WO2022174545A1 - Procédé d'optimisation de trajectoire, véhicule sous-marin et support de stockage lisible par ordinateur - Google Patents

Procédé d'optimisation de trajectoire, véhicule sous-marin et support de stockage lisible par ordinateur Download PDF

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Publication number
WO2022174545A1
WO2022174545A1 PCT/CN2021/104062 CN2021104062W WO2022174545A1 WO 2022174545 A1 WO2022174545 A1 WO 2022174545A1 CN 2021104062 W CN2021104062 W CN 2021104062W WO 2022174545 A1 WO2022174545 A1 WO 2022174545A1
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state vector
preset
motion information
visual
underwater vehicle
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PCT/CN2021/104062
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English (en)
Chinese (zh)
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陈娟
孙彩明
张爱东
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鹏城实验室
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06311—Scheduling, planning or task assignment for a person or group

Definitions

  • the present application relates to the technical field of underwater navigation, and in particular, to a path optimization method, an underwater vehicle, and a computer-readable storage medium.
  • underwater underwater vehicle Unmanned Underwater Vehicle
  • more and more underwater tasks can be controlled by manual remote control or autonomous operating system to complete underwater work.
  • the underwater vehicle has the ability of underwater positioning and navigation and advanced control, which reduces the manual participation in the process of task execution, making the role of the underwater vehicle more and more obvious.
  • the main purpose of the present application is to provide a path optimization method, an underwater vehicle, and a computer-readable storage medium, aiming to solve the problem that the final path accuracy rate of the underwater vehicle obtained by using the existing path optimization method in the prior art is higher than that of the underwater vehicle. Low technical issues.
  • the present application proposes a path optimization method, which is applied to an underwater vehicle in a preset positioning system, and the method includes:
  • the step of obtaining the resultant motion information of the underwater vehicle based on the historical motion information and the real-time observation amount includes:
  • Resulting motion information is obtained based on the resulting state vector and a preset control signal in the preset motion information.
  • the historical motion information includes a historical state vector and a historical control signal; the historical motion information is used to predict the state of the underwater vehicle, so as to obtain a state of the underwater vehicle.
  • the steps to predict the state vector include:
  • the predicted state vector is obtained by using formula 1;
  • t is the time corresponding to the predicted state vector
  • M t is the motion uncertainty
  • x t is the predicted state vector
  • x t-1 is the historical state vector
  • u t-1 is the History control signal
  • f is the first function.
  • the step of obtaining a resulting state vector based on the predicted state vector and the real-time observed quantity includes:
  • the predicted state vector is corrected by formula 2 to obtain a result state vector
  • z t is the real-time observation amount
  • N t is the measurement uncertainty
  • A is the observation visual beacon
  • h is the second function.
  • the resultant motion information includes a result state vector
  • the preset motion information includes a preset state vector
  • the visual beacon is based on the resultant motion information and the preset motion information.
  • a first output state vector is obtained based on a first preset optimization objective, a first preset objective function, the result state vector, and the preset state vector, where the first preset optimization objective is to minimize a quadratic cost function ;
  • the first preset objective function is:
  • E is the mathematical expectation
  • t is the time corresponding to the result state vector
  • x′ t is the result state vector
  • T is the transpose of the matrix
  • C is a positive definite weighting matrix
  • M is the number of the preset state vectors.
  • the resultant motion information includes a resultant state vector and a resultant control signal
  • the preset motion information includes a preset state vector and a preset control signal
  • the resultant motion information and the preset Motion information the step of determining the resulting visual identification in the visual beacon cluster includes:
  • a second output state vector and output control are obtained based on a second preset optimization objective, a second preset objective function, the resulting state vector, the resulting control signal, the preset state vector, and the preset control signal signal, the second preset optimization objective is to minimize the quadratic cost function;
  • the second preset objective function is:
  • E is the mathematical expectation
  • t is the time corresponding to the result state vector
  • x' t is the result state vector
  • u' t is the result control signal
  • T is the transpose of the matrix
  • C and D are both positive definite weighting matrices
  • M is the number of the preset state vectors.
