Construction method and device of net-free underwater pasture, management equipment and storage medium

Abstract

The invention relates to the technical field of cultivation, and discloses a net-free underwater pasture construction method, which comprises the following steps: generating a networking strategy containing the number and spacing of networking nodes by acquiring underwater pasture setting conditions and robot operation capability parameters, selecting a networking starting point according to underwater environment parameters, and constructing a net-free underwater pasture according to the networking starting point; and the networking robot constructs a network-free underwater pasture according to a selected strategy. When the pasture adjusting condition is detected to be met, the position, the size or the shape of the pasture can be dynamically adjusted. The robot cluster is adopted to replace a traditional fixed net cage, the problem of fish school escape caused by damage of the net cage is effectively avoided, natural exchange of water is promoted through reconfigurability of a pasture, and pollutant accumulation is reduced.

Description

Technical Field

[0001] This invention relates to the field of aquaculture technology, and in particular to a method, apparatus, management equipment, and storage medium for constructing a netless underwater ranch. Background Technology

[0002] Marine ranching, as an intensive marine aquaculture model, plays an important role in modern fisheries production. Current technology commonly employs cage-type marine ranching, which confines farmed fish within a specific water area using fixed cage structures. This traditional model has many drawbacks.

[0003] First, traditional net cage structures have significant shortcomings in coping with extreme marine environments. Because net cages are usually fixed in place, they are prone to deformation and damage when encountering severe sea conditions such as typhoons and giant waves. This can lead to serious malfunctions such as torn netting and disintegration of the frame, resulting in large-scale escapes of farmed fish and causing significant economic losses to aquaculture enterprises.

[0004] Secondly, traditional cage aquaculture has a significant negative impact on the marine ecosystem. In the enclosed cage environment, leftover feed and fish excrement accumulate continuously, making it difficult to disperse and dilute them through natural water exchange. This large accumulation of organic matter not only deteriorates the water quality inside the cages but also promotes the proliferation of harmful algae, disrupting the ecological balance of the local sea area. Furthermore, maintaining cage cleanliness requires regular net cleaning, which increases aquaculture costs, and the chemical cleaning agents used may cause secondary pollution to the surrounding environment. Summary of the Invention

[0005] Based on this, it is necessary to address the technical problems of poor wind and wave resistance and significant pollution caused by existing fixed net cages, and propose a method, device, management equipment and storage medium for constructing a netless underwater ranch.

[0006] Firstly, a method for constructing a netless underwater ranch is provided, the method comprising: The underwater ranch setting conditions and the underwater robot's operational capability parameters are obtained. The underwater ranch setting conditions include ranch shape parameters and ranch volume parameters. At least one networking strategy is generated based on the underwater ranch setting conditions and the operational capability parameters; the networking strategy includes at least: the number of networking nodes and the spacing between networking nodes; Acquire underwater environmental parameters and select the network starting point based on the underwater environmental parameters; Select a target networking strategy from the at least one networking strategy, and determine multiple networking robots in the robot cluster according to the number of networking nodes, and instruct the multiple networking robots to construct an underwater ranch based on the networking starting point according to the spacing between networking nodes. When the conditions for adjusting the underwater ranch are met, the attribute parameters of the underwater ranch are adjusted. The attribute parameters include one or more of the following: location, volume, and shape.

[0007] Secondly, a device for constructing a netless underwater ranch is provided, the device comprising: The acquisition module is used to acquire the underwater ranch setting conditions and the underwater robot's operational capability parameters. The underwater ranch setting conditions include ranch shape parameters and ranch volume parameters. A generation module is used to generate at least one networking strategy based on the underwater ranch setting conditions and the operational capability parameters; the networking strategy includes: the number of networking nodes and the spacing between networking nodes; Select a module to acquire underwater environmental parameters and select the network starting point based on the underwater environmental parameters; The control module is configured to select a target networking strategy among the at least one networking strategy, and determine multiple networking robots in the robot cluster according to the number of networking nodes, and instruct the multiple networking robots to construct an underwater ranch based on the networking starting point according to the spacing between networking nodes. An adjustment module is used to adjust the attribute parameters of the underwater ranch when the ranch adjustment conditions are met. The attribute parameters include one or more of the following: location, volume, and shape.

[0008] Thirdly, a management device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described intelligent question-answering processing method.

[0009] Fourthly, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described intelligent question-answering processing method.

[0010] Beneficial Effects: Underwater ranches constructed using underwater robot swarms effectively reduce the risk of fish escaping due to damaged net cages. Robot nodes can dynamically adjust their positions according to wind and wave conditions, significantly improving the ranch's resistance to wind and waves and its environmental adaptability. The netless structure promotes natural water exchange, effectively reducing the accumulation of residual feed and excrement in the aquaculture area. Combined with the intelligent adjustment of the ranch's location and shape by the robots, the aquaculture area can be rotated and renewed, thus significantly mitigating the ecological impact on the local sea area. Managers can dynamically adjust the ranch's spatial layout, volume, and geometry according to aquaculture needs, realizing a transformation from static, fixed aquaculture to dynamic, reconfigurable aquaculture, flexibly adapting to various different scenarios. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] in: Figure 1 This is an application environment diagram of a method for constructing a netless underwater ranch in one embodiment; Figure 2 This is a flowchart of a method for constructing a netless underwater ranch in one embodiment; Figure 3 This is a schematic diagram of the network starting point in one embodiment; Figure 4 This is a schematic diagram illustrating a horizontal layer network configuration in one embodiment; Figure 5 This is a schematic diagram of the ranch adjustment mode in one embodiment; Figure 6 This is a structural block diagram of a construction device for a netless underwater ranch in one embodiment; Figure 7 This is a structural block diagram of the management device in one embodiment. Detailed Implementation

[0013] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0014] The method for constructing a netless underwater ranch provided in this invention can be applied to, for example... Figure 1 In the application environment. The underwater ranching management system of this application includes: management equipment, a surface base station, and a robot swarm. The management equipment can communicate with each robot in the robot swarm via the surface base station.

[0015] The management equipment allows for remote configuration of underwater robots, such as setting parameters for a netless underwater ranch, and scheduled feeding or monitoring patrols of the farmed organisms. It also enables real-time monitoring of the underwater ranch's environmental parameters and remote control of the networked robot cluster (e.g., controlling the networked robots to expand or shrink the underwater ranch). The management equipment can be a mobile device, tablet, or fixed computer, and this application does not impose any restrictions.

[0016] The surface base station is equipped with GNSS (Global Navigation Satellite System) and a USBL (Ultra Short Baseline) transducer array positioned below the water surface. Serving as a communication hub between management equipment and underwater robots, the surface base station handles operation scheduling, ensuring coordinated responses from management equipment commands and underwater robots. Furthermore, the surface base station is capable of supplying power to the underwater robots. It carries its own generator or high-capacity battery and provides power or charging to nearby underwater robots via umbilical cables or wireless charging interfaces, significantly extending the underwater robots' operating time.

[0017] The robot swarm consists of networked robots and patrolling robots. Multiple networked robots form a swarm to define the boundaries of the underwater ranch. Several patrolling robots monitor and feed the farmed organisms. The networked robots are required to remain in the underwater environment for extended periods, while the patrolling robots, based on needs or pre-defined conditions, perform patrol / inspection actions within the ranch area established by the networked robots. It is understood that patrolling robots do not participate in the network unless absolutely necessary, but they can join the network in emergency situations.

[0018] In this embodiment, both the networked robot and the patrolling robot are ROVs (Remotely Operated Vehicles). The underwater robot is equipped with a USBL transponder, which works in conjunction with the USBL transponder array set up by the surface base station for cooperative positioning. The positioning principle is as follows: the surface base station obtains the surface position coordinates based on the GNSS module, the underwater robot uses the USBL transponder to measure the relative position offset between itself and the surface base station, and then calculates its own current position coordinates based on the relative position offset and the position coordinates of the surface base station.

[0019] The present invention will now be described in detail through specific embodiments.

[0020] Please see Figure 2 As shown, Figure 2 A flowchart illustrating a method for constructing a netless underwater ranch according to an embodiment of the present invention includes the following steps: S1: Obtain the underwater ranch setting conditions and the underwater robot's operational capability parameters. The underwater ranch setting conditions include ranch shape parameters and ranch volume parameters.

[0021] The management equipment can obtain underwater ranch setting parameters based on user input. Underwater ranch setting conditions represent the basic spatial attributes defined when constructing a meshless underwater ranch in an underwater environment, used to spatially constrain the underwater ranch. Underwater ranch setting conditions include: ranch shape parameters and ranch volume parameters. Ranch shape parameters represent the geometric shape of the underwater ranch in three-dimensional space, specifying the basic form of the spatial boundary formed after the robots are networked. This shape can be a regular geometric shape, such as a cube, sphere, or cylinder, or an irregular polyhedron set according to the actual seabed topography or aquaculture needs. Shape parameters are the core indicator for determining the spatial relative positions of network nodes. Ranch volume parameters represent the size of the space that the underwater ranch can accommodate, and are a key indicator for measuring the scale of aquaculture. Volume parameters and shape parameters are interrelated and jointly determine the spatial scale of the ranch. For example, after the shape parameter is determined to be a cube, the volume parameter will directly determine the side length of the cube, thereby accurately defining the required spatial range.

