CN117709000A - Unmanned underwater vehicle simulation method, unmanned underwater vehicle simulation device, computer equipment and medium - Google Patents
Unmanned underwater vehicle simulation method, unmanned underwater vehicle simulation device, computer equipment and medium Download PDFInfo
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Abstract
The application relates to an unmanned underwater vehicle simulation method, an unmanned underwater vehicle simulation device, computer equipment and a medium. The method comprises the following steps: according to a simulation task of an unmanned underwater vehicle model of the unmanned underwater vehicle, a motion control model and a sensor model of the unmanned underwater vehicle model are built on a simulation platform; determining an unmanned underwater vehicle module according to the motion control model and a three-dimensional model of the unmanned underwater vehicle, and determining a sensor module according to the sensor model; acquiring state information of the unmanned underwater vehicle model through the unmanned underwater vehicle module; the state information is determined according to the first state information sent by the sensor module and the second state information sent by the control platform; and controlling the unmanned underwater vehicle model to move in a simulation environment according to the state information through the unmanned underwater vehicle module. By adopting the method, the expandability of the simulation task can be improved.
Description
Technical Field
The application relates to the technical field of unmanned underwater vehicle simulation, in particular to an unmanned underwater vehicle simulation method, an unmanned underwater vehicle simulation device, computer equipment and a medium.
Background
Unmanned underwater vehicles (Unmanned Underwater Vehicle, UUV) are widely applied to underwater tasks such as environmental observation, resource exploration, biological investigation, disaster prediction, auxiliary positioning and the like due to intelligence and maneuverability. In an underwater environment, path planning and formation control are two core application scenarios of UUV. In consideration of high cost of a hardware platform and high risk of physical test, a UUV simulation platform is often adopted to carry out simulation test on a path planning algorithm and a formation control algorithm of the UUV, and the UUV simulation platform comprises an MVSPU platform, a stone fish platform and the like.
In the prior art, when a UUV is subjected to simulation test by adopting an MVSPU platform, a stone fish and other platforms, only a single underwater task can be simulated, so that the existing MVSPU platform, stone fish and other platforms have the problem of poor expandability of simulation tasks.
Disclosure of Invention
In view of the foregoing, it is desirable to provide an unmanned underwater vehicle simulation method, apparatus, computer device, and medium capable of improving the expandability of the simulation task.
In a first aspect, the present application provides a method for unmanned aerial vehicle simulation. The method comprises the following steps:
according to a simulation task of an unmanned underwater vehicle model of the unmanned underwater vehicle, a motion control model and a sensor model of the unmanned underwater vehicle model are built on a simulation platform;
Determining an unmanned underwater vehicle module according to the motion control model and a three-dimensional model of the unmanned underwater vehicle, and determining a sensor module according to the sensor model;
acquiring state information of the unmanned underwater vehicle model through the unmanned underwater vehicle module; the state information is determined according to the first state information sent by the sensor module and the second state information sent by the control platform;
and controlling the unmanned underwater vehicle model to move in a simulation environment according to the state information through the unmanned underwater vehicle module.
In one embodiment, the control platform includes a local planning module; the obtaining, by the unmanned submersible vehicle module, the status information of the unmanned submersible vehicle model includes:
acquiring the first state information and the second state information through the local planning module;
processing the first state information and the second state information by the local planning module through a vector field histogram algorithm to obtain state information of the unmanned underwater vehicle model;
and sending state information of the unmanned underwater vehicle model to the unmanned underwater vehicle module through the local planning module.
In one embodiment, the control platform further comprises a task scheduling module, a global planning module and a control module; the obtaining, by the local planning module, the first state information and the second state information includes:
transmitting path starting point information corresponding to the simulation task to the global planning module through the task scheduling module;
obtaining each path point information corresponding to the simulation task through the global planning module according to an A-star algorithm and the path starting point information, and sending each path point information to the control module;
obtaining the second state information by the control module according to a pure tracking algorithm and the path point information;
sending the second state information to the local planning module through the control module;
and acquiring the state information of the obstacles around the unmanned underwater vehicle module through the sensor module, taking the state information of the obstacles as the first state information, and sending the first state information to the local planning module.
