impact value, The saturation effect coefficient representing the salinity impact value, The threshold coefficient of the saturation effect term representing the salinity impact value, represents the real-time pressure of the ith node, The logarithmic coefficient representing the pressure influence value, The fractional coefficient representing the pressure influence value, The fractional threshold coefficient representing the pressure impact value, Represents the cube root coefficient of the pressure effect value.

[0078] in: , , , Under laboratory conditions, multiple experiments were carried out at different temperatures to record the changes in the physical quantity of the speed of sound. The linear regression method, polynomial regression method, and nonlinear regression method were used to fit the data and obtain , , , .

[0079] , , , , Under laboratory conditions, multiple experiments were conducted at different salinities to record the physical changes in the speed of sound. The data were fitted using regression analysis and nonlinear regression methods, respectively. , , , , .

[0080] , , , Under laboratory conditions, multiple experiments were conducted at different pressures to record the physical changes in the speed of sound. The data were fitted using regression analysis and nonlinear regression methods to obtain , , , .

[0081] Furthermore, temperature has a significant effect on the speed of sound, especially when it varies greatly at different depths and geographical locations. Salinity can also affect the speed of sound, especially in marine environments where salinity can vary greatly from region to region. Pressure reflects the depth of the water body and also has a significant effect on the speed of sound. Therefore, this embodiment takes into account real-time temperature, pressure, and salinity to correct the speed of sound. Specifically:

[0082] , this part is the linear effect of temperature on the speed of sound, which indicates the direct effect of temperature change on the speed of sound and provides the basic temperature-speed of sound relationship. , which is the quadratic term of temperature on the speed of sound. It is used to capture the nonlinear effect of temperature change on the speed of sound, describe the change law of the speed of sound in a large temperature range, and improve the accuracy of the speed of sound under extreme conditions. , this part is the exponential decay term of the temperature on the sound speed, which is used to simulate the phenomenon that the sound speed changes tend to be stable within the temperature range. When it is close to the reference temperature, the sound speed changes less; when it is far away from the reference temperature, the sound speed changes more. Through the organic combination of these three parts, not only can a wide temperature range from low temperature to high temperature be fully covered, but also the complex nonlinear effect of temperature on the sound speed can be captured, thereby providing high-precision temperature impact values ​​under different temperature conditions.

[0083] This part considers the effect of salinity on the speed of sound. The square root term indicates that the effect of salinity on the speed of sound increases gradually, but as the salinity increases, the growth rate of this effect will slow down. This part considers the periodic effect of salinity on the sound velocity. By introducing the sine function, the different effects of salinity on the sound velocity at different concentrations can be simulated. For example, in certain salinity ranges, the sound velocity change may be periodic. , which considers the saturation effect of salinity on the sound velocity. The fractional term indicates that when the salinity reaches a certain level, its effect on the sound velocity tends to be saturated and will no longer increase significantly. Through the organic combination of these three parts, the function can not only fully cover a wide range from low salinity to high salinity, but also capture the complex nonlinear effect of salinity on the sound velocity, thereby obtaining a high-precision impact value.

[0084] , which is the logarithmic effect of real-time pressure on the speed of sound. The logarithmic term indicates that the effect of real-time pressure on the speed of sound is more significant under low pressure conditions, while the effect gradually weakens under high pressure conditions. , which is the saturation effect of real-time pressure on the speed of sound. The fractional term indicates that when the real-time pressure reaches a certain level, its effect on the speed of sound tends to be saturated and will no longer increase significantly. , which is the cube root effect of real-time pressure on the speed of sound. The cube root term indicates that the effect of real-time pressure on the speed of sound still exists under high pressure conditions, but the growth rate is slower. Through the organic combination of these three parts, the function can not only fully cover a wide range of pressures from low pressure to high pressure, but also capture the complex nonlinear effect of real-time pressure on the speed of sound, thereby obtaining a more accurate impact value.

[0085] Among them, the straight-line distance between each node and the robot is :

[0086] .

[0087] represents the corrected sound speed of the ith node, Represents the time difference of the i-th node.

