A seabed node laying and recovering method and device, electronic equipment and storage medium

Abstract

The application discloses a seabed node laying and recovering method and device, electronic equipment and a storage medium. The method comprises the following steps: in response to a first laying instruction, a basket is lowered to a working area by a mother ship; the basket is loaded with a plurality of seabed nodes; in response to a second laying instruction, the seabed nodes are grabbed by a floating robot cluster and then released to each target laying point in the working area; and in response to a recovering instruction, the seabed nodes at the target laying points are recovered based on the floating robot cluster and the basket. The seabed nodes are initially laid to the working area by the basket, and then the seabed nodes are grabbed and released to each target laying point in the working area by the coordinated control of the floating robot cluster. The seabed nodes can be recovered by the floating robot cluster and the basket in turn. The application can effectively save the control path of the robot, realize efficient and accurate laying and recovering of the seabed nodes, and can be widely applied to the technical field of data processing.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a method, apparatus, electronic device and storage medium for deploying and recovering seabed nodes. Background Technology

[0002] Seismic exploration is a core method in geophysical surveys, and marine seismic exploration and seafloor time-lapse seismic surveys are important tools for investigating and precisely exploiting seafloor oil and gas resources. OBN, short for Ocean Bottom Node, is a multi-component seismograph located on the seabed that can independently acquire and record seismic signals. Unlike exploration cables, OBNs, as independent detectors, are free from cable constraints, allowing for flexible deployment on the seabed, more accurate positioning, and higher-quality data acquisition. However, the current methods of OBN deployment and retrieval are a major bottleneck restricting their large-scale adoption. Shallow-sea OBNs are often deployed and retrieved via cables, i.e., OBNs are connected in series, making node spacing and location relatively easy to control precisely. Deep-sea OBN deployment and retrieval are primarily achieved through ROV (Remotely Operated Vehicle), i.e., the deployment and retrieval of OBNs within the seabed collection device are achieved through remote human control of the ROV. However, because ROVs are cabled, only one ROV can be operated at a time, resulting in extremely low efficiency. There are also cases of developing flying nodes, where each node has its own floating function to achieve autonomous positioning and adjustment. However, such flying nodes are only suitable for a few applications, and the scenarios are generally only scientific research and investigation, not suitable for large-scale oil and gas exploration and investigation. Summary of the Invention

[0003] The main objective of this application is to provide a method, apparatus, electronic device, and storage medium for deploying and recovering seabed nodes, aiming to solve at least one problem in the prior art.

[0004] To achieve the above objectives, one aspect of this application proposes a method for deploying and recovering seabed nodes, the method comprising:

[0005] In response to the first deployment command, the basket was lowered to the work area via the mother ship; the basket was pre-loaded with multiple seabed nodes.

[0006] In response to the second deployment command, the floating robot swarm will capture seabed nodes and release them to various target deployment points in the work area.

[0007] In response to the recovery command, the system uses a cluster of floating robots and a gondola to recover the seabed nodes at the target deployment point.

[0008] In some embodiments, the floating robot swarm includes multiple floating robots, and the second deployment command includes communication commands and allocation commands. In response to the second deployment command, the floating robot swarm captures seabed nodes and releases them to various target deployment points in the work area, including the following steps:

[0009] In response to communication commands, the grid coordinates of the work area are transmitted to the cloud management system via the mother ship. The cloud management system then divides the work area into a spiral path based on a preset planning algorithm to generate a dynamic ocean current compensation trajectory. The work area is further divided into multiple subdomains using the region decomposition method.

[0010] In response to the allocation command, the working unit corresponding to each subdomain is constructed according to the floating robot cluster, so that the working unit can grab the seabed node from the basket and release it to the target deployment point of the corresponding subdomain.

[0011] The work unit includes a first number of floating robots.

[0012] In some embodiments, the working unit retrieves a seabed node from the basket and releases it to a target deployment point in the corresponding subdomain, including the following steps:

[0013] The long baseline positioning system assists the work unit in navigating to the basket, and the floating robot of the work unit grabs the seabed node from the basket;

[0014] In response to the feedback signal that the floating robot has completed its grasping, the working unit is assisted in navigating to the target deployment point in the subdomain based on the long baseline positioning system.

[0015] In some embodiments, each seabed node is equipped with an ID-coded reflective tag, and the floating robot is equipped with a vision component and a bionic mechanical claw. The floating robot of the working unit grasps the seabed node from the basket, including the following steps:

[0016] The floating robot in the work unit uses a bionic mechanical claw to grasp the seabed node in the basket;

[0017] The visual components are used to visually identify the reflective markings of the captured seabed nodes and determine the ID code corresponding to the subdomain.

[0018] In some embodiments, the floating robot is equipped with a multi-beam sonar, and the operation unit is guided to the target deployment point in the subdomain based on a long baseline positioning system, including the following steps:

[0019] The floating robots of the work unit are guided to the target deployment point in the subdomain by diving in a diamond formation.

