Multi-tool cooperative control method of deep-sea special operation robot

Abstract

The application relates to a robot, and particularly discloses a multi-tool cooperative control method of a deep-sea special operation robot, which comprises a positioning system and a caterpillar walking mechanism assembled on the operation robot. The positioning system is used for the following steps: S01, acquiring marine environment data in real time to form first data transmitted to a shipborne terminal; S02, determining distance data of the shipborne terminal from the operation robot based on an acoustic response mode; S03, acquiring picture data of current operation of the operation robot in real time to form second data transmitted to the shipborne terminal; and S04, acquiring a surrounding environment magnetic field of the operation robot located under a seabed to determine attitude data of the operation robot and transmit the attitude data to the shipborne terminal as third data. Through coordination of the data, the caterpillar walking mechanism, the buoyancy control system of the operation robot and the underwater propulsion system can be self-adaptively cooperated according to the seabed topography.

Description

TECHNICAL FIELD

[0001] The present application relates to a robot, in particular to a multi-tool cooperative control method of a deep-sea special operation robot. BACKGROUND

[0002] The deep-sea special operation robot is applied to the needs of ocean oil and gas fields, underwater oil extraction device construction detection, artificial reef detection, and submarine salvage.

[0003] Publication (announcement) number: CN114839875A, publication (announcement) date: 2022-08-02, a kind of tracked deep-sea ore car inner and outer ring control method and system, comprising: step 1, through the outer ring transverse controller, the desired speed of the left track and right track of tracked deep-sea ore car is obtained;Outer ring transverse controller is based on tracked deep-sea ore car error kinematics model, and the influence of dynamic ocean current on the longitudinal velocity and yaw angular velocity of ore car is considered to obtain.This application is not only suitable for tracked deep-sea ore car, but also suitable for most tracked vehicles that need to overcome external interference to work, and has good adaptability to various complex working conditions.

[0004] In the prior art including the above-mentioned patent, due to the complexity of deep-sea operation and the need to meet the operation, based on the detection means, the operation environment under the deep-sea operation is more accurately positioned by comprehensive correction, so that the operation robot located in the deep-sea operation can make flexible changes in the process of moving forward according to the terrain. SUMMARY

[0005] The purpose of the present application is to provide a multi-tool cooperative control method of a deep-sea special operation robot, which solves the above problems.

[0006] In order to achieve the above-mentioned purpose, the present application provides the following technical scheme:

[0007] A multi-tool cooperative control method of a deep-sea special operation robot, comprising a positioning system and a tracked walking mechanism mounted on the operation robot, the positioning system is used for the following steps:

[0008] S01, real-time acquisition of marine environment data to form first data transmission to shipborne terminal;

[0009] S02, based on acoustic response mode to determine the distance data of the shipborne terminal from the operation robot;

[0010] S03, real-time acquisition of current operation robot moving picture data to form second data transmission to shipborne terminal;

[0011] S04, real-time acquisition of the ambient magnetic field under the seabed where the current working robot is located to determine the attitude data of the working robot and transmit the same as the third data to the shipborne terminal;

[0012] S05, real-time acquisition of the positioning data of the current working robot on the seabed, and then acquisition of satellite cloud image data of the current seabed according to the positioning data, and transmission of the same as the fourth data to the shipborne terminal;

[0013] S06, real-time acquisition of the sonar data of the advancing direction of the current working robot on the seabed, and transmission of the same as the fifth data to the shipborne terminal;

[0014] S07, the shipborne terminal dynamically corrects the operation parameters of the working robot based on the first data, the second data, the third data, the fourth data, the fifth data and the distance data to control the adaptive cooperation of the tracked walking mechanism, the buoyancy control system of the working robot and the underwater propulsion system.

[0015] As a preferred, the positioning system comprises:

[0016] A magnetometer for transmitting the third data;

[0017] A multi-parameter sensor for transmitting the first data;

[0018] An ultra-short baseline positioning system for transmitting the distance data;

[0019] A deep-sea camera and a 4k high-definition camera for transmitting the second data;

[0020] A forward-looking scanning sonar for transmitting the fifth data;

[0021] A navigation positioning system for transmitting the fourth data.