[0088] The robot's position is used as the origin of the three-dimensional coordinate system (x0, y0, z0), the direction pointing to the front of the robot is used as the X axis, the direction pointing to the right of the robot is used as the Y axis, and the direction pointing to the bottom of the robot is used as the Z axis. The origin of the three-dimensional coordinate system (x0, y0, z0) is used as the reference coordinate.

[0089] The azimuth angle refers to the angle from the reference direction (the direction in front of the robot) to the direction line projected by the node on the horizontal plane, measured in a clockwise direction.

[0090] First, calculate the projection of the node relative to the reference coordinate on the horizontal plane (i.e., the XY plane) :

[0091] ;

[0092] ;

[0093] Then, use the inverse tangent function (atan2) to calculate the azimuth :

[0094] ;

[0095] The pitch angle is the angle measured upward from the horizontal plane, which represents the change in the height of the node relative to the reference coordinates. First, calculate the vertical distance :

[0096] ;

[0097] Then, calculate the slope distance d:

[0098] ;

[0099] Finally, the pitch angle is calculated using the inverse sine function :

[0100] ;

[0101] Finally, the distance is converted into three-dimensional coordinates based on the elevation and azimuth angles:

[0102] ;

[0103] ;

[0104] ;

[0105] in, Represents the radial distance, that is, the straight-line distance between the origin (the robot's location) and the target point (the i-th node).

[0106] 3D model building unit: used to build a 3D model according to 3D coordinates.

[0107] Inertial navigation module: It is arranged at the center of gravity of the robot and connected to the three-dimensional sonar module. It is used to obtain the real-time position data and real-time attitude data of the robot in the three-dimensional model, and update the real-time position data and real-time attitude data to the three-dimensional model.

[0108] The inertial navigation module consists of an accelerometer and a gyroscope, and is used to obtain the real-time position data and attitude data of the robot in three-dimensional space. The accelerometer is used to measure the acceleration of the robot on three axes (X, Y, Z). By integrating the acceleration over time, the velocity of each axis is obtained, and the velocity is integrated over time again to obtain the displacement of each axis. The gyroscope is used to measure the angular velocity of the robot around the three axes (X, Y, Z), and the change in attitude angle is obtained by integrating the angular velocity over time.

[0109] Water depth measurement module: It consists of several directional probes, which are evenly arranged at the bottom of the robot and connected to the three-dimensional sonar module. It is used to calculate the real-time water depth value of the underwater environment and update the real-time water depth value to the three-dimensional model.

[0110] Depth measurement module, including the following units:

[0111] Real-time water depth value calculation unit: used to obtain the three-dimensional coordinates of the silt to be maintained on the bottom of the water, transmit and receive sound wave signals to the three-dimensional coordinates of the silt to be maintained, obtain the time difference, and calculate the real-time water depth value of each node based on the time difference and the corrected sound speed.

[0112] The calculation process of the time difference is the same as the principle of time difference calculation, except that the object of the sound wave signal is different.

[0113] ;

[0114] In the formula, represents the real-time water depth value of the i-th node, represents the corrected sound speed of the ith node, Represents the time difference of the i-th node.

[0115] This embodiment also includes: an autonomous mobile system; the autonomous mobile system is connected to the three-dimensional sonar module to generate a final path; according to the real-time position data, real-time posture data and real-time water depth value in the three-dimensional model, a maximum allowable depth change rate is obtained; the real-time depth value change of the shortest path is obtained, and the shortest path in which all real-time depth value changes are less than or equal to the maximum allowable depth change rate is used as the final path, and the robot moves autonomously on the final path.

[0116] Autonomous mobile system, including the following modules:

[0117] Shortest path generation module: used to generate the shortest path using the A* algorithm. The shortest path is formed by connecting several continuous three-dimensional coordinates.

[0118] Robot real-time speed and real-time acceleration acquisition module: used to obtain the robot's real-time speed and real-time acceleration through the inertial navigation module;

[0119] Maximum allowable depth change rate calculation module: used to calculate the maximum allowable depth change rate according to the real-time speed, real-time acceleration, real-time temperature and real-time pressure of the robot;

[0120] ;

[0121] In the formula, represents the maximum allowable depth change rate, Represents the current speed of the robot, Represents the current acceleration of the robot, represents the real-time pressure of the ith node, represents the real-time temperature of the i-th node, n represents the total number of nodes, i represents the number of nodes, represents the speed influence coefficient, represents the acceleration influence coefficient, represents the pressure index term coefficient, represents the pressure exponential decay rate coefficient, Represents the squared temperature coefficient.

