Underwater robot path planning method in intelligent marine ranch by improving artificial potential field method

Abstract

The invention discloses an underwater robot path planning method in an improved artificial potential field method intelligent marine ranch, and belongs to the technical field of intelligent marine ranch engineering in ship and ocean engineering. The improved artificial potential field method comprises the steps of improving a gravitational field and a gravitational function, improving a repulsive force field and a repulsive force function and simulating an annealing strategy model, and realizing path planning of the underwater robot; the gravitational field and the gravitational function are improved by applying a force in the direction of a target point to guide the robot to move towards the target, so that the target point of the robot is prevented from being unreachable due to collision between the robot and an obstacle. The improvement of the repulsive force potential field and the repulsive force function is mainly to increase the repulsive force between the robot and the obstacle and prevent collision. Meanwhile, according to the simulated annealing strategy model, when the underwater robot is located at a local minimum point, target points are set at random positions around the obstacle to change the stress condition, and the robot continues to move to break through the local minimum point through the gravitation of the two target points and the repulsive force of the obstacle.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent ocean ranch engineering in ship and ocean engineering. Specifically, it particularly relates to a path planning method for an underwater robot in a metaverse intelligent ocean ranch based on an improved artificial potential field method. Background Technique

[0002] To accelerate the digital and digital-intelligent transformation, the development of various fields tends towards intelligent manufacturing, and the same is true for the technical development of underwater robots. Similarly, the path planning of underwater robots in the metaverse intelligent ocean ranch has emerged as the times require. The underwater robot in the metaverse intelligent ocean ranch uses intelligent means to display the movement trajectory of the underwater robot in a digital and intelligent form in a virtual space, and provides a virtual, diverse, and interconnected digital world, providing users with a brand-new experience.

[0003] Currently, in the context of the era of big data, the Internet of Things, and artificial intelligence, the metaverse virtual technology is used to simulate the complex real-time underwater environment, combined with underwater robots and sensor networks to create a virtual underwater world, and through the interaction with the real world, the perception of the underwater environment, the exploration and management of underwater paths are realized. The continuous increase in the development and application of this technology for ocean resource development, environmental protection, scientific research, and military needs, as well as emerging technologies such as virtual reality and augmented reality, have enabled people's exploration and utilization of the underwater world to enter a brand-new era.

[0004] The basic idea of the artificial potential field method is to regard the movement of a robot in the environment as being affected by forces in a virtual potential field. This potential field consists of two parts: the target gravitational field and the obstacle repulsive field. The traditional artificial potential field method (TAPF) has problems such as the target being unreachable, being prone to collision with obstacles, and being easily trapped in local extreme points when the underwater robot conducts path planning. Summary of the Invention

[0005] According to the above-mentioned technical problems, the present invention provides a path planning method for an underwater robot in an intelligent ocean ranch using an improved artificial potential field method. Aiming at the shortcomings of the traditional artificial potential field method, a distance influence factor is used to improve the gravitational function to solve the problem that when the underwater robot is far from the target point, the robot is prone to collision with obstacles; the repulsive potential field function is improved to alleviate the rapid increase of the repulsive force to solve the problem of the target being unreachable.

[0006] The present invention uses virtual reality (VR) and augmented reality (AR) display space, digital twin (Digital Twin) model space, intelligent monitoring and data analysis space, remote control underwater robot space, improved artificial potential field method path planning algorithm space, user interaction and community construction system space to form a metaverse ocean ranch smart space, forming a sensor network technology to monitor the water and underwater environment of the smart ocean ranch, and store the collected data and analyze the big data in real time, so as to obtain the intelligent monitoring and data analysis space; the positioning and navigation system of the remote control underwater robot space is combined with the improved artificial potential field method path planning algorithm gravity field function, improved gravity function, improved repulsion field function, improved repulsion function to avoid the underwater robot from falling into the local optimal solution and the problem of unreachable target, so as to obtain the underwater robot path planning; through the virtual world, virtual intelligent body, blockchain and digital assets, a blockchain and digital metaverse user interaction and community construction system space is provided; virtual reality (VR) and augmented reality (AR) display space technology and digital twin (Digital Twin) are used to display space technology and digital twin (Digital Twin) to form a metaverse smart space, forming ... Twin) model space technology provides users with a new all-round, immersive, personalized and interactive virtual experience above and below the water, thus avoiding the loss of manpower and financial resources caused by the harsh and changeable underwater environment.

