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

Abstract

The invention relates to a robot, and particularly discloses a multi-tool cooperative control method for a deep-sea special operation robot, the multi-tool cooperative control method comprises a positioning system and a crawler-type walking mechanism which are assembled on the operation robot, and the positioning system is used for implementing the following steps: S01, acquiring marine environment data in real time to form first data, and transmitting the first data to a shipborne terminal; s02, based on an acoustic response mode, enabling the shipborne terminal to determine distance data between the shipborne terminal and the operation robot; s03, picture data of advancing of the current operation robot are obtained in real time, so that second data are formed and transmitted to the shipborne terminal; and S04, acquiring a surrounding environment magnetic field of the current operation robot walking under the seabed in real time to determine attitude data of the operation robot, and transmitting the attitude data to the shipborne terminal as third data. According to the invention, through mutual coordination of the data, the crawler-type walking mechanism, the buoyancy control system of the operation robot and the underwater propulsion system are controlled to realize self-adaptive cooperation according to the seabed terrain.

Description

Technical Field

[0001] The invention relates to a robot, and in particular to a multi-tool cooperative control method for a deep-sea special operation robot. Background Art

[0002] Deep-sea special operation robots are used in marine oil and gas fields, underwater oil production equipment construction inspection, artificial reef inspection, seabed rescue and other needs.

[0003] Publication (announcement) number: CN114839875A, Publication (announcement) date: 2022-08-02, a method and system for controlling inner and outer rings of a crawler deep-sea ore collecting vehicle is disclosed, comprising: Step 1, obtaining the desired speeds of the left and right crawlers of the crawler deep-sea ore collecting vehicle through the outer ring lateral controller; the outer ring lateral controller is based on the error kinematic model of the crawler deep-sea ore collecting vehicle, and is obtained by considering the influence of dynamic ocean currents on the longitudinal speed and yaw angular velocity of the ore collecting vehicle. The present invention is not only applicable to crawler deep-sea ore collecting vehicles, but also to the vast majority of crawler vehicles that need to overcome external interference to operate, and has good adaptability to various complex working conditions.

[0004] In the prior art including the above-mentioned patents, due to the complexity of deep-sea operations and the need to meet the operations, comprehensive corrections are made through a variety of detection methods to obtain more accurate positioning information for the working environment under deep-sea operations, thereby facilitating the working robots in deep-sea operations to make flexible changes according to the terrain during the process of moving forward. Summary of the invention

[0005] The purpose of the present invention is to provide a multi-tool collaborative control method for a deep-sea special operation robot to solve the above-mentioned problems.

[0006] In order to achieve the above object, the present invention provides the following technical solutions:

[0007] A multi-tool collaborative control method for a deep-sea special operation robot includes a positioning system and a crawler walking mechanism mounted on the operation robot, wherein the positioning system is used to implement the following steps:

[0008] S01. Acquire marine environment data in real time to form first data and transmit it to the shipborne terminal;

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

[0010] S03, acquiring the image data of the current operation robot moving forward in real time to form second data and transmit it to the ship-borne terminal;

[0011] S04, acquiring in real time the surrounding magnetic field of the current working robot walking on the seabed, so as to determine the posture data of the working robot, and transmitting the posture data to the shipborne terminal as the third data;

[0012] S05, obtaining the positioning data of the current operating robot on the seabed in real time, and then obtaining the satellite cloud image data of the current seabed according to the positioning data, and transmitting it to the shipborne terminal as the fourth data;

[0013] S06, acquiring sonar data of the current operating robot at the forward direction of the seabed in real time, and transmitting the data as the fifth data to the shipborne terminal;

[0014] S07. The shipborne terminal dynamically corrects the operating parameters of the working robot based on the acquired first data, second data, third data, fourth data dynamics, fifth data and the distance data to control the adaptive collaboration of the crawler walking mechanism, the buoyancy control system of the working robot and the underwater propulsion system.

[0015] Preferably, 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 said distance data;

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

[0020] a forward-looking scanning sonar for transmitting said fifth data;

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

[0022] Preferably, the first data acquired in step S01 includes temperature data, time data, and seawater surging data, and the marine environment data of the water area where the operating robot is currently moving is acquired;

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

[0024] Preferably, dynamically correcting the distance data in step S02 includes:

[0025] S21. Determine a pilot signal in a pilot signal sequence based on a preset ocean environment data value range.