[0022] The operational capability parameters of an underwater robot represent the inherent performance indicators determined by its hardware configuration. They describe the physical boundaries and performance limits of the underwater robot. For example, operational capability parameters include: maximum diving depth, maximum effective range of the fish deterrent, positioning capability parameters, and maneuverability parameters.

[0023] The maximum diving depth indicates the depth at which the underwater robot's structural strength and sealing performance can withstand the ultimate underwater pressure. It is used to limit the vertical range in which underwater ranches can be deployed, ensuring that the robot will not be damaged by water pressure when operating within this depth range.

[0024] The maximum effective distance of a fish repeller indicates the maximum spatial range within which the fish repeller device on an underwater robot can effectively influence and repel fish using physical forces such as sound, light, electricity, or bubbles. It is a core indicator for determining the spacing between network nodes, ensuring that the fish-repelling ranges of adjacent robots can effectively overlap or connect, forming a continuous and comprehensive pasture protection boundary. The maximum effective distance of the fish repeller is determined by its hardware performance.

[0025] The positioning capability parameter represents the accuracy and stability of the positioning system (such as acoustic positioning system or inertial navigation system) carried by the robot in determining its own spatial position in the underwater environment. It can affect the accuracy of the network node layout, and thus affect the degree to which the shape of the final underwater ranch matches the set conditions.

[0026] Mobility parameters represent the motion performance of a robot based on its propulsion system, control system, and structural design. They typically include maximum speed, cruising speed, turning radius, and the ability to resist disturbances and maintain position under specific water flow conditions.

[0027] S2: Generate at least one networking strategy based on the underwater ranch settings and operational capability parameters;

[0028] The networking strategy includes at least the number of networking nodes and the spacing between them. The number of networking nodes represents the number of underwater robots required to construct an underwater ranch that conforms to a set shape and volume. The spacing between networking nodes represents the Euclidean distance that two adjacent networking robots need to maintain in the three-dimensional space constituting the underwater ranch. Specifically, the upper limit of the spacing between networking nodes is determined by the effective range of the fish repellers. To ensure that the coverage areas of adjacent fish repellers can be fully connected to form a continuous protective barrier, the spacing between networking nodes should be less than twice the maximum effective range of a single fish repeller. At the same time, the lower limit of the spacing between networking nodes is determined by the physical size of the robots themselves and operational safety requirements. To avoid collisions between underwater robots during operation or position maintenance, the spacing between networking nodes should be greater than the preset minimum safe contact distance.

[0029] Based on the acquired underwater ranch settings and the operational capabilities of the underwater robots, the management equipment generates one or more feasible networking strategies through calculation and optimization. The process of generating networking strategies essentially involves decomposing the spatial objectives of the ranch and mapping them onto the physical deployment scheme of the robot swarm.

[0030] The specific generation process includes: First, the management equipment performs spatial analysis on the set conditions of the underwater ranch. Based on the ranch's shape parameters (such as cube, sphere, etc.) and volume parameters, it calculates the boundary dimensions of the ranch in three-dimensional space. For example, for a cubic ranch, its side length can be calculated based on its volume; for a spherical ranch, its radius can be calculated.

[0031] Secondly, the management equipment determines the feasible range of node spacing based on key indicators in the operational capability parameters (e.g., the maximum effective distance and minimum safe contact distance of the fish repeller). This spacing must meet the following core constraints: its value must be less than twice the maximum effective distance of the fish repeller to ensure that the fish-repelling range of adjacent nodes can fully overlap, forming a continuous and comprehensive protective barrier; simultaneously, its value must be greater than the minimum safe contact distance to prevent collisions with the robot body during operation. Therefore, the management equipment determines a node spacing range with clearly defined upper and lower bounds.

[0032] Then, based on the determined pasture spatial scale and node spacing range, the management equipment calculates the required number of network nodes. This is done by discretizing the pasture boundary (e.g., the edges of a cube) according to the node spacing. By dividing the total boundary length by the node spacing and considering the node arrangement at the corners, the minimum number of nodes required to cover the boundary can be calculated. For complex shapes, this process may involve three-dimensional surface coverage calculations. It should be noted that the number of network nodes is not less than this minimum number; that is, the number of network nodes in the underwater pasture can be set with some redundancy to cope with failure situations. For example: number of network nodes = estimated number calculated based on pasture volume / single operating area + emergency number, where the emergency number can be 1%-10% of the estimated number.

[0033] The volume of the underwater ranch refers to the total three-dimensional space required to construct it. This directly determines the underwater ranch's spatial capacity and is typically determined based on the aquaculture plan, the types of organisms, and the expected yield. Its value is calculated using geometric dimensions such as length, width, and height. For example, for a cubical ranch, its volume is the cube of its side length. For instance, planning a cubical underwater ranch for salmon farming, based on the need to raise 10,000 adult salmon, would set the ranch volume at 1,000 cubic meters, corresponding to a cube side length of 10 meters.

[0034] The single working area refers to the maximum horizontal projected area that a single networked robot can effectively control or influence under ideal conditions using its onboard fish deterrent device. This area parameter is a key indicator for measuring the operational capability of an individual robot, determined by its hardware performance, particularly the maximum effective distance of the fish deterrent device. For example, if the fish deterrent device can form a circular area of ​​influence with radius R, then its single working area is πR². For instance, if the maximum effective distance of the fish deterrent device on an underwater robot is eight meters, forming an approximately circular control area, then its single working area is approximately two hundred square meters.

[0035] The estimated number refers to the initial number of networked robots calculated theoretically based on the ratio of pasture volume to single working area to achieve preliminary spatial coverage of the pasture volume. This number is a theoretical lower limit based on the principle of space filling and does not consider factors such as the specific shape of the pasture, redundancy of robot collaborative operation, and environmental disturbances. The calculation formula is: Estimated Number = Pasture Volume / (Single Working Area × Average Working Depth), or, in practical applications, it can be simplified to coverage of the horizontal projected area, i.e., Estimated Number = Pasture Base Area / Single Working Area. For example, the base area of ​​this 1000 cubic meter cube pasture is 100 square meters. Given that the single working area of ​​a single robot is 200 square meters, theoretically one robot can cover this base area. However, to form a three-dimensional barrier, vertical coverage needs to be considered. If the average working depth is 10 meters, the estimated number can be calculated as 1000 cubic meters divided by (200 square meters × 10 meters), resulting in 0.5. In this case, it needs to be rounded up according to engineering principles, or the number of nodes required to cover the entire cube surface can be directly used. The initial estimate is that eight nodes are needed to complete the basic configuration.

[0036] Finally, the management device performs iterative calculations within the feasible range of node spacing to evaluate the number of nodes, coverage uniformity, and system redundancy corresponding to different spacing values, thereby generating one or more networking strategies that can achieve the ranch construction goal while satisfying all constraints and have different focuses under different optimization goals (such as lowest cost, most uniform coverage, and highest redundancy).

[0037] For example, consider constructing a 1000-cubic-meter underwater ranch. Calculations show its side length is 10 meters. If the maximum effective distance of the underwater robot's fish deterrent is 6 meters and the minimum safe contact distance is 2 meters, then the feasible range for node spacing is between 2 and 12 meters. To achieve effective coverage of the cube's 12 edges, the management device might generate two strategies: Strategy 1 uses a larger spacing (e.g., 10 meters), requiring nodes only at 8 vertices, resulting in the fewest nodes; Strategy 2 uses a smaller spacing (e.g., 5 meters), requiring additional nodes in the middle of each edge, resulting in more nodes but providing higher protection redundancy and coverage uniformity.

[0038] S3: Obtain underwater environmental parameters and select the network starting point based on the underwater environmental parameters.

[0039] The management equipment can acquire underwater environmental parameters, including water flow velocity and direction, seabed topography, water depth distribution, and water visibility, through sensor networks or pre-stored hydrological databases. Underwater environmental parameters refer to the collective term for various physical and geographical environmental variables that directly affect robot deployment within the pre-defined deployment area. They describe the external objective conditions of the underwater operation site, aiming to ensure that the generated networking strategy and deployment plan can adapt to real sea conditions, guaranteeing operational safety and effectiveness.

[0040] For example, underwater environmental parameters include: water flow parameters, water depth parameters, seabed topography parameters, visibility, and salinity. Water flow parameters represent the speed and direction of seawater flow, directly affecting the underwater robot's navigation stability, positioning accuracy, and energy consumption. Excessive water flow speed may cause the robot to deviate from its planned route or struggle to maintain its network position. Seabed topography parameters represent the undulations, slope, and obstacle distribution of the seabed surface, used to identify suitable flat areas for deployment and avoid steep slopes, reefs, or shipwrecks that may hinder robot deployment or damage it. Water depth parameters represent the vertical distance from sea level to the seabed. These parameters are compared with operational capability parameters such as the underwater robot's maximum diving depth to ensure the entire ranch is deployed within the robot's safe operating depth range.