  • the resultant motion information includes a result state vector
  • the preset motion information includes a preset state vector
  • the visual beacon is based on the resultant motion information and the preset motion information.
  • the preset maximum Euclidean distance, the preset minimum probability, the result state vector, and the preset state vector, formula 3 is used to obtain a third output state vector, and the third output state vector is obtained.
  • the preset optimization goal is to minimize the number of the observed visual beacons;
  • B is the minimum beacon number of the observed beacons
  • d max is the preset maximum Euclidean distance
  • P min is the preset minimum probability
  • M is the preset state vector
  • t is the time corresponding to the result state vector
  • x′ t is the result state vector
  • t is the preset state vector corresponding to time t in the preset state vector.
  • the resultant motion information includes a result state vector
  • the preset motion information includes a preset state vector
  • the visual beacon is based on the resultant motion information and the preset motion information.
  • a fourth output state vector is obtained, and the fourth preset optimization objective is that the number of observed visual beacons is fixed value;
  • F is the fixed value
  • M is the number of the preset state vectors
  • t is the time corresponding to the result state vector
  • x′ t is the result state vector
  • the present application also proposes an underwater vehicle, the underwater vehicle includes: a memory, a processor, and a path optimization program stored in the memory and running on the processor, The path optimization program, when executed by the processor, implements the steps of the path optimization method described in any of the above.
  • the present application also proposes a computer-readable storage medium, where a path optimization program is stored on the computer-readable storage medium, and when the path optimization program is executed by a processor, any one of the above-mentioned steps is implemented.
  • the steps of the path optimization method are described in detail below.
  • the technical solution of the present application proposes a path optimization method, which is applied to an underwater vehicle in a preset positioning system.
  • the method includes: obtaining preset motion information corresponding to the preset path based on the received control instructions;
  • the historical motion information of the underwater vehicle and the real-time observation amount corresponding to the observation visual beacon, the observation visual beacon is the visual beacon observed by the underwater vehicle in the visual beacon cluster in the preset positioning system beacon; based on the historical motion information and the real-time observation, obtain the result motion information of the underwater vehicle; based on the result motion information and the preset motion information, in the visual beacon cluster
  • a resulting visual signature is determined; based on the resulting visual signature, a final path is obtained.
  • the acoustic positioning technology is used to obtain the final navigation action of the underwater vehicle, but the accuracy of the acoustic positioning under water is poor, which makes the final path accuracy of the obtained underwater vehicle low;
  • the result motion information is obtained based on the historical motion information of the underwater vehicle and the real-time observation amount corresponding to the observation visual beacon, and the final path is obtained based on the result visual identification corresponding to the result motion information.
  • the higher the accuracy the higher the accuracy of obtaining the final path of the underwater vehicle. Therefore, using the path optimization method of the present application, the obtained final path of the underwater vehicle has a higher accuracy.
  • FIG. 1 is a schematic structural diagram of an underwater vehicle of a hardware operating environment involved in an embodiment of the application
  • FIG. 2 is a schematic flowchart of the first embodiment of the path optimization method of the present application
  • FIG. 3 is a schematic diagram of the final path obtained by the underwater vehicle of the application.
  • Fig. 4 is the schematic diagram of the underwater vehicle operation of the application.
  • Fig. 5 is the schematic diagram of the underwater vehicle of the application moving to the operation area
  • Figure 6 is a schematic diagram of a plurality of underwater vehicles operating in an operation area
  • FIG. 7 is a schematic diagram of the operation of multiple underwater vehicles in the application to multiple operation areas
  • FIG. 8 is a structural block diagram of the first embodiment of the path optimization apparatus of the present application.
  • FIG. 1 is a schematic structural diagram of an underwater vehicle of a hardware operating environment involved in an embodiment of the present application.
  • an underwater vehicle typically includes at least one processor 301, a memory 302, and a path optimization program stored on the memory and executable on the processor, the path optimization program being configured to implement the aforementioned The steps of the path optimization method.
  • the processor 301 may include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like.
  • Memory 302 may include one or more computer-readable storage media, which may be non-transitory.