[0020] During the navigation of the floating robots to the target deployment point, all floating robots in the swarm perform overall path planning through a cooperative collision avoidance algorithm. Each floating robot performs the following operations:

[0021] Use the real-time location of the floating robot as the target location;

[0022] A digital elevation model of the seabed at the target location is constructed using multibeam sonar based on a preset frequency;

[0023] The seabed digital elevation model and real-time positioning are matched with the feature point cloud constructed by the map in real time, and the real-time position is corrected by the long baseline positioning system based on the real-time matching results.

[0024] Determine whether the corrected real-time position has reached the target deployment point. If it has not reached the target deployment point, take the real-time position of the floating robot at the next time point along the spiral path as the target position, and return to execute the step of constructing the seabed digital elevation model of the target position using multibeam sonar based on a preset frequency, until the real-time position reaches the target deployment point.

[0025] In some embodiments, the retrieval command includes a robot retrieval command and a basket retrieval command. In response to the retrieval command, the seabed node at the target deployment point is retrieved based on the floating robot swarm and the basket, including the following steps:

[0026] In response to the robot retrieval command, a cluster of floating robots will capture the seabed nodes of each target deployment point in the work area and transfer them to the basket.

[0027] When the seabed nodes loaded in the gondola reach full load, in response to the gondola recovery command, the seabed nodes on the gondola are recovered to the mother ship.

[0028] In some embodiments, a swarm of floating robots is used to retrieve seabed nodes from various target deployment points in the work area and place them into a gondola, including the following steps:

[0029] The coordinates of the target deployment point of each seabed node are transmitted to the floating robot cluster via communication.

[0030] The target deployment point is approached by a cluster of floating robots using a spiral expansion search pattern.

[0031] When a certain floating robot identifies a seabed node, it will use the corresponding floating robot as the target floating robot;

[0032] Among them, the floating robot is equipped with a laser polarization imaging component, which is used to identify and verify seabed nodes.

[0033] The target floating robot and the second-closest floating robot in the floating robot cluster form a swarm cooperation unit;

[0034] The swarm cooperative unit uses a swarm cooperative mode to capture the identified seabed nodes and transfer them to the basket.

[0035] In some embodiments, the method further includes the following steps:

[0036] In response to the surfacing command, the target floating robot in the floating robot cluster is controlled to rise to the area where the mother ship is located, so that the mother ship can retrieve the target floating robot.

[0037] To achieve the above objectives, another aspect of this application proposes a seabed node deployment and recovery device, the device comprising:

[0038] The first deployment module is used to lower the basket to the work area via the mother ship in response to the first deployment command; wherein, the basket is pre-loaded with multiple seabed nodes;

[0039] The second deployment module is used to respond to the second deployment command by using a cluster of floating robots to grab seabed nodes and release them to various target deployment points in the work area.

[0040] The recovery module is used to recover seabed nodes at the target deployment point in response to recovery commands, based on a cluster of floating robots and a gondola.

[0041] In some embodiments, the apparatus further includes:

[0042] The surfacing module is used to respond to surfacing commands and control the target floating robot in the floating robot cluster to rise to the area where the mother ship is located, so that the mother ship can recover the target floating robot.

[0043] To achieve the above objectives, another aspect of the embodiments of this application proposes an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the aforementioned method.

[0044] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned method.

[0045] To achieve the above objectives, another aspect of this application provides a computer program product, including a computer program that, when executed by a processor, implements the aforementioned method.

[0046] The embodiments of this application include at least the following beneficial effects: This application provides a method, apparatus, electronic device, storage medium, and program product for deploying and recovering seabed nodes. This solution, in response to a first deployment command, lowers a basket to the work area via a mother ship; wherein, the basket is pre-loaded with multiple seabed nodes; in response to a second deployment command, a swarm of floating robots grasps the seabed nodes and releases them to various target deployment points in the work area; in response to a recovery command, the seabed nodes at the target deployment points are recovered based on the floating robot swarm and the basket. This application first lowers the seabed nodes to the work area using the basket, then uses the coordinated control of the floating robot swarm to grasp and release the seabed nodes to various target deployment points in the work area. Simultaneously, the seabed nodes can be recovered sequentially using the floating robot swarm and the basket. This application effectively saves on robot control paths, achieving efficient and accurate deployment and recovery of seabed nodes. Attached Figure Description

[0047] Figure 1 This is a schematic diagram of an implementation environment for the seabed node deployment and recovery method provided in this application embodiment;

[0048] Figure 2 This is a schematic flowchart of a method for deploying and recovering seabed nodes provided in an embodiment of this application;

[0049] Figure 3 This is a schematic diagram illustrating the unfolding process of step S200 provided in the embodiments of this application;

[0050] Figure 4 This is a schematic diagram of the deployment process provided in this application embodiment, in which the working unit grabs the seabed node from the basket and releases it to the target deployment point in the corresponding subdomain;

[0051] Figure 5 This is a schematic diagram of the deployment process of a floating robot using a work unit to grab a seabed node from a basket, as provided in an embodiment of this application.

[0052] Figure 6 This is a schematic diagram of the unfolding process of step S300 provided in the embodiments of this application;

[0053] Figure 7 This is a schematic diagram of the deployment process provided in this application embodiment, in which a cluster of floating robots is used to capture seabed nodes of various target deployment points in the work area and place them into a basket.