[0041] The network starting point refers to a specific three-dimensional spatial coordinate point determined by the management equipment within a pre-defined deployment area based on a comprehensive assessment of underwater environmental parameters. This point serves as the baseline position and initial reference point for the underwater robot swarm to begin its network deployment task. Selecting an optimal network starting point is fundamental to the smooth and efficient unfolding of the entire deployment sequence, with the goal of creating the most favorable initial conditions for subsequent deployments.

[0042] For example, the selection of the starting point for the network follows these principles: the starting point should be located in an area with relatively gentle water flow, flat terrain, and no obstacles, so that the first robot can stably and safely complete its initial positioning and stationing. The location of the starting point should facilitate the deployment of the entire network formation, usually near a key vertex or center point of the pre-defined pasture shape, so that subsequent robots can use this as a reference to expand outward according to the predetermined spacing between network nodes, efficiently constructing the entire pasture outline.

[0043] For example, underwater environmental parameters acquired by the management equipment show that the water flow velocity in the eastern part of the target area is 0.2 meters per second, and the seabed is a sandy plain, while the western area contains reefs and the water flow velocity reaches 0.5 meters per second. Based on this, the management equipment selects a specific coordinate (e.g., longitude X, latitude Y, depth Z) in the eastern area as the starting point for the network. This point has a superior environment, allowing the robot swarm to start from this point and deploy sequentially along a preset direction, gradually building a complete underwater ranch, thereby ensuring the safety of the deployment process and the rationality of the overall layout.

[0044] S4: Select a target networking strategy from at least one networking strategy, and determine multiple networking robots in the robot cluster according to the number of networking nodes, and instruct the multiple networking robots to build an underwater ranch based on the networking starting point according to the spacing between networking nodes.

[0045] In this process, after determining at least one networking strategy, the management device selects one as the final target networking strategy for execution. The selection process can be an optimization process based on multi-objective decision-making: according to preset priority rules, such as highest deployment efficiency, lowest overall energy consumption, or strongest system redundancy, each candidate networking strategy is quantitatively evaluated. Key factors considered in the evaluation include the number of networking nodes required by the strategy, the rationality of the spacing between networking nodes, and its adaptability to the current underwater environmental parameters. For example, in scenarios with limited robot resources, the management device tends to choose the strategy with the fewest networking nodes; while in environments with unstable water flow, it may prefer a strategy with smaller spacing between networking nodes, thus forming a denser and more stable network. Through weighted calculation or rule matching, the management device ultimately determines the optimal target networking strategy under the current constraints.

[0046] After the target networking strategy is determined, the management device selects a corresponding number of healthy underwater robots from its managed robot cluster, based on the number of networking nodes specified in the strategy, and designates them as the networking robots for this task. The management device then issues a collaborative deployment command to these networking robots, containing the precise coordinates of the networking starting point, the target spatial location assigned to each robot, and the required spacing between networking nodes. Upon receiving the command, the networking robots, using the networking starting point as a common spatial reference, move sequentially and precisely to their respective target locations through autonomous navigation and collaborative control, ultimately constructing an underwater ranch structure in three-dimensional underwater space that conforms to the preset shape and volume. The networking robots are equipped with fish deterrents to drive away schools of fish that approach from the outside or inside.

[0047] For example, the management device generates two networking strategies: Strategy A requires six networking nodes with a node spacing of 28 meters; Strategy B requires eight networking nodes with a node spacing of 20 meters. Given the presence of slight water flow in the deployment area and a sufficient number of available robots, the management device prioritizes network stability after deployment. Therefore, Strategy B is selected as the target networking strategy because its smaller node spacing provides stronger structural stability and redundancy. Subsequently, the management device assigns eight underwater robots from the cluster as networking robots and sends them instructions to deploy in a cubic array centered on the selected networking starting point, with a fixed spacing of 20 meters, thereby constructing a more stable underwater ranch.

[0048] It's important to note that a distributed consensus negotiation process is initiated before each networked robot can form a network. Each robot, based on a global adjustment strategy, knows its own target position and exchanges position adjustment intentions with its directly adjacent robots in the communication network. Through a specific consensus algorithm, such as using a Laplace matrix for state feedback, each robot iteratively adjusts its desired movement trajectory, causing the motion decisions of all robots to converge to a consensus state. This ensures that the robot cluster maintains a safe relative distance during movement, preventing any intersections or conflicts between the movement paths of any two robots, and preserving the network topology during dynamic adjustments. After reaching a consensus, each robot then performs position adjustments according to the negotiated, conflict-free movement trajectory.

[0049] S5: When the ranch adjustment conditions are met, adjust the attribute parameters of the underwater ranch. The aforementioned attribute parameters can be one or more of location, volume, and shape. The management device can automatically adjust the attribute parameters of the underwater ranch based on parameters monitored by the sensor network, or adjust them upon receiving external commands. For example, ranch adjustment conditions include, but are not limited to, significant changes in underwater environmental parameters, receiving a ranch change command from a user, or detecting an anomaly in the ranch's structural integrity. Subsequently, the management device recalculates and configures one or more attribute parameters of the underwater ranch based on the identified specific adjustment requirements. These attribute parameters primarily include the ranch's location, volume, and shape. During the adjustment process, the management device first re-executes the S2 calculation process based on the new attribute parameter requirements to generate a new networking strategy. Then, the management device issues adjustment commands to the relevant networked robot group, instructing them to collaboratively change the spatial configuration of the entire underwater ranch by altering their own spatial positions, thereby adapting it to the new operational requirements.

[0050] For example, the management equipment detects a strong current flowing towards the current location of the underwater ranch through environmental monitoring data. This situation meets the ranch adjustment conditions set to mitigate risks. The management equipment initiates the adjustment program, deciding to move the entire underwater ranch 50 meters upstream. Based on the new target location, the original volume, and the cube shape parameters, it calculates the new coordinates of the network node distribution and instructs all networked robots to move collaboratively to the new designated location, thus completing the overall translation of the ranch's location.

[0051] For example, if a user commands the ranch volume to be increased by 20%, the management equipment, after confirming that the command is a valid adjustment condition, will recalculate the new number and spacing of network nodes, and instruct the existing robots to combine with the newly added robots to redeploy and build a larger cubic space.

[0052] In one possible embodiment, the target networking strategy in S4 includes networking methods. These methods specify the deployment sequence and path followed by the networking robot when building an underwater ranch in three-dimensional space. The management device can select one of three networking methods based on actual task requirements. For example, the rule for selecting a networking method is: when the surface waves are small and there is no navigation interference, a top-level initial deployment is preferred. This rule fully utilizes calm surface conditions to quickly establish a baseline framework, achieving efficient deployment through a top-down construction process. When the seabed topography is complex or obstacles exist, a bottom-level initial deployment is used. This rule ensures the stability of the overall structure under complex geological conditions by first establishing a stable bottom foundation, effectively mitigating seabed risks. When rapid ranch construction is required, an intermediate-layer initial deployment is selected. This rule uses the intermediate layer as the central hub to simultaneously carry out bidirectional construction, significantly shortening the deployment cycle through parallel operations, suitable for scenarios with high time requirements.

[0053] The first approach is a top-down deployment. The management equipment controls the networked robots to first assemble at a predetermined depth in the target water area, using the network's starting point as the core, and prioritize constructing the top horizontal layer of the underwater ranch structure. Once the top layer is stable, the robot cluster then uses this top layer as a reference to vertically expand downwards, constructing each subsequent horizontal layer until the entire ranch structure is complete.

[0054] The second approach is a bottom-up deployment. The management equipment controls the networked robots to first reach a predetermined location near the seabed. Using the network's starting point as the core, they prioritize constructing the lowest horizontal layer of the underwater ranch structure. Once this bottom layer is stable, the robot swarm uses it as a solid foundation to extend vertically upwards, building each subsequent horizontal layer until the entire ranch structure is complete.

[0055] The third approach is a mid-layer initial deployment. The management equipment controls the networked robots to first assemble at a mid-depth location in the target water area, using the network's starting point as the core, and prioritize the construction of the horizontal layer structure of the underwater ranch's mid-layer. Once the mid-layer is complete, the robot cluster uses this layer as a central reference, simultaneously or sequentially expanding upwards and downwards in both vertical directions, constructing the horizontal layers above and below it in parallel or alternately, thus efficiently completing the overall ranch construction.

[0056] It should be noted that, see Figure 3 The diagram shows the starting point of the network.

[0057] The network starting point is a specific coordinate point used to establish a spatial reference base. However, before actual network deployment, the overall robot coordinate set of the initial horizontal layer containing this starting point is not uniquely determined. This means that under the same network strategy, multiple different robot spatial coordinate distribution schemes can be formed using the same starting point as a reference, all of which can meet the shape and node spacing requirements of that horizontal layer. When generating specific deployment instructions, the management device needs to select an optimal scheme from multiple feasible coordinate sets. This selection process is based on additional optimization criteria, such as selecting the scheme with the shortest overall deployment path to improve efficiency, or selecting the scheme with the highest structural stability to enhance network robustness.

[0058] See Figure 4 The diagram shown illustrates the network topology. Figure 4 In this example, the underwater ranch is shaped like a cylinder. The networking method is based on horizontal layers, meaning the underwater ranch consists of multiple horizontal layers. Within the same horizontal layer, the networked robots are at the same depth, and the distance between any two adjacent horizontal layers is equal. For example, a distance of... Figure 4 The △H shown is illustrated.