In one embodiment, the constructing a motion control model and a sensor model of the unmanned submersible model on a simulation platform according to a simulation task of the unmanned submersible model of the unmanned submersible comprises:
Determining the force and torque corresponding to the simulation task, which the unmanned submarine model receives;
determining a motion control model of the unmanned underwater vehicle model according to the force and the torque, corresponding to the simulation task, of the unmanned underwater vehicle model;
determining an error model corresponding to a simulation task of the unmanned submarine model;
and determining a sensor model of the unmanned submarine model according to the error model.
In one embodiment, the method further comprises:
based on the Gazebo platform in the simulation platform, sea surface waves are rendered by utilizing the sea wave world and the wave coloring device, so that a sea surface environment is obtained;
obtaining a submarine environment based on the Gazebo platform and the electronic chart data;
and determining the simulation environment according to the sea surface environment and the seabed environment.
In one embodiment, the obtaining the subsea environment based on the Gazebo platform and the electronic chart data includes:
processing the electronic chart data to obtain raster data; the raster data comprises blank areas and non-blank areas;
performing interpolation processing on the blank area based on the non-blank area to obtain a terrain file;
Performing file conversion on the topographic file and the non-blank area to obtain a digital elevation file;
and obtaining the submarine environment based on the digital elevation file.
In one embodiment, the method further comprises:
modeling the size, material and shape of the unmanned underwater vehicle by utilizing SolidWorks software to obtain a first model;
layout is carried out on the executor of the first model to obtain a second model;
processing the second model by using ANSYS software to obtain a first file;
according to the first file, a three-dimensional model of the unmanned underwater vehicle is obtained;
and obtaining the unmanned underwater vehicle model according to the three-dimensional model, the motion control model and the sensor model.
In a second aspect, the application also provides an unmanned submarine simulator. The device comprises:
the model construction module is used for constructing a motion control model and a sensor model of the unmanned underwater vehicle model on a simulation platform according to a simulation task of the unmanned underwater vehicle model of the unmanned underwater vehicle;
the first determining module is used for determining an unmanned underwater vehicle module according to the motion control model and the unmanned underwater vehicle model and determining a sensor module according to the sensor model;
The state information acquisition module is used for acquiring the state information of the unmanned underwater vehicle model through the unmanned underwater vehicle module; the state information is determined according to the first state information sent by the sensor module and the second state information sent by the control platform;
and the movement control module is used for controlling the unmanned underwater vehicle model to move in a simulation environment according to the state information through the unmanned underwater vehicle module.
In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the steps of the method according to any of the first aspects above when the processor executes the computer program.
In a fourth aspect, the present application also provides a computer-readable storage medium. The computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method of any of the first aspects above.
According to the unmanned underwater vehicle simulation method, the unmanned underwater vehicle simulation device, the computer equipment and the medium, different motion control models and sensor models can be built aiming at different simulation tasks, the state information of the unmanned underwater vehicle model is obtained based on the different motion control models and the sensor models, and then the unmanned underwater vehicle model is controlled to execute different simulation tasks in a simulation environment according to the state information.
