Marine operation towing obstacle avoidance method, device, electronic equipment and storage medium

Abstract

The present invention discloses a method, device, electronic device and storage medium for obstacle avoidance in marine towing operations. The method comprises: determining obstacle status information, first state data of a seismic acquisition system and environmental data in a target sea area; matching a target control instruction generation strategy from candidate control instruction generation strategies based on the obstacle status information; determining a target control instruction through a target control instruction generation strategy based on the obstacle status information, first state data of a seismic acquisition system and environmental data; and controlling a lateral control bird and / or a compass bird according to the target control instruction to drive the towing operation to avoid obstacles. The method matches different control instruction generation strategies according to different obstacle types, generates control instructions according to the control instruction generation strategy, and controls the lateral control bird and / or the compass bird to drive the towing operation to avoid obstacles, thereby improving the efficiency of the towing operation and the accuracy of the marine operation vessel in avoiding obstacles.

Description

Technical Field

[0001] The present invention relates to the field of marine exploration technology, and in particular to a method, device, electronic equipment and storage medium for towing and avoiding obstacles in marine operations. Background Art

[0002] During offshore towing operations, especially offshore three-dimensional seismic towing operations, interference from obstacles such as drilling platforms, fishing boats, cargo ships, and offshore buoys is often encountered. The presence of offshore obstacles will not only interfere with the normal operation of the seismic operation vessel along the planned survey line, but will also affect the quality of the collected data. In order to avoid obstacles during the operation process, the existing technology obtains an obstacle avoidance plan based on manual experience after detecting the existence of obstacles. The obstacle avoidance plan obtained based on manual experience usually gives an operation towing sinking depth based on manual experience, and controls the compass bird to sink the operation towing to the sinking depth, or the seismic operation vessel tows the operation towing at a large distance to bypass the obstacle, thereby directly abandoning the collection of the current survey line. This will not only waste the precious offshore operation window period, but also cause a waste of resources. Summary of the Invention

[0003] The present invention provides a method, device, electronic equipment and storage medium for towing obstacles in marine operations, so as to solve the problem of waste of resources caused by failure to avoid obstacles in time when encountering obstacles.

[0004] According to one aspect of the present invention, a method for towing and avoiding obstacles in marine operations is provided, comprising:

[0005] Determine obstacle status information, first state data of the seismic acquisition system, and environmental data of the target sea area; the obstacle status information is used to characterize the type of obstacles in the target sea area and the corresponding operating status of the obstacles; the first state data of the seismic acquisition system is used to characterize the operating status data of the seismic acquisition system in the target sea area; the environmental data is used to characterize the natural environment of the target sea area; the seismic acquisition system includes: a seismic operation vessel and an operation tug; the seismic operation vessel is equipped with the operation tug; the operation tug is equipped with a lateral control bird and a compass bird;

[0006] Matching a target control instruction generation strategy from candidate control instruction generation strategies according to the obstacle state information; the target control instruction generation strategy is used to generate target control instructions for the lateral control bird and / or compass bird; the target control instructions are used to control the lateral control bird and / or compass bird to drive the work tow to avoid obstacles; the target control instructions include at least one of a first target control instruction, a second target control instruction and a third target control instruction; the first target control instruction is used to control the lateral control bird to drive the work tow to avoid fixed-position objects; the second target control instruction is used to control the lateral control bird to drive the work tow to avoid floating objects; the third target control instruction is used to control the lateral control bird and compass bird to drive the work tow to avoid fast-moving objects;

[0007] determining a target control instruction through the target control instruction generation strategy according to the obstacle state information, the first state data of the seismic acquisition system, and the environmental data;

[0008] The lateral control bird and / or the compass bird are controlled according to the target control instruction to drive the working tractor to avoid obstacles.

[0009] According to another aspect of the present invention, there is provided a towing obstacle avoidance device for marine operations, comprising:

[0010] A data determination module is configured to determine obstacle status information, first state data of a seismic acquisition system, and environmental data of a target sea area; the obstacle status information is configured to characterize the types of obstacles within the target sea area and the corresponding operating states of the obstacles; the first state data of the seismic acquisition system is configured to characterize the operating state of the seismic acquisition system within the target sea area; and the environmental data is configured to characterize the natural environment of the target sea area. The seismic acquisition system comprises: a seismic operation vessel and an operation tug; the seismic operation vessel is equipped with the operation tug; and the operation tug is equipped with a lateral control bird and a compass bird.

[0011] a target control instruction generation strategy determination module, configured to match a target control instruction generation strategy from candidate control instruction generation strategies based on the obstacle state information; the target control instruction generation strategy is configured to generate a target control instruction for the lateral control bird and / or compass bird; the target control instruction is configured to control the lateral control bird and / or compass bird to drive the work tow truck to avoid obstacles; the target control instruction includes at least one of a first target control instruction, a second target control instruction, and a third target control instruction; the first target control instruction is configured to control the lateral control bird to drive the work tow truck to avoid fixed-position objects; the second target control instruction is configured to control the lateral control bird to drive the work tow truck to avoid floating objects; the third target control instruction is configured to control the lateral control bird and compass bird to drive the work tow truck to avoid fast-moving objects;

[0012] a target control instruction determination module, configured to determine a target control instruction through the target control instruction generation strategy according to the obstacle state information, the first state data of the seismic acquisition system, and the environmental data;

[0013] The control module is used to control the lateral control bird and / or the compass bird according to the target control instruction, so as to drive the working tractor to avoid obstacles.

[0014] According to another aspect of the present invention, an electronic device is provided, comprising:

[0015] at least one processor; and

[0016] a memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the marine operation towing obstacle avoidance method described in any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the marine operation towing obstacle avoidance method according to any embodiment of the present invention when executed.

[0019] The technical solution of the embodiment of the present invention determines the obstacle status information, the first state data of the seismic acquisition system and the environmental data of the target sea area; matches the target control instruction generation strategy from the candidate control instruction generation strategy according to the obstacle status information, and can realize matching the corresponding control instruction generation strategy according to the specific obstacle type, avoiding the problem that only a single control instruction generation strategy is used, resulting in the generated control instructions being unable to accurately avoid obstacles; determines the target control instruction through the target control instruction generation strategy according to the obstacle status information, the first state data of the seismic acquisition system and the environmental data, and can ensure that the control instruction is generated using the control instruction generation strategy dedicated to the current obstacle type, greatly improving the generation efficiency of the control instruction; controls the lateral control bird and / or the compass bird according to the target control instruction, drives the operation towing to avoid obstacles, reduces manual participation, makes the obtained avoidance plan more in line with the objective environment, effectively utilizes the marine operation window period, and improves the operation efficiency of the marine lateral control bird and the compass bird. This method matches different control instruction generation strategies according to different obstacle types, generates control instructions according to the control instruction generation strategies, and controls the lateral control bird and / or compass bird to drive the operating towing vessel to avoid obstacles. While improving the efficiency of the operating towing vessel, it also improves the accuracy of the marine operating vessel in avoiding obstacles.