[0059] For example, in areas with complex seabed topography but relatively calm waters, management equipment may opt for a top-level initial deployment to avoid obstacles encountered by the robots when operating near the bottom. The networking robot first constructs a top-level square network with sides of 10 meters at a depth of 5 meters, centered on the network's starting point. It then descends sequentially to depths of 10 meters and 15 meters to construct the lower layers, ultimately forming a tall cubic ranch.

[0060] Conversely, in areas with large surface waves but flat seabed, management equipment may be deployed in a bottom-up, initial manner to enhance the overall structural stability. The networking robot first builds a bottom-layer network at a depth of 20 meters on the seabed as a solid foundation, and then ascends sequentially to depths of 18 meters and 16 meters to build the upper-layer structure.

[0061] When a deep, symmetrical ranch needs to be built quickly, management equipment can be deployed using a mid-layer-based approach. For example, a command robot first completes the mid-layer deployment at a depth of 15 meters, then one group of robots rises to a depth of 10 meters to build the upper layer, while another group of robots simultaneously descends to a depth of 20 meters to build the lower layer, thus significantly improving deployment efficiency.

[0062] In one possible embodiment of this application, S3: the step of acquiring underwater environmental parameters and selecting the network starting point based on the underwater environmental parameters includes: S31: Display the water environment distribution map based on pre-stored underwater environment parameters, and determine the network starting point based on the user's selection operation on the water environment distribution map.

[0063] Specifically, the management device calls upon its internally stored underwater environmental parameters and generates an intuitive water environment distribution map through a graphics rendering engine. This map visually displays the differences and distribution of underwater environmental parameters such as water flow velocity, water depth, and seabed topography at different geographical coordinates. The management device then displays this map on a user-friendly interface. By observing the map, users can comprehensively assess the environmental suitability of each area and mark what they deem ideal deployment areas on the map through interactive methods such as clicking or selecting. The management device receives and parses the user's selection, converting it into precise geospatial coordinates, and then officially designates these coordinates as the starting point for subsequent network deployment operations.

[0064] In one possible embodiment of this application, S3: the step of acquiring underwater environmental parameters and selecting the network starting point based on the underwater environmental parameters includes: S31': Instructs at least one robot in the robot swarm to perform an underwater measurement task and obtain underwater environmental parameters based on the measurement results of the underwater measurement task.

[0065] Specifically, the management equipment sends instructions to the managed robot swarm, directing at least one underwater robot with environmental awareness to perform an underwater measurement task. According to the instructions, this underwater robot performs mobile probing within a pre-defined deployment area, using its onboard sensors to systematically scan and collect data about the aquatic environment. The management equipment receives the measurement data in real time or retrieves it after the robot completes its task and is recovered. This measurement data reflects the underwater environmental parameters reflecting the actual physical conditions of the area.

[0066] S32': Based on underwater environmental parameters, select a location in the water body that meets the constraints of the aquaculture environment as the starting point for network formation.

[0067] Specifically, aquaculture environmental constraints refer to the requirements regarding the physical and geographical environment of the water body set to ensure the healthy growth of cultured organisms in underwater ranches. Aquaculture environmental constraints include one or more of the following: hydrodynamic constraints, water depth constraints, topographic constraints, and water quality constraints.

[0068] After obtaining underwater environmental parameters, the management equipment analyzes the detection area based on preset aquaculture environment constraints. The equipment analyzes the measurement data, selects qualified areas that simultaneously meet all constraints, and ultimately determines an optimal location from these qualified areas as the network starting point. This ensures that the network starting point is in an environment most conducive to aquaculture operations and stable robot deployment.

[0069] In one possible embodiment of this application, it further includes: S6: Select at least one robot from the robot cluster as a patrol robot.

[0070] Specifically, after completing the construction of the underwater ranch, the management equipment dynamically or statically designates at least one specific robot from its managed robot cluster to undertake patrol tasks. The management equipment can specify the matching degree between the robot's current state and the task. The management equipment prioritizes selecting robots that are in good working condition and have the corresponding sensing payload, setting their role as patrol robots. It is understood that the underwater robots acting as patrol robots do not participate in the ranch networking process; this embodiment distinguishes and coordinates fixed ranch protection nodes with mobile ranch internal monitoring functions, forming a dynamic and static combined monitoring system.

[0071] For example, among the underwater robots that have never participated in the fixed network, the management equipment selects a robot with sufficient power and equipped with multi-parameter water quality sensors, and configures it as a dedicated patrol robot to be responsible for subsequent monitoring of the ranch's internal environment.

[0072] S7: Monitors the aquaculture environment parameters of the underwater ranch in real time through patrol robots.

[0073] Specifically, the management equipment issues monitoring commands to the patrol robot, controlling it to cruise within the three-dimensional space defined by the underwater ranch, following a preset path or adaptive rules. During its movement, the patrol robot continuously uses its onboard sensor array to measure and sample key environmental factors in the water. The real-time collected data constitutes aquaculture environmental parameters reflecting the actual ecological environment within the ranch, and is transmitted back to the management equipment by the patrol robot, providing continuous data input for environmental assessment and decision-making.

[0074] For example, after receiving instructions, the patrol robot traverses the entire cubic ranch along a zigzag path. Its sensors continuously record water temperature, dissolved oxygen content, and pH data at different locations and send these real-time updated aquaculture environment parameters back to the management equipment.

[0075] S8: Visualize the parameters of the aquaculture environment.

[0076] Specifically, after receiving the aquaculture environment parameters transmitted back by the patrolling robot, the management equipment converts this numerical data into intuitive graphical information. The management equipment generates a visualization interface that includes various elements such as contour lines, color rendering, or dynamic curves, clearly displaying the distribution of each environmental parameter within the ranch space and its changing trends over time. This visualization interface is presented to the user through a human-computer interaction interface, enabling the user to quickly and comprehensively grasp the overall ecological status within the ranch.

[0077] For example, the management equipment will receive dissolved oxygen data and render it in a three-dimensional cube model representing an underwater ranch, using a gradient of blue to red, with blue areas representing low concentrations and red areas representing high concentrations, thereby generating a spatial distribution map of dissolved oxygen, which will then be displayed on a screen in the control center for aquaculture managers.

[0078] In one possible embodiment of this application, S5: the step of adjusting the attribute parameters of the underwater ranch when the ranch adjustment conditions are detected includes: S51: Measure the effective stock density of underwater ranches using a patrol robot.

[0079] Specifically, the management equipment assigns dedicated patrol robots within the robot swarm to perform monitoring tasks within the constructed underwater ranch space. Equipped with specific sensors, these patrol robots can cruise within the ranch waters and non-contactly measure the actual quantity or total volume of cultured organisms using image recognition or biomass detection technology. The management equipment receives and processes the data collected by the patrol robots, calculating the effective quantity or biomass of cultured organisms per unit water volume to obtain the current effective culture density of the underwater ranch. For example: Effective culture density = Effective culture volume / Underwater ranch volume. The effective culture volume represents the total volume actually occupied by individual cultured organisms within the ranch waters, estimated by the patrol robots using their detection equipment (such as sonar or optical cameras). This volume reflects the space occupied by the physical presence of the cultured organisms. The underwater ranch volume represents the volume of the entire three-dimensional enclosed space constructed by the network of robots to accommodate the cultured organisms.

[0080] S52: Determine whether the conditions for pasture adjustment are met based on the effective stock density.

[0081] In this context, the pasture adjustment condition indicates that the density exceeds a certain threshold range. The management equipment compares the measured effective density of the cultured organisms with a pre-stored density threshold range. The density threshold range defines the reasonable density interval required to maintain the healthy growth of the cultured organisms. Its upper limit is the maximum allowable density, and its lower limit is the minimum effective density. The density threshold is determined experimentally based on the species and growth stage of the cultured organisms. In this embodiment, the judgment method is as follows: if the current effective density of the cultured organisms is higher than the preset maximum allowable density, it indicates that the pasture space is overcrowded, which may lead to survival competition or water quality deterioration; if the current density is lower than the preset minimum effective density, it indicates that the pasture space utilization rate is too low. That is, when the current effective density of the cultured organisms exceeds this density threshold range, the management equipment determines that the pasture adjustment condition is met.

[0082] S53: If so, calculate the pasture volume adjustment amount based on the effective aquaculture density, generate a pasture volume adjustment strategy based on the pasture volume adjustment amount, and instruct the networked robots in the underwater pasture to adjust the volume according to the pasture volume adjustment strategy.