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

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

[0028] Preferably, the second data in step S03 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;

[0029] Extracting picture data at one frame per second and comparing it with image data of the same time phase to determine the geographical form of the direction in which the working robot is moving;

[0030] Combined with the sonar data obtained in step S06, the system determines the height data of the geographical features located in the vertical plane through analysis;

[0031] The working robot is located at a continuous periodic collection point formed by a dot in the satellite cloud image data, and the movement trajectory of the working robot is determined based on the periodic collection points. The geographic morphological data of the working robot's forward direction in the satellite cloud image data is obtained according to the movement trajectory, and is fitted with the height data to correct the floating / diving parameters of the working robot.

[0032] Preferably, the distance data acquired in step S02 includes a vertical horizontal plane distance and a horizontal horizontal plane distance established with the shipborne terminal as the origin;

[0033] The positioning data obtained in step S05 includes the positioning of the shipborne terminal and the positioning of the working robot. The straight-line reference value is obtained by the straight-line distance between the positioning of the shipborne terminal and the working robot, and the error value is obtained by subtracting the straight-line reference value from the lateral horizontal plane distance. The error factor is obtained by calculating the percentage, and then the floating / diving parameters are corrected for the second time according to the error factor.

[0034] Preferably, the acoustic response mode in step S02 is to enable the operating robot to contact the ship-borne terminal once every eight seconds.

[0035] Preferably, the step S04 of obtaining the surrounding magnetic field of the current working robot when it is walking on the seabed to determine the posture data of the working robot includes:

[0036] S41, based on the obtained determined geographic morphological data and the moving trajectory of the working robot obtained by the system;

[0037] S42, simulating and generating a magnetic field form under a characteristic unit that can be touched around the working robot in the moving trajectory, and comparing it with the third data;

[0038] S43, removing the magnetic field form under the characteristic unit contained in the third data, obtaining the magnetic field form of the moving unit, and thus generating correction parameters for the working robot posture.

[0039] In the above technical solution, the multi-tool collaborative control method of a deep-sea special operation robot provided by the present invention has the following beneficial effects:

[0040] 1. A method of data collection using multiple tools is formed based on magnetometers, multi-parameter sensors, ultra-short baseline positioning systems, deep-sea cameras, 4k high-definition cameras, forward-looking scanning sonars and navigation and positioning systems. Through the coordination of various data, the crawler walking mechanism, the buoyancy control system of the working robot and the underwater propulsion system can be controlled to adaptively collaborate according to the seabed terrain.

[0041] 2. Dynamically filter the collected distance data signals through the Wiener filter formula to solve the problem that the wave reflection and refraction caused by sea surface fluctuations will form multiple path signals to reach the receiver, resulting in multipath effect and signal distortion.

[0042] 3. The images collected by the deep-sea camera and 4k high-definition camera are compared with the images in the video frame by frame at the same second to determine the collected images and the geographical morphology. The height data of the geographical morphology is determined by the data collected by the forward-looking scanning sonar, and the satellite cloud map data is fitted to determine the forward floating / diving parameters of the operating robot.

[0043] 4. By removing the magnetic field form under the characteristic unit contained in the third data, the avoidance measures for the marine life in the forward path are obtained, that is, the correction parameters of the working robot posture are generated. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0045] Figure 1 A schematic diagram of the structure provided by an embodiment of the present invention;

[0046] Figure 2 A flowchart provided for an embodiment of the present invention.

[0047] Description of reference numerals:

[0048] 1. Working robot; 2. Tracked 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 working arm. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments 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 creative work are within the scope of protection of the present invention.

[0050] like Figure 1-2 As shown, a multi-tool collaborative control method for a deep-sea special operation robot includes a positioning system and a crawler walking mechanism 2 mounted on the operation robot 1.