[0054] Figure 8 This is a schematic diagram illustrating an application scenario of a seabed node deployment and recovery method provided in this application embodiment;

[0055] Figure 9 This is a schematic diagram of the structure of a seabed node deployment and recovery device provided in an embodiment of this application;

[0056] Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0058] It is understood that the terms “first,” “second,” etc., used in this application may be used herein to describe various concepts, but unless otherwise stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words “if,” “when,” or “in response to a determination” as used herein may be interpreted as “when…” or “when…” or “in response to a determination.”

[0059] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.

[0060] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0061] In related technologies, the current deployment and retrieval methods of OBNs are a major bottleneck restricting their large-scale application. In shallow waters, OBN deployment and retrieval are often achieved through cables, i.e., connecting OBNs in series, where node spacing and location are relatively easy to control precisely. In deep waters, the primary method for OBN deployment and retrieval is through ROVs, i.e., remotely controlling ROVs to deploy and retrieve OBNs within the seabed collection device. However, because ROVs are cabled, only one ROV can be operated at a time, resulting in extremely low efficiency.

[0062] In view of this, this application provides a method for deploying and recovering seabed nodes. This method involves, in response to a first deployment command, lowering a basket from a mother ship to the work area; wherein the basket is pre-loaded with multiple seabed nodes; in response to a second deployment command, a swarm of floating robots grasps the seabed nodes and releases them to various target deployment points in the work area; in response to a recovery command, the seabed nodes at the target deployment points are recovered based on the floating robot swarm and the basket. This application first lowers the seabed nodes to the work area using the basket, then uses the coordinated control of the floating robot swarm to grasp and release the seabed nodes to various target deployment points in the work area. Simultaneously, the seabed nodes can be recovered sequentially using the floating robot swarm and the basket. This application effectively saves robot control paths, achieves efficient and accurate deployment and recovery of seabed nodes, and effectively solves the problem of low efficiency in conventional ROV OBN deployment.

[0063] It is understood that the seabed node deployment and recovery method provided in this application can be applied to any computer device with data processing and computing capabilities, and this computer device can be various types of terminals or servers. When the computer device in the embodiment is a server, the server is an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. Optionally, the terminal can be a smartphone, tablet, laptop, or desktop computer, but it is not limited to these.

[0064] like Figure 1 The diagram shown is a schematic representation of an implementation environment provided in an embodiment of this application. (Refer to...) Figure 1 The implementation environment includes at least one terminal 102 and a server 101. The terminal 102 and the server 101 can be connected via a network, either wirelessly or via a wired connection, to complete data transmission and exchange.

[0065] Server 101 can be a standalone physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0066] Additionally, server 101 can also be a node server in a blockchain network. Blockchain is a novel application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms.

[0067] Terminal 102 can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, etc., but is not limited to these. Terminal 102 and server 101 can be directly or indirectly connected via wired or wireless communication, and this embodiment of the application does not impose any limitations.

[0068] For example, based on Figure 1 The implementation environment shown in this application embodiment provides a method for deploying and recovering seabed nodes. The following description uses the application of this method in server 101 as an example. It can be understood that this method can also be applied in terminal 102. Specifically, terminal 102 or server 101 can be used to execute the relevant data processing logic of the method in this application to implement the corresponding method flow.

[0069] Reference Figure 2 , Figure 2 This is an optional flowchart of the seabed node deployment and recovery method provided in the embodiments of this application. The execution subject of the seabed node deployment and recovery method can be any of the aforementioned computer devices (including servers or terminals). Figure 2 The method may include, but is not limited to, steps S100 to S300.

[0070] In step S100, in response to the first deployment command, the basket is lowered to the work area via the mother ship;

[0071] The basket is pre-loaded with multiple seabed nodes;

[0072] For example, in some specific implementations, the OBN is released to the seabed. Specifically, the mother ship uses a basket method to deploy multiple OBNs to the seabed at once.

[0073] In step S200, in response to the second deployment command, the floating robot swarm grabs the seabed node and releases it to various target deployment points in the work area.

[0074] It should be noted that the floating robot swarm includes multiple floating robots, and the second deployment command includes communication commands and allocation commands. In some embodiments, such as... Figure 3As shown, step S200 may include the following steps: S210, in response to a communication command, the grid coordinates of the work area are transmitted to the cloud management system via the mother ship, so that the cloud management system divides the work area into a spiral path based on a preset planning algorithm to generate a dynamic ocean current compensation trajectory, and divides the work area into multiple sub-domains using a region decomposition method; S220, in response to an allocation command, a work unit corresponding to each sub-domain is constructed according to the floating robot cluster, so that the work unit grabs the seabed node from the basket and releases it to the target deployment point of the corresponding sub-domain; wherein, the work unit includes a first number of floating robots.

[0075] For example, in some specific implementations, task division and robot diving are carried out. Specifically, the mother ship transmits the grid coordinates of the operation area (e.g., 5km × 5km) via satellite communication. The cloud management system automatically divides the area into a spiral path and generates a dynamic current-compensated trajectory. The operation area is divided into multiple sub-domains using a region decomposition method. Each sub-domain consists of 3 to 5 robots (the number can be set according to actual needs) forming an operation unit. Then, the operation unit is used as a transfer component to grab seabed nodes from the basket and release them to the target deployment point in the corresponding sub-domain.