[0022] As a preferred, the first data acquired in the step S01 includes temperature data, time data and sea surge data, and the marine environment data of the water area where the current working robot moves is acquired;

[0023] The distance data acquired in the step S02 is dynamically corrected by the marine environment data transmitted by the step S01.

[0024] As a preferred, the dynamic correction of the distance data in the step S02 comprises:

[0025] S21, determining one pilot signal in the pilot signal sequence based on a preset marine environment data value range.

[0026] S22, the receiving end can estimate the delay and attenuation of each path by sending a known pilot signal;

[0027] S23, the ship-borne terminal receives the pilot signal, performs channel estimation, constructs an autocorrelation matrix R according to the autocorrelation characteristics of the received signal, calculates the cross-correlation vector p of the received signal and the expected signal, and uses the Wiener filter formula to calculate the filter coefficient w = R -1 p to eliminate the clutter in the distance data.

[0028] As a preferred, the second data in step S03 includes real-time picture data and continuous frame image data, a window is created for a predetermined time length, and the continuous frame image data in the predetermined window is compared with the picture data;

[0029] The picture data is extracted at one frame per second, and the image data at the same time phase is compared to determine the geographical form of the forward direction of the working robot;

[0030] In combination with the sonar data obtained in step S06, the system analyzes the height data of the geographical form located in the vertical horizontal plane;

[0031] The working robot is located in the satellite cloud data to form a continuous periodic collection point in a point form, and the moving track of the working robot is determined based on the periodic collection point, and the geographical form data of the forward direction of the working robot is obtained from the satellite cloud data, and is fitted with the height data to correct the floating / submerging parameters of the working robot.

[0032] As a preferred, the distance data obtained in step S02 includes the vertical horizontal plane distance and the horizontal plane distance established with the ship-borne terminal as the origin;

[0033] The positioning data obtained in step S05 includes the positioning of the ship-borne terminal and the positioning of the working robot, a straight line reference value is obtained by the straight line distance between the positioning of the ship-borne terminal and the positioning of the working robot, an error value is obtained by the difference between the straight line reference value and the horizontal plane distance, an error factor is obtained by percentage, and the floating / submerging parameters are corrected again according to the error factor.

[0034] As a preferred, the acoustic response mode in step S02 is to contact the working robot with the ship-borne terminal once every eight seconds.

[0035] As a preferred, the step S04 obtains the surrounding environment magnetic field under the sea bed walking of the current working robot to determine the attitude data of the working robot, which includes:

[0036] S41, based on the acquired determined geographical form data and the system acquired movement trajectory of the work robot;

[0037] S42, simulate and generate the magnetic field form of the feature unit located in the movement trajectory around the work robot, and compare with the third data;

[0038] S43, remove the magnetic field form of the feature unit contained in the third data to obtain the magnetic field form of the movement unit, thereby generating the correction parameter of the work robot posture.

[0039] In the above technical solution, the multi-tool cooperative control method of the deep-sea special work robot provided by the application has the following beneficial effects:

[0040] 1. Based on the magnetometer, multi-parameter sensor, ultra-short baseline positioning system, deep-sea camera, 4k high-definition camera, forward-looking scanning sonar and navigation positioning system, a variety of tool data acquisition modes are formed, and through the coordination of each data, the control of the tracked walking mechanism, the buoyancy control system of the work robot and the underwater propulsion system is realized according to the seabed topography self-adaptive cooperation.

[0041] 2. The signal of the collected distance data is dynamically filtered by the Wiener filter formula, so as to solve the problem that the wave reflection and refraction caused by the sea surface fluctuation will form multiple path signals to the receiver, causing multipath effect and signal distortion.

[0042] 3. According to the images and videos collected by the deep-sea camera and the 4k high-definition camera, the images are compared frame by frame at the same second, so as to determine the collected pictures, determine the geographical form, and determine the height data of the geographical form through the data collected by the forward-looking scanning sonar, and combine the satellite cloud map data to fit, so as to determine the work robot forward floating / dive parameters.