[0020] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0022] Figure 1 A flow chart of a method for towing and avoiding obstacles in marine operations provided by an embodiment of the present invention;

[0023] Figure 2 A flowchart of generating a first target control instruction provided by an embodiment of the present invention;

[0024] Figure 3 A flow chart of generating a second target control instruction provided by an embodiment of the present invention;

[0025] Figure 4 A flowchart of generating a third target control instruction provided by an embodiment of the present invention;

[0026] Figure 5 A schematic structural diagram of a towing obstacle avoidance device for marine operations provided by an embodiment of the present invention;

[0027] Figure 6 A schematic structural diagram of an electronic device for implementing the method for towing and avoiding obstacles in marine operations according to an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0030] Figure 1 This is a flow chart of a method for avoiding obstacles in a towing vessel for marine operations provided by an embodiment of the present invention. This embodiment is applicable to situations where a towing vessel for marine operations encounters obstacles and avoids obstacles by matching different avoidance modes to different obstacles. This method can be executed by an obstacle avoidance device for a towing vessel for marine operations. The obstacle avoidance device for a towing vessel for marine operations can be implemented in the form of hardware and / or software. The obstacle avoidance device for a towing vessel for marine operations can be configured in any electronic device with network communication capabilities. Figure 1 As shown, the method includes:

[0031] S110: Determine obstacle status information of the target sea area, first status data of the seismic acquisition system, and environmental data.

[0032] Among them, the obstacle status information is used to characterize the type of obstacles in the target sea area and the corresponding operating status of the obstacles.

[0033] Furthermore, obstacle status information includes the obstacle type and the corresponding operational status data. Obstacle types include fixed objects, floating objects, and fast-moving objects. Solid objects typically include fixed operating vessels, drilling platforms, and fishing nets. Floating objects are typically buoys. Fast-moving objects typically include fast-moving cargo ships or passenger ships.

[0034] Furthermore, the operational status data corresponding to the obstacle includes at least the obstacle's location and size. Different obstacle types have different obstacle status information. When the obstacle type is a fixed-position object, the operational status data corresponding to the obstacle includes at least the location and size of the fixed-position object; when the obstacle type is a floating object, the operational status data corresponding to the obstacle includes at least the location, speed, and direction of the floating object; when the obstacle type is a fast-moving object, the operational status data corresponding to the obstacle includes at least the location, speed, and direction of the fast-moving object.

[0035] The aforementioned obstacle classification process is based on the fact that a seismic vessel tows at least one long tow canoe astern. Fixed, floating, and fast-moving objects can significantly interfere with offshore seismic operations. Furthermore, different obstacles move at varying speeds. Therefore, using the same approach to generate avoidance strategies would not only affect the quality of acquired data but also hinder the seismic acquisition system's ability to collect data along the planned survey line. Furthermore, this could result in the tow canoe failing to avoid obstacles in a timely manner.

[0036] The first state data of the seismic acquisition system is used to represent the operating state data of the seismic acquisition system in the target sea area.

[0037] Furthermore, the first status data of the seismic acquisition system includes at least the current position, movement direction, and speed of the seismic vessel, as well as the status information of the depth-fixing and direction-controlling device and the working towline structure diagram. The depth-fixing and direction-controlling device includes a compass bird and a lateral control bird, and is mounted on the working towline. The status information of the depth-fixing and direction-controlling device includes the current wing angles of the compass bird and the lateral control bird. The working towline structure diagram, i.e., the distribution of the lateral control bird and the compass bird, includes the connection structure of each acquisition segment in the towline and the interface points between the compass bird and the lateral control bird.

[0038] The seismic acquisition system includes a seismic operation vessel and an operation tug. The seismic operation vessel is equipped with an operation tug, which is equipped with a lateral control bird and a compass bird.

[0039] Furthermore, the seismic acquisition system is usually composed of a seismic operation vessel, a seismic data acquisition system, a navigation and positioning system, and an operation tow. When performing marine seismic exploration operations, at least one operation tow and at least one set of seismic sources are usually towed at the stern of the seismic operation vessel. Each operation tow is equipped with multiple compass birds and multiple lateral control birds to control the attitude of the operation tow. Among them, the compass bird is used to control the depth of the operation tow. By receiving control instructions, the angle of the compass bird's wings is adjusted, and the operation tow is sunk to the preset depth; the lateral control bird is used to control the lateral offset of the operation tow. By receiving control instructions, the angle of the lateral control bird's wings is adjusted, and the operation tow is kept on the preset survey line. At the same time, head and tail markers are also deployed on the operation tow to position the operation tow.

[0040] Among them, environmental data is used to characterize the natural environment of the target sea area.

[0041] Specifically, radar data acquired by the radar sensor is used to determine whether there are obstacles within the target sea area of ​​the seismic vessel's operation. If so, obstacle status information is determined based on the radar data. Meteorological data is used to mine operational environmental data such as currents, tides, and wind speeds within the target sea area. Sensors configured on the acquisition system acquire first state data of the seismic acquisition system.

[0042] S120 : Match a target control instruction generation strategy from candidate control instruction generation strategies according to the obstacle state information.

[0043] The target control instruction generation strategy is used to generate target control instructions for the lateral control bird and / or the compass bird.

[0044] The target control instruction is used to control the lateral control bird and / or the compass bird to drive the working towing to avoid obstacles. The target control instruction includes at least one of the first target control instruction, the second target control instruction and the third target control instruction.

[0045] The first target control command is used to control the lateral control bird to drive the work tow truck to avoid fixed objects. The second target control command is used to control the lateral control bird to drive the work tow truck to avoid floating objects. The third target control command is used to control the lateral control bird and the compass bird to drive the work tow truck to avoid fast-moving objects.

[0046] Specifically, when receiving the obstacle state information, the server matches the target control instruction generation strategy from the candidate control instruction generation strategies according to the obstacle type included in the obstacle state information.

[0047] Furthermore, when the obstacle type label is a fixed-position object, the first target control instruction generation strategy is matched; when the obstacle type is a floating object, the second target control instruction generation strategy is matched; when the obstacle type is a fast-moving object, the third target control instruction generation strategy is matched.

[0048] Furthermore, a mapping relationship between obstacle types and candidate control instruction generation strategies is pre-set in the server, as shown in Table 1:

[0049] Table 1 Mapping relationship between obstacle types and candidate control instruction generation strategies

[0050] Obstacle type Candidate control instruction generation strategy Fixed position objects First target control instruction generation strategy floating objects Second target control instruction generation strategy Fast-moving objects The third target control instruction generation strategy

[0051] In the above steps, the construction of the candidate control instruction generation strategy not only takes into account the obstacle status information and the first state data of the seismic acquisition system, but also takes into account the environmental information of the seismic acquisition system, which further makes the obtained avoidance plan conform to the objective environment and improves the accuracy of obstacle avoidance.

[0052] S130 , determining a target control instruction through a target control instruction generation strategy according to the obstacle state information, the first state data of the seismic acquisition system, and the environmental data.

[0053] Specifically, according to the target control instruction generation strategy, corresponding data is selected from the obstacle state information, the first state data of the seismic acquisition system and the environmental data, and the selected data is calculated through the target control instruction to obtain the target control instruction.

[0054] Furthermore, due to the possibility of simultaneous operations, i.e., the presence of not only cargo ships but also fishing boats and fishing nets, or drilling platforms, in the target sea area, which may cause the seismic vessel to encounter different types of fault objects simultaneously near the survey line, the target control instruction may include one or more of the first target control instruction, the second target control instruction, and the third target control instruction.