[0076] In some embodiments, such as Figure 4 As shown, the operation unit can retrieve a seabed node from the basket and release it to the target deployment point in the corresponding subdomain, which may include the following steps: S221, the operation unit navigates to the basket with the assistance of a long baseline positioning system, and the floating robot of the operation unit retrieves the seabed node from the basket; S222, in response to the feedback signal of the floating robot's retrieval completion, the operation unit navigates to the target deployment point in the subdomain with the assistance of the long baseline positioning system.

[0077] In some embodiments, each seabed node is equipped with an ID-coded reflective tag, and the floating robot is equipped with vision components and a bionic mechanical claw, such as... Figure 5 As shown, the process of using a floating robot in the work unit to grab a seabed node from a basket may include the following steps: S2211, using a bionic mechanical claw to grab the seabed node in the basket; S2212, using a vision component to visually identify the reflective markings of the grabbed seabed node and determine the ID code corresponding to the subdomain.

[0078] Specifically, by determining the ID code of the seabed nodes deployed in each sub-domain of the work area, the exploration data of each sub-domain can be specifically organized for subsequent exploration and surveys of the work area.

[0079] For example, in some specific implementations, the robot uses an acoustic positioning network (long baseline positioning system) for positioning and navigation. Each OBN (On-Board Network) has a specially designed reflective tag on top, forming a unique ID code. Specifically, the robot identifies and grasps the OBNs, which are then sequentially identified and grasped by the robot according to task assignment. The robot's optical recognition system can integrate technologies such as 532nm laser scanning and polarization imaging, maintaining extremely high recognition accuracy even in turbid water (visibility <1m).

[0080] In some embodiments, the floating robot is equipped with a multi-beam sonar, and the operation unit is assisted in navigating to the target deployment point in the subdomain based on a long baseline positioning system. This may include the following steps: using a diamond formation diving method to navigate the floating robot of the operation unit to the target deployment point in the subdomain along a spiral path;

[0081] For example, in some specific implementations, after receiving the assignment instructions, the robot swarm descends in a diamond formation (with a spacing of 15-20m, and the specific spacing parameters can be set according to actual needs), and synchronously updates the inertial navigation data and acoustic positioning grid.

[0082] During the navigation of the floating robots to the target deployment point, all floating robots in the swarm perform overall path planning through a cooperative collision avoidance algorithm. Each floating robot performs the following operations: using the real-time position of the floating robot as the target position; constructing a digital elevation model of the seabed at the target position using multibeam sonar based on a preset frequency; performing real-time matching between the digital elevation model of the seabed and the feature point cloud constructed by real-time positioning and mapping, and correcting the real-time position using a long baseline positioning system based on the real-time matching results; determining whether the corrected real-time position has reached the target deployment point. If it has not reached the target deployment point, the real-time position of the floating robot at the next time point along the spiral path is used as the target position, and the process returns to the step of constructing a digital elevation model of the seabed at the target position using multibeam sonar based on a preset frequency, until the real-time position reaches the target deployment point.

[0083] For example, in some specific implementations, the OBN is precisely deployed. Specifically, after the robot grasps the OBN, a forward-looking multibeam sonar (120° field of view) constructs a digital elevation model (DEM) of the seabed at a frequency of 10Hz, and matches it in real time with SLAM (Simultaneous Localization and Mapping) feature point cloud (accuracy ±0.3m). The position is then corrected in real time using a long baseline system. When the target deployment point is reached (error <0.5m), the release mechanism is triggered (working pressure 60MPa), and the OBN is deployed with an accuracy of ±2cm. The positioning data is simultaneously recorded to the cloud, and the terrain adaptive algorithm automatically adjusts the release angle to ensure that the fit between the OBN base and the seabed plane is greater than a preset threshold (e.g., 95%).

[0084] Step S300: In response to the recovery command, the seabed node at the target deployment point is recovered based on the floating robot cluster and the gondola.

[0085] It should be noted that the retrieval command includes robot retrieval commands and basket retrieval commands. In some embodiments, such as... Figure 6 As shown, step S300 may include the following steps: S310, in response to the robot recovery command, the floating robot cluster grabs the seabed nodes of each target deployment point in the work area and puts them into the basket; S320, when the seabed nodes loaded in the basket reach full load, in response to the basket recovery command, the seabed nodes on the basket are recovered to the mother ship.

[0086] In some embodiments, such as Figure 7 As shown, the process of using a swarm of floating robots to retrieve seabed nodes from various target deployment points in the work area and transfer them to a gondola can include the following steps: S311, transmitting the coordinates of the target deployment point for each seabed node to the floating robot swarm via communication; S312, using a spiral expansion search mode to approach the target deployment point through the floating robot swarm; S313, when a floating robot identifies a seabed node, designating that floating robot as the target floating robot; wherein, the floating robot is equipped with a laser polarization imaging component, and the floating robot uses the laser polarization imaging component to identify and verify the seabed node; S314, forming a swarm cooperative unit by combining the target floating robot with the second-closest floating robot in the floating robot swarm; S315, using a swarm cooperative mode to retrieve the identified seabed node from the swarm cooperative unit and transfer it to the gondola.