Drawings
FIG. 1 is an application environment diagram of an unmanned aerial vehicle simulation method in one embodiment;
FIG. 2 is a flow diagram of a method of unmanned aerial vehicle simulation in one embodiment;
FIG. 3 is a flow chart of acquiring first status information and second status information by a local planning module according to one embodiment;
FIG. 4 is a schematic diagram of control logic of an unmanned submersible model in one embodiment;
FIG. 5 is a schematic flow diagram of a subsea environment obtained based on Gazebo platform and electronic chart data in one embodiment;
FIG. 6 is a schematic diagram of a process for constructing a subsea environment in one embodiment;
FIG. 7 is a flow chart of a method of constructing an unmanned submersible vehicle model in one embodiment;
FIG. 8 is a flow chart of an unmanned submersible simulation method in an exemplary embodiment;
FIG. 9 is a schematic diagram of a framework developed based on the unmanned submersible simulation method of the present application in an exemplary embodiment;
FIG. 10 is a schematic diagram of a control platform interacting with a simulation platform in an exemplary embodiment;
FIG. 11 is a schematic diagram of an unmanned submersible simulator in one embodiment;
FIG. 12 is an internal block diagram of a server in one embodiment;
Fig. 13 is an internal structural view of a terminal in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
The unmanned underwater vehicle simulation method provided by the embodiment of the application can be applied to an application environment shown in fig. 1. The computer equipment 102 constructs a motion control model and a sensor model of the unmanned underwater vehicle model on a simulation platform according to a simulation task of the unmanned underwater vehicle model of the unmanned underwater vehicle; determining an unmanned submarine module according to the motion control model and the three-dimensional model of the unmanned submarine, and determining a sensor module according to the sensor model; acquiring state information of an unmanned underwater vehicle model through the unmanned underwater vehicle module; the state information is determined according to the first state information sent by the sensor module and the second state information sent by the control platform; and controlling the unmanned underwater vehicle model to move in the simulation environment according to the state information through the unmanned underwater vehicle module. The computer device 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things devices, and portable wearable devices, and the internet of things devices may be smart speakers, smart televisions, smart air conditioners, smart vehicle devices, and the like. The portable wearable device may be a smart watch, smart bracelet, headset, or the like.
In one embodiment, as shown in fig. 2, there is provided an unmanned submarine simulation method, which is described by taking the computer device 102 in fig. 1 as an example, and includes the following steps:
step 202, constructing a motion control model and a sensor model of the unmanned underwater vehicle model on a simulation platform according to a simulation task of the unmanned underwater vehicle model of the unmanned underwater vehicle.
The simulation task may be path planning of the unmanned underwater vehicle model, or formation control of the unmanned underwater vehicle model, which is not limited in this embodiment.
Optionally, if the simulation task is to perform path planning on the unmanned underwater vehicle model, a motion control model of the unmanned underwater vehicle model is obtained according to the stress condition and the torque condition of the unmanned underwater vehicle model, and a sensor model of the unmanned underwater vehicle model is obtained according to an error model corresponding to the path planning. And if the simulation task is to perform formation control on the unmanned underwater vehicle model, obtaining a motion control model of the unmanned underwater vehicle model according to the stress condition and the torque condition of the unmanned underwater vehicle model, and obtaining a sensor model of the unmanned underwater vehicle model according to an error model corresponding to the formation control.
Step 204, determining an unmanned submersible module according to the motion control model and the three-dimensional model of the unmanned submersible, and determining a sensor module according to the sensor model.
Optionally, integrating the motion control model and the three-dimensional model of the unmanned underwater vehicle model to obtain an unmanned underwater vehicle module, and integrating the sensor model to obtain a sensor module.
Step 206, acquiring state information of the unmanned underwater vehicle model through the unmanned underwater vehicle module; the state information is determined according to the first state information sent by the sensor module and the second state information sent by the control platform.
The state information of the unmanned submersible vehicle model may include, but is not limited to, an angular velocity and a linear velocity of the unmanned submersible vehicle model, which is not limited in this embodiment.
Optionally, the first state information sent by the sensor module and the second state information sent by the control platform are processed by using a preset algorithm to obtain the state information of the unmanned underwater vehicle model. The preset algorithm may be a vector field histogram algorithm, or may be other algorithms, which is not limited in this embodiment.
And step 208, controlling the unmanned underwater vehicle model to move in the simulation environment according to the state information through the unmanned underwater vehicle module.
The state information of the unmanned submersible vehicle model may include, but is not limited to, an angular velocity and a linear velocity of the unmanned submersible vehicle model, which is not limited in this embodiment.