[0055] In the above steps, different control instruction generation strategies are designed according to different types of obstacles, and control instructions for avoiding corresponding obstacles are generated according to the control instruction generation strategies, so that obstacle avoidance instructions can be quickly obtained.

[0056] S140: Control the lateral control bird and / or the compass bird according to the target control instruction to drive the working tractor to avoid obstacles.

[0057] Specifically, the target control instruction adjusts the wing angles of each lateral control bird and / or compass bird configured on the work trailer to drive the work trailer away from obstacles.

[0058] The above steps obtain target control instructions, so that the lateral control bird and / or compass bird control the operating towline to avoid obstacles according to the target control instructions. Since human participation is reduced, the obtained avoidance plan is more in line with the objective environment, effectively utilizes the marine operation window period, improves the efficiency of marine seismic operations, and greatly saves the waste of manpower, material resources and financial resources.

[0059] Optionally, determining obstacle status information of the target sea area includes steps A1-A3:

[0060] Step A1: Acquire radar data within the target sea area.

[0061] Specifically, radar data within the target sea area is obtained by performing real-time scanning within the radar scanning fence.

[0062] Furthermore, the range of the radar scanning fence can be set manually or automatically. That is, when the radar scanning fence is set manually, a user interface is provided for inputting the fence size; when the radar scanning fence is set automatically, the fence size is calculated by the calculation model and the fence size value is automatically filled in.

[0063] Furthermore, the setting of the scanning fence needs to comprehensively consider the length, width, and width of the streamer, etc.

[0064] Step A2: Determine whether there are obstacles in the target sea area based on radar data.

[0065] Specifically, the recognition algorithm is used to determine in real time whether there are suspected obstacles within the fence based on radar data.

[0066] Among them, the recognition algorithm can adopt support vector machine (SVM), decision tree, random forest, neural network and other algorithms.

[0067] Step A3: If an obstacle exists, determine the obstacle status information based on the obstacle change data in the radar data.

[0068] Specifically, if an obstacle exists, an early warning is issued, and obstacle status information is determined based on the changing state of the obstacle in the radar data.

[0069] For example, if an obstacle is detected and the radar data corresponding to the obstacle always remains within the corresponding range, the obstacle is considered to be a fixed-position object, and the location information of the fixed-position object is obtained; if an obstacle is detected and the position of the radar data corresponding to the obstacle is constantly changing in a certain direction, but the change is not fast, the obstacle is considered to be a floating object, and the position, moving speed and moving direction of the floating object are determined according to the changes in the radar data corresponding to the floating object; if an obstacle is detected and the position of the radar data corresponding to the obstacle is constantly changing in a certain direction, but the change is rapid, the obstacle is considered to be a fast-moving object, and the position, moving speed and moving direction of the fast-moving object are determined according to the changes in the radar data corresponding to the fast-moving object.

[0070] Furthermore, the obstacle type can be manually determined. Specifically, if an obstacle is identified, its authenticity can be determined manually. This means that when an obstacle alarm is issued, the system can manually determine its authenticity through methods such as observation and high-frequency calling. Observation involves using telescopes installed on seismic vessels to observe the location of the obstacle and determine if it is a real obstacle. High-frequency calling involves calling a vessel suspected of being an obstacle via intercom and verifying its location based on the location information it receives. If an obstacle is identified as a real obstacle, an obstacle type tag is set and obstacle status information is collected.

[0071] Furthermore, the obstacle type may be set by selecting it through a user interface or by directly inputting it.

[0072] Among them, the real obstacles can be objects artificially constructed and placed in the target sea area.

[0073] Optionally, determining the target control instruction through a target control instruction generation strategy according to the obstacle state information, the first state data of the seismic acquisition system, and the environmental data includes steps B1-B7:

[0074] Step B1: Acquire the angle data of the lateral control bird, the distribution and towing structure data of the lateral control bird and the compass bird, and the operation data of the seismic operation vessel from the first state data of the seismic acquisition system.

[0075] Specifically, if the obstacle is a fixed-position object, the angle data of the lateral control bird, the distribution and towing structure data of the lateral control bird and the compass bird, and the operation data of the seismic operation vessel are obtained from the first state data of the seismic acquisition system.

[0076] For example, when the obstacle type is a fixed-position object, the position and size of the fixed-position object are obtained from the obstacle status information; the ocean current velocity data is obtained from the operating environment information; and the position of the seismic operation vessel, the moving direction of the seismic operation vessel, and the moving speed of the seismic operation vessel are obtained from the first state data of the seismic acquisition system.

[0077] Step B2: construct a first undirected graph based on the angle data of the lateral control bird and the distribution drag structure data of the lateral control bird and the compass bird.

[0078] The first undirected graph is used to represent the wing distribution of the lateral control bird.

[0079] Specifically, the adjacent lateral control birds in the distribution drag structure data of the lateral control bird and the compass bird are connected by edges, and the lateral control bird is used as the node V in the first undirected graph. (1) , adjacent nodes are connected into edges E (1) , horizontally controls the angle of the bird's wings and forms the node attribute X (1) , the distance between nodes constitutes the weight W (1) .

[0080] Step B3: Encode the operation data of the seismic operation vessel and the state data of the fixed-position object through the first data encoding layer to obtain a first sub-eigenvector.

[0081] The first data coding layer is used to construct the relationship between the first state data of the seismic acquisition system and the obstacle state information.

[0082] Furthermore, the first data encoding layer may adopt a domain dictionary model, which is obtained by training the BERT pre-trained language model using domain data, specifically by training the BERT pre-trained language model using historical domain data.

[0083] For example, the position and size of the fixed position object, as well as the position, moving direction and moving speed of the seismic operation vessel are encoded through the first sub-coding layer to obtain the first sub-feature vector

[0084]

[0085] in, They respectively represent the position of the seismic operation ship, the moving direction of the seismic operation ship, the moving speed of the seismic operation ship, the position of the fixed-position object and the size of the fixed-position object; the position can be expressed in latitude and longitude data or geographic coordinate position data, and the size can be expressed in length, width and height data.

[0086] Step B4: Encode the first undirected graph through an image coding layer to obtain a second sub-feature vector.

[0087] The image coding layer is used to construct the distribution relationship between the lateral control birds and / or the compass birds in the undirected graph.

[0088] Specifically, the first undirected graph is input into the image coding layer for encoding to obtain the second sub-feature vector.

[0089] Furthermore, the second sub-eigenvector can be expressed by the following formula:

[0090]

[0091] Where σ represents the activation function; I represents the identity matrix; Indicates based on The corresponding degree matrix obtained; A (1) is the adjacency matrix constructed according to the first undirected graph.

[0092] Step B5: Encode the ocean current data through the second data encoding layer to obtain a third sub-eigenvector.

[0093] The second data encoding layer is used to construct the relationship between environmental data.

[0094] Specifically, the ocean current velocity data is input into the second data encoding layer for encoding to obtain the third sub-eigenvector.

[0095] Furthermore, the third sub-eigenvector can be expressed as follows:

[0096]

[0097] in, Indicates the speed of ocean current.