[0087] In some exemplary embodiments, the robot identifies and grasps the OBN (On-Board Novel). Specifically, the cloud-based task management system assigns the retrieval task to the robot based on grid division. The robot descends in formation to the task block, activates the OBN's acoustic transponder (37.5kHz band), and approaches the target using a spiral expansion search mode (radius increment 1.5m / revolution). It then uses 532nm laser polarization imaging (92% recognition rate @ 5NTU turbidity) for triple verification, thereby identifying the OBN. Simultaneously, the target coordinates are shared in real time through an underwater acoustic communication network. The robot that detects the target sends a broadcast signal to three neighboring robots (the specific number can be adjusted according to actual needs), forming a "swarm collaboration" mode. After identification, a bionic mechanical claw (8 degrees of freedom, grasping force 25kg) is used to grip the OBN.

[0088] In addition, OBN collection and retrieval are handled by a robot that, after successfully grabbing the OBN, triggers an automatic return procedure when fully loaded. Following a Z-shaped path to avoid ocean current interference, the robot deploys the OBN into a basket. An optical camera is installed on the basket, and shipboard operators determine if it is fully loaded. Once fully loaded, a command is sent to the robot via the underwater acoustic communication network to stop operation and ascend back to the surface. The deck then retrieves the basket, completing the OBN retrieval operation.

[0089] In some embodiments, the method may further include the following steps: in response to an ascent command, controlling a target floating robot in the floating robot cluster to ascent to the area where the mother ship is located, so that the mother ship can recover the target floating robot.

[0090] For example, in some specific implementations, the robot's surfacing and recovery is specifically achieved by the cloud-based task management system issuing a surfacing command via underwater acoustic communication (a technology for sending and receiving information underwater). After receiving the command, the robot cluster rises to the sea surface, where manual operations retrieve it to the deck, where it can then be maintained, recharged, and performed other operations.

[0091] To explain in detail the principles of the technical solution of this application, the overall process of this application will be described below with reference to some specific embodiments. It is easy to understand that the following is an explanation of the technical principles of this application and should not be regarded as a limitation of this application.

[0092] First, it's important to clarify that seismic exploration is a core method of geophysical surveys, and marine seismic exploration and seafloor time-lapse seismic surveys are crucial tools for investigating and precisely extracting seafloor oil and gas resources. OBN, short for Ocean Bottom Node, is a multi-component seismograph located on the seabed that can independently acquire and record seismic signals. Unlike exploration cables, OBNs, acting as independent detectors, are free from cable constraints, allowing for flexible deployment on the seabed, more accurate positioning, and higher-quality data acquisition. However, the current methods of OBN deployment and retrieval are a significant bottleneck limiting their large-scale adoption. Shallow-sea OBNs are often deployed and retrieved via cables, i.e., OBNs are connected in series, making node spacing and location relatively easy to control precisely. Deep-sea OBN deployment and retrieval primarily rely on ROVs (Remotely Operated Vehicles), where ROVs are remotely controlled to deploy and retrieve OBNs within the seabed collection device. However, because ROVs are cabled, only one ROV can be operated at a time, resulting in extremely low efficiency. There are also cases of developing flying nodes, where each node has its own floating function to achieve autonomous positioning and adjustment. However, such flying nodes are only suitable for a few applications, and the scenarios are generally only scientific research and investigation, not suitable for large-scale oil and gas exploration and investigation.

[0093] Currently, the deployment and retrieval methods of OBNs are a major bottleneck restricting their large-scale adoption. In shallow waters, OBN deployment and retrieval are often achieved through cables, i.e., connecting OBNs in series, where node spacing and location are relatively easy to control precisely. In deep waters, the primary method for OBN deployment and retrieval is through ROVs, i.e., remotely controlling ROVs to deploy and retrieve OBNs within the seabed collection device. However, because ROVs are cabled, only one ROV can be operated at a time, resulting in extremely low efficiency.

[0094] In view of this, this application proposes a method for deploying and recovering seabed nodes, which can achieve precise and efficient deployment and recovery of deep-sea seabed OBNs based on a swarm of floating robots and a cooperative control method, thus solving the problem of low efficiency in deploying OBNs using conventional ROVs.

[0095] like Figure 8 The diagram shown illustrates an application scenario of seabed node deployment and recovery according to this application. The scenario includes a mother ship 100, a gondola 200, and a cluster of floating robots 300 (illustrated using only one label). The bottom line represents the seabed. Specifically, the method embodiment of this application can achieve the following operations:

[0096] First, it should be noted that this application is based on deep-sea floating robots and their swarms to achieve precise and efficient deployment and retrieval of seabed OBNs. The deployment process involves placing the OBN into the seabed in one go via a basket. Multiple robots use an acoustic positioning network (long baseline positioning system) for positioning and navigation, dive to the seabed, identify and grab the OBN from the basket, and deploy the OBN to the seabed according to the task block division and autonomous path planning. The retrieval process involves multiple robots equipped with optical guidance and autonomous identification. According to the task division, they autonomously identify and grab the OBN, and retrieve and collect it into the basket to achieve retrieval.