[0051] Embodiment 1

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

[0053] S01. Acquire marine environment data in real time to form first data and transmit it to the shipborne terminal;

[0054] S02, based on the acoustic response mode, so that the ship-borne terminal determines the distance data from the working robot 1;

[0055] S03, acquiring the image data of the current working robot 1 moving forward in real time to form second data and transmit it to the ship-borne terminal;

[0056] S04, obtaining in real time the surrounding magnetic field of the current working robot 1 walking on the seabed, so as to determine the posture data of the working robot 1, and transmitting it to the shipborne terminal as the third data;

[0057] S05, obtaining the current positioning data of the working robot 1 on the seabed in real time, and then obtaining the satellite cloud image data of the current seabed according to the positioning data, and transmitting it to the shipborne terminal as the fourth data;

[0058] S06, acquiring in real time the sonar data of the current working robot 1 at the forward direction of the seabed, and transmitting the data as the fifth data to the shipborne terminal;

[0059] S07. The shipborne terminal dynamically corrects the operating parameters of the working robot 1 based on the acquired first data, second data, third data, fourth data dynamics, fifth data and distance data to control the adaptive collaboration of the crawler 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 includes:

[0061] A magnetometer 31 for transmitting third data;

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

[0063] Ultra-short baseline positioning system for transmitting distance data33;

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

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

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

[0067] Secondly, the operation is performed by using a 4k high-definition camera 35 in conjunction with a mechanical working arm 5.

[0068] Furthermore, in step S02, the acoustic response mode enables the working robot 1 to communicate with the ship-borne terminal once every eight seconds.

[0069] In the above technology, a method of collecting data from multiple tools is formed based on the magnetometer 31, multi-parameter sensor 32, ultra-short baseline positioning system 33, deep-sea camera 34, 4k high-definition camera 35, forward-looking scanning sonar 36 and navigation positioning system 37. Through the coordination of data, the crawler walking mechanism 2, the buoyancy control system of the working robot 1 and the underwater propulsion system can be controlled to cooperate adaptively according to the seabed terrain.

[0070] Embodiment 2

[0071] Based on the above-mentioned embodiment 1, the first data obtained includes temperature data, time data, and seawater surging data, and the marine environment data of the water area where the working robot 1 is currently moving is obtained;

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

[0073] Secondly, dynamically correcting the distance data in step S02 includes:

[0074] S21, determining a pilot signal in a pilot signal sequence based on a preset ocean environment data value range;

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

[0076] S23, after receiving the pilot signal, the shipborne terminal performs channel estimation, constructs the autocorrelation matrix R according to the autocorrelation characteristics of the received signal, calculates the cross-correlation vector p between the received signal and the expected signal, and uses the Wiener filter formula to calculate the filter coefficient w = R -1 p, to eliminate clutter in the distance data.

[0077] The above-mentioned Wiener filter formula is used to dynamically filter the signal of the collected distance data, thereby solving the problem that the wave reflection and refraction caused by the sea surface fluctuation will form multiple path signals to reach the receiver, resulting in multipath effect and signal distortion.

[0078] Embodiment 3

[0079] Based on the above-mentioned first embodiment, the second data includes real-time screen 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 screen data;

[0080] Extracting picture data at one frame per second and comparing it with the image data of the same time phase, to determine the geographical form of the direction in which the working robot 1 is moving;

[0081] Combined with the sonar data obtained in step S06, the system analyzes and obtains the height data of the geographical form located on the vertical horizontal plane;

[0082] The working robot 1 is located at a continuous periodic collection point formed by a dot in the satellite cloud map data, and the moving trajectory of the working robot 1 is determined based on the periodic collection points. The geographic morphological data of the working robot 1's forward direction in the satellite cloud map data is obtained according to the moving trajectory, and is fitted with the height data to correct the floating / diving parameters of the working robot 1.

[0083] Furthermore, the acquired distance data includes a vertical horizontal plane distance and a lateral horizontal plane distance established with the shipborne terminal as the origin;

[0084] The positioning data obtained in step S05 includes the positioning of the shipborne terminal and the positioning of the working robot 1. The straight-line reference value is obtained by the straight-line distance between the positioning of the shipborne terminal and the working robot 1, and the error value is obtained by subtracting the straight-line reference value from the lateral horizontal plane distance. The error factor is obtained by calculating the percentage, and then the floating / diving parameters are corrected for the second time according to the error factor.