[0007] The specific technical means adopted by the present invention are as follows:

[0008] The improved artificial potential field method for underwater robot path planning in smart ocean ranching includes the following steps:

[0009] S1, the robot's starting position The final target position is ; When the robot starts Distance to target node Distance value , ;

[0010] Based on starting position and the final destination Distance The distance threshold is set Compare and then determine how to calculate gravity:

[0011] like , the gravity is calculated using the following formula:

[0012] The formula is:

[0013] Where: is the scale factor, Represents gravity, Indicates the deviation between the robot's starting position and target position;

[0014] like , gravity will increase with distance The calculation formulas of gravitational field and gravity are as follows:

[0015]

[0016]

[0017] Where: Gravitational gain coefficient, Indicates the robot's starting position. represents the target position of the robot, is the set distance threshold;

[0018] S2. Calculate repulsion

[0019] The improved repulsive field function is:

[0020]

[0021] The improved repulsion function is:

[0022]

[0023] in and They are:

[0024]

[0025]

[0026] in: is the relative distance between the robot’s starting position and the target point, is the relative distance between the robot’s starting position and the obstacle, Take any number greater than zero; and They are:

[0027]

[0028]

[0029] S3, the underwater robot reaches the target point under the combined force of repulsion and gravity; fusion simulated annealing strategy model: after setting a random target point, the combined force on the robot is shown in the following formula:

[0030]

[0031] in, is the gravitational force of the random target point on the underwater robot;

[0032] S4. Determine whether the robot is trapped in a local extreme point based on the size. If the resultant force is zero, use the simulated annealing algorithm to set a random target point to escape from the local minimum point area. Specifically:

[0033] When the underwater robot is at a local minimum, a random target point is set at a random position around the obstacle. The robot continues to move due to the gravitational force of the random target point and the final target position and the repulsive force of the obstacle. First, the robot moves from the current local minimum point to the final target point. Pick a random point from the position , then the potential fields corresponding to the random target point and the final target position are calculated as and , then get ,like , then the random point Accepted; if , then the random point according to For the probability to be accepted;

[0034]

[0035] in, Gravity The potential energy of time, for the next moment; For the previous moment; for The potential energy of the moment; for Potential energy of the moment; Represents the current gravity;

[0036] S5. If the resultant force is not zero, the artificial potential field method with improved attraction and repulsion is directly used to make the robot move toward the target point to determine whether the robot has reached the target point;

[0037] S6. If the target point is reached, the planning is terminated; if the target point is not reached, the starting position is updated and the process returns to step S1 to continue iterating until the target point is reached.

[0038] Further, it includes space for remote-controlled underwater robots, artificial potential field method algorithms, intelligent detection and data analysis, digital twin models, virtual reality and augmented reality display, and user interaction and community building systems;

[0039] The space of the remotely controlled underwater robot feeds back data to the artificial potential field method algorithm space, and the above-mentioned path planning method is used in the artificial potential field method algorithm space for path planning of the underwater robot; the remotely controlled underwater robot advances along the planned path;

[0040] The intelligent detection and data analysis space transmits data to the digital twin model space, and the digital twin model space conducts virtual reality virtual display and augmented reality virtual display.

[0041] Furthermore, the virtual reality and augmented reality display space includes full immersion experience, virtual ocean scene, training and simulation, data visualization and analysis, virtual information overlay, environmental perception and interaction, real-time data display, remote collaboration and monitoring.

[0042] Furthermore, the virtual reality and augmented reality display space is used to realize the three-dimensional physical entity mapping above and below water, enabling users to obtain an immersive virtual world. It uses a head-mounted display to receive three-dimensional graphic signals and data signals sent from the sensor network, and through a data analysis module, uses big data and artificial intelligence technologies to collect, integrate, and comprehensively analyze the signals and data sent by the sensors and transfer them to the virtual reality and augmented reality display space.

[0043] Furthermore, the digital twin model space includes virtual replication of entities, sensor data acquisition system, data processing and analysis platform, simulation and prediction capabilities, cloud computing, and real-time communication technologies.

[0044] Furthermore, the digital twin model space is used to convert the data signals received by the sensors into corresponding digital twins, which are used to reflect the physical state and data dynamics in real time, and assist staff in simulating the actions and states in the real world in a virtual environment.

[0045] Furthermore, the space of the remotely controlled underwater robot includes an underwater robot body, a communication system, a navigation and positioning system, and an energy system.

[0046] Furthermore, the space of the remotely controlled underwater robot is used to realize real-time monitoring and equipment maintenance of the cages in the underwater intelligent ocean ranch, and transmits the signals received by the sensors to the digital twin model space and the virtual reality and augmented reality display space through communication technology.