[0043] 4. By removing the magnetic field form of the feature unit contained in the third data, the avoidance measures of marine organisms in the forward path are obtained, that is, the correction parameter of the work robot posture is generated. BRIEF DESCRIPTION OF DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments described in the present application, and other drawings can also be obtained by those skilled in the art based on these drawings.

[0045] Figure 1 The structural schematic diagram provided by the embodiment of the present application;

[0046] Figure 2 Flow chart provided for the embodiments of the present application.

[0047] Reference signs:

[0048] 1, work robot; 2, crawler walking mechanism; 31, magnetometer; 32, multi-parameter sensor; 33, ultra-short baseline positioning system; 34, deep-sea camera; 35, 4k high-definition camera; 36, forward-looking scanning sonar; 37, navigation positioning system; 5, mechanical work arm. DETAILED DESCRIPTION

[0049] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0050] As shown in Figures 1-2 A multi-tool cooperative control method of a deep-sea special work robot, comprising a positioning system and a crawler walking mechanism 2 assembled on the work robot 1.

[0051] Embodiment one

[0052] The positioning system is used for the following steps:

[0053] S01, real-time acquisition of marine environment data to form first data transmitted to a shipborne terminal;

[0054] S02, based on an acoustic response mode to enable the shipborne terminal to determine distance data from the work robot 1;

[0055] S03, real-time acquisition of picture data of the current work robot 1 advancing to form second data transmitted to the shipborne terminal;

[0056] S04, real-time acquisition of the surrounding environment magnetic field under the current work robot 1 walking on the seabed to determine the attitude data of the work robot 1 and transmit the attitude data as third data to the shipborne terminal;

[0057] S05, real-time acquisition of the positioning data of the current work robot 1 on the seabed, and then acquisition of satellite cloud image data of the current seabed according to the positioning data, and transmission of the satellite cloud image data as fourth data to the shipborne terminal;

[0058] S06, real-time acquisition of sonar data of the current work robot 1 advancing in the direction of the seabed, and transmission of the sonar data as fifth data to the shipborne terminal;

[0059] S07, the shipboard terminal dynamically corrects the operation parameters of the working robot 1 based on the acquired first data, second data, third data, fourth data, fifth data and distance data, so as to control the adaptive cooperation of the tracked walking mechanism 2, the buoyancy control system of the working robot 1 and the underwater propulsion system.

[0060] Specifically, the positioning system in the above embodiment comprises:

[0061] A magnetometer 31 for transmitting third data;

[0062] A multi-parameter sensor 32 for transmitting first data;

[0063] An ultra-short baseline positioning system 33 for transmitting distance data;

[0064] A deep-sea camera 34 and a 4k high-definition camera 35 for transmitting second data;

[0065] A forward-looking scanning sonar 36 for transmitting fifth data;

[0066] A navigation positioning system 37 for transmitting fourth data.

[0067] Secondly, the 4k high-definition camera 35 cooperates with the mechanical working arm 5 to work.

[0068] Further, the acoustic response mode in step S02 makes the working robot 1 contact the shipboard terminal once every eight seconds.

[0069] In the above technology, based on the magnetometer 31, the multi-parameter sensor 32, the ultra-short baseline positioning system 33, the deep-sea camera 34, the 4k high-definition camera 35, the forward-looking scanning sonar 36 and the navigation positioning system 37 form a variety of tool data acquisition modes, and through the coordination of data with each other, the tracked walking mechanism 2, the buoyancy control system of the working robot 1 and the underwater propulsion system are realized according to the adaptive cooperation of the seabed topography.

[0070] Embodiment two

[0071] Based on the above embodiment one, the first data acquired includes temperature data, time data and sea surge data, and the marine environment data of the water area where the current working robot 1 moves is acquired;

[0072] The distance data acquired in step S02 is dynamically corrected by the marine environment data transmitted in step S01.