[0098] Step B6: Determine a first eigenvector based on the first sub-eigenvector, the second sub-eigenvector, and the third sub-eigenvector.

[0099] Specifically, the first sub-eigenvector, the second sub-eigenvector, and the third sub-eigenvector are fused to obtain the first eigenvector.

[0100] Step B7: Decode the first eigenvector to obtain a first target control instruction.

[0101] Among them, the first target control instruction is used to control the lateral control bird to adjust the angle.

[0102] Specifically, the first feature vector is decoded by the first decoding layer to obtain the first target control instruction.

[0103] The first decoding layer adopts a bidirectional long short-term memory neural network to decode the first eigenvector through the bidirectional long short-term memory neural network.

[0104] Furthermore, the first target control instruction can be expressed by the following formula:

[0105] ANGLE (1) =BI_LSTM(H (1) ).

[0106] For example, assuming ANGLE (1) =(6.0, 7.5, 12.5, 15, ...), which means that the angle that needs to be adjusted for the first lateral control bird is 6.5, the angle that needs to be adjusted for the second is 7.5, and so on.

[0107] For example, Figure 3 As shown, when the obstacle type is a fixed-position object, the position and dimensions of the fixed-position object are obtained from the obstacle status information, ocean current velocity data is obtained from the operating environment information, and the position, movement direction, and movement speed of the seismic operation vessel are obtained from the first state data of the seismic acquisition system. The position and dimensions of the fixed-position object, the position, movement direction, and movement speed of the seismic operation vessel are input into the first data encoding layer for encoding, resulting in a first sub-eigenvector. The first undirected graph constructed based on the angle data of the lateral control bird and the distribution and towing structure data of the lateral control bird and the compass bird is input into the image encoding layer for encoding, resulting in a second sub-eigenvector. The ocean current velocity data is input into the second data encoding layer for encoding, resulting in a third sub-eigenvector. The first, second, and third sub-eigenvectors are fused to obtain the first eigenvector, which is then decoded by the first decoding layer to obtain the first target control instruction.

[0108] Optionally, determining the target control instruction through a target control instruction generation strategy according to the obstacle state information, the first state data of the seismic acquisition system, and the environmental data includes steps C1-C7:

[0109] Step C1: Acquire angle data of the lateral control bird, distribution and towing structure data of the lateral control bird and the compass bird, and operation data of the seismic operation vessel from the first state data of the seismic acquisition system.

[0110] Specifically, if the obstacle is a floating object, the angle data of the lateral control bird, the distribution and towing structure data of the lateral control bird and the compass bird, and the operation data of the seismic operation vessel are obtained from the first state data of the seismic acquisition system.

[0111] For example, when the obstacle type is a floating object, the position of the floating object, the moving speed of the floating object and the moving direction of the floating object are obtained from the obstacle status information; the ocean current velocity data and wind data are obtained from the operating environment information; and the position of the seismic operation vessel, the moving direction of the seismic operation vessel and the moving speed of the seismic operation vessel are obtained from the first state data of the seismic acquisition system.

[0112] Step C2: construct a second undirected graph based on the angle data of the lateral control bird and the distribution drag structure data of the lateral control bird and the compass bird.

[0113] The second undirected graph is used to represent the lateral distribution of the bird's wings.

[0114] Specifically, the adjacent lateral control birds in the distribution drag structure data of the lateral control bird and the compass bird are connected by edges, and the lateral control bird is used as the node V in the undirected graph. (2) , adjacent nodes are connected into edges E (2) , horizontally controls the angle of the bird's wings and forms the node attribute X (2) , the distance between nodes constitutes the weight W (2) The construction method of the second undirected graph is the same as that of the first undirected graph.

[0115] Step C3: Encode the operation data of the seismic operation vessel and the state data of the floating object through the first data encoding layer to obtain a fourth sub-eigenvector.

[0116] Specifically, the position, moving speed and moving direction of the floating object, as well as the position, moving direction and moving speed of the seismic operation vessel are encoded through the first data encoding layer to obtain the fourth sub-eigenvector

[0117]

[0118] in, They respectively represent the position of the seismic operation ship, the moving direction of the seismic operation ship, the moving speed of the seismic operation ship, the position of the floating object, the moving direction of the floating object, and the moving speed of the floating object.

[0119] Step C4: Encode the second undirected graph through the image coding layer to obtain a fifth sub-eigenvector.

[0120] Specifically, the second undirected graph is input into the image coding layer for encoding to obtain the fifth sub-feature vector.

[0121] Furthermore, the fifth sub-eigenvector can be expressed by the following formula:

[0122]

[0123] Where σ represents the activation function; I represents the identity matrix; Indicates based on The corresponding degree matrix obtained; A (2) is the adjacency matrix constructed according to the second undirected graph.

[0124] Step C5: Encode the ocean current data and wind data through the second data encoding layer to obtain a sixth sub-eigenvector.

[0125] Specifically, the ocean current velocity data is input into the second data encoding layer for encoding to obtain the sixth sub-eigenvector.

[0126] Furthermore, the sixth sub-eigenvector can be expressed by the following formula:

[0127]

[0128] in, Indicates the speed of ocean current; Indicates wind speed.

[0129] Step C6: Determine the second eigenvector based on the fourth sub-eigenvector, the fifth sub-eigenvector, and the sixth sub-eigenvector.

[0130] Specifically, the fourth sub-eigenvector, the fifth sub-eigenvector, and the sixth sub-eigenvector are fused to obtain the second eigenvector.

[0131] Step C7: Decode the second eigenvector to obtain a second target control instruction.

[0132] Among them, the second target control instruction is used to control the lateral control bird to adjust the angle.

[0133] Specifically, the second feature vector is decoded by the second decoding layer to obtain a second target control instruction.

[0134] Furthermore, the second target control instruction can be expressed by the following formula:

[0135] ANGLE (2) =BI_LSTM(H (2) ).

[0136] For example, assuming ANGLE (2) =(2.0, 3.5, 5.5, 7.0, ...), which means that the angle that needs to be adjusted for the first lateral control bird is 2.0, the angle that needs to be adjusted for the second is 3.5, and so on.

[0137] For example, Figure 4As shown, when the obstacle type is a floating object, the floating object's position, speed, and direction are obtained from the obstacle status information, ocean current velocity data and wind data are obtained from the operating environment information, and the seismic vessel's position, direction, and speed are obtained from the first state data of the seismic acquisition system. The floating object's position, speed, and direction, as well as the seismic vessel's position, direction, and speed, are input into the first data encoding layer for encoding, yielding a fourth sub-eigenvector. A second undirected graph constructed based on the lateral control bird's angle data and the distribution and towing structure data of the lateral control bird and the compass bird is input into the image encoding layer for encoding, yielding a fifth sub-eigenvector. Ocean current velocity data and wind data are input into the second data encoding layer for encoding, yielding a sixth sub-eigenvector. The fourth, fifth, and sixth sub-eigenvectors are fused to yield a second eigenvector, which is then decoded by the second decoding layer to yield a second target control instruction.

[0138] Optionally, determining the target control instruction through a target control instruction generation strategy according to the obstacle state information, the first state data of the seismic acquisition system, and the environmental data includes steps D1-D7:

[0139] Step D1: Obtain the angle data of the compass bird, the angle data of the lateral control bird, the distribution and towing structure data of the lateral control bird and the compass bird, and the operation data of the seismic operation vessel from the first state data of the seismic acquisition system.