  • a non-transitory computer-readable storage medium in the memory 302 is used to store at least one instruction, and the at least one instruction is used to be executed by the processor 301 to implement the path optimization provided by the method embodiments in this application. method.
  • the underwater vehicle may also optionally include: a communication interface 303 and at least one peripheral device.
  • the processor 301, the memory 302 and the communication interface 303 may be connected through a bus or a signal line.
  • Various peripheral devices can be connected to the communication interface 303 through a bus, a signal line or a circuit board.
  • the peripheral device includes: at least one of a radio frequency circuit 304 , a display screen 305 and a power supply 306 .
  • the communication interface 303 may be used to connect at least one peripheral device related to I/O (Input/Output) to the processor 301 and the memory 302 .
  • the processor 301, the memory 302, and the communication interface 303 are integrated on the same chip or circuit board; in some other embodiments, any one or both of the processor 301, the memory 302, and the communication interface 303 are integrated It may be implemented on a separate chip or circuit board, which is not limited in this embodiment.
  • the radio frequency circuit 304 is used for receiving and transmitting RF (Radio Frequency, radio frequency) signals, also called electromagnetic signals.
  • the radio frequency circuit 304 communicates with the communication network and other communication devices through electromagnetic signals.
  • the radio frequency circuit 304 may communicate with other terminals through at least one wireless communication protocol.
  • the wireless communication protocols include, but are not limited to, metropolitan area networks, mobile communication networks of various generations (2G, 3G, 4G and 5G), wireless local area networks and/or WiFi (Wireless Fidelity, wireless fidelity) networks.
  • the radio frequency circuit can also be replaced by a wired transmission circuit, and the underwater vehicle communicates with other electronic devices through the wired transmission circuit; at the same time, the radio frequency circuit can also be replaced by an underwater acoustic communication circuit, and the underwater vehicle communicates with other electronic devices through the wired transmission circuit.
  • the underwater acoustic communication circuit is communicatively connected with other electronic devices.
  • the display screen 305 is used for displaying UI (User Interface, user interface).
  • the UI can include graphics, text, icons, video, and any combination thereof.
  • Power supply 306 is used to power various components in the underwater vehicle.
  • the power source 306 may be alternating current, direct current, a primary battery, or a rechargeable battery.
  • FIG. 1 does not constitute a limitation on the underwater vehicle, and may include more or less components than the one shown, or combine some components, or arrange different components.
  • an embodiment of the present application also provides a computer-readable storage medium, where a path optimization program is stored on the computer-readable storage medium, and when the path optimization program is executed by a processor, the path optimization method as described above is implemented. step. Therefore, it will not be repeated here.
  • the description of the beneficial effects of using the same method will not be repeated.
  • program instructions may be deployed to be executed on one underwater vehicle, or on multiple underwater vehicles located at one location, or alternatively, distributed at multiple locations and interconnected by a communication network. Multiple underwater vehicles are prepared for execution.
  • the above-mentioned computer-readable storage medium may be a magnetic disk, an optical disk, a read-only memory (Read-Only Memory, ROM), or a random access memory (Random Access Memory, RAM) or the like.
  • FIG. 2 is a schematic flowchart of the first embodiment of the path optimization method of the present application.
  • the method is applied to an underwater vehicle in a preset positioning system, and the method includes:
  • Step S11 Obtain preset motion information corresponding to the preset path based on the received control instruction.
  • Step S12 Obtain the historical motion information of the underwater vehicle and the real-time observation amount corresponding to the observation visual beacon, the observation visual beacon is the underwater navigation in the visual beacon cluster in the preset positioning system. visual beacon observed by the monitor.
  • the execution body of the present application is an underwater vehicle, and the underwater vehicle is installed with a path optimization program.
  • the path optimization program may also be installed in a main control device, and the main control device may be a computer or a personal computer or the like.
  • the main control device executes the path optimization method of the present application, and sends the obtained final path to the underwater vehicle, and the underwater vehicle moves to the target object according to the final path.
  • the control instructions include end position information and starting point position information, etc.
  • the preset path of the underwater vehicle is obtained (it can be a preset path obtained based on the end position information and starting point position information through any existing technical means. path), the preset path corresponds to the preset motion information, and the preset motion information includes a preset state vector and a preset control signal.