Optionally, assuming that the state information of the unmanned underwater vehicle model is the angular velocity and the linear velocity of the unmanned underwater vehicle model, the angular velocity and the linear velocity are sent to the unmanned underwater vehicle module so as to control the unmanned underwater vehicle model to move in the simulation environment.
In the unmanned underwater vehicle simulation method, a motion control model and a sensor model of the unmanned underwater vehicle model are built on a simulation platform according to the simulation task of the unmanned underwater vehicle model of the unmanned underwater vehicle; determining an unmanned submarine module according to the motion control model and the unmanned submarine model, and determining a sensor module according to the sensor model; acquiring state information of an unmanned underwater vehicle model through the unmanned underwater vehicle module; the state information is determined according to the first state information sent by the sensor module and the second state information sent by the control platform; and controlling the unmanned underwater vehicle model to move in the simulation environment according to the state information through the unmanned underwater vehicle module. According to the unmanned underwater vehicle simulation method, different motion control models and sensor models can be built aiming at different simulation tasks, the state information of the unmanned underwater vehicle model is obtained based on the different motion control models and the sensor models, and then the unmanned underwater vehicle model is controlled to execute different simulation tasks in a simulation environment according to the state information.
In one embodiment, the control platform includes a local planning module; acquiring state information of the unmanned submersible vehicle model through the unmanned submersible vehicle module comprises the following steps:
and acquiring the first state information and the second state information through the local planning module.
Wherein the first status information is sent by the sensor module and the second status information is sent by a control module in the control platform.
Optionally, the sensor module sends the first state information to the local planning module, and the control module in the control platform sends the second state information to the local planning module.
And processing the first state information and the second state information by using a vector field histogram algorithm through a local planning module to obtain the state information of the unmanned underwater vehicle model.
The vector field histogram algorithm is an algorithm for robot navigation and is suitable for obstacle avoidance of a mobile robot.
Optionally, the local planning module calculates the acquired first state information and second state information by using a vector field histogram algorithm to obtain state information of the unmanned underwater vehicle model, wherein the state information of the unmanned underwater vehicle model comprises a linear speed and an angular speed of the unmanned underwater vehicle model.
And sending state information of the unmanned underwater vehicle model to the unmanned underwater vehicle module through the local planning module.
Optionally, the local planning module sends state information of the unmanned submersible vehicle model to the unmanned submersible vehicle module, wherein the state information of the unmanned submersible vehicle model comprises a linear speed and an angular speed of the unmanned submersible vehicle model.
In this embodiment, the local planning module obtains the first state information and the second state information; processing the first state information and the second state information by using a vector field histogram algorithm through a local planning module to obtain the state information of the unmanned underwater vehicle model; and sending state information of the unmanned underwater vehicle model to the unmanned underwater vehicle module through the local planning module. The local planning module processes the first state information and the second state information by using a vector field histogram algorithm to obtain the state information of the unmanned underwater vehicle model, the obtained state information is accurate, surrounding obstacles can be effectively avoided when the unmanned underwater vehicle model is controlled based on the state information, and the simulation accuracy is improved.
In one embodiment, the control platform further comprises a task scheduling module, a global planning module and a control module; the first state information and the second state information are acquired through the local planning module, and the flow is shown in fig. 3, and includes:
Step 301, sending path starting point information corresponding to the simulation task to the global planning module through the task scheduling module.
Optionally, if the simulation task is path planning, the task scheduling module sends path starting point information corresponding to the path planning to the global planning module. And if the simulation task is formation control, transmitting path starting point information corresponding to the formation control to the global planning module through the task scheduling module.
Step 302, obtaining information of each path point corresponding to the simulation task through the global planning module according to the A-star algorithm and the path starting point information, and sending the information of each path point to the control module.
The A-star algorithm is the most effective direct search method for solving the shortest path, and the core idea is that an optimal path is found through an evaluation function in the path search process.