[0047] Furthermore, the intelligent detection and data analysis space includes a sensor network, a data acquisition and storage system, a real-time data processing and analysis platform, a big data analysis and prediction model;

[0048] The intelligent monitoring and data analysis space is used to deploy a large-scale sensor intelligent monitoring network to collect various environmental data of the ocean ranch in real time, including water temperature, salinity, pH value, and dissolved oxygen; and use big data and artificial intelligence technologies to comprehensively analyze the collected data to provide decision-making support and early warning systems.

[0049] Furthermore, the user interaction and community building system space includes a virtual world, virtual agents, blockchain, and digital assets; creating a virtual community for farmers, experts, and consumers to communicate and interact in the metaverse.

[0050] A metaverse intelligent ocean ranch includes a virtual reality (VR) and augmented reality (AR) display space, a digital twin model space, an intelligent monitoring and data analysis space, a remotely controlled underwater robot space, a path planning algorithm space for the improved artificial potential field method, and a user interaction and community building system space: among them;

[0051] The virtual reality (VR) and augmented reality (AR) display space part displays the virtual environment above water and the virtual ocean environment of the intelligent ocean ranch, showing real-time or historical ocean data, where the ocean data is presented in the form of virtual graphics or information, and various data and devices of the ocean ranch can be viewed and operated in real time.

[0052] The path planning algorithm space for the improved artificial potential field method is used for underwater robot path planning. The gravitational potential field function is improved to enable the underwater robot to shorten the effective distance from the target point, avoiding the situation where the gravitational force is too large and the repulsive force is too small due to the large underwater space environment and the long distance to the target point, which may cause the underwater robot to collide with obstacles; the gravitational function is improved to apply a gravitational force towards the target to the underwater robot, and the gravitational force becomes larger as the robot gets closer to the target point; the repulsive potential field function is mainly to overcome the collision with obstacles caused by the excessive gravitational force between the underwater robot and the obstacles. The repulsive potential field function is a virtual force field constructed in the form of integration or accumulation, a repulsive force field centered on the obstacle, which generates a repulsive reaction force when the underwater robot approaches the obstacle; the repulsive function is to determine the magnitude of the force exerted by the obstacle on the robot, a function that decreases as the distance between the obstacle and the underwater robot increases, mainly for calculating the distance between the underwater robot and the obstacle; the simulated annealing strategy model is to overcome the situation when the artificial potential field method falls into a local optimal solution. By setting up target points around the obstacles, the force balance of the underwater robot is broken, and the obstacle avoidance state is maintained.

[0053] The digital twin model space part creates a corresponding digital twin with the real intelligent ocean ranch as the carrier, and uses sensor network technology to reflect its physical state and dynamic changes in real time for simulation and prediction.

[0054] The intelligent monitoring and data analysis space part uses a large number of sensor network technologies to collect environmental data of the intelligent ocean ranch in real time, and uses big data and artificial intelligence technologies to sort out, analyze and statistically process the collected data, so as to provide a scientific early warning system.

[0055] The user interaction and community building system space part realizes a virtual community, which satisfies the virtual communication, shopping, interaction and sharing of technologies and experiences of users and consumers. Through virtual interaction displays, consumers can understand and experience the underwater operation process of the intelligent ocean ranch, thereby enhancing the user experience and trust.

[0056] Compared with the prior art, the present invention has the following advantages:

[0057] The improved artificial potential field algorithm is used for path planning. After the algorithm is improved, no matter what power the distance between the robot and the target point is, the repulsive force component approaches 0. Therefore, the underwater robot is only affected by the repulsive force component and the gravitational force of the target point. However, both the repulsive force component and the gravitational force component are in the direction pointed by the underwater robot and the target point. Therefore, when the underwater robot approaches the target point, the underwater robot can reach the target point under the resultant force of these two components.

[0058] In the improved gravitational function, the search time of the improved algorithm is reduced by 1.89 s compared with the original algorithm, and the search efficiency is increased by 9.3%; in the improved repulsive force function, the search time of the improved algorithm is reduced by 2.79 s compared with the original algorithm, and the search efficiency is increased by 23.9%; in the simulated annealing strategy, the search time of the improved algorithm is reduced by 3.72 s compared with the original algorithm, and the search efficiency is increased by 77%. Generally speaking, the search efficiency of the improved algorithm is increased by 36.7% compared with the original algorithm. And in a complex environment, the optimal path can be found faster, which can shorten the operation cycle of the underwater robot.