[0140] Specifically, if the obstacle is a fast-moving object, the angle data of the lateral control bird, the distribution and towing structure data of the lateral control bird and the compass bird, and the operation data of the seismic operation vessel are obtained from the first state data of the seismic acquisition system.

[0141] For example, when the obstacle type is a fast-moving object, the position, moving speed and moving direction of the fast-moving object are obtained from the obstacle status information; the ocean current velocity data and wind data are obtained from the operating environment information; and the position, moving direction and moving speed of the seismic operation vessel are obtained from the first state data of the seismic acquisition system.

[0142] Step D2: construct a third undirected graph based on the angle data of the compass bird, the angle data of the lateral control bird, and the distribution drag structure data of the lateral control bird and the compass bird.

[0143] Among them, the third undirected graph is used to represent the wing distribution of the lateral control bird and the compass bird.

[0144] Specifically, all lateral control birds and compass birds in the distribution drag structure data of lateral control birds and compass birds are edge-connected, and lateral control birds and compass birds are used as nodes V in the third undirected graph. (3) , adjacent nodes are connected into edges E (3) , the horizontal control bird angle and the compass bird angle constitute the node attribute X (3) , X (3) The wing angles of all lateral control birds and all compass birds are included, and the distance between nodes constitutes the weight W (3) .

[0145] Step D3: Encode the operation data of the seismic operation vessel and the state data of the fast-moving object through the first data encoding layer to obtain a seventh sub-eigenvector.

[0146] Specifically, the position, speed and direction of the fast-moving object, as well as the position, direction and speed of the seismic operation vessel are input into the first data encoding layer for encoding to obtain the seventh sub-eigenvector

[0147]

[0148] in, They respectively represent the position of the seismic operation ship, the moving direction of the seismic operation ship, the moving speed of the seismic operation ship, the position of the fast-moving object, the moving direction of the fast-moving object, and the moving speed of the fast-moving object.

[0149] Step D4: Encode the third undirected graph through the image coding layer to obtain an eighth sub-eigenvector.

[0150] Specifically, the third undirected graph is input into the image coding layer for encoding to obtain the eighth sub-eigenvector.

[0151] Furthermore, the eighth sub-eigenvector Specifically:

[0152]

[0153] Where σ represents the activation function; I represents the identity matrix, Indicates based on The corresponding degree matrix obtained; A (3) is the adjacency matrix constructed according to the third undirected graph.

[0154] Step D5: Encode the ocean current data and wind data through the second data encoding layer to obtain a ninth sub-eigenvector.

[0155] Specifically, the ocean current data and wind data are input into the second data encoding layer for encoding to obtain a ninth sub-eigenvector.

[0156] Furthermore, the ninth sub-eigenvector It can be expressed by the following formula:

[0157]

[0158] in, Indicates the ocean current velocity, Indicates wind speed.

[0159] Step D6: Determine a third eigenvector based on the seventh sub-eigenvector, the eighth sub-eigenvector, and the ninth sub-eigenvector.

[0160] Specifically, the seventh sub-eigenvector, the eighth sub-eigenvector, and the ninth sub-eigenvector are fused to obtain the third eigenvector.

[0161] Furthermore, the third eigenvector can be expressed as follows:

[0162]

[0163] Step D7: Decode the third eigenvector to obtain a third target control instruction.

[0164] Among them, the third target control instruction is used to control the lateral control bird and the compass bird to adjust the angle.

[0165] Specifically, the third eigenvector is decoded by the third decoding layer to obtain a third target control instruction.

[0166] Exemplarily, the third target control instruction can be expressed by the following formula:

[0167] ANGLE (3) =ATTENTION_BI_LSTM(H (3) ).

[0168] For example, assuming ANGLE (3) =(2.0, -2.1, 2.5, -3.0, 5, -5.5, 7.0, ...), which means that the angle that needs to be adjusted for the first lateral control bird is 2.0, the angle that needs to be adjusted for the first compass bird is -2.1, and so on.

[0169] For example, Figure 5As shown, when the obstacle type is a fast-moving object, the fast-moving object's position, speed, and direction are obtained from the obstacle status information, ocean current velocity data and wind data are obtained from the operating environment information, and the seismic vessel's position, direction, and speed are obtained from the first state data of the seismic acquisition system. The fast-moving object's position, speed, and direction, as well as the seismic vessel's position, direction, and speed, are input into the first data encoding layer for encoding, yielding the seventh sub-eigenvector. A third undirected graph constructed based on the lateral control bird's angle data and the distribution and towing structure data of the lateral control bird and the compass bird is input into the image encoding layer for encoding, yielding the eighth sub-eigenvector. Ocean current velocity data and wind data are input into the second data encoding layer for encoding, yielding the ninth sub-eigenvector. The seventh, eighth, and ninth sub-eigenvectors are fused to yield the third eigenvector, which is then decoded by the third decoding layer to yield the third target control instruction.

[0170] Optionally, the lateral control bird and / or the compass bird are controlled according to the target control instruction to drive the working towing vehicle to avoid obstacles, including steps E1-E2:

[0171] Step E1: Convert the acquired target control instruction into motor rotation angle information.

[0172] Specifically, after generating the adjustment angles of the lateral control bird and / or the compass bird, the server converts the adjustment angles into motor rotation angle information.

[0173] Step E2: adjusting the wing angles of the lateral control bird and / or the compass bird through the lateral control bird and compass bird control system according to the motor rotation angle information, so as to drive the working tractor to avoid obstacles.

[0174] Exemplarily, the server sends the motor rotation information to the PCS control system (lateral control bird and compass bird control system), and the PCS control system sends the motor rotation information to each lateral control bird and / or compass bird in the form of a protocol packet. After each lateral control bird and / or compass bird receives the protocol packet, it parses the protocol packet to obtain the motor rotation information, drives the motor to rotate according to the motor rotation information, thereby driving the wings of each lateral control bird and / or compass bird to move to adjust to the adjustment angle.

[0175] Optionally, after the lateral control bird and / or the compass bird are controlled according to the target control instruction to drive the working tow truck to avoid obstacles, steps F1-F3 are included:

[0176] Step F1: Acquire the second state data of the seismic acquisition system.

[0177] The second state data of the seismic acquisition system is used to characterize the position and orientation of the seismic operation vessel, the lateral control bird, and the compass bird.

[0178] Furthermore, the second state data of the seismic acquisition system includes the location information and orientation information of the acquisition system. The location information of the acquisition system includes the longitude and latitude coordinates of the seismic operation vessel, the head beacon, the tail beacon, and the depth-fixing direction finder; and the orientation information includes the orientation of the seismic operation vessel, the head beacon, the tail beacon, and the depth-fixing direction finder.

[0179] Furthermore, the acquisition system status information is expressed as:

[0180] S={(lon0, lat0, dir0), (lon1, lat1, dir1), ..., (lon n ,lat n ,dir n )},

[0181] Among them, (lon0, lat0, dir0) represents the longitude, latitude and azimuth of the seismic operation ship; (lon1, lat1, dir1) represents the longitude, latitude and azimuth of the head marker; (lon n ,lat n ,dir n ) indicates the longitude, latitude and azimuth of the tail marker; the others indicate the longitude, latitude and azimuth of each lateral control bird and the compass bird.