Optionally, if the simulation task is path planning, the global planning module plans an optimal path according to the a-star algorithm and path starting point information, and assumes that each path point on the optimal path is respectively: if the route points 1 and 2 and … are the route point n, the global planning module sends the information of the route points 1 and 2 and … to the control module.
And step 303, obtaining second state information by the control module according to the pure tracking algorithm and the path point information.
The pure tracking algorithm is a control algorithm for making an unmanned vehicle or other moving object travel along a predetermined path or trajectory.
Optionally, if the simulation task is path planning, the control module calculates according to the pure tracking algorithm and the path point information to obtain second state information, where the second state information includes a middle angular velocity, a middle linear velocity and a target azimuth of the unmanned underwater vehicle model.
And step 304, sending second state information to the local planning module through the control module.
Optionally, the control module sends second state information to the local planning module, the second state information including an intermediate angular velocity, an intermediate linear velocity, and a target orientation of the unmanned submersible model.
In step 305, the sensor module obtains the state information of the obstacles around the unmanned underwater vehicle module, takes the state information of the obstacles as the first state information, and sends the first state information to the local planning module.
Optionally, the sensor module acquires the state information of the obstacle around the unmanned submarine module, takes the state information of the obstacle as the first state information, and sends the first state information to the local planning module. The first state information comprises angle information and distance information of the obstacle and the unmanned submarine module.
In the embodiment, the task scheduling module sends path starting point information corresponding to the simulation task to the global planning module; obtaining each path point information corresponding to the simulation task through a global planning module according to the A-star algorithm and the path starting point information, and sending each path point information to a control module; obtaining second state information according to a pure tracking algorithm and the information of each path point through a control module; sending second state information to the local planning module through the control module; the method comprises the steps of obtaining state information of obstacles around an unmanned submarine module through a sensor module, taking the state information of the obstacles as first state information, and sending the first state information to a local planning module. The simulation task is characterized in that each path point information corresponding to the simulation task is obtained according to an A-star algorithm and path starting point information, and the second state information is obtained according to a pure tracking algorithm and each path point information, so that the unmanned underwater vehicle model can be controlled more accurately, and the simulation accuracy is improved.
In one embodiment, constructing a motion control model and a sensor model of the unmanned submersible model on a simulation platform according to a simulation task of the unmanned submersible model of the unmanned submersible comprises:
Determining the force and torque corresponding to the simulation task, which are born by the unmanned submarine model;
and determining a motion control model of the unmanned underwater vehicle model according to the force and the torque, corresponding to the simulation task, of the unmanned underwater vehicle model.
Alternatively, the unmanned submarine model may be regarded as a six-degree-of-freedom rigid body model, the motion control model of which may be determined by the forces and torques it receives during the simulation task, and the equations corresponding to the motion control model are shown in equations (1), (2) and (3).
(1)
(2)
(3)
In the formula (1),representing the position of the unmanned submarine model in the world inertial coordinate system, < >>Representing the velocity of the unmanned submarine model in the world inertial coordinate system.
In the formula (2),representing the speed of the unmanned submersible model in the world inertial coordinate system, m representing the mass of the unmanned submersible model, +.>A rotation matrix representing a transfer of a reference frame of vectors from an object coordinate system to a world coordinate system, F representing an unmanned submersibleThe forces experienced by the aircraft model during the simulation task.
In the formula (3),the angular velocity of the unmanned submersible vehicle model in the rigid motion coordinate system is represented, J represents the inertia of the unmanned submersible vehicle model, and M represents the torque applied to the unmanned submersible vehicle model in the simulation task.