[0059] The metaverse intelligent ocean ranch intelligent space that uses the improved artificial potential field algorithm for path planning, with virtual reality (VR) and augmented reality (AR) to display the space: full immersion experience, virtual ocean scenes, training and simulation, data visualization and analysis, virtual information overlay, environmental perception and interaction, real-time data display, remote collaboration and monitoring to complete the virtual display of the real world. With the digital twin model space: virtual replication of entities, sensor data acquisition system, data processing and analysis platform, simulation and prediction capabilities, cloud computing and real-time communication technologies, and security protection mechanisms, etc., to achieve efficient monitoring, management and optimization. With the intelligent monitoring and data analysis space: sensor network, data acquisition and storage system, real-time data processing and analysis platform, big data analysis and prediction models to complete data collection, analysis and prediction. With the remote control of underwater robots space: underwater robot body, communication system, navigation and positioning system, energy system, etc., to assist the improved artificial potential field method algorithm to complete path planning. With the path planning algorithm of the improved artificial potential field method: improved gravitational field function, improved gravitational function, improved repulsive field function, improved repulsive function, simulated annealing strategy model, to achieve the path planning of underwater robots. The virtual world, virtual agents, blockchain and digital assets provide a blockchain and digital metaverse user interaction and community building system space, providing customers with an immersive and all-round virtual experience. At the same time, use the virtual environment for aquaculture experiments, underwater inspections, simulation operations and other actions to reduce the actual operation risks and accumulate experience and data.

[0060] Based on the above invention reasons, this invention method can be extended to the intelligent ocean ranch technology field of ship and ocean engineering. Brief Description of the Drawings

[0061] In order to more clearly describe the implementation method of the present invention or the prior art solutions, the following will describe the implementation method or the prior art solutions in the form of drawings and briefly introduce. It can be seen from the drawings that the following drawings are the implementation methods of the present invention. For those skilled in this field, without involving creative labor, they can be extended according to the drawings.

[0062] Figure 1 Metaverse ocean ranch intelligent space framework diagram.

[0063] Figure 2 Metaverse improved artificial potential field algorithm path planning flowchart.

[0064] Figure 3 Improved artificial potential field algorithm path planning effect diagram.

[0065] Figure 4 Metaverse ocean ranch intelligent space structure block diagram.

[0066] Figure 5It is a virtual block diagram of the metaverse system.

[0067] Figure 6 It is a force analysis diagram of an underwater robot. Specific implementation manners

[0068] It is hereby declared that the implementation methods in the present invention can be combined with each other on the premise of not conflicting. The following is a detailed description of the present invention in combination with the drawings and implementation methods.

[0069] In order to describe the implementation methods in the present invention more clearly, the following will elaborate on the technical solutions of the drawings in the implementation methods. Obviously, the described implementation embodiments are only a part of the present invention, not all implementation methods. The following will explain the implementation methods for some of the following drawings, but it does not limit the application or use of the present invention. For the implementation methods in the present invention, those within the technical field who have not made creative efforts belong to the protection scope of the present invention.

[0070] It should be noted that the expressions used in the present invention are only for better describing the specific implementation methods and do not limit the implementation manners of this invention. Unless specifically pointed out in the present invention, the singular expression also means the plural expression.

[0071] It should be noted that the parts, systems, operation methods, relative positions, front and rear arrangements, numerical values, and mathematical expressions described in the present invention do not limit the protection scope of the present invention. In addition, in order to clearly express the implementation methods of the present invention, the sizes in the drawings of the present invention are not made in proportion. For those skilled in the art who are already clear about the technologies, solutions, equipment, and drawings, no detailed discussion will be made. However, in special cases, the described equipment, technologies, solutions, and block diagrams should be regarded as part of the authorization specification. The implementation methods in the present invention are only exemplary. It should be noted in the present invention that the numbers and letters in the block diagrams represent similar items. Therefore, once defined in the drawings, the subsequent drawings do not need to be discussed in detail.

[0072] It should be noted that the orientations pointed out in the present invention are only based on the directions and positions shown in the drawings, only for making the description of the solutions in the present invention clearer. Similarly, the devices or equipment in the present invention do not represent the operation sequence and operation steps. Therefore, it cannot be stated that the protection scope of the present invention is limited.

[0073] It should be noted that the sequential arrangement of the parts in the present invention is only for easy distinction. Without special instructions, the above description has no substantial meaning. Therefore, it cannot be stated that the protection object of the present invention is limited.

[0074] The path effect diagram of the path planning method for an underwater robot in an improved artificial potential field method in an intelligent ocean ranch is asFigure 2 As shown, the flow chart is as Figure 3 shown below:

[0075] 1) Judge the distance between the starting position and the target position. If , the traditional gravitational function formula is used to calculate the gravity. Otherwise, the improved gravitational function formula is used for calculation.