[0097] In some specific implementation scenarios, the embodiments of this application can be applied to the following system architecture, which includes the following modules: (1) a cluster of floating robots equipped with high-precision inertial navigation units, with a single robot load capacity ≥50kg and a battery life of 72 hours; (2) a distributed acoustic positioning network, using frequency-orthogonal LFM (linear frequency modulation) signals, with a positioning accuracy of 0.1% slant range; (3) a cloud-based task management system to realize real-time three-dimensional operation monitoring. Multiple robots, through cooperative collision avoidance algorithms, such as the improved ORCA (optimal reciprocal collision avoidance) model, enable 20 robots to operate safely within a 50m range. Based on the above architecture, the operation steps of the method of this application can be implemented as follows:

[0098] 1) Step 1: OBNs are released to the seabed. Specifically, the mother ship uses a basket method to release multiple OBNs to the seabed at once. Each OBN is equipped with a special reflective tag on top, forming a unique ID code.

[0099] 2) Step Two: Task Division and Robot Dive. Specifically, the mothership transmits the grid coordinates of the work area (e.g., 5km × 5km) via satellite communication. The cloud management system automatically divides the area into a spiral path, generating a dynamic current-compensated trajectory. The work area is divided into multiple sub-domains using a region decomposition method, with each sub-domain consisting of 3 to 5 robots forming a work unit. After receiving the assigned instructions, the robot swarm dives in a diamond formation (spaced 15-20m apart), synchronously updating inertial navigation data and acoustic positioning grid.

[0100] 3) Step Three: Robot Identifies and Grabs OBNs. Specifically, the robot identifies and grasps the OBNs in the basket sequentially through task allocation. The optical recognition system integrates 532nm laser scanning and polarization imaging technology, maintaining a 92% recognition accuracy rate even in turbid water (visibility <1m).

[0101] 4) Step Four: Precise OBN Deployment. Specifically, after the robot grasps the OBN, its forward-looking multibeam sonar (120° field of view) constructs a digital elevation model (DEM) of the seabed at a frequency of 10Hz. This is then matched in real-time with SLAM (Simultaneous Localization and Mapping) feature point clouds (accuracy ±0.3m), and the position is corrected in real-time using a long baseline system. Upon reaching the target deployment point (error <0.5m), the release mechanism is triggered (working pressure 60MPa), completing the OBN deployment with an accuracy of ±2cm. Simultaneously, positioning data is recorded to the cloud, and a terrain-adaptive algorithm automatically adjusts the release angle to ensure that the OBN base adheres to the seabed surface with a fit greater than 95%.

[0102] 5) Step Five: Robot Ascent and Recovery. Specifically, the cloud-based task management system issues an ascent command via underwater acoustic communication (a technology for sending and receiving information underwater). After receiving the command, the robot cluster rises to the surface, and manual labor retrieves it to the deck for charging.

[0103] 6) Step Six: Robot Identification and Grasp of OBN. Specifically, the cloud-based task management system assigns retrieval tasks to robots based on grid division. Robots descend in formation (same as in Step Two) to the task area, activate the OBN's acoustic transponder (37.5kHz band), and approach the target using a spiral expansion search mode (radius increment 1.5m / revolution). This is combined with 532nm laser polarization imaging (92% recognition rate @ 5NTU turbidity) for triple verification, thus identifying the OBN. Simultaneously, the target coordinates are shared in real-time via the underwater acoustic communication network. The robot that detects the target sends a broadcast signal to the three nearest robots, forming a "swarm collaboration" mode. After identification, a bionic mechanical claw (8 degrees of freedom, grasping force 25kg) is used to grip the OBN.

[0104] 7) Step Seven: OBN Collection and Recovery. After the robot successfully grabs the OBN, the fully loaded robot triggers an automatic return procedure, avoiding ocean current interference along a Z-shaped path, and deploys the OBN into the basket. An optical camera is installed on the basket, and the ship's control personnel determine whether the basket is fully loaded. Once fully loaded, a command is sent to the robot via the underwater acoustic communication network to stop the operation and surface for return. Then, the deck retrieves the basket, completing the OBN recovery operation.

[0105] In some specific application scenarios, when the OBN is full of gondolas, it can be recovered via deck-mounted electro-optical armored cables. Correspondingly, the deployment of the gondola is completed by lowering the deck-mounted electro-optical armored cables. Acoustic beacons are installed on the gondolas, and the robot identifies and locates itself through the acoustic beacons. Optical cameras can also be installed on the gondolas, allowing shipboard operators to determine whether the gondolas are fully loaded. Once fully loaded, the robot is controlled to stop operating, surface, and return via underwater acoustic communication. Then, the deck-mounted gondola is retrieved to complete the OBN recovery operation.