[0122] in: Under laboratory conditions, by changing the speed of the robot and recording the change in the maximum allowable depth change rate, the influence of speed was fitted and obtained. ;

[0123] ,Under laboratory conditions, by changing the acceleration of the robot and recording the change in the maximum allowable depth change rate, the influence relationship of acceleration was fitted and obtained. ;

[0124] , Under laboratory conditions, by changing the pressure of the node and recording the change of the maximum allowable depth change rate, the influence relationship of pressure is fitted and obtained. , ;

[0125] Under laboratory conditions, by changing the temperature of the node and recording the change of the maximum allowable depth change rate, the temperature influence relationship is fitted and obtained. .

[0126] Furthermore, the above calculation formula takes into account physical quantities such as velocity, acceleration, temperature, and pressure. In the case of different physical meanings, each physical quantity needs to be normalized into a dimensionless value first, and then the maximum allowable depth change rate is obtained based on the dimensionless value multiplied by 100%.

[0127] The normalization method is the existing technology, and the mapping result of [0, 1] is obtained by the current physical quantity and the minimum and maximum values ​​of the current physical quantity, which will not be described in detail in this embodiment.

[0128] Adjacent node real-time depth value change calculation module: used to calculate the real-time depth value change between two adjacent nodes in the shortest path.

[0129] Path screening module: used to determine whether all real-time depth value changes in the shortest path are less than or equal to the maximum allowable depth change rate. If so, the shortest path is used as the final path; if not, a new path is regenerated and the real-time depth value changes between two adjacent nodes in the new path are calculated until all real-time depth value changes in the new path are less than or equal to the maximum allowable depth change rate, and the current new path is used as the final path.

Claims

1. A self-propelled water depth maintenance robot, characterized in that: A navigation system is included to guide the robot to move autonomously; the navigation system is composed of the following modules: 3D sonar module: used to transmit and receive sound wave signals to the underwater environment and build a 3D model of the underwater environment based on the sound wave signals; Inertial navigation module: It is arranged at the center of gravity of the robot and connected to the 3D sonar module to obtain the real-time position data and real-time attitude data of the robot in the 3D model, and update the real-time position data and real-time attitude data to the 3D model; Depth measurement module: It consists of several directional probes evenly arranged at the bottom of the robot and connected to the 3D sonar module to calculate the real-time depth value of the underwater environment and update the real-time depth value to the 3D model. It also includes: an autonomous mobile system; the autonomous mobile system is connected to the three-dimensional sonar module to generate a final path; according to the real-time position data, real-time posture data and real-time water depth value in the three-dimensional model, a maximum allowable depth change rate is obtained; the real-time depth value change amount of the shortest path is obtained, and the shortest path in which all real-time depth value changes are less than or equal to the maximum allowable depth change rate is taken as the final path, and the robot moves autonomously on the final path; The autonomous mobile system comprises the following modules: Shortest path generation module: used to generate the shortest path using the A* algorithm. The shortest path is formed by connecting several continuous three-dimensional coordinates. Robot real-time speed and real-time acceleration acquisition module: used to obtain the real-time speed and real-time acceleration of the robot; Maximum allowable depth change rate calculation module: used to calculate the maximum allowable depth change rate according to the real-time speed, real-time pressure, real-time temperature and real-time acceleration of the robot; Adjacent node real-time depth value change calculation module: used to calculate the real-time depth value change between two adjacent nodes in the shortest path; Path screening module: used to determine whether all real-time depth value changes in the shortest path are less than or equal to the maximum allowable depth change rate. If so, the shortest path is used as the final path; if not, a new path is regenerated and the real-time depth value changes between two adjacent nodes in the new path are calculated until all real-time depth value changes in the new path are less than or equal to the maximum allowable depth change rate, and the current new path is used as the final path.