[0076] The starting position where the robot is located , and the final target position is ; When the starting position of the robot The distance from the target node Distance value , ;

[0077] According to the distance between the starting position and the final target position is compared with the set distance threshold to determine the calculation method of gravity:

[0078] If , the following formula is used to calculate the gravity:

[0079] The formula is:

[0080] In the formula: is the scale factor, represents the gravity, represents the deviation between the starting position and the target position of the robot;

[0081] If , the gravity will decrease as the distance increases. Then the calculation formulas for the gravitational field and gravity are:

[0082]

[0083]

[0084] In the formula: Gravitational gain coefficient, represents the starting position where the robot is located, represents the target position of the robot, is the set distance threshold;

[0085] 2) Calculate the repulsive force

[0086] The improved repulsive force field function is:

[0087]

[0088] The improved repulsive force function is as follows:

[0089]

[0090] Wherein and are respectively:

[0091]

[0092]

[0093] Wherein: is the relative distance from the starting position of the robot to the target point, is the relative distance from the starting position of the robot to the obstacle, takes any number greater than zero; and are respectively:

[0094]

[0095]

[0096] The underwater robot reaches the target point under the combined force of the repulsive force and the gravitational force; Fusion simulated annealing strategy model: After setting a random target point, the combined force received by the robot is shown in the following formula:

[0097]

[0098] Wherein, is the gravitational force of the random target point on the underwater robot;

[0099] 3) Determine whether the robot falls into a local extreme point according to the magnitude. If the combined force is zero, jump to step 4); if not, jump to 5).

[0100] 4) Use the simulated annealing algorithm to set a random target point to get out of the local minimum point area. Specifically:

[0101] When the underwater robot is in the local minimum point, a random target point is set at a random position around the obstacle, and the robot continues to move under the gravitational force of the random target point and the final target position and the repulsive force of the obstacle; First, extract a random point from the current position in the local minimum point , then calculate the potential fields corresponding to the random target point and the final target position as and , and then get . If , then the random point is accepted; if , then the random point According to is the probability of being accepted;

[0102]

[0103] wherein, is the gravitational force when the potential energy is; is the latter moment; is the previous moment; is the potential energy at the moment; is the potential energy at the moment; represents the current gravitational force; 5) If the resultant force is not zero, directly use the artificial potential field method after improving the gravitational and repulsive forces to make the robot move towards the target point to determine whether the robot reaches the target point. If so, jump to 6), otherwise jump to 2) and continue the iteration.

[0104] 6) End the planning.

[0105] In the improved gravitational function, the search time of the improved algorithm is reduced by 1.89 s compared with the original algorithm, and the search efficiency is improved by 9.3%; in the improved repulsive force function, the search time of the improved algorithm is reduced by 2.79 s compared with the original algorithm, and the search efficiency is improved by 23.9%; in the simulated annealing strategy, the search time of the improved algorithm is reduced by 3.72 s compared with the original algorithm, and the search efficiency is improved by 77%. Generally speaking, the search efficiency of the improved algorithm is improved by 36.7% compared with the original algorithm. And in a complex environment, the optimal path can be found faster, which can shorten the operation cycle of the underwater robot.

[0106] As Figure 1 shown, the present invention provides a metaverse intelligent ocean ranch intelligent space, including virtual reality (VR) and augmented reality (AR) display spaces, digital twin model spaces, intelligent monitoring and data analysis spaces, remote control underwater robot spaces, path planning algorithm spaces of the improved artificial potential field method, user interaction and community construction system spaces, wherein the virtual reality (VR) and augmented reality (AR) display spaces further include full immersion experience, virtual ocean scenes, training and simulation, data visualization and analysis, virtual information superposition, environmental perception and interaction, real-time data display, remote collaboration and monitoring.

[0107] The digital twin model space further includes virtual replication of entities, sensor data acquisition systems, data processing and analysis platforms, simulation and prediction capabilities, cloud computing and real-time communication technologies; the improved artificial potential field method algorithm further includes improved gravitational field functions, improved gravitational functions, improved repulsive field functions, improved repulsive functions, and simulated annealing strategy models.

[0108] The intelligent monitoring and data analysis space also includes a sensor network, a data acquisition and storage system, a real-time data processing and analysis platform, and a big data analysis and prediction model; the remote control underwater robot space also includes an underwater robot body, a communication system, a navigation and positioning system, and an energy system; the user interaction and community building system space also includes a virtual world, virtual intelligent agents, blockchain, and digital assets.

[0109] The present invention uses virtual reality (VR) and augmented reality (AR) spaces to display the water ecological environment and equipment operation status of a smart ocean ranch, the underwater robot patrol status, the real-time data display of the underwater robot, and the maintenance of underwater equipment. It uses a digital twin model space to complete the virtual mapping, data processing, and simulation prediction of the real world. Through the sensor network technology and big data analysis in the intelligent monitoring and data analysis space, the physical signals of the real world are fed back to the virtual world, and big data analysis and artificial intelligence technologies are used to record the physical quantities of the real world in real time, predict the possibility of future events based on the existing state, and at the same time combine the remote control underwater robot with the artificial potential field method algorithm to complete path planning.