  • the corresponding path is the preset path.
  • the underwater vehicle receives the control command, it will obtain the preset path, and the preset path is not the optimal path, and the following steps S12-S15 need to be continued to obtain the optimal final path.
  • the purpose of this application is to optimize the preset path to obtain a better or optimal final path.
  • an underwater vehicle usually refers to an underwater unmanned vehicle.
  • the underwater vehicle has the ability to move and can be an ROV (remotely controlled unmanned vehicle) or an AUV (autonomous underwater vehicle), that is, the present application
  • the target environment corresponding to the path optimization method is usually water, the underwater vehicle usually moves underwater, and the final path obtained is usually the underwater path obtained when the underwater vehicle runs in the water.
  • the underwater vehicle may be one or multiple, and the underwater vehicle may have a camera, and the camera may be a front view, a rear view, a bottom view, a top view, and the like.
  • the target can be mobile or fixed, can be one or more, and can be located on the ground, in the air, underground, underwater, on the surface of the water, and so on.
  • the visual beacon cluster usually includes multiple visual beacons, and at the same time, the number of observed visual beacons is usually multiple, and the observed visual beacon includes multiple observed visual beacons.
  • the preset positioning system may refer to a positioning system.
  • the preset positioning system includes underwater vehicles (which may be multiple) and visual beacon clusters (multiple visual beacons).
  • a preset positioning system usually uses For underwater operations of a target object, for example, a ship corresponds to a preset positioning system.
  • the visual beacon can be a two-dimensional code
  • the visual beacon can also be a code similar to a circle or a black and white square
  • the visual beacon can be a one-dimensional, two-dimensional or three-dimensional visual beacon
  • a visual beacon can also be a type or a combination of types.
  • the arrangement of visual beacons can be nested arrangement, one-word arrangement or multi-row arrangement, etc.
  • Visual beacons can also be arranged in regular shapes, such as circles or squares, etc.
  • Visual beacons can also be arranged in irregular shapes. make restrictions.
  • Visual beacons can be of one or more sizes.
  • the visual beacon can be an LED or laser capable of emitting an active light source, or a visual light strip, etc.; the minimum size of the visual beacon should be such that the camera of the underwater vehicle can still fully capture it when the underwater vehicle is operating at the shortest distance. To at least one visual beacon to ensure the completeness of the positioning function, it may also be required to be able to fully capture multiple visual beacons to ensure that the accuracy of the positioning system is maintained even if a visual beacon is lost.
  • one visual beacon corresponds to one visual signal
  • different visual beacons have different visual signals
  • the visual signal emitted by one visual beacon includes the serial number or device information of the beacon.
  • the beacon may also be an acoustic beacon.
  • the sensor used by the underwater vehicle is an acoustic sensor corresponding to the acoustic beacon.
  • the acoustic signal transmitted by the acoustic beacon obtained by the acoustic sensor in the water is obtained, the multipath and noise interference in the acoustic signal is relatively large, which makes the underwater vehicle based on the The path obtained by the acoustic signal is less accurate. Therefore, in this application, visual beacons are the preferred choice for beacons.
  • the use of visual beacons instead of acoustic beacons reduces the cost of the underwater vehicle.
  • the real-time beacon signal includes less Multipath and noise make the real-time observations obtained with high accuracy.
  • Step S13 Based on the historical motion information and the real-time observation amount, obtain the resultant motion information of the underwater vehicle.
  • step S13 includes: using the historical motion information to predict the state of the underwater vehicle to obtain a predicted state vector of the underwater vehicle; based on the predicted state vector and the real-time observation The resultant state vector is obtained; based on the resultant state vector and the preset control signal in the preset motion information, the resultant motion information is obtained.
  • the historical motion information includes a historical state vector and a historical control signal; the state of the underwater vehicle is predicted by using the historical motion information, so as to obtain the predicted state vector of the underwater vehicle. Steps include:
  • the predicted state vector is obtained by using formula 1;
  • t is the time corresponding to the predicted state vector
  • M t is the motion uncertainty
  • x t is the predicted state vector
  • x t-1 is the historical state vector
  • u t-1 is the History control signal
  • f is the first function.