[0182] Specifically, the second state data of the seismic acquisition system is obtained from sensors configured on the seismic operation vessel.

[0183] Step F2: Determine the operation plan.

[0184] Among them, the operation plan refers to the operation survey line where data collection has not been completed.

[0185] Specifically, the operation plan is determined based on the predicted survey line and the survey line for which data collection has been completed.

[0186] The preset survey line is a linear measurement path that is pre-arranged according to the locations where data collection is required in the target sea area.

[0187] Furthermore, the target operation line is expressed as:

[0188]

[0189] in, They respectively represent the starting point longitude, starting point latitude, ending point longitude, ending point latitude and survey line representation of the mth operating survey line for which data collection has not been completed.

[0190] Step F3: Determine an operation adjustment plan based on the second state data of the seismic acquisition system and the operation plan, and display the operation adjustment plan.

[0191] Among them, the operation adjustment plan is the acquisition probability of each operation survey line.

[0192] Specifically, the second state data S of the seismic acquisition system and the operation plan LINE are input into the operation adjustment model. The operation adjustment model predicts the acquisition probability of each operation line after avoiding obstacles, and displays each operation line in different visual modes according to the size of the probability.

[0193] For example, the working survey line with the highest probability is displayed in red, and the other working survey lines are displayed in green; or the working survey lines with a probability greater than a first threshold are displayed in red, the working survey lines with a probability greater than a second threshold and less than the first threshold are displayed in yellow, and the working survey lines with a probability less than the second threshold are displayed in green.

[0194] Among them, the job adjustment model adopts a deep neural network model.

[0195] After avoiding obstacles, the above steps also generate an operation adjustment plan in real time through the trained operation adjustment model and the second state data of the acquisition system, and update the existing operation plan according to the generated operation adjustment plan, thereby further improving the efficiency of offshore operations.

[0196] The technical solution of this embodiment determines the obstacle status information, the first state data of the seismic acquisition system and the environmental data of the target sea area; matches the target control instruction generation strategy from the candidate control instruction generation strategies based on the obstacle status information, which can achieve matching of the corresponding control instruction generation strategy according to the specific obstacle type, avoiding the problem of using only a single control instruction generation strategy, resulting in the generated control instructions being unable to accurately avoid obstacles; determines the target control instruction through the target control instruction generation strategy based on the obstacle status information, the first state data of the seismic acquisition system and the environmental data, which can ensure that the control instruction is generated using the control instruction generation strategy specific to the current obstacle type, greatly improving the control instruction generation efficiency; controls the lateral control bird and / or the compass bird according to the target control instruction, drives the operation towing to avoid obstacles, reduces manual participation, makes the obtained avoidance plan more in line with the objective environment, effectively utilizes the marine operation window period, and improves the operation efficiency of the marine lateral control bird and the compass bird. This method matches different control instruction generation strategies according to different obstacle types, generates control instructions according to the control instruction generation strategies, and controls the lateral control bird and / or compass bird to drive the operating towing vessel to avoid obstacles. While improving the efficiency of the operating towing vessel, it also improves the accuracy of the marine operating vessel in avoiding obstacles.

[0197] Figure 5This is a schematic diagram of the structure of a marine operation towing obstacle avoidance device provided by an embodiment of the present invention. This embodiment is applicable to situations where a marine operation towing device encounters an obstacle and avoids the obstacle by matching different avoidance modes to different obstacles. The marine operation towing obstacle avoidance device can be implemented in the form of hardware and / or software, and can be configured in any electronic device with network communication function. Figure 5 As shown, the device includes: a data determination module 210, a target control instruction generation strategy determination module 220, a target control instruction determination module 230 and a control module 240, wherein:

[0198] Data determination module 210 is used to determine obstacle status information, first state data of the seismic acquisition system, and environmental data in the target sea area. The obstacle status information is used to characterize the types of obstacles in the target sea area and the corresponding operating states of the obstacles. The first state data of the seismic acquisition system is used to characterize the operating state data of the seismic acquisition system in the target sea area. The environmental data is used to characterize the natural environment in which the target sea area is located. The seismic acquisition system includes: a seismic operation vessel and an operation tug; the seismic operation vessel is equipped with an operation tug; the operation tug is equipped with a lateral control bird and a compass bird.

[0199] Target control instruction generation strategy determination module 220: used to match a target control instruction generation strategy from candidate control instruction generation strategies based on obstacle state information; the target control instruction generation strategy is used to generate target control instructions for the lateral control bird and / or the compass bird; the target control instructions are used to control the lateral control bird and / or the compass bird to drive the working tow truck to avoid obstacles; the target control instructions include at least one of a first target control instruction, a second target control instruction, and a third target control instruction; the first target control instruction is used to control the lateral control bird to drive the working tow truck to avoid fixed-position objects; the second target control instruction is used to control the lateral control bird to drive the working tow truck to avoid floating objects; the third target control instruction is used to control the lateral control bird and the compass bird to drive the working tow truck to avoid fast-moving objects;

[0200] Target control instruction determination module 230: used to determine the target control instruction through the target control instruction generation strategy according to the obstacle state information, the first state data of the seismic acquisition system and the environmental data;

[0201] Control module 240: used to control the lateral control bird and / or the compass bird according to the target control instruction, so as to drive the working tractor to avoid obstacles.

[0202] Optionally, the data determination module 210 includes:

[0203] Radar data acquisition unit: used to acquire radar data within the target sea area;

[0204] Obstacle judgment unit: used to determine whether there are obstacles in the target sea area based on radar data;

[0205] Obstacle status information determination unit: used to determine obstacle status information based on obstacle change data in radar data if an obstacle exists.

[0206] Optionally, the target control instruction determination module 230 includes:

[0207] Data determination unit: used for obtaining angle data of the lateral control bird, distribution and towing structure data of the lateral control bird and the compass bird, and operation data of the seismic operation vessel from the first state data of the seismic acquisition system;

[0208] A first undirected graph determining unit is configured to construct a first undirected graph based on the angle data of the lateral control bird and the distribution drag structure data of the lateral control bird and the compass bird, wherein the first undirected graph is used to represent the wing distribution of the lateral control bird;

[0209] A first sub-eigenvector determining unit is configured to encode the operating data of the seismic operation vessel and the state data of the fixed-position object through a first data encoding layer to obtain a first sub-eigenvector; the first data encoding layer is configured to establish a relationship between the first state data of the seismic acquisition system and the obstacle state information;

[0210] A second sub-eigenvector determining unit is configured to encode the first undirected graph through an image coding layer to obtain a second sub-eigenvector; the image coding layer is configured to construct a distribution relationship between the lateral control birds and / or the compass birds in the undirected graph;

[0211] A third sub-eigenvector determining unit is configured to encode the ocean current data through a second data encoding layer to obtain a third sub-eigenvector; the second data encoding layer is configured to construct a relationship between environmental data;

[0212] A first eigenvector determining unit: configured to determine a first eigenvector based on the first sub-eigenvector, the second sub-eigenvector, and the third sub-eigenvector;

[0213] The first target control instruction determining unit is used to decode the first eigenvector to obtain a first target control instruction, where the first target control instruction is used to control the lateral control bird to adjust the angle.