Based on equations (1), (2) and (3), control logic for the unmanned submersible model may be derived, as shown in FIG. 4. The left side of fig. 4 has three control loops from top to bottom in sequence, namely a first control loop, a second control loop and a third control loop, wherein i can be any one of X, Y, Z, and is used for indicating the direction along any one of the X axis, the Y axis and the Z axis, PI is a proportional integral controller, PD is a proportional differential controller, and PID is a proportional integral controller. A first control loop for controlling the linear velocity, v, of the unmanned submersible vehicle model i,d For a desired linear velocity along the coordinate axis i, p i,d For the desired position along coordinate axis i, p i,t V is the actual position along the coordinate axis i i,t For the actual linear velocity along the coordinate axis i, F i F is a force in the direction of the coordinate axis i i Is the output of the first control loop. A second control loop for controlling the attitude of the unmanned submarine model, v b i,d Is the speed of the unmanned submarine model under a rigid coordinate system, a i,d For a desired acceleration in the direction of the coordinate axis i, θ i,d θ is the desired angle in the direction of coordinate axis i i,t For the actual angle along the direction of the coordinate axis i, R is a rotation matrix for converting the unmanned submarine model in a rigid coordinate system and a world coordinate system, g is the gravity acceleration, M i For torque in the direction of coordinate axis i, M i Is the output of the first control loop. The third control loop is provided with a third control loop,for a desired angular velocity in the direction of the coordinate axis i +.>The actual angular velocity along the coordinate axis i. The output of the three control loops is input into a gesture solver to obtain the actual position p of the unmanned submarine model along the direction of the coordinate axis i i,t Actual linear velocity v along coordinate axis i i,t And the actual angle theta along the coordinate axis i i,t 。
Determining an error model corresponding to a simulation task of the unmanned submarine model;
and determining a sensor model of the unmanned submarine model according to the error model.
Alternatively, the error model can be represented by formulas (4) and (5).
(4)
(5)
In the formula (4), s represents a signal of the sensor,representing a real signal +.>Represents additive noise directly acting on the measurement, n represents current bias, and the calculation formula is shown as formula (5).
In the formula (5) of the present invention,is a time constant->For passing time constant->Random drift characteristics are described.
And (3) obtaining a sensor model of the unmanned submarine model according to the formulas (4) and (5).
In the embodiment, determining the force and torque corresponding to the simulation task, which are born by the unmanned submarine model; determining a motion control model of the unmanned underwater vehicle model according to the force and torque, corresponding to the simulation task, of the unmanned underwater vehicle model; determining an error model corresponding to a simulation task of the unmanned submarine model; and determining a sensor model of the unmanned submarine model according to the error model. The motion control model and the error model of the unmanned underwater vehicle model are determined according to different simulation tasks, so that the requirements of the different simulation tasks are met, and the expandability of the simulation tasks is improved.
In one embodiment, a method for constructing a simulation environment is provided, including:
based on the Gazebo platform in the simulation platform, sea surface waves are rendered by utilizing the sea wave world and the wave coloring device, and a sea surface environment is obtained.
The Gazebo is a three-dimensional physical simulation platform, supports simulation of various physical engines and sensors, and can adapt to different robot platforms and scene requirements.
Optionally, on a Gazebo platform in the simulation platform, sea surface waves are rendered by utilizing the sea wave world and the wave colorants, so as to obtain sea surface environment.
And obtaining the submarine environment based on the Gazebo platform and the electronic chart data.
The electronic chart data is standardized by the international sea channel measuring organization and comprises navigation information such as ocean depth, sounding, contour lines and other information.
Optionally, the electronic chart data is processed to obtain a digital elevation file, and the submarine environment is obtained based on the digital elevation file.
And determining a simulation environment according to the sea surface environment and the seabed environment.
Alternatively, the simulation environment is obtained according to the sea surface environment and the seabed environment.
In the embodiment, sea surface waves are rendered by utilizing the sea wave world and a wave coloring device based on a Gazebo platform in the simulation platform to obtain a sea surface environment; obtaining a submarine environment based on the Gazebo platform and the electronic chart data; and determining a simulation environment according to the sea surface environment and the seabed environment. The electronic chart data are close to the real submarine environment data, the accuracy of the submarine environment obtained based on the Gazebo platform and the electronic chart data is high, and the simulation accuracy of the simulation environment is improved.