  • the motion information of the underwater vehicle at the historical time is continuous
  • the continuous motion information corresponding to the continuous time and the continuous time is usually discretized to obtain multiple Discrete historical motion information corresponding to a discrete moment and multiple discrete moments
  • the motion information of the current moment is the historical motion information (that is, the predicted state vector is obtained based on the state vector of the current moment)
  • the historical motion information usually includes the historical state vector.
  • the first function may be a Newton-Euler equation or a Lagrange equation or the like.
  • a control signal may refer to the sum of the mechanical environment (including force and torque) of the underwater vehicle at the moment corresponding to the control signal.
  • the preset control signal corresponding to the preset state vector at the moment is determined as the result control signal in the result state information at the moment, that is, the result control signal corresponding to the result state vector at the moment,
  • the preset control signal and the resultant control signal at the same time are the same control signal.
  • the step of obtaining a result state vector based on the predicted state vector and the real-time observation quantity includes:
  • the predicted state vector is corrected by formula 2 to obtain a result state vector
  • z t is the real-time observation amount
  • N t is the measurement uncertainty
  • A is the observation visual beacon
  • h is the second function.
  • a visual beacon cluster usually includes multiple visual beacons, and at the same time, the number of observed visual beacons is usually multiple, and the observed visual beacon includes multiple observed visual beacons.
  • Beacon A is the set of observed visual beacons.
  • the second function may be a linear or nonlinear equation, and the second function may be the same as the first function.
  • the underwater vehicle does not observe any visual beacon at a certain moment (or at a certain moment)
  • the underwater vehicle does not obtain any real-time observation at this moment, and at this time
  • the predicted state vector at this time is obtained according to the above method, and the predicted state vector at this time is used as the result state vector at this time.
  • Set the control signal and obtain the result motion information at the moment based on the result control signal at the moment and the result state vector at the moment. And continue to perform steps S14-S15 of the present application to obtain the final path.
  • Step S14 Determine a resultant visual identifier in the visual beacon cluster based on the resultant motion information and the preset motion information.
  • the resultant motion information includes a result state vector
  • the preset motion information includes a preset state vector
  • the visual beacon is based on the resultant motion information and the preset motion information.
  • a first output state vector is obtained based on a first preset optimization objective, a first preset objective function, the result state vector, and the preset state vector, where the first preset optimization objective is to minimize a quadratic cost function ;
  • the first preset objective function is:
  • E is the mathematical expectation
  • t is the time corresponding to the result state vector
  • x′ t is the result state vector
  • T is the transpose of the matrix
  • C is a positive definite weighting matrix
  • M is the number of the preset state vectors.
  • the time t corresponding to the result state vector is the same as the time t corresponding to the predicted state vector.
  • the historical state information is the state information after discretization
  • the obtained preset state information is also the state information after discretization, that is, a preset discrete state information corresponds to a preset state vector and a preset state vector.
  • the preset state information can be expressed as: x is the state vector, and u is the corresponding control signal.
  • the resultant motion information includes a resultant state vector and a resultant control signal
  • the preset motion information includes a preset state vector and a preset control signal
  • the resultant motion information and the preset Motion information the step of determining the resulting visual identification in the visual beacon cluster includes:
  • a second output state vector and output control are obtained based on a second preset optimization objective, a second preset objective function, the resulting state vector, the resulting control signal, the preset state vector, and the preset control signal signal, the second preset optimization objective is to minimize the quadratic cost function;
  • the second preset objective function is:
  • E is the mathematical expectation
  • t is the time corresponding to the result state vector
  • x' t is the result state vector
  • u' t is the result control signal
  • T is the transpose of the matrix
  • C and D are both positive definite weighting matrices
  • M is the number of the preset state vectors.
  • the resultant motion information includes a result state vector
  • the preset motion information includes a preset state vector
  • the visual beacon is based on the resultant motion information and the preset motion information.
  • the preset maximum Euclidean distance, the preset minimum probability, the result state vector, and the preset state vector, formula 3 is used to obtain a third output state vector, and the third output state vector is obtained.