[0083] Specifically, once the management equipment determines that the ranch adjustment conditions are met, it initiates adjustment calculations. Based on the difference between the current effective cultured organism density and the target density, and combined with the existing ranch volume, it calculates the amount of ranch volume adjustment required to achieve the ideal density level. Subsequently, based on this volume adjustment amount and the original ranch shape parameters, the management equipment generates a new networking strategy after the target volume change. This ranch volume adjustment strategy specifies the changes in the spacing and / or number of networking nodes required to achieve the new volume. Finally, the management equipment issues adjustment commands to the group of networking robots currently constituting the underwater ranch, controlling the robots to change their relative positions to execute the new networking strategy, thereby collectively expanding or shrinking the underwater ranch volume. For example: Volume adjustment amount = (Current density - Target density) × Current volume / Target density. Here, the current density refers to the effective cultured organism density of the underwater ranch at the current moment, measured and calculated by the patrolling robots. This parameter reflects the real-time space occupancy of the cultured organisms within the ranch before adjustment and is a dynamically changing value based on actual measurements. Target density refers to the ideal effective density of cultured organisms pre-set to ensure healthy growth and maintain optimal aquaculture efficiency. This parameter is a relatively fixed baseline or optimal range value that the management equipment sets based on the cultured species, growth stage, and management strategy. Current volume refers to the actual spatial volume of the underwater ranch formed by the networked robot cluster before volume adjustment. It is the target and calculation basis for volume adjustment operations. Volume adjustment amount refers to the specific numerical change in the underwater ranch volume required to achieve the target density. A positive value for this parameter indicates that the ranch volume needs to be expanded; a negative value indicates that the ranch volume needs to be reduced.

[0084] If the management equipment determines that the conditions for adjusting the underwater ranch are not met based on the effective stock density, i.e., the current density is within the preset reasonable range, the management equipment will maintain the existing underwater ranch operation and will not initiate the volume adjustment procedure.

[0085] In one possible embodiment of this application, S5: the step of adjusting the attribute parameters of the underwater ranch when the ranch adjustment conditions are detected includes: S51: When receiving a pasture volume adjustment command input by the user, determine that the pasture adjustment conditions are met.

[0086] The management equipment continuously monitors user commands through its human-machine interface. When it receives a user-initiated command to adjust the volume of the underwater ranch, the management equipment determines that one of the preset ranch adjustment conditions has been met. This user-initiated command-based triggering mechanism empowers operators to proactively intervene in the system's operation based on actual aquaculture needs or changes in management strategies.

[0087] For example, if a livestock manager observes that the livestock are growing well and plans to expand the scale of farming, they can click the "Expand Size" function on the control interface of the management equipment and submit the request. Upon receiving this instruction, the management equipment will determine that the conditions for adjusting the livestock are met.

[0088] For example, when aquaculture managers determine that they need to catch fish, they click the "Shrink Size" function on the control interface of the management equipment and submit the request. After receiving the instruction, the management equipment determines that the conditions for adjusting the ranch are met.

[0089] S52: Parse the pasture volume adjustment command to obtain the pasture volume adjustment amount.

[0090] Specifically, the management equipment decodes and analyzes the received user commands, which include specific volume adjustment requirements. The equipment extracts key numerical parameters, namely the pasture volume adjustment amount. This adjustment amount may be an absolute target volume value, or it may be an increase or decrease relative to the current volume. Through calculation, the management equipment ultimately converts this into a precise target volume value, providing accurate input for generating the adjustment strategy.

[0091] S53: Generate a pasture volume adjustment strategy based on the pasture volume adjustment amount, and instruct the networked robots in the underwater pasture to adjust the volume according to the pasture volume adjustment strategy.

[0092] Specifically, based on the analyzed ranch volume adjustment amount and combined with the original shape parameters of the underwater ranch, the management equipment initiates the strategy generation process. The management equipment recalculates the required spacing or number of network nodes to meet the new volume requirements, thus forming a specific ranch volume adjustment strategy. This strategy specifies in detail the new spatial coordinates that each networked robot needs to move to. Subsequently, the management equipment synchronously issues adjustment commands to all relevant networked robots, controlling them to change their positional relationships according to the new spatial layout requirements, ultimately achieving precise adjustment of the underwater ranch volume.

[0093] In one possible embodiment of this application, the ranch volume adjustment strategy is a specific implementation plan devised by the management equipment to achieve precise changes in the spatial volume of the underwater ranch. It specifies how to change the configuration of the ranch in three-dimensional space by controlling the coordinated displacement of networked robots, thereby achieving the purpose of volume adjustment.

[0094] Depending on different aquaculture needs and environmental conditions, this strategy primarily supports the following adjustment models: See Figure 5 As shown, Figure 5 The adjustment mode shown above is: only adjust the size of one or more horizontal layers in the ranch, while keeping the distance between the horizontal layers unchanged.

[0095] The underwater ranch underwent a comprehensive adjustment: while maintaining the overall shape of the ranch, all its three-dimensional dimensions were proportionally and synchronously changed. The management equipment recalculated and instructed all networked robots to move synchronously along the line connecting them to the original geometric center point, thus achieving a proportional scaling up or down of the ranch. This adjustment method altered the ranch's volume while preserving its original geometry.

[0096] Adjusting the depth of multiple horizontal layers in an underwater ranch: Independently changing the vertical depth of one or more specific horizontal layers within the ranch without altering the shape and area of ​​the layers themselves. Management equipment generates commands that cause the network of robots constituting the target horizontal layer to rise or descend synchronously in the vertical direction, thereby changing the vertical distribution structure of that layer and even the entire ranch to adapt to different water temperatures, light levels, or current conditions at different depths.

[0097] See Figure 5 As shown, Figure 5 The adjustment mode shown below is as follows: Adjusting the depth of a specific horizontal layer in the underwater ranch: The management equipment precisely calculates the required depth for that specific layer and instructs only the networked robots constituting that layer to perform vertical displacement, while keeping the positions of the networked robots in all other horizontal layers fixed. This method allows for precise control of local water layers within the ranch.

[0098] In one possible embodiment, S5: the step of adjusting the attribute parameters of the underwater ranch when the ranch adjustment conditions are detected includes: S51: Determine whether the aquaculture environment parameters of the underwater ranch meet the constraints of the cultured organisms.

[0099] The management equipment receives aquaculture environment parameters monitored by the patrolling robot and compares and analyzes this real-time data with pre-existing constraints on the cultured organisms. These constraints are safety ranges for key environmental factors set to ensure the healthy growth of the cultured organisms. The management equipment checks each aquaculture environment parameter to ensure it falls within its corresponding constraint range.

[0100] S52: If yes, the conditions for ranch adjustment are met.

[0101] When the management equipment determines that the current environmental conditions do not meet the constraints of the cultured organisms, it indicates that the conditions for triggering adjustments to the underwater ranch have been met. This means that the environment at the current location of the ranch is no longer suitable for continued aquaculture operations, and the ranch location must be changed to avoid the adverse effects of the unfavorable environment on the cultured organisms.

[0102] S53: Select a migration location outside the underwater ranch that meets the constraints of the cultured organisms based on the measurement results of the patrol robot.

[0103] The management equipment controls a patrol robot to conduct environmental surveys of the waters surrounding the current underwater ranch. The patrol robot extends its detection range beyond the original ranch boundary, measuring environmental parameters in the surrounding area. Based on the measurement data transmitted back by the patrol robot, the management equipment filters out candidate waters where all environmental parameters meet the constraints for aquaculture. Subsequently, according to preset rules, such as selecting the area closest to the current ranch or the area with the best environment, the management equipment ultimately determines a specific coordinate as the target location for ranch relocation.

[0104] S54: Based on the offset between the current location and the migration location of the underwater ranch, send a position adjustment command to the networked robots in the underwater ranch, instructing the underwater ranch to move as a whole.

[0105] The management device calculates the offset between the current geographic center coordinates of the underwater ranch and the selected migration location coordinates. This offset is a three-dimensional vector containing direction and distance. The management device generates a location adjustment command, which includes the offset. This command is then synchronously sent to all networked robots. Upon receiving the command, each networked robot moves collaboratively in the same direction and distance, enabling the underwater ranch as a whole to migrate smoothly to the new target location.

[0106] It should be noted that if the management equipment determines, based on the aquaculture environment parameters, that the current environment meets the constraints for the cultured organisms—that is, all key environmental parameters are within the preset safe range—then the management equipment determines that the adjustment conditions for triggering the relocation of the underwater ranch are not met. In this case, the management equipment maintains the underwater ranch at its current location and does not initiate the relocation procedure.

[0107] In one possible embodiment of this application, S5: the step of adjusting the attribute parameters of the underwater ranch when the ranch adjustment conditions are detected includes: S51: When receiving a location adjustment instruction from the user, determine that the ranch adjustment conditions are met.

[0108] Specifically, the management equipment receives user-initiated commands regarding changes to the spatial location of the underwater ranch through its human-machine interface. When such commands are successfully received and verified as valid, the management equipment identifies them as ranch adjustment trigger signals. This means that the user, based on their actual needs or external circumstances, decides to initiate the ranch relocation process, and the management equipment responds to this decision, entering a readiness state.

[0109] For example, if aquaculture managers learn from a weather forecast that the current ranch area is about to encounter severe sea conditions, they can trigger an "emergency relocation" command on the control terminal to avoid losses. Upon receiving this command, the management equipment immediately confirms that the ranch adjustment conditions are met.

[0110] S52: Parse the position adjustment instruction to obtain the migration position.

[0111] Specifically, the management equipment parses and processes the received user commands, extracting key information about the target location. This command may directly contain the precise coordinates of the target location, or it may provide descriptive information such as relative orientation and distance. Through calculation and transformation, the management equipment ultimately outputs a specific three-dimensional spatial coordinate point, which is the target location to which the underwater ranch will migrate.