[0106] In summary, the technical solution of this application achieves precise and efficient deployment and retrieval of deep-sea OBNs through a swarm of floating robots and a cooperative control method. This solves the problems of low efficiency in conventional ROV operations and the inability to widely apply flight nodes, significantly reducing exploration costs and shortening operation cycles. Furthermore, this application, through multi-source sensor fusion and distributed swarm control technology, significantly improves operational efficiency compared to traditional ROVs.

[0107] like Figure 9 As shown in the figure, this application embodiment also provides a seabed node deployment and recovery device 900, which can implement the above-mentioned method. The device includes:

[0108] The first deployment module 901 is used to lower the basket to the work area via the mother ship in response to the first deployment command; wherein, the basket is pre-loaded with multiple seabed nodes;

[0109] The second deployment module 902 is used to respond to the second deployment command by using a cluster of floating robots to grab seabed nodes and release them to various target deployment points in the work area.

[0110] The recovery module 903 is used to recover the seabed nodes at the target deployment point based on the floating robot cluster and the basket in response to the recovery command.

[0111] In some embodiments, the apparatus further includes:

[0112] The surfacing module is used to respond to surfacing commands and control the target floating robot in the floating robot cluster to rise to the area where the mother ship is located, so that the mother ship can recover the target floating robot.

[0113] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0114] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0115] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0116] like Figure 10 As shown, Figure 10 The hardware structure of an electronic device 1000 according to another embodiment is illustrated. The electronic device 1000 includes:

[0117] The processor 1001 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (aSIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application.

[0118] The memory 1002 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RaM). The memory 1002 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1002 and is called and executed by the processor 1001 using the network node population optimization method of the embodiments of this application.

[0119] Input / output interface 1003 is used to implement information input and output;

[0120] The communication interface 1004 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0121] Bus 1005 transmits information between various components of the device (e.g., processor 1001, memory 1002, input / output interface 1003, and communication interface 1004);

[0122] The processor 1001, memory 1002, input / output interface 1003 and communication interface 1004 are connected to each other within the device via bus 1005.

[0123] The electronic device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0124] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0125] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0126] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0127] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0128] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0129] The seabed node deployment and retrieval method, apparatus, electronic device, storage medium, and program product provided in this application embodiment, in response to a first deployment command, lowers a basket to the work area via a mother ship; wherein, the basket is pre-loaded with multiple seabed nodes; in response to a second deployment command, a swarm of floating robots grasps the seabed nodes and releases them to various target deployment points in the work area; in response to a retrieval command, the seabed nodes at the target deployment points are retrieved based on the swarm of floating robots and the basket. This application first lowers the seabed nodes to the work area in a preliminary unified manner via the basket, and then grasps and releases the seabed nodes to various target deployment points in the work area through the coordinated control of the swarm of floating robots. Simultaneously, the seabed nodes can be retrieved sequentially via the swarm of floating robots and the basket. This application can effectively save robot control paths and achieve efficient and accurate deployment and retrieval of seabed nodes.

[0130] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0131] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0132] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0133] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0134] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0135] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0136] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0137] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0138] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0139] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0140] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for deploying and recovering seabed nodes, characterized in that, The method includes the following steps: In response to the first deployment command, the basket is lowered to the work area via the mother ship; wherein, the basket is pre-loaded with multiple seabed nodes; In response to the second deployment command, the floating robot swarm captures the seabed node and releases it to various target deployment points in the work area; The floating robot swarm comprises multiple floating robots, and the second deployment command includes communication and allocation commands. The step of responding to the second deployment command by having the floating robot swarm capture the seabed node and release it to various target deployment points in the operational area includes the following steps: In response to the communication command, the grid coordinates of the work area are transmitted to the cloud management system via the mother ship, so that the cloud management system can divide the work area into a spiral path based on a preset planning algorithm to generate a dynamic ocean current compensation trajectory, and divide the work area into multiple subdomains using the region decomposition method. In response to the allocation instruction, a working unit corresponding to each subdomain is constructed according to the floating robot cluster, so that the working unit can grab the seabed node from the basket and release it to the target deployment point of the corresponding subdomain; The operating unit includes a first number of the floating robots; the operating unit retrieves the seabed node from the basket and releases it to the target deployment point corresponding to the subdomain, including the following steps: The work unit navigates to the basket with the assistance of a long baseline positioning system, and the floating robot of the work unit retrieves the seabed node from the basket; In response to the feedback signal that the floating robot has completed its grasping action, the working unit is assisted in navigating to the target deployment point in the subdomain based on the long baseline positioning system. The floating robot is equipped with a multi-beam sonar, and the navigation of the work unit to the target deployment point in the subdomain based on the long baseline positioning system includes the following steps: The floating robots of the work unit are navigated to the target deployment point in the subdomain by using a diamond-shaped formation diving method and following the spiral path; During the navigation of the floating robots to the target deployment point, all the floating robots in the cluster perform overall path planning through a cooperative collision avoidance algorithm, and each floating robot performs the following operations: The real-time position of the floating robot is used as the target position; The multibeam sonar is used to construct a digital elevation model of the seabed at the target location based on a preset frequency; The seabed digital elevation model and real-time positioning are matched with the feature point cloud constructed by the map in real time, and the real-time position is corrected using the long baseline positioning system based on the result of the real-time matching. Determine whether the corrected real-time position has reached the target deployment point. If it has not reached the target deployment point, take the real-time position of the floating robot at the next time point along the spiral path as the target position, and return to execute the step of using the multibeam sonar to construct the seabed digital elevation model of the target position based on a preset frequency, until the real-time position reaches the target deployment point. In response to a recovery command, the seabed node at the target deployment point is recovered using the floating robot cluster and the gondola.