[0073] Secondly, the distance data in step S02 is dynamically corrected, which comprises:

[0074] S21, determining one pilot signal in the pilot signal sequence based on the preset marine environment data value range;

[0075] S22, the receiving end can estimate the delay and attenuation of each path by sending a known pilot signal;

[0076] S23, after the ship-borne terminal receives the pilot signal, channel estimation is performed, the autocorrelation matrix R is constructed according to the autocorrelation characteristics of the received signal, the cross-correlation vector p of the received signal and the expected signal is calculated, and the filter coefficient w=R -1 p is calculated using the Wiener filter formula to eliminate clutter in the distance data.

[0077] The above dynamic filtering of the collected distance data signal through the Wiener filter formula solves the problem that wave reflection and refraction caused by sea surface fluctuations will form multiple path signals reaching the receiver, causing multipath effect and signal distortion.

[0078] Embodiment three

[0079] Based on the above embodiment one, the second data includes real-time picture data and continuous frame image data, a window is created with a predetermined time length, and the continuous frame image data in the predetermined window is compared with the picture data;

[0080] The picture data is extracted at one frame per second, and the extracted picture data is compared with the image data at the same time phase to determine the geographical form of the forward direction of the operation robot 1;

[0081] In combination with the height data of the geographical form located in the vertical horizontal plane obtained by the sonar data in step S06, the system analysis obtains the height data of the geographical form located in the vertical horizontal plane;

[0082] The operation robot 1 is located in the satellite cloud data to form a continuous periodic collection point in a dot shape, and the movement trajectory of the operation robot 1 is determined based on the periodic collection point, and the geographical form data of the forward direction of the operation robot 1 is obtained based on the movement trajectory, and is fitted with the height data to correct the floating / submerging parameters of the operation robot 1.

[0083] Further, the obtained distance data includes the vertical horizontal plane distance and the horizontal plane distance established with the ship-borne terminal as the origin;

[0084] The positioning data obtained in step S05 includes the positioning of the ship-borne terminal and the positioning of the operation robot 1, a straight line reference value is obtained through the straight line distance between the positioning of the ship-borne terminal and the positioning of the operation robot 1, an error value is obtained by subtracting the horizontal plane distance from the straight line reference value, a percentage error factor is obtained, and the floating / submerging parameters are further corrected according to the error factor.

[0085] The above technology compares the images in the images and videos collected by the deep-sea camera 34 and the 4K high-definition camera 35 frame by frame at the same second, thereby determining the collected images, determining the geographical form, and determining the height data of the geographical form through the data collected by the forward-looking scanning sonar 36, fitting the satellite cloud data, and thereby determining the forward floating / descent parameters of the operation robot 1.

[0086] Embodiment Four

[0087] Based on the above embodiment one, when the surrounding environment magnetic field under the seabed walking of the current operation robot 1 is obtained, the attitude data of the operation robot 1 is determined to include:

[0088] S41, based on the obtained determined geographical form data and the movement trajectory of the operation robot 1 obtained by the system;

[0089] S42, simulating and generating the magnetic field form of the feature units located in the movement trajectory around the operation robot 1, and comparing with the third data;

[0090] S43, removing the magnetic field form of the feature units contained in the third data to obtain the magnetic field form of the movement units (that is, the moving organisms in front of the operation robot 1), thereby generating the correction parameters of the attitude of the operation robot 1.

[0091] In the above technology, by removing the magnetic field form of the feature units contained in the third data, the avoidance measures of the marine organisms in the forward path are obtained, that is, the correction parameters of the attitude of the operation robot 1 are generated.

[0092] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer usable program code.

[0093] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices produce a device that implements the flowcharts and / or block diagrams. Figure 1one or more processes and / or blocks Figure 1 an apparatus for performing the functions specified in the flowchart or multiple flows and / or blocks.

[0094] These computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instructions apparatus implementing the flowchart Figure 1 one or more processes and / or blocks Figure 1 an apparatus for performing the functions specified in the flowchart or multiple flows and / or blocks.

[0095] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process so that the instructions executed on the computer or other programmable apparatus provide steps for implementing the flowchart Figure 1 one or more processes and / or blocks Figure 1 an apparatus for performing the functions specified in the flowchart or multiple flows and / or blocks.