[0112] S53: Based on the offset between the current location and the migration location of the underwater ranch, send a position adjustment command to the networked robots in the underwater ranch, instructing the underwater ranch to move as a whole.

[0113] Specifically, the management device calculates the offset between the current geographic center coordinates of the underwater ranch and the selected migration location coordinates. This offset is a three-dimensional vector containing direction and distance. The management device generates a location adjustment command, which includes the offset. This command is then synchronously sent to all networked robots. Upon receiving the command, each networked robot moves collaboratively in the same direction and distance, enabling the underwater ranch as a whole to migrate smoothly to the new target location.

[0114] In one possible embodiment of this application, it further includes: A1: When a malfunction is detected in the networked robot in the underwater ranch, the corresponding icon position of the malfunctioning robot is determined on the displayed ranch topology diagram, and a fault prompt is given based on the icon position.

[0115] Specifically, the management equipment continuously monitors the operational status of all networked robots. When a communication link is interrupted or a fault alarm signal is received, confirming a malfunction in a networked robot, the management equipment immediately locates the fault in the ranch topology diagram displayed on its graphical user interface. This topology diagram is a visual representation of the underwater ranch's spatial structure and the connection relationships between robot nodes. Based on the malfunctioning robot's unique identifier, the management equipment locks the corresponding graphical element position in the diagram and immediately activates a prominent visual alarm mechanism, such as changing the icon color to red and making it flash continuously, while simultaneously displaying detailed fault status information in the sidebar of the interface, thus providing operators with intuitive and clear fault prompts.

[0116] A2: Determine the adjacent normal robots based on the location of the faulty robot.

[0117] Specifically, after identifying and locating the faulty robot, the management equipment analyzes the associated nodes based on pre-stored underwater ranch network topology data. The management equipment queries the direct connections of the faulty robot within the network structure, identifying one or more normally functioning network robots that are spatially adjacent to it in the original networking strategy and together form the local boundary or surface of the ranch. These identified normal robots are the main entities responsible for executing subsequent fault-tolerant adjustment actions.

[0118] A3: Instructs normal robots to perform local contraction and update the pasture topology graph.

[0119] Specifically, the management device generates a local adjustment command and sends it to the aforementioned identified adjacent normal robots. The command instructs these normal robots to make small movements along a predetermined network topology direction, moving away from the fault point or towards the interior of the structure—essentially performing a local contraction. This action aims to partially close the network gap created by the robot failure, maintaining the continuity and effectiveness of the remaining pasture structure as much as possible. After the normal robots confirm the displacement, the management device updates the pasture topology data in memory based on their new position information and re-renders the pasture topology diagram on the graphical user interface to accurately reflect the adjusted network configuration.

[0120] In one possible embodiment of this application, it further includes: B1: When a fault is detected in the networked robot in the underwater ranch, select the corresponding number of backup robots from the robot cluster based on the number of faulty robots.

[0121] Specifically, after detecting a failure in a networked robot, the management device initiates a fault recovery process. The management device first counts the number of failed networked robots, and then selects backup robots from its managed robot cluster that are available and match the number of failed robots. This selection process comprehensively considers the backup robot's current location, energy reserves, and the degree to which its hardware configuration matches the failed robot's role, ensuring that the selected backup robot can quickly and effectively take over the responsibilities of the failed robot.

[0122] For example, the management equipment detects that two networked robots have lost mobility due to thruster failure. The system then selects two backup robots with sufficient power, matching models, and located closest to the fault point from the backup robot resource pool in the standby area, ready to perform the replacement task.

[0123] B2: Instruct the backup robot to replace the faulty robot in its new location.

[0124] Specifically, based on the spatial coordinates of the faulty robot within the underwater ranch network structure, the management equipment calculates the target replacement location for each backup robot. The management equipment then sends replacement instructions containing their respective target location information to all selected backup robots. Upon receiving the instructions, the backup robots autonomously navigate to the designated coordinates and remain stably stationed at that location, thus physically and functionally replacing the faulty robot. Simultaneously, the management equipment updates the node's status from faulty to normal within the system and records this maintenance operation.

[0125] For example, the management device sends precise latitude, longitude, and depth coordinates to the selected backup robot, which represent the original location of the network node occupied by the faulty robot. The backup robot navigates to this point according to the instructions and accurately positions itself, successfully integrating into the underwater ranch's network structure and restoring the ranch network to its complete form. The management device then marks the node as normal in the system interface.

[0126] It should be noted that this application prioritizes backup replacement and triggers local contraction when the number of underwater robots in the robot cluster is insufficient.

[0127] In one possible embodiment, the management device monitors the operational status of each networked robot by maintaining a periodic communication connection with it. For example, the management device sends a status query signal (heartbeat inquiry) to all networked robots at preset fixed time intervals; each normally functioning networked robot, upon receiving this signal, immediately returns an acknowledgment signal containing its basic status information (heartbeat response) to the management device. This periodic question-and-answer communication process constitutes the heartbeat mechanism.

[0128] The management device starts timing from the moment a heartbeat query is sent. If no heartbeat response is received from a networked robot within the preset response time window, the communication link with that robot is considered potentially faulty. The management device will not determine a fault based on a single timeout, but will initiate a retry procedure, sending heartbeat queries multiple times. Only if no valid response is received from the robot after several consecutive queries can the management device definitively confirm that the networked robot has malfunctioned.

[0129] In one possible embodiment of this application, S1: the step of obtaining the underwater ranch setting conditions includes: S11: Calculate pasture shape parameters and pasture volume parameters based on aquaculture scale parameters; or Specifically, the management equipment receives input parameters related to the scale of the cultured organisms, reflecting the planned number of organisms or total biomass. The equipment combines these scale parameters with coefficients such as the volume requirement per unit of cultured organism to derive the required total volume of the underwater ranch, i.e., the ranch volume parameter. Simultaneously, the equipment further determines a suitable three-dimensional shape that matches this volume and is easy to construct and maintain, thus outputting the ranch shape parameter.

[0130] S12: Obtain the pasture shape parameters and pasture volume parameters based on the parameters entered by the user on the configuration interface.

[0131] Specifically, the management device receives key parameters directly set by the user through its graphical configuration interface. Based on their specific needs and design intentions, the user explicitly inputs the desired three-dimensional geometry and specific spatial volume of the underwater ranch in the designated input area of ​​the interface. The management device directly reads and records these user-defined input values, using them as the shape and volume parameters for constructing the underwater ranch. This method grants users the highest level of autonomy in customizing the ranch design.

[0132] In some embodiments of this application, the networked robot has anti-disturbance capabilities after the underwater ranch is established. This application also includes: D1: The network robot monitors the offset between its current location coordinates and its deployment location coordinates in real time.

[0133] Specifically, the networked robot monitors its real-time 3D spatial coordinates underwater. Simultaneously, the robot internally stores the coordinates of its designated deployment position, issued by the management device. The networked robot periodically calculates the vector difference between its current real-time position and the target deployment position in 3D space. This vector difference includes both horizontal distance deviation and vertical depth deviation, collectively referred to as position offset. Through this continuous monitoring, the networked robot can perceive in real time whether it has deviated from its designated position due to environmental disturbances such as water flow.

[0134] D2: If the offset is greater than the offset threshold, the network robot calculates the thruster's propulsion parameters based on the offset.

[0135] Specifically, the networked robot has a preset offset threshold, which defines the maximum allowable deviation from its deployment position. This offset threshold must be greater than the inherent error of the positioning system itself, typically set to 2 to 3 times the positioning accuracy. This avoids unnecessary frequent adjustments due to measurement noise, ensuring that correction actions are only initiated when a real, significant displacement occurs. The robot compares the magnitude of the real-time calculated position offset (i.e., the overall deviation distance) with this threshold. If the overall deviation distance exceeds this threshold, the current offset is deemed unacceptable, and an anti-disturbance process is initiated to return to the original position. Subsequently, the robot's control unit, based on the specific direction and magnitude of the position offset and in conjunction with a dynamic model, calculates the magnitude and direction of the thrust required to counteract the offset. For example, the networked robot is equipped with at least two horizontal thrusters and at least four vector thrusters, and the thrust parameters can be specifically allocated to each horizontal thruster and vector thruster. The horizontal thrusters are primarily responsible for providing forward, backward, and lateral thrust within the horizontal plane to correct horizontal position deviations; the vector thrusters, by changing the thrust direction, provide both horizontal and vertical thrust components to accurately correct depth deviations and assist in adjusting the robot's posture. If the offset is less than the offset threshold, the anti-disturbance process is not initiated.

[0136] D3: Indicates that the thruster moves based on the propulsion parameters.

[0137] Specifically, the networked robot issues specific drive commands to each designated thruster. These commands include the target rotational speed or thrust value for each horizontal thruster, and the target thrust value and thrust vector direction for each vector thruster. Upon receiving the commands, all thrusters work together to generate a precisely controlled resultant force and torque, driving the networked robot to move in the direction that counteracts the positional offset. This process continues until the offset between the robot's real-time position coordinates and its deployment position coordinates is eliminated within the aforementioned threshold, at which point the thrusters will return to an attitude-maintaining idle state or a shut-off state.