[0110] The improved artificial potential field algorithm is used for path planning. After the algorithm is improved, no matter what power the distance between the robot and the target point is, the repulsive force component approaches 0. Therefore, the underwater robot is only affected by the repulsive force component and the gravitational force of the target point. However, both the repulsive force component and the gravitational force component are in the direction pointed by the underwater robot and the target point. Therefore, when the underwater robot approaches the target point, the underwater robot can reach the target point under the combined force of these two components. A virtual community is created using the user interaction and community building system space, which can provide an immersive, personalized, and highly interactive virtual community experience, meet the virtual interaction display of users and consumers, and let consumers understand and experience the underwater operation process of the smart ocean ranch, thereby enhancing the user experience and trust.

[0111] Figure 4 The virtual reality (VR) and augmented reality (AR) display space, which includes full-immersion experience, virtual ocean scenes, training and simulation, data visualization and analysis, virtual information overlay, environmental perception and interaction, real-time data display, remote collaboration and monitoring. Among them, virtual reality creates a realistic virtual ocean ranch environment, allowing users to have an immersive experience through VR devices and observe and manage various activities and states in the ranch; augmented reality superimposes virtual information on the real world, and through AR glasses or mobile devices, users can view and operate the various data and equipment of the ocean ranch in real time.

[0112] The Digital Twin model space, which includes virtual replication, sensor data acquisition systems, data processing and analysis platforms, simulation and prediction capabilities, cloud computing and real-time communication technologies, and security protection mechanisms, is mainly used to reflect the physical information and state changes of the real world in real time.

[0113] The path planning algorithm space of the improved artificial potential field method. The path planning algorithm space of the improved artificial potential field method includes an improved gravitational field function, an improved gravitational function, an improved repulsive field function, an improved repulsive function, and a simulated annealing strategy model. For the improved gravitational field function and the improved gravitational function, when the spatial environment is large, there is a situation where the robot is far from the target point. According to the gravitational formula, at this time, the gravity will become very large, while the repulsive force will appear relatively small, and the robot is likely to collide with obstacles during movement, resulting in the inability to reach the target point. In response to the above situation, the gravitational function is improved. The improved gravitational field function is:

[0114] (1)

[0115] The improved gravitational function is:

[0116] (2)

[0117] In the formula Gravitational gain coefficient, Represents the starting position of the robot, Represents the position of the target point, Is a certain set distance. It can be seen from formula (2) that when the starting position of the robot Distance from the target node Distance value Greater than When, the gravity will decrease with the increase of the distance ; For the improved repulsive field function and the improved repulsive function, in response to the problem of unreachable target, by adding the Power of the distance between the robot and the target point to the repulsive force function. Although it seems that the repulsive force is still increasing when the object approaches the target, its growth rate is significantly slower than before, which can effectively alleviate the problem of excessive repulsive force.

[0118] The improved repulsive field function is:

[0119] (3)

[0120] The improved repulsive function is:

[0121] (4)

[0122] Where And respectively as follows:

[0123] (5)

[0124] (6)

[0125] In equations (5) and (6), is the relative distance from the starting position of the robot to the target point, is the relative distance from the starting position of the robot to the obstacle, can take any number greater than zero. The force analysis diagrams of the robot in different situations are as shown in Figure 6 shown. In the formula, and are respectively as follows:

[0126] (7)

[0127] (8)

[0128] According to formula (2), it can be known that if the distance between the starting position of the robot and the target point position is greater than the set distance , then the gravitational force of the target point on the robot will decrease as the distance increases. Similarly, the gravitational force of the target point on the robot will increase as the distance decreases. No matter what power the distance between the robot and the target point is, the repulsive force component approaches 0. Therefore, the underwater robot is only affected by the repulsive force component and the gravitational force of the target point. However, both the repulsive force component and the gravitational force component are in the direction pointed by the underwater robot and the target point. Therefore, when the underwater robot approaches the target point, the underwater robot can reach the target point under the resultant force of these two components; Fusion simulated annealing strategy model: After setting a random target point, the resultant force received by the robot is as shown in (9):

[0129] (9)

[0130] wherein, is the gravitational force of the random target point on the underwater robot. The simulated annealing algorithm is a method that uses a random strategy to find the optimal solution.