[0085] In the above technology, the images collected by the deep-sea camera 34 and the 4k high-definition camera 35 are compared with the images in the video frame by frame at the same second, so as to determine the collected pictures and thus the geographical morphology, and then the height data of the geographical morphology is determined by the data collected by the forward-looking scanning sonar 36, and is fitted with the satellite cloud map data to determine the forward floating / diving parameters of the working robot 1.

[0086] Embodiment 4

[0087] Based on the above embodiment 1, when the surrounding magnetic field of the current working robot 1 walking on the seabed is obtained to determine the posture data of the working robot 1, it includes:

[0088] S41, based on the obtained determined geographic morphological data and the moving trajectory of the working robot 1 obtained by the system;

[0089] S42, simulating and generating a magnetic field form under a characteristic unit that can be touched around the working robot 1 in the moving trajectory, and comparing it with the third data;

[0090] S43. Remove the magnetic field form under the characteristic unit contained in the third data to obtain the magnetic field form of the moving unit (that is, the organism moving in front of the working robot 1), thereby generating correction parameters for the posture of the working robot 1.

[0091] In the above technology, by removing the magnetic field form under the characteristic unit contained in the third data, the avoidance measures for marine organisms in the forward path are obtained, that is, the correction parameters of the posture of the working robot 1 are generated.

[0092] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0093] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0094] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0095] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0096] The present invention uses specific embodiments to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

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

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

[0099] Wherein, the processor, memory, and communication interface communicate with each other via the bus;

[0100] The processor is used to call the computer program in the memory, and when the processor executes the computer program, all the steps in the method in the above embodiment are implemented.

[0101] The embodiments of the present application also provide a computer-readable storage medium capable of implementing all the steps of the method in the above embodiments, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, all the steps of the method in the above embodiments are implemented.

[0102] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the hardware + program embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. Although the embodiment of this specification provides the method operation steps described in the embodiment or flow chart, more or less operation steps can be included based on conventional or non-creative means. The order of steps listed in the embodiment is only one way of executing the order of many steps, and does not represent the only execution order. When the device or terminal product in practice is executed, it can be executed in sequence or in parallel according to the method shown in the embodiment or the accompanying drawings (for example, a parallel processor or a multi-threaded processing environment, or even a distributed data processing environment). The term "include", "include" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, product or device including a series of elements includes not only those elements, but also includes other elements that are not explicitly listed, or also includes elements inherent to such a process, method, product or device. In the absence of more restrictions, it is not excluded that there are other identical or equivalent elements in the process, method, product or device including the elements. For the convenience of description, the above device is described by dividing it into various modules according to its functions. Of course, when implementing the embodiments of this specification, the functions of each module can be implemented in the same one or more software and / or hardware, or the module implementing the same function can be implemented by a combination of multiple sub-modules or sub-units. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the coupling or direct coupling or communication connection between each other shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms. The present invention is described with reference to the flowchart and / or block diagram of the method, device (system) and computer program product according to the embodiments of the present invention. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the process and / or box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the process Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0103] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems or computer program products. Therefore, the embodiments of this specification may be in the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the embodiments of this specification may be in the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. Each embodiment in this specification is described in a progressive manner, and the same and similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts refer to the partial description of the method embodiment. In the description of this specification, the description of the reference term "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the embodiment of this specification.

[0104] In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradicting each other. The above is only an embodiment of the embodiment of this specification and is not intended to limit the embodiment of this specification. For those skilled in the art, the embodiment of this specification may have various changes and variations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiment of this specification shall be included in the scope of the claims of the embodiment of this specification.

Claims

1. A multi-tool collaborative control method for a deep-sea special operation robot, characterized in that: The invention comprises a positioning system and a crawler-type walking mechanism (2) mounted on a working robot (1), wherein the positioning system is used to implement the following steps: S01. Acquire marine environment data in real time to form first data and transmit it to the shipborne terminal; S02, based on the acoustic response mode, enabling the shipborne terminal to determine the distance data from the working robot (1); S03, acquiring in real time the image data of the current working robot (1) moving forward, so as to form second data and transmit it to the ship-borne terminal; S04, acquiring in real time the surrounding magnetic field of the current working robot (1) walking on the seabed, so as to determine the posture data of the working robot (1), and transmitting the posture data to the ship-borne terminal as the third data; S05, obtaining in real time the positioning data of the current operating robot (1) on the seabed, and then obtaining satellite cloud image data of the current seabed according to the positioning data, and transmitting the data as fourth data to the shipborne terminal; S06, acquiring in real time the sonar data of the current operating robot (1) at the forward direction of the seabed, and transmitting the data as the fifth data to the ship-borne terminal; S07. The shipborne terminal dynamically corrects the operating parameters of the working robot (1) based on the acquired first data, second data, third data, fourth data dynamics, fifth data and the distance data, so as to control the adaptive collaboration of the crawler walking mechanism (2), the buoyancy control system and the underwater propulsion system of the working robot (1).