[0138] In one possible embodiment of this application, it further includes: E1: The patrol robot generates a bait delivery instruction; wherein, the bait delivery instruction generation includes: periodic generation, generation when the position interval between two adjacent feeding positions is greater than the interval threshold, or generation when the density of farmed organisms in a specified depth area is greater than the density threshold.

[0139] Specifically, the patrolling robot autonomously determines when to initiate the feeding task. The generation of feeding instructions is mainly based on three triggering conditions. The first is periodic generation: the patrolling robot automatically creates feeding instructions at preset fixed time intervals to achieve timed feeding. The second is generation based on spatial location: when the patrolling robot detects that the distance between its current feeding location and the last feeding location exceeds a set interval threshold during patrol, it generates a new feeding instruction to ensure the uniformity of food distribution in space. The third is generation based on biological distribution: when the patrolling robot detects that the real-time density of aquatic organisms in the designated water depth exceeds a preset density threshold, it generates a feeding instruction to achieve precise feeding on demand.

[0140] E2: The patrol robot responds to the bait delivery command and measures the density of farmed organisms in water within a preset depth range.

[0141] Specifically, the patrol robot locates the specific water area associated with the command, and then uses its onboard acoustic or optical detection equipment to perform a needle scan within a preset depth range. By actively emitting detection signals and receiving echoes, or by acquiring and analyzing images, the patrol robot can obtain information on the distribution of aquatic organisms within that water layer, and calculate the average density of aquatic organisms within that preset depth range at the current moment.

[0142] E3: The patrol robot calculates the feed weight based on the density of the farmed organisms and activates the built-in feed dispensing device to dispense feed according to the feed weight.

[0143] Specifically, the patrol robot first estimates the total biomass of the cultured organisms in the area based on the measured density of the cultured organisms and the volume of the water in which they are distributed. Then, it multiplies this total biomass by the basal feeding rate to obtain the approximate daily total feed requirement for the cultured organisms in that area. Finally, according to a preset feeding strategy (e.g., feeding four times a day), the total daily requirement is divided by the number of feedings to determine the weight of feed required per feeding for this task. The basal feeding rate represents the weight of feed required per unit weight of cultured organisms at a specific growth stage, and this data is preset based on the nutritional requirements of the cultured species. The effective total culture volume is determined by the density of the cultured organisms measured by the patrol robot and the volume of the water space in which they are distributed, and is used to estimate the total biomass of the cultured organisms in the target area.

[0144] In one possible embodiment, the netless underwater ranch can be divided into multiple zones at different depths; The steps for a patrol robot to measure the effective stock density in a netless underwater ranch include: Measure the local culture density in each zone; Based on the weights configured for each zone, the overall culture density is obtained by weighted averaging of the local culture densities. Based on the species being farmed, the corresponding target zones are determined from multiple zones; Measure the density of the target cultured organisms in the target zone; The overall stock density and the target stock density are sent to the management terminal via the waterborne base station; If the overall density of farmed organisms is greater than the first density threshold and the density of the target farmed organisms is greater than the second density threshold, then the conditions for farm expansion are met. If the overall stock density is less than the third density threshold and the target stock density is less than the fourth density threshold, the conditions for pasture shrinkage are met.

[0145] Specifically, the underwater ranch of this application is pre-divided into multiple zones of different depths in its spatial planning. Following instructions from the management equipment, the patrol robot sequentially enters each zone to conduct monitoring. Using its onboard detection equipment, it systematically scans the distribution of cultured organisms within each zone. By analyzing echo signals or image data, it calculates the number of cultured organisms per unit volume in each zone, i.e., the local cultured organism density of that zone. For example, the underwater ranch is divided into three depth zones: a shallow water zone (0-10 meters), a medium water zone (10-20 meters), and a deep water zone (20-30 meters). The patrol robot sequentially surveys these three areas, measuring the local cultured organism densities as follows: 3 organisms / cubic meter in the shallow water zone, 5 organisms / cubic meter in the medium water zone, and 2 organisms / cubic meter in the deep water zone.

[0146] The patrolling robot calculates a weighted average of the measured local stock density based on the weighting coefficients pre-configured for each zone by the management equipment, thus obtaining the overall stock density representing the entire farm's stocking status. The weighting coefficients take into account factors such as water volume, stocking importance, and historical output of each zone. Continuing the example, assuming the weighting coefficients for the three zones are 0.3, 0.5, and 0.2 respectively, the patrolling robot calculates the overall stock density as: 3 fish / m³ × 0.3 + 5 fish / m³ × 0.5 + 2 fish / m³ × 0.2 = 3.9 fish / m³.

[0147] For specific farmed species, management equipment determines corresponding target zones based on their ecological habits. Upon receiving relevant instructions, the patrol robot conducts focused monitoring within the designated target zone, acquiring distribution data of specific farmed organisms in that area through enhanced scanning to calculate the target organism density. For example, for the primarily farmed salmon, the management equipment identifies a 10-20 meter deep mid-water area as the target zone based on their activity characteristics. The patrol robot then performs intensive scanning in this area, measuring the target salmon density at 5.5 fish per cubic meter.

[0148] The patrolling robot transmits the calculated overall culture density and the measured target culture density to the management terminal via the data transmission channel of the waterborne base station. Upon receiving this data, the management terminal compares and analyzes it against multiple preset density thresholds. When the overall culture density is greater than the first density threshold and the target culture density is greater than the second density threshold, the ranch expansion condition is met; when the overall culture density is less than the third density threshold and the target culture density is less than the fourth density threshold, the ranch contraction condition is met.

[0149] Please see Figure 6 As shown, in one embodiment, a construction device for a netless underwater ranch is provided, the device comprising: The acquisition module 601 is used to acquire the underwater ranch setting conditions and the underwater robot's operational capability parameters. The underwater ranch setting conditions include ranch shape parameters and ranch volume parameters. The generation module 602 is used to generate at least one networking strategy based on the underwater ranching settings and operational capability parameters; the networking strategy includes: the number of networking nodes and the spacing between networking nodes. Select module 603 to acquire underwater environmental parameters and select the network starting point based on the underwater environmental parameters; The control module 604 is used to select a target networking strategy among at least one networking strategy, and to determine multiple networking robots in the robot cluster according to the number of networking nodes, and to instruct the multiple networking robots to build an underwater ranch based on the networking starting point according to the spacing between networking nodes. The adjustment module 605 is used to adjust the attribute parameters of the underwater ranch when the ranch adjustment conditions are met; wherein the attribute parameters include one or more of location, volume and shape.

[0150] In one possible embodiment, the target networking strategy further includes: networking method.

[0151] Specifically, the networking method is as follows: the top layer of the underwater ranch is built from the network starting point, and then each horizontal layer is built vertically downwards from the top layer; or the bottom layer of the underwater ranch is built from the network starting point, and then each horizontal layer is built vertically upwards from the bottom layer; or the middle layer of the underwater ranch is built from the network starting point, and each horizontal layer is built vertically upwards or downwards from the middle layer as a reference.

[0152] In one possible embodiment, the steps performed by the selection module 603 to acquire underwater environmental parameters and select the network starting point based on the underwater environmental parameters include: Display a water environment distribution map based on pre-stored underwater environmental parameters, and determine the network starting point based on the user's selection operation on the water environment distribution map; or Instruct at least one robot in the robot swarm to perform an underwater measurement task and obtain underwater environmental parameters based on the measurement results of the underwater measurement task; Based on underwater environmental parameters, a location in the water body that meets the constraints of the aquaculture environment is selected as the starting point for network formation.

[0153] In one possible embodiment, it also includes: A monitoring module is used to select at least one robot as a patrol robot in the robot swarm. The underwater ranch's aquaculture environment parameters are monitored in real time using patrol robots; It also provides a visual representation of aquaculture environment parameters.

[0154] In one possible embodiment, the step of adjusting the attribute parameters of the underwater ranch when the ranch adjustment conditions are detected by the adjustment module 605 includes: The effective stock density of underwater ranches is measured using a patrol robot; Determine whether the conditions for pasture adjustment are met based on the effective stock density; If so, calculate the ranch volume adjustment amount based on the effective aquaculture density, generate a ranch volume adjustment strategy based on the ranch volume adjustment amount, and instruct the networked robots in the underwater ranch to adjust the volume according to the ranch volume adjustment strategy.

[0155] In one possible embodiment, the step of adjusting the attribute parameters of the underwater ranch when the ranch adjustment conditions are detected by the adjustment module 605 includes: When receiving a user's input command to adjust the pasture volume, determine if the pasture adjustment conditions are met; Parse the pasture volume adjustment command to obtain the pasture volume adjustment amount; The system generates a pasture volume adjustment strategy based on the amount of pasture volume adjustment, and instructs the networked robots in the underwater pasture to adjust their volume according to the pasture volume adjustment strategy.