[0214] Optionally, the target control instruction determination module 230 includes:

[0215] Data determination unit: used for obtaining angle data of the lateral control bird, distribution and towing structure data of the lateral control bird and the compass bird, and operation data of the seismic operation vessel from the first state data of the seismic acquisition system;

[0216] A second undirected graph determining unit is configured to construct a second undirected graph based on the angle data of the lateral control bird and the distribution drag structure data of the lateral control bird and the compass bird, wherein the second undirected graph is configured to represent the wing distribution of the lateral control bird;

[0217] A fourth sub-eigenvector determining unit is configured to encode the operation data of the seismic operation vessel and the state data of the floating object through the first data encoding layer to obtain a fourth sub-eigenvector;

[0218] a fifth sub-eigenvector determining unit configured to encode the second undirected graph through an image coding layer to obtain a fifth sub-eigenvector;

[0219] a sixth sub-eigenvector determining unit configured to encode the ocean current data and the wind data through the second data encoding layer to obtain a sixth sub-eigenvector;

[0220] A second eigenvector determining unit: configured to determine a second eigenvector based on the fourth sub-eigenvector, the fifth sub-eigenvector, and the sixth sub-eigenvector;

[0221] The second target control instruction determining unit is used to decode the second eigenvector to obtain a second target control instruction, and the second target control instruction is used to control the lateral control bird to adjust the angle.

[0222] Optionally, the target control instruction determination module 230 includes:

[0223] Data determination unit: used for obtaining the angle data of the compass bird, the angle data of the lateral control bird, the distribution and towing structure data of the lateral control bird and the compass bird, and the operation data of the seismic operation vessel from the first state data of the seismic acquisition system;

[0224] A third undirected graph determining unit is configured to construct a third undirected graph based on the angle data of the compass bird, the angle data of the lateral control bird, and the distribution drag structure data of the lateral control bird and the compass bird, wherein the third undirected graph is used to represent the wing distribution of the lateral control bird and the compass bird;

[0225] a seventh sub-eigenvector determining unit configured to encode the operation data of the seismic operation vessel and the state data of the fast-moving object through the first data encoding layer to obtain a seventh sub-eigenvector;

[0226] An eighth sub-eigenvector determining unit is configured to encode the third undirected graph through an image coding layer to obtain an eighth sub-eigenvector;

[0227] a ninth sub-eigenvector determining unit configured to encode the ocean current data and the wind data through the second data encoding layer to obtain a ninth sub-eigenvector;

[0228] A third eigenvector determining unit: configured to determine a third eigenvector based on the seventh sub-eigenvector, the eighth sub-eigenvector, and the ninth sub-eigenvector;

[0229] The third target control instruction determination unit is used to decode the third eigenvector to obtain a third target control instruction, and the third target control instruction is used to control the lateral control bird and the compass bird to adjust the angle.

[0230] Optionally, the control module 240 includes:

[0231] A rotation angle information determining unit is configured to convert the acquired target control instruction into motor rotation angle information;

[0232] Adjustment unit: used to adjust the wing angle of the lateral control bird and / or compass bird through the lateral control bird and compass bird control system according to the motor rotation angle information, so as to drive the working towing to avoid obstacles.

[0233] Optional, ocean lateral control bird and compass bird avoidance device, including:

[0234] Second state data acquisition module: used to acquire second state data of the seismic acquisition system, the second state data of the seismic acquisition system is used to represent the position and orientation of the seismic operation vessel, the lateral control bird and the compass bird;

[0235] Operation plan determination module: used to determine the operation plan, which is the operation line for which data collection has not been completed;

[0236] Operation adjustment plan determination module: used to determine the operation adjustment plan according to the second state data of the seismic acquisition system and the operation plan, and display the operation adjustment plan. The operation adjustment plan is the acquisition probability of each operation survey line.

[0237] The marine operation towing obstacle avoidance device provided in the embodiment of the present invention can execute the marine operation towing obstacle avoidance method provided in any embodiment of the present invention mentioned above, and has the corresponding functions and beneficial effects of executing the marine operation towing obstacle avoidance method. For detailed process, please refer to the relevant operations of the marine operation towing obstacle avoidance method in the aforementioned embodiment.

[0238] Figure 6A schematic diagram of the structure of an electronic device for implementing the marine towing obstacle avoidance method according to an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are provided for example purposes only and are not intended to limit the implementation of the present inventions described and / or claimed herein.

[0239] like Figure 6 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0240] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0241] Processor 11 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning strategy algorithms, digital signal processors (DSPs), and any other suitable processor, controller, microcontroller, etc. Processor 11 executes the various methods and processes described above, such as the marine towing obstacle avoidance method.

[0242] In some embodiments, the marine operation towing obstacle avoidance method can be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the marine operation towing obstacle avoidance method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to execute the marine operation towing obstacle avoidance method in any other suitable manner (e.g., via firmware).

[0243] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system comprising at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0244] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0245] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0246] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0247] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0248] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0249] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0250] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A method for towing and avoiding obstacles in marine operations, characterized in that: include: Determine the obstacle status information, first status data of the seismic acquisition system and environmental data of the target sea area; The obstacle status information is used to characterize the type of obstacles in the target sea area and the corresponding operating status of the obstacles; the first state data of the seismic acquisition system is used to characterize the operating status data of the seismic acquisition system in the target sea area; The environmental data is used to characterize the natural environment of the target sea area; The seismic acquisition system includes: a seismic operation vessel and an operation tow truck; the seismic operation vessel is equipped with the operation tow truck; the operation tow truck is equipped with a lateral control bird and a compass bird; Matching a target control instruction generation strategy from candidate control instruction generation strategies according to the obstacle state information; the target control instruction generation strategy is used to generate target control instructions for the lateral control bird and / or compass bird; the target control instruction includes at least one of a first target control instruction, a second target control instruction, and a third target control instruction; the first target control instruction is used to control the lateral control bird to drive the work tow to avoid fixed-position objects; the second target control instruction is used to control the lateral control bird to drive the work tow to avoid floating objects; the third target control instruction is used to control the lateral control bird and the compass bird to drive the work tow to avoid fast-moving objects; determining a target control instruction through the target control instruction generation strategy according to the obstacle state information, the first state data of the seismic acquisition system, and the environmental data; Among them, include: Obtain angle data of the lateral control bird, distribution and towing structure data of the lateral control bird and the compass bird, and operation data of the seismic operation vessel from the first state data of the seismic acquisition system; construct a first undirected graph based on the angle data of the lateral control bird and the distribution and towing structure data of the lateral control bird and the compass bird, wherein the first undirected graph is used to characterize the wing distribution of the lateral control bird; encode the operation data of the seismic operation vessel and the state data of the fixed-position object through a first data coding layer to obtain a first sub-eigenvector; the first data coding layer is used to construct a relationship between the first state data of the seismic acquisition system and the obstacle state information; encode the first undirected graph through an image coding layer to obtain a second sub-eigenvector; the image coding layer is used to construct a distribution relationship between the lateral control bird and / or the compass bird in the undirected graph; encode the ocean current data through a second data coding layer to obtain a third sub-eigenvector; the second data coding layer is used to construct a relationship between environmental data; determine a first eigenvector based on the first sub-eigenvector, the second sub-eigenvector, and the third sub-eigenvector; decode the first eigenvector to obtain a first target control instruction, which is used to control the lateral control bird to adjust its angle; The lateral control bird and / or the compass bird are controlled according to the target control instruction to drive the working tractor to avoid obstacles.