[0096] The principles and implementation of the present application are described in the specific embodiments, and the above description of the embodiments is only to help understand the method and core idea of the present application; at the same time, for those skilled in the art, according to the idea of the present application, there will be changes in specific implementation and application range, and the above description of the present application should not be understood as a limitation.

[0097] The embodiments of the present application also provide a specific implementation of an electronic device capable of implementing all steps in the method in the above embodiments, which specifically includes the following content:

[0098] processor, memory, communications interface and bus;

[0099] The processor, memory and communications interface complete mutual communication through the bus;

[0100] The processor is configured to invoke a computer program in the memory, and the processor implements all steps in the method in the above embodiments when executing the computer program.

[0101] The embodiments of the present application also provide a computer readable storage medium capable of implementing all steps in the method in the above embodiments, and the computer readable storage medium stores a computer program, which is executed by a processor to implement all steps in the method in the above embodiments.

[0102] The various embodiments described in this specification are intended to be illustrative only and in no way limit the scope of the application. Thus, changes and modifications can be made by those skilled in the art, with the scope of the application being indicated by the following claims. For example, although the various embodiments have been described above in the context of fully functional devices, the implementation is equally applicable to distributed or networked implementations where tasks are performed by remote processing devices that are linked through a communications network. In other embodiments, various operational elements of the described embodiments can be combined or eliminated, and other operational elements can be added. Various embodiments can be implemented using hardware elements, software elements, or a combination of both. Examples of hardware elements can include devices, logic devices, components, processors, microprocessors, circuits, boards, memories, storage devices, buses, wires, communication devices, transmitters, receivers, and / or the like. Examples of software elements can include software components, programs, applications, computer programs, application programs, system programs, software development programs, machine programs, operating system Figure 1 one or more functions specified by one or more blocks or a combination of blocks. Figure 1 one or more functions specified by one or more blocks or a combination of blocks.

[0103] Those skilled in the art will appreciate that embodiments of the present specification can be devised for a method, a system, or a computer program product. Accordingly, embodiments of the present specification can be embodied in the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present specification can be in the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk memory, CD-ROM, optical storage medium, etc.) embodying computer usable program code. Each of the various embodiments of the present specification is described in a progressive manner, and reference can be made to other embodiments for the same or similar parts. Each embodiment focuses on the differences from other embodiments. In particular, for system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and reference can be made to the description of the method embodiments. In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the embodiments of the present specification.

[0104] In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. In addition, those skilled in the art can combine and combine the different embodiments or examples described in the present specification and the features of the different embodiments or examples without contradiction. The above is only an embodiment of the embodiments of the present specification and is not intended to limit the embodiments of the present specification. The embodiments of the present specification can have various modifications and changes for those skilled in the art. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the embodiments of the present specification shall be included in the scope of the claims of the embodiments of the present specification.

Claims

1. A multi-tool collaborative control method for a deep-sea special operations robot, characterized in that, Includes a positioning system mounted on the work robot (1) and a tracked walking mechanism (2), the positioning system being used to perform the following steps: S01. Acquire marine environmental data in real time to form the first data and transmit it to the shipborne terminal; S02, Based on the acoustic response mode, the shipborne terminal determines the distance data with the working robot (1); S03. Real-time acquisition of the image data of the current working robot (1) moving forward, so as to form a second data transmission to the shipborne terminal; S04. Real-time acquisition of the surrounding magnetic field of the current working robot (1) under the seabed to determine the attitude data of the working robot (1) and transmit it to the shipborne terminal as third data. S05. Real-time acquisition of the positioning data of the current working robot (1) on the seabed, and then acquisition of the satellite cloud image data of the current seabed based on the positioning data, and transmission of the data to the shipboard terminal as the fourth data. S06. Real-time acquisition of sonar data of the current working robot (1) at the seabed forward position, and transmission of the data to the shipboard terminal as the fifth data. S07. The shipborne terminal dynamically corrects the operating parameters of the work robot (1) based on the acquired first data, second data, third data, fourth data, fifth data and distance data, so as to control the adaptive cooperation of the tracked walking mechanism (2), the buoyancy control system of the work robot (1) and the underwater propulsion system. The second data in step S03 includes real-time screen data and continuous frame image data. A window is created for a predetermined duration, and the continuous frame image data within the predetermined window is compared with the screen data. The image data is extracted at one frame per second and compared with the image data at the same time phase to determine the geographical features of the direction of the operation robot (1) moving forward; Then, by combining the sonar data obtained in step S06, the system analyzes and obtains the height data of the geographical feature located in the vertical horizontal plane; The operation robot (1) is located in the satellite cloud image data, which forms a continuous periodic collection point in the form of dots. The movement trajectory of the operation robot (1) is determined based on the periodic collection point. The geographical morphology data of the forward direction of the operation robot (1) is obtained according to the movement trajectory and fitted with the height data to correct the ascent / descent parameters of the operation robot (1).