[0156] In one possible embodiment, the step of adjusting the attribute parameters of the underwater ranch when the ranch adjustment conditions are detected by the adjustment module 605 includes: Determine whether the constraints on the cultured organisms are met based on the parameters of the aquaculture environment. If so, the conditions for pasture adjustment are met; Based on the measurement results of the patrol robot, a migration location that meets the constraints of the cultured organisms is selected outside the underwater ranch. Based on the offset between the current location and the relocation location of the underwater ranch, a position adjustment command is sent to the networked robots in the underwater ranch, instructing the underwater ranch to move as a whole.

[0157] In one embodiment, a management device is provided, which may be a client, and its internal structure diagram may be as follows: Figure 7 As shown, the management device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used to communicate with an external server via a network connection. When the computer program is executed by the processor, it implements client-side functions or steps of a method for constructing a network-free underwater ranch.

[0158] In one embodiment, a management device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to perform the following steps: Obtain the underwater ranch setting conditions and the underwater robot's operational capability parameters. The underwater ranch setting conditions include at least the ranch shape parameters and the ranch volume parameters. At least one networking strategy is generated based on the underwater ranching settings and operational capability parameters; the networking strategy includes at least: the number of networking nodes and the spacing between networking nodes; Acquire underwater environmental parameters and select the network starting point based on the underwater environmental parameters; Select a target networking strategy from at least one networking strategy, and determine multiple networking robots in the robot cluster according to the number of networking nodes, and instruct the multiple networking robots to build an underwater ranch based on the networking starting point according to the spacing between networking nodes. When the conditions for adjusting the underwater ranch are met, the attribute parameters of the underwater ranch are adjusted; these attribute parameters can be one or more of location, volume, and shape.

[0159] This application utilizes a netless underwater ranch constructed with an underwater robot swarm, effectively reducing the risk of fish escape due to net cage damage. Robot nodes can dynamically adjust their positions according to wind and wave conditions, significantly improving the ranch's resistance to wind and waves and its environmental adaptability. The netless structure promotes natural water exchange, effectively reducing the accumulation of residual feed and excrement in the aquaculture area. Combined with the intelligent adjustment of the ranch's location and shape by the robots, the aquaculture area can be rotated and renewed, thereby significantly mitigating the ecological impact on the local sea area. Managers can dynamically adjust the ranch's spatial layout, volume, and geometry according to aquaculture needs, realizing a transformation from static, fixed aquaculture to dynamic, reconfigurable aquaculture, flexibly adapting to various different scenarios.

[0160] In one embodiment, a computer-readable storage medium is provided that stores a computer program, which, when executed by a processor, performs the following steps: Obtain the underwater ranch setting conditions and the underwater robot's operational capability parameters. The underwater ranch setting conditions include at least the ranch shape parameters and the ranch volume parameters. At least one networking strategy is generated based on the underwater ranching settings and operational capability parameters; the networking strategy includes at least: the number of networking nodes and the spacing between networking nodes; Acquire underwater environmental parameters and select the network starting point based on the underwater environmental parameters; Select a target networking strategy from at least one networking strategy, and determine multiple networking robots in the robot cluster according to the number of networking nodes, and instruct the multiple networking robots to build an underwater ranch based on the networking starting point according to the spacing between networking nodes. When the conditions for adjusting the underwater ranch are met, the attribute parameters of the underwater ranch are adjusted. These attribute parameters can be one or more of the following: location, volume, and shape.

[0161] This application utilizes a netless underwater ranch constructed with an underwater robot swarm, effectively reducing the risk of fish escape due to net cage damage. Robot nodes can dynamically adjust their positions according to wind and wave conditions, significantly improving the ranch's resistance to wind and waves and its environmental adaptability. The netless structure promotes natural water exchange, effectively reducing the accumulation of residual feed and excrement in the aquaculture area. Combined with the intelligent adjustment of the ranch's location and shape by the robots, the aquaculture area can be rotated and renewed, thereby significantly mitigating the ecological impact on the local sea area. Managers can dynamically adjust the ranch's spatial layout, volume, and geometry according to aquaculture needs, realizing a transformation from static, fixed aquaculture to dynamic, reconfigurable aquaculture, flexibly adapting to various different scenarios.

[0162] It should be noted that the functions or steps that the computer-readable storage medium or management device can achieve are described in the relevant descriptions of the server side and client side in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0163] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0164] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0165] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for constructing a netless underwater ranch, characterized in that, include: The underwater ranch setting conditions and the underwater robot's operational capability parameters are obtained. The underwater ranch setting conditions include ranch shape parameters and ranch volume parameters. At least one networking strategy is generated based on the underwater ranch setting conditions and the operational capability parameters; The networking strategy includes at least: the number of networking nodes and the spacing between networking nodes; Acquire underwater environmental parameters and select the network starting point based on the underwater environmental parameters; Select a target networking strategy from the at least one networking strategy, and determine multiple networking robots in the robot cluster according to the number of networking nodes, and instruct the multiple networking robots to construct an underwater ranch based on the networking starting point according to the spacing between networking nodes. When the conditions for adjusting the underwater ranch are met, the attribute parameters of the underwater ranch are adjusted. The attribute parameters include one or more of the following: location, volume, and shape.

2. The method for constructing a netless underwater ranch according to claim 1, characterized in that, The target networking strategy further includes: a networking mode, wherein the networking mode is: The underwater ranch is constructed with the network starting point as the top layer, and then, starting from the top layer, horizontal layers are constructed sequentially downwards in the vertical direction; or The underwater ranch is constructed using the network starting point as the bottom layer, and then, starting from the bottom layer, horizontal layers are constructed sequentially in the vertical direction; or The intermediate layer of the underwater ranch is constructed from the network starting point. Based on the intermediate layer, each horizontal layer is constructed sequentially in the vertical direction, either upwards or downwards.

3. The method for constructing a netless underwater ranch according to claim 1 or 2, characterized in that, The acquisition of underwater environmental parameters and the selection of the network starting point based on the underwater environmental parameters include: Display a water environment distribution map based on pre-stored underwater environment parameters, and determine the network starting point based on the user's selected operation on the water environment distribution map; or The robot cluster is instructed to perform an underwater measurement task and obtain underwater environmental parameters based on the measurement results of the underwater measurement task. Based on the underwater environmental parameters, a location in the water body that meets the constraints of the aquaculture environment is selected as the starting point for network formation.

4. The method for constructing a netless underwater ranch according to claim 1, characterized in that, Also includes: At least one robot is selected from the robot cluster as a patrol robot; the Xunyou robot does not participate in the network formation. The patrol robot monitors the aquaculture environment parameters of the underwater ranch in real time. And the parameters of the breeding environment are visualized.

5. The method for constructing a netless underwater ranch according to claim 4, characterized in that, When the ranch adjustment conditions are detected, the attribute parameters of the underwater ranch are adjusted, including: The effective stock density of the underwater ranch is measured using the aforementioned patrol robot; Determine whether the pasture adjustment conditions are met based on the effective stock density; If so, calculate the ranch volume adjustment amount based on the effective aquaculture density, generate a ranch volume adjustment strategy based on the ranch volume adjustment amount, and instruct the networked robots in the underwater ranch to adjust the volume according to the ranch volume adjustment strategy.

6. The method for constructing a netless underwater ranch according to claim 4, characterized in that, When the ranch adjustment conditions are detected, the attribute parameters of the underwater ranch are adjusted, including: When receiving a user's input command to adjust the pasture volume, determine if the pasture adjustment conditions are met; The ranch volume adjustment command is parsed to obtain the ranch volume adjustment amount; A pasture volume adjustment strategy is generated based on the pasture volume adjustment amount, and the networked robots in the underwater pasture are instructed to adjust their volume according to the pasture volume adjustment strategy.

7. The method for constructing a netless underwater ranch according to claim 4, characterized in that, When the ranch adjustment conditions are detected, the attribute parameters of the underwater ranch are adjusted, including: Determine whether the constraints on the cultured organisms are met based on the aforementioned aquaculture environment parameters; If yes, the ranch adjustment conditions are met; Based on the measurement results of the patrol robot, a migration location that meets the constraints of the cultured organisms is selected outside the underwater ranch. Based on the offset between the current location and the migration location of the underwater ranch, a position adjustment command is sent to the networked robots in the underwater ranch, instructing the underwater ranch to move as a whole.

8. A device for constructing a netless underwater ranch, characterized in that, include: The acquisition module is used to acquire the underwater ranch setting conditions and the underwater robot's operational capability parameters. The underwater ranch setting conditions include ranch shape parameters and ranch volume parameters. The generation module is used to generate at least one networking strategy based on the underwater ranch setting conditions and the operation capability parameters; The networking strategy includes: the number of networking nodes and the spacing between networking nodes; Select a module to acquire underwater environmental parameters and select the network starting point based on the underwater environmental parameters; The control module is configured to select a target networking strategy among the at least one networking strategy, and determine multiple networking robots in the robot cluster according to the number of networking nodes, and instruct the multiple networking robots to construct an underwater ranch based on the networking starting point according to the spacing between networking nodes. An adjustment module is used to adjust the attribute parameters of the underwater ranch when the ranch adjustment conditions are met. The attribute parameters include one or more of the following: location, volume, and shape.

9. A management device, characterized in that, The computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method for constructing a netless underwater ranch as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the method for constructing a netless underwater ranch as described in any one of claims 1 to 7.

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