  • the preset optimization goal is to minimize the number of the observed visual beacons;
  • B is the minimum beacon number of the observed beacons
  • d max is the preset maximum Euclidean distance
  • P min is the preset minimum probability
  • M is the preset state vector
  • t is the time corresponding to the result state vector
  • x′ t is the result state vector
  • t is the preset state vector corresponding to time t in the preset state vector.
  • an elliptical surface can also be obtained based on the result state vector, the preset state vector, and the preset minimum probability.
  • a third output state vector is determined.
  • ⁇ t is the maximum eigenvalue of the position deviation variance matrix
  • k is the scaling factor of the preset minimum probability (P min ).
  • the resultant motion information includes a result state vector
  • the preset motion information includes a preset state vector
  • the visual beacon is based on the resultant motion information and the preset motion information.
  • a fourth output state vector is obtained, and the fourth preset optimization objective is that the number of observed visual beacons is fixed value;
  • F is the fixed value
  • M is the number of the preset state vectors
  • t is the time corresponding to the result state vector
  • x′ t is the result state vector
  • the visual identifier corresponding to the output state vector (and the output control signal) can be determined in the visual beacon cluster, that is, the resulting visual identifier , the resulting visual logo is obtained after optimizing the preset motion information, and the resulting visual logo is usually the optimal layout.
  • Step S15 Obtain a final path based on the result visual identification.
  • the path corresponding to the underwater vehicle from the starting point position information to the end point position information, that is, the final path can be obtained.
  • Fig. 3 is a schematic diagram of the final path obtained by the underwater vehicle of the application; the final path manifestation is the path formed by a plurality of visual beacons, and the black block is the final path formed by the visual beacons, and the underwater navigation move along the final path.
  • FIG. 4 is a schematic diagram of the operation of the underwater vehicle of the application;
  • the underwater vehicle corresponding to the ship 21 includes an underwater vehicle 22, an underwater vehicle 23, an underwater vehicle 24, an underwater vehicle 25 and
  • the underwater vehicles 26, 27 and 28 are guiding devices, the underwater vehicle 22 performs underwater tasks, such as ship cleaning or ship detection;
  • the underwater vehicle 23 is docked with the guiding device 28;
  • the underwater vehicle 24 is connected to the underwater
  • the underwater vehicle 25 is docked;
  • the underwater vehicle 26 is docked with the guide device 27 to retract the underwater vehicle 26 .
  • Ships can also be carriers in the air, on land, underground, on the surface, and underwater, and the carriers can be dynamic or static.
  • Fig. 5 is a schematic diagram of the underwater vehicle of the application moving to the operation area; the underwater vehicle corresponding to the ship 31 has an underwater vehicle 32, an underwater vehicle 33 and an underwater vehicle 34, and the underwater navigation
  • the underwater vehicle 33 performs underwater tasks and moves from the non-operation area to the operation area.
  • the underwater vehicle 34 docks with the underwater vehicle 32 in the operation area, and the underwater vehicle 34 needs to move from the non-operation area to the operation area.
  • the operation area is also the area covered by the preset positioning system proposed in this application.
  • the coverage area depends on the size, layout, water quality, light, allowable accuracy, etc. of the logo.
  • Real-time evaluation to determine dynamically, such as using statistical principles to evaluate the consistency of the data.
  • FIG. 6 is a schematic diagram of a plurality of underwater vehicles working on an operation area; an operation area is an operation area corresponding to a ship 41, and the underwater vehicle includes an underwater vehicle 42, an underwater vehicle 43 and The underwater vehicle 44, the underwater vehicle 42 is used to detect and clean the ship, the positioning 43 is docked with the ship, and the underwater vehicle 44 moves to a designated position.
  • FIG. 7 is a schematic diagram of the operation of multiple underwater vehicles in the application for multiple operation areas; multiple operation areas correspond to multiple objects, including ships 51, 52 and 53 respectively, and the underwater vehicles include underwater vehicles.
  • the underwater vehicle 54, the underwater vehicle 55, the underwater vehicle 56 and the underwater vehicle 57; the underwater vehicle 54 and the underwater vehicle 55 are used to operate the ship 51, and the operation area is the operation area corresponding to the ship 51 , the underwater vehicle 56 is used to operate the ship 52 , and the underwater vehicle is used to operate the 53 .