2. A self-propelled deep water maintenance robot according to claim 1, characterized in that: 3D sonar module, including the following units: The sound wave transmitting unit is arranged at the front end of the robot and covers the angle range of ±60° in front of the robot. The angle range of ±60° in front of the robot includes several nodes, which are used to transmit sound wave signals to each node in the angle range of ±60° in front of the robot; Echo receiving unit: arranged at the front end of the robot and installed coaxially with the sound wave transmitting unit, used to receive the sound wave signal reflected to each node; Three-dimensional coordinate generation unit: used to construct a three-dimensional reference coordinate system, calculate the distance between each node and the robot according to the sound wave signal reflected to each node, and convert the distance into three-dimensional node coordinates of the three-dimensional reference coordinate system; 3D model building unit: used to build a 3D model according to 3D coordinates.

3. A self-propelled deep water maintenance robot according to claim 2, characterized in that: The three-dimensional coordinate generation unit includes the following subunits: The time difference acquisition subunit is used to calculate the time difference of the sound wave signal of each node according to the sound wave signal emitted by each node and the sound wave signal reflected to each node; Initial sound velocity presetting subunit: used to preset an initial sound velocity for the sound wave signal; Initial temperature preset subunit: used to preset an initial temperature; Sound velocity correction subunit: used to obtain the real-time temperature, real-time salinity, and real-time pressure of each node in real time, obtain the temperature influence value according to the real-time temperature and the initial temperature, obtain the salinity influence value according to the real-time salinity, and obtain the pressure influence value according to the real-time pressure; calculate and obtain the corrected sound velocity according to the initial sound velocity, temperature influence value, salinity influence value, and pressure influence value; Node distance calculation subunit: used to calculate the distance between each node and the robot according to the time difference and the corrected sound speed, and generate three-dimensional coordinates based on the distance.

4. A self-propelled deep water maintenance robot according to claim 3, characterized in that: Depth measurement module, including the following units: Real-time water depth value calculation unit: used to obtain the three-dimensional coordinates of the silt to be maintained at the bottom of the water, transmit and receive sound wave signals to the three-dimensional coordinates of the silt to be maintained, obtain the time difference, and calculate the real-time water depth value of each node based on the time difference and the corrected sound speed: ； In the formula, represents the real-time water depth value of the i-th node, represents the corrected sound speed of the ith node, Represents the time difference of the i-th node.

5. The self-propelled deep water maintenance robot according to claim 4, characterized in that: for: ； In the formula, represents the initial sound speed, represents the temperature influence value of the i-th node, represents the salinity impact value of the ith node, Represents the pressure impact value of the i-th node.

6. The self-propelled deep water maintenance robot according to claim 5, characterized in that: for: ； In the formula, represents the real-time temperature of the i-th node, represents the initial temperature, Represents the temperature difference between the real-time temperature and the initial temperature of the i-th node, The linear coefficient representing the temperature influence value, The quadratic coefficient representing the temperature effect, The exponential decay coefficient representing the temperature effect, Represents the exponential decay rate coefficient of the temperature effect value.

7. The self-propelled deep water maintenance robot according to claim 5, characterized in that: for: ； In the formula, represents the real-time salinity of the ith node, The square root coefficient representing the salinity impact value, The periodic coefficient representing the salinity impact value, The frequency coefficient of the periodic term representing the salinity impact value, The saturation effect coefficient representing the salinity impact value, The threshold coefficient of the saturation effect term representing the salinity impact value.

8. The self-propelled water depth maintenance robot according to claim 5, characterized in that: for: ； In the formula, represents the real-time pressure of the ith node, The logarithmic coefficient representing the pressure influence value, The fractional coefficient representing the pressure influence value, The fractional threshold coefficient representing the pressure impact value, Represents the cube root coefficient of the pressure effect value.

9. The self-propelled deep water maintenance robot according to claim 1, characterized in that: The maximum allowable depth change rate is calculated as: ； In the formula, represents the maximum allowable depth change rate, Represents the current speed of the robot, Represents the current acceleration of the robot, represents the real-time pressure of the ith node, represents the real-time temperature of the i-th node, n represents the total number of nodes, i represents the number of nodes, represents the speed influence coefficient, represents the acceleration influence coefficient, represents the pressure index term coefficient, represents the pressure exponential decay rate coefficient, Represents the squared temperature coefficient.

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