2. The multi-tool collaborative control method of a deep-sea special operation robot according to claim 1, characterized in that: The positioning system comprises: A magnetometer (31) for transmitting the third data; A multi-parameter sensor (32) for transmitting said first data; An ultra-short baseline positioning system (33) for transmitting said distance data; A deep sea camera (34) and a 4k high definition video camera (35) for transmitting the second data; a forward-looking scanning sonar (36) for transmitting said fifth data; A navigation and positioning system (37) for transmitting said fourth data.

3. The multi-tool collaborative control method of a deep-sea special operation robot according to claim 1, characterized in that: The first data acquired in step S01 includes temperature data, time data, and seawater surging data, and the marine environment data of the water area where the working robot (1) is currently moving is acquired; The distance data acquired in step S02 is dynamically corrected by the ocean environment data transmitted in step S01.

4. The multi-tool collaborative control method of a deep-sea special operation robot according to claim 3 is characterized in that: Dynamically correcting the distance data in step S02 includes: S21, determining a pilot signal in a pilot signal sequence based on a preset ocean environment data value range S22. By sending a known pilot signal, the receiving end 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 according to the autocorrelation characteristics of the received signal, calculates the cross-correlation vector p between the received signal and the expected signal, and uses the Wiener filter formula to calculate the filter coefficient w=R -1 p, in order to eliminate clutter in the distance data.

5. The multi-tool collaborative control method of a deep-sea special operation robot according to claim 1, characterized in that: The second data in step S03 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; Extracting picture data at one frame per second and comparing it with image data of the same time phase to determine the geographical form of the direction in which the working robot (1) is moving; Combined with the sonar data obtained in step S06, the system determines the height data of the geographical features located in the vertical plane through analysis; The working robot (1) is located at a continuous periodic collection point formed by the satellite cloud image data in a dotted form, and the movement trajectory of the working robot (1) is determined based on the periodic collection point, and the geographical morphological data of the direction of advance of the working robot (1) in the satellite cloud image data is obtained according to the movement trajectory, and is fitted with the height data to correct the floating / diving parameters of the working robot (1).

6. The multi-tool collaborative control method of a deep-sea special operation robot according to claim 1, characterized in that: The distance data acquired in step S02 includes a vertical horizontal plane distance and a horizontal horizontal plane 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 working robot (1). The straight line reference value is obtained by the straight line distance between the positioning of the shipborne terminal and the working robot (1), and the error value is obtained by subtracting the straight line reference value from the horizontal plane distance. The error factor is obtained by calculating the percentage, and then the floating / diving parameters are corrected for the second time according to the error factor.

7. The multi-tool collaborative control method of a deep-sea special operation robot according to claim 1, characterized in that: The acoustic response mode in step S02 is to make the operating robot (1) contact the ship-borne terminal once every eight seconds.

8. The multi-tool collaborative control method of a deep-sea special operation robot according to claim 1, characterized in that: The step S04 of obtaining the surrounding magnetic field of the current working robot (1) when it is walking on the seabed to determine the posture data of the working robot (1) includes: S41, based on the obtained and determined geographic morphological data and the movement trajectory of the working robot (1) obtained by the system; S42, simulating and generating a magnetic field form under a characteristic unit that can be touched around the working robot (1) in the moving trajectory, and comparing it with the third data; S43, removing the magnetic field form under the characteristic unit contained in the third data, obtaining the magnetic field form of the moving unit, and thus generating correction parameters for the posture of the working robot (1).

9. 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, the steps of the multi-tool collaborative control method of the deep-sea special operation robot according to any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the multi-tool collaborative control method of the deep-sea special operation robot described in any one of claims 1 to 8 are implemented.

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