  • one ship corresponds to one operating area, and multiple ships obtain their respective latitude and longitude information through the installed GPS or other position sensing units.
  • ECEF coordinate system Cartesian coordinate system
  • x ECEF , y ECEF and z ECEF are the three-dimensional coordinate information of the ship's Cartesian coordinate system, respectively, ⁇ is the dimensional information before the ship's transformation, ⁇ is the longitude information before the ship's transformation, h is the altitude of the ship, and r e is The radius of the earth, ⁇ is the first oblateness of the earth (the area where the ship is located).
  • the technical solution of the present application proposes a path optimization method, which is applied to an underwater vehicle in a preset positioning system.
  • the method includes: obtaining preset motion information corresponding to the preset path based on the received control instructions;
  • the historical motion information of the underwater vehicle and the real-time observation amount corresponding to the observation visual beacon, the observation visual beacon is the visual beacon observed by the underwater vehicle in the visual beacon cluster in the preset positioning system beacon; based on the historical motion information and the real-time observation, obtain the result motion information of the underwater vehicle; based on the result motion information and the preset motion information, in the visual beacon cluster
  • a resulting visual signature is determined; based on the resulting visual signature, a final path is obtained.
  • the acoustic positioning technology is used to obtain the final navigation action of the underwater vehicle, but the accuracy of the acoustic positioning under water is poor, which makes the final path accuracy of the obtained underwater vehicle low;
  • the result motion information is obtained based on the historical motion information of the underwater vehicle and the real-time observation amount corresponding to the observation visual beacon, and the final path is obtained based on the result visual identification corresponding to the result motion information.
  • the higher the accuracy the higher the accuracy of obtaining the final path of the underwater vehicle. Therefore, using the path optimization method of the present application, the obtained final path of the underwater vehicle has a higher accuracy.
  • FIG. 8 is a structural block diagram of the first embodiment of the path optimization device of the present application.
  • the device is applied to an underwater vehicle in a preset positioning system, and the device includes:
  • the receiving module 10 is configured to obtain preset motion information corresponding to the preset path based on the received control instruction;
  • the acquisition module 20 is used to acquire the historical motion information of the underwater vehicle and the real-time observation amount corresponding to the observation visual beacon, and the observation visual beacon is the one described in the visual beacon cluster in the preset positioning system.
  • an obtaining module 30 configured to obtain the resultant movement information of the underwater vehicle based on the historical movement information and the real-time observation;
  • a determination module 40 configured to determine a result visual identifier in the visual beacon cluster based on the result motion information and the preset motion information;
  • the path obtaining module 50 is configured to obtain the final path based on the result visual identification.

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Abstract

L'invention concerne un procédé d'optimisation de trajectoire, un véhicule sous-marin et un support de stockage lisible par ordinateur, qui sont appliqués à un véhicule sous-marin dans un système de positionnement prédéfini. Le procédé consiste à : sur la base d'une instruction de commande reçue, acquérir des informations de mouvement prédéfinies correspondant à une trajectoire prédéfinie (S11) ; acquérir des informations de mouvement historiques d'un véhicule sous-marin et une grandeur d'observation en temps réel correspondant à une balise visuelle d'observation, la balise visuelle d'observation étant une balise visuelle observée par le véhicule sous-marin parmi un groupe de balises visuelles dans un système de positionnement prédéfini (S12) ; sur la base des informations de mouvement historiques et de la grandeur d'observation en temps réel, acquérir des informations de mouvement résultantes du véhicule sous-marin (S13) ; sur la base des informations de mouvement résultantes et des informations de mouvement prédéfinies, déterminer un identifiant visuel résultant dans le groupe de balises visuelles (S14) ; et sur la base de l'identifiant visuel résultant, acquérir une trajectoire finale (S15).
PCT/CN2021/104062 2021-02-19 2021-07-01 Procédé d'optimisation de trajectoire, véhicule sous-marin et support de stockage lisible par ordinateur WO2022174545A1 (fr)

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