[0131] Use the simulated annealing algorithm to set random target points to get out of the local minimum point area. Specifically:

[0132] When the underwater robot is in the local minimum point, set random target points at random positions around the obstacle, and the robot continues to move under the gravitational force of the random target point and the final target position and the repulsive force of the obstacle; First, from the current local minimum point Extract a random point from the positions , then calculate the potential fields corresponding to the random target point and the final target position respectively as and , and then obtain . If , then the random point is accepted; if , then the random point is accepted with a probability according to ;

[0133]

[0134] Among them, is the gravitational force when the potential energy is is the next moment; is the previous moment; is the potential energy at the moment; is the potential energy at the moment; represents the current gravitational force; 5) If the resultant force is not zero, directly use the artificial potential field method after improving the gravitational and repulsive forces to make the robot move towards the target point to determine whether the robot reaches the target point.

[0135] Intelligent monitoring and data analysis space, including sensor networks, data collection and storage systems, real-time data processing and analysis platforms, big data analysis and prediction models. This module is equipped with a large number of sensors to receive water surface and underwater environment signals, and uses artificial intelligence and big data analysis technologies to provide technical support for path planning of underwater robots, collect environmental data of ocean ranches in real time, and provide scientific predictions for smart ocean ranches.

[0136] Remote control underwater robot space, including underwater robot body, communication system, navigation and positioning system, energy system, mainly providing power energy and position sharing for underwater robots to facilitate path planning of underwater robots.

[0137] User interaction and community building system space, including virtual worlds, virtual agents, blockchains and digital assets. This space provides virtual interactions for customers, enabling users to have an immersive, personalized and highly interactive virtual community experience.

[0138] The intelligent monitoring and data analysis space reads the data of the intelligent ocean ranch, and information is transmitted between the intelligent monitoring and data analysis space and the digital twin model space by means of data transmission; the digital twin model space presents the information of the real world in the virtual world by means of physical mapping, and transfers the virtual model and parameters of the physical world to the virtual reality (VR) and augmented reality (AR) display space and the user interaction and community construction system space by means of virtual mapping; at the same time, the remotely controlled underwater robot space reads the underwater data information of the intelligent ocean ranch, and information is transmitted between the remotely controlled underwater robot space and the path planning algorithm space of the improved artificial potential field method by means of data feedback; the path planning algorithm space of the improved artificial potential field method transfers the transmitted information to the virtual reality (VR) and augmented reality (AR) display space and the user interaction and community construction system space by means of algorithm embedding and virtual mapping; thus, an immersive, personalized and highly interactive virtual experience of metaverse picture display and user interaction is obtained.

[0139] The virtual block diagram of the metaverse system in the present invention is as Figure 5 shown, and the specific process includes:

[0140] Step 1. When traditional operations are carried out underwater, first, experienced workers need to teach their experience, and after training, workers dive into the seabed manually for inspection work.

[0141] Step 2. Underwater equipment collects information and stores the collected data information in the user space.

[0142] Step 3. Data interaction is carried out with the metaverse time and space through information virtual-real mapping, so as to obtain a virtual world. In the virtual world, digital robots replace traditional workers to conduct underwater inspections, virtual ocean ranches replace physical ranches, and virtual humans are used as the first perspective to experience underwater scenes.

[0143] Step 4. Through the data loop interaction module, the information in the physical space and the metaverse time and space is fused and interacted to obtain a social space.

[0144] Step 5. The fused information is transmitted to the social space in real time, so that users can feel the deep-sea working scene on land.

[0145] Step 6. The virtual community generated in the social space is displayed in a five-dimensional space. Users receive information and make decisions, and at the same time, the virtual community processes the instructions sent by users.

[0146] Step 7. The information decided by users is fed back to the metaverse time and space through the virtual community.

[0147] Finally, it should be noted that the above is only the technical solution of the present invention and does not limit it; even if the above real-time method has been introduced in detail, it is not restricted; those skilled in the art can modify the described cases or replace the technologies with the same features; however, no matter the modification or replacement, it should not deviate from the technical essence of the present invention.