2. The method according to claim 1, characterized in that The determining of obstacle status information of the target sea area includes: Acquire radar data within the target sea area; determining whether there are obstacles in the target sea area according to the radar data; If an obstacle exists, the obstacle status information is determined based on the obstacle change data in the radar data.

3. The method according to claim 1, characterized in that The determining the target control instruction by the target control instruction generation strategy according to the obstacle state information, the first state data of the seismic acquisition system and the environmental data includes: Acquire angle data of the lateral control bird, distribution and towing structure data of the lateral control bird and the compass bird, and operation data of the seismic operation vessel from the first state data of the seismic acquisition system; constructing a second undirected graph based on the angle data of the lateral control bird and the distribution drag structure data of the lateral control bird and the compass bird, wherein the second undirected graph is used to represent the wing distribution of the lateral control bird; Encoding the operation data of the seismic operation vessel and the state data of the floating object through the first data encoding layer to obtain a fourth sub-eigenvector; encoding the second undirected graph through an image coding layer to obtain a fifth sub-eigenvector; The ocean current data and wind data are encoded by the second data encoding layer to obtain a sixth sub-eigenvector; determining a second eigenvector based on the fourth sub-eigenvector, the fifth sub-eigenvector, and the sixth sub-eigenvector; The second characteristic vector is decoded to obtain a second target control instruction, where the second target control instruction is used to control the lateral control bird to adjust the angle.

4. The method according to claim 1, wherein The determining the target control instruction by the target control instruction generation strategy according to the obstacle state information, the first state data of the seismic acquisition system and the environmental data includes: Obtaining the angle data of the compass bird, the angle data of the lateral control bird, the distribution and towing structure data of the lateral control bird and the compass bird, and the operation data of the seismic operation vessel from the first state data of the seismic acquisition system; constructing a third undirected graph based on the angle data of the compass bird, the angle data of the lateral control bird, and the distribution drag structure data of the lateral control bird and the compass bird, wherein the third undirected graph is used to represent the wing distribution of the lateral control bird and the compass bird; Encoding the operation data of the seismic operation vessel and the state data of the fast-moving object through the first data encoding layer to obtain a seventh sub-eigenvector; Encoding the third undirected graph through an image coding layer to obtain an eighth sub-eigenvector; The ocean current data and wind data are encoded by the second data encoding layer to obtain a ninth sub-eigenvector; determining a third eigenvector based on the seventh sub-eigenvector, the eighth sub-eigenvector, and the ninth sub-eigenvector; The third eigenvector is decoded to obtain a third target control instruction, where the third target control instruction is used to control the lateral control bird and the compass bird to adjust the angle.

5. The method according to claim 1, characterized in that The step of controlling the lateral control bird and / or the compass bird according to the target control instruction to drive the working towing machine to avoid obstacles includes: Converting the acquired target control instruction into motor rotation angle information; According to the motor rotation angle information, the wing angles of the lateral control bird and / or the compass bird are adjusted through the lateral control bird and compass bird control system to drive the working tractor to avoid obstacles.

6. The method according to claim 5, characterized in that After the lateral control bird and / or the compass bird are controlled according to the target control instruction to drive the working towing vehicle to avoid obstacles, the method includes: Acquiring second state data of the seismic acquisition system, wherein the second state data of the seismic acquisition system is used to represent the position and orientation of the seismic operation vessel, the lateral control bird, and the compass bird; Determine an operation plan, wherein the operation plan is an operation survey line for which data collection has not been completed; An operation adjustment plan is determined according to the second state data of the seismic acquisition system and the operation plan, and the operation adjustment plan is displayed. The operation adjustment plan is the acquisition probability of each operation survey line.

7. A towing obstacle avoidance device for marine operations, characterized in that: include: A data determination module is used to determine the obstacle status information of the target sea area, the first state data of the seismic acquisition system and the environmental data; The obstacle status information is used to characterize the type of obstacles in the target sea area and the corresponding operating status of the obstacles; the first state data of the seismic acquisition system is used to characterize the operating status data of the seismic acquisition system in the target sea area; The environmental data is used to characterize the natural environment of the target sea area; The seismic acquisition system includes: a seismic operation vessel and an operation tow truck; the seismic operation vessel is equipped with the operation tow truck; the operation tow truck is equipped with a lateral control bird and a compass bird; a target control instruction generation strategy determination module, configured to match a target control instruction generation strategy from candidate control instruction generation strategies based on the obstacle state information; the target control instruction generation strategy is configured to generate a target control instruction for the lateral control bird and / or the compass bird; the target control instruction includes at least one of a first target control instruction, a second target control instruction, and a third target control instruction; the first target control instruction is configured to control the lateral control bird to drive the work tow truck to avoid fixed-position objects; the second target control instruction is configured to control the lateral control bird to drive the work tow truck to avoid floating objects; and the third target control instruction is configured to control the lateral control bird and the compass bird to drive the work tow truck to avoid fast-moving objects. a target control instruction determination module, configured to determine a target control instruction through the target control instruction generation strategy according to the obstacle state information, the first state data of the seismic acquisition system, and the environmental data; Among them, include: A data determination unit is configured to obtain angle data of the lateral control bird, distribution and towing structure data of the lateral control bird and the compass bird, and operation data of the seismic operation vessel from the first state data of the seismic acquisition system; A first undirected graph determining unit is configured to construct a first undirected graph based on the angle data of the lateral control bird and the distribution drag structure data of the lateral control bird and the compass bird, wherein the first undirected graph is used to represent the wing distribution of the lateral control bird; A first sub-eigenvector determining unit is configured to encode the operating data of the seismic operation vessel and the state data of the fixed-position object through a first data encoding layer to obtain a first sub-eigenvector; the first data encoding layer is configured to establish a relationship between the first state data of the seismic acquisition system and the obstacle state information; A second sub-eigenvector determining unit is configured to encode the first undirected graph through an image coding layer to obtain a second sub-eigenvector; the image coding layer is configured to construct a distribution relationship between lateral control birds and / or compass birds in the undirected graph; A third sub-eigenvector determining unit is configured to encode the ocean current data through a second data encoding layer to obtain a third sub-eigenvector; the second data encoding layer is configured to construct a relationship between environmental data; A first eigenvector determining unit: configured to determine a first eigenvector according to the first sub-eigenvector, the second sub-eigenvector, and the third sub-eigenvector; A first target control instruction determining unit is configured to decode the first feature vector to obtain a first target control instruction, wherein the first target control instruction is used to control the lateral control bird to adjust the angle; The control module is used to control the lateral control bird and / or the compass bird according to the target control instruction, so as to drive the working tractor to avoid obstacles.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the marine operation towing obstacle avoidance method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the marine operation towing obstacle avoidance method according to any one of claims 1 to 6 when executed.

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