2. The method according to claim 1, characterized in that, Each of the seabed nodes is equipped with a reflective tag with an ID code. The floating robot is equipped with a vision component and a bionic mechanical claw. The floating robot, through the working unit, grasps the seabed node from the basket, including the following steps: The floating robot in the work unit uses the bionic mechanical claw to grab the seabed node in the basket; The visual component is used to visually identify the reflective markings of the captured seabed node to determine the ID code corresponding to the subdomain.

3. The method according to claim 1, characterized in that, The retrieval instructions include robot retrieval instructions and basket retrieval instructions. In response to these retrieval instructions, the seabed node at the target deployment point is retrieved based on the floating robot cluster and the basket, including the following steps: In response to the robot retrieval command, the floating robot cluster retrieves the seabed nodes of each of the target deployment points in the work area into the basket; When the seabed nodes loaded in the gondola reach full load, in response to the gondola recovery command, the seabed nodes on the gondola are recovered to the mother ship.

4. The method according to claim 3, characterized in that, The process of using the floating robot cluster to retrieve the seabed nodes of each target deployment point in the work area to the basket includes the following steps: The coordinates of the target deployment point of each of the aforementioned seabed nodes are transmitted to the floating robot cluster via communication. The floating robot cluster approaches the target deployment point using a spiral expansion search pattern. When a certain floating robot identifies the seabed node, the corresponding floating robot will be designated as the target floating robot; The floating robot is equipped with a laser polarization imaging component, which is used to identify and verify the seabed nodes. The target floating robot and the second number of floating robots in the floating robot cluster that are closest to the target floating robot constitute a swarm cooperative unit; The swarm cooperative unit uses a swarm cooperative mode to capture the seabed node it identifies and transfer it to the basket.

5. The method according to any one of claims 1 to 4, characterized in that, The method further includes the following steps: In response to a surface command, the target floating robot in the floating robot cluster is controlled to surface to the area where the mother ship is located, so that the mother ship can retrieve the target floating robot.

6. A seabed node deployment and recovery device, characterized in that, The device includes: The first deployment module is used to lower the basket to the work area via the mother ship in response to the first deployment command; wherein the basket is pre-loaded with multiple seabed nodes; The second deployment module is used to respond to the second deployment command by using a cluster of floating robots to grab the seabed node and release it to various target deployment points in the work area. The floating robot swarm comprises multiple floating robots, and the second deployment command includes communication and allocation commands. The step of responding to the second deployment command by having the floating robot swarm capture the seabed node and release it to various target deployment points in the operational area includes the following steps: In response to the communication command, the grid coordinates of the work area are transmitted to the cloud management system via the mother ship, so that the cloud management system can divide the work area into a spiral path based on a preset planning algorithm to generate a dynamic ocean current compensation trajectory, and divide the work area into multiple subdomains using the region decomposition method. In response to the allocation instruction, a working unit corresponding to each subdomain is constructed according to the floating robot cluster, so that the working unit can grab the seabed node from the basket and release it to the target deployment point of the corresponding subdomain; The operating unit includes a first number of the floating robots; the operating unit retrieves the seabed node from the basket and releases it to the target deployment point corresponding to the subdomain, including the following steps: The work unit navigates to the basket with the assistance of a long baseline positioning system, and the floating robot of the work unit retrieves the seabed node from the basket; In response to the feedback signal that the floating robot has completed its grasping action, the working unit is assisted in navigating to the target deployment point in the subdomain based on the long baseline positioning system. The floating robot is equipped with a multi-beam sonar, and the navigation of the work unit to the target deployment point in the subdomain based on the long baseline positioning system includes the following steps: The floating robots of the work unit are navigated to the target deployment point in the subdomain by using a diamond-shaped formation diving method and following the spiral path; During the navigation of the floating robots to the target deployment point, all the floating robots in the cluster perform overall path planning through a cooperative collision avoidance algorithm, and each floating robot performs the following operations: The real-time position of the floating robot is used as the target position; The multibeam sonar is used to construct a digital elevation model of the seabed at the target location based on a preset frequency; The seabed digital elevation model and real-time positioning are matched with the feature point cloud constructed by the map in real time, and the real-time position is corrected using the long baseline positioning system based on the result of the real-time matching. Determine whether the corrected real-time position has reached the target deployment point. If it has not reached the target deployment point, take the real-time position of the floating robot at the next time point along the spiral path as the target position, and return to execute the step of using the multibeam sonar to construct the seabed digital elevation model of the target position based on the preset frequency, until the real-time position reaches the target deployment point. The recovery module is used to recover the seabed node at the target deployment point based on the floating robot cluster and the basket in response to a recovery command.

7. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method according to any one of claims 1 to 5.

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