Claims

1. Improved artificial potential field method for underwater robot path planning in smart ocean ranching, characterized in that: The following steps are involved: S1, the robot's starting position The final target position is ; When the robot starts Distance to target node Distance value , ; Based on starting position and the final destination Distance The distance threshold is set Compare and then determine how to calculate gravity: like , the gravity is calculated using the following formula: The formula is: Where: is the scale factor, Represents gravity, Indicates the deviation between the robot's starting position and target position; like , gravity will increase with distance The calculation formulas of gravitational field and gravity are as follows: ； ； Where: Gravitational gain coefficient, Indicates the robot's starting position. represents the target position of the robot, is the set distance threshold; S2. Calculate repulsion The improved repulsive field function is: ； The improved repulsion function is: ； in and They are: ； ； in: is the relative distance between the robot’s starting position and the target point, is the relative distance between the robot’s starting position and the obstacle, Take any number greater than zero; and They are: ； ； S3, the underwater robot reaches the target point under the combined force of repulsion and gravity; fusion simulated annealing strategy model: after setting a random target point, the combined force on the robot is as follows: ； in, is the gravitational force of the random target point on the underwater robot; S4. Determine whether the robot is trapped in a local extreme point based on the size. If the resultant force is zero, use the simulated annealing algorithm to set a random target point to escape from the local minimum point area. Specifically: When the underwater robot is at a local minimum, a random target point is set at a random position around the obstacle. The robot continues to move due to the gravitational force of the random target point and the final target position and the repulsive force of the obstacle. First, the robot moves from the current local minimum point to the final target point. Pick a random point from the position , then the potential fields corresponding to the random target point and the final target position are calculated as and , then get ,like , then the random point Accepted; if , then the random point according to For the probability to be accepted; ； in, Gravity The potential energy of time, is the potential energy corresponding to the final target position; The potential energy corresponding to the random target point; Represents the current gravity; S5. If the resultant force is not zero, the artificial potential field method with improved attraction and repulsion is directly used to make the robot move toward the target point to determine whether the robot has reached the target point; S6. If the target point is reached, the planning is terminated; if the target point is not reached, the starting position is updated and the process returns to step S1 to continue iterating until the target point is reached.

2. A metaverse smart ocean ranch smart space, characterized by: It includes space for remote-controlled underwater robots, artificial potential field method algorithms, intelligent detection and data analysis, digital twin models, virtual reality and augmented reality display, and user interaction and community building systems; The remote-controlled underwater robot space feeds back data to the artificial potential field method algorithm space, and the path planning method of claim 1 is used in the artificial potential field method algorithm space to plan the path of the underwater robot; the remote-controlled underwater robot moves forward according to the planned path; The intelligent detection and data analysis space transmits data to the digital twin model space, and the digital twin model space performs virtual reality virtual display and augmented reality virtual display.

3. The metaverse smart ocean ranch smart space according to claim 2 is characterized by: The virtual reality and augmented reality display space includes full immersion experience, virtual ocean scenes, training and simulation, data visualization and analysis, virtual information overlay, environmental perception and interaction, real-time data display, remote collaboration and monitoring.

4. The metaverse smart ocean ranch smart space according to claim 3 is characterized by: The virtual reality and augmented reality display space is used to achieve three-dimensional physical entity mapping above and below the water so that users can obtain an immersive virtual world. A head-mounted display is used to receive three-dimensional graphic signals and data signals emitted by a sensor network. Through a data analysis module, big data and artificial intelligence technology are used to collect, integrate, and comprehensively analyze the signals and data emitted by the sensors and transmit them to the virtual reality and augmented reality display space.

5. The metaverse smart ocean ranch smart space according to claim 2 is characterized by: The digital twin model space includes virtual replication of entities, sensor data acquisition systems, data processing and analysis platforms, simulation and prediction capabilities, cloud computing and real-time communication technologies.

6. The metaverse smart ocean ranch smart space according to claim 5 is characterized by: The digital twin model space is used to convert the data signals received by the sensor into corresponding digital twins, which are used to reflect the changes in its physical state and data dynamics in real time, and assist staff in simulating real-world actions and states in a virtual environment.

7. The metaverse smart ocean ranch smart space according to claim 2 is characterized by: The remote-controlled underwater robot space includes an underwater robot body, a communication system, a navigation and positioning system, and an energy system.

8. The metaverse smart ocean ranch smart space according to claim 7 is characterized by: The remote-controlled underwater robot space is used to realize real-time monitoring of cages and equipment maintenance of underwater smart ocean ranches, and transmits signals received by sensors to the digital twin model space and virtual reality and augmented reality display space through communication technology.

9. The metaverse smart ocean ranch smart space according to claim 2 is characterized by: The intelligent monitoring and data analysis space includes sensor networks, data acquisition and storage systems, real-time data processing and analysis platforms, big data analysis and prediction models; The intelligent monitoring and data analysis space is used to deploy a large-scale sensor intelligent monitoring network to collect various environmental data of the marine ranch in real time, including water temperature, salinity, pH value, and dissolved oxygen; use big data and artificial intelligence technology to conduct comprehensive analysis of the collected data to provide decision support and early warning systems.

10. The metaverse smart ocean ranch smart space according to claim 2 is characterized by: The user interaction and community building system space includes a virtual world, virtual agents, blockchains and digital assets; creating a virtual community for farmers, experts and consumers to communicate and interact in the metaverse.

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