2. The multi-tool collaborative control method for a deep-sea special operations robot according to claim 1, characterized in that, The positioning system includes: Magnetometer (31) used to transmit the third data. A multi-parameter sensor (32) used to transmit the first data; An ultra-short baseline positioning system (33) for transmitting the distance data. A deep-sea camera (34) and a 4K high-definition camera (35) are used to transmit the second data. Forward scanning sonar (36) used to transmit the fifth data; The navigation and positioning system (37) is used to transmit the fourth data.

3. The multi-tool collaborative control method for a deep-sea special operations robot according to claim 1, characterized in that, The first data obtained in step S01 includes temperature data, time data, and seawater surge data, and the marine environment data of the water area where the current operation robot (1) is moving is obtained; The distance data obtained in step S02 is dynamically corrected using the marine environmental data transmitted in step S01.

4. The multi-tool collaborative control method for a deep-sea special operations robot according to claim 3, characterized in that, Dynamically correcting the distance data in step S02 includes: S21. Determine a pilot signal from the pilot signal sequence based on a preset marine environmental data range. S22. By sending known pilot signals, the receiver can estimate the delay and attenuation of each path; S23. After receiving the pilot signal, the shipborne terminal performs channel estimation, constructs an autocorrelation matrix R based on the autocorrelation characteristics of the received signal, calculates the cross-correlation vector p between the received signal and the desired signal, and calculates the filter coefficients using the Wiener filter formula. This is to eliminate clutter in the distance data.

5. The multi-tool collaborative control method for a deep-sea special operations robot according to claim 1, characterized in that, The distance data obtained in step S02 includes the vertical horizontal distance and the horizontal horizontal distance established with the shipborne terminal as the origin. The positioning data obtained in step S05 includes the positioning of the shipborne terminal and the positioning of the operation robot (1). A straight reference value is obtained by the straight-line distance between the positioning of the shipborne terminal and the operation robot (1), and an error value is obtained by subtracting the straight reference value from the horizontal distance. The percentage is calculated to obtain the error factor, and then the surfacing / diving parameters are corrected a second time according to the error factor.

6. The multi-tool collaborative control method for a deep-sea special operations robot according to claim 1, characterized in that, In step S02, the acoustic response mode is to make the working robot (1) contact the shipborne terminal once every eight seconds.

7. The multi-tool collaborative control method for a deep-sea special operations robot according to claim 1, characterized in that, In step S04, obtaining the surrounding magnetic field of the current working robot (1) while it is walking on the seabed to determine the attitude data of the working robot (1) includes: S41. Based on the acquired and determined geographic morphology data and the movement trajectory of the operation robot (1) acquired by the system; S42. Simulate and generate the magnetic field pattern of the tangible feature unit around the working robot (1) on the movement trajectory, and compare it with the third data; S43. Remove the magnetic field shape of the feature unit contained in the third data to obtain the magnetic field shape of the moving unit, thereby generating the posture correction parameters of the working robot (1).

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the multi-tool collaborative control method for the deep-sea special operation robot according to any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the multi-tool collaborative control method for the deep-sea special operation robot according to any one of claims 1 to 7.

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