In one embodiment, based on the Gazebo platform and the electronic chart data, a subsea environment is obtained, and the process is shown in fig. 5, comprising:
step 502, processing the electronic chart data to obtain raster data; the raster data includes blank areas and non-blank areas.
Optionally, the electronic chart data is processed by using an Anaconda ogr2ogr library and a quantum geographic information system to obtain raster data, wherein the raster data comprises blank areas and non-blank areas. The Anaconda ogr2ogr library is a library for data format conversion. The quantum geographic information system is an open-source geographic information system application program, provides the viewing and editing functions of geographic space data, and supports geographic information analysis.
And step 504, carrying out interpolation processing on the blank area based on the non-blank area to obtain a terrain file.
Optionally, interpolation processing is performed on the blank area in the raster data based on the non-blank area in the raster data, so as to obtain the topographic file. The interpolation processing may be interpolation by a kriging interpolation method or interpolation by other interpolation methods, and this embodiment is not limited thereto.
And step 506, converting the topographic file and the non-blank area to obtain a digital elevation file.
Optionally, the Global Mapper software is used for converting the terrain file and the non-blank area to obtain the digital elevation file. The Global Mapper software is a kind of mapping software.
Step 508, obtaining the subsea environment based on the digital elevation file.
Optionally, converting the digital elevation file by using a Python3-gdal library on the simulation platform to obtain the submarine environment. Wherein the Python3-gdal library is a library for processing geospatial data.
In fig. 6, the construction process of a subsea environment is shown. Wherein the first step to the fourth step correspond to the steps 502 to 508, respectively.
In the embodiment, processing is performed on the electronic chart data to obtain raster data; the raster data includes blank areas and non-blank areas; interpolation processing is carried out on the blank area based on the non-blank area to obtain a topography file; carrying out file conversion on the topographic file and the non-blank area to obtain a digital elevation file; and obtaining the submarine environment based on the digital elevation file. The electronic chart data are close to the real submarine environment data, the accuracy of the submarine environment obtained based on the Gazebo platform and the electronic chart data is high, and the simulation accuracy of the simulation environment is improved.
In one embodiment, a method for constructing an unmanned submarine model is provided, and the flow is shown in fig. 7, and includes:
step 701, modeling the size, the material and the shape of the unmanned submarine to obtain a first model by using SolidWorks software.
The SolidWorks is three-dimensional CAD design software, and can quickly and efficiently create various three-dimensional models and assemblies to perform virtual experiments and simulations.
Optionally, modeling the size, the material and the shape of the unmanned submarine by using SolidWorks software to obtain a first model, wherein the first model is a CAD model.
Step 702, layout the actuator of the first model to obtain a second model.
Wherein the actuator is a virtual component for driving the first model to move.
Optionally, the layout of the actuators of the first model includes the layout of the installation position, the connection angle and the rotation direction of the actuators of the first model, so as to obtain a second model.
In step 703, the second model is processed using ANSYS software to obtain a first file.
The ANSYS software is large finite element analysis software, can perform various complex physical and mechanical simulations, provides various plug-ins and extensions, and can be integrated with other CAD software.
Optionally, calculating the second model by ANSYS software to obtain physical parameters such as mass, volume, rotational inertia and the like of the second model, exporting the second model into stl files and dae files, and taking the stl files and the dae files as the first files.
Step 704, obtaining a three-dimensional model of the unmanned underwater vehicle according to the first file.
Optionally, stl files and dae files are used as first files, the xacro files are written based on the first files, and then the xacro files are converted through an ROS platform in the simulation platform, so that a three-dimensional model of the unmanned underwater vehicle is obtained. The ROS platform is a robot software platform with powerful functions, flexibility and easiness in use, and can be used for rapidly developing and deploying a robot application program.
Step 705, obtaining the unmanned underwater vehicle model according to the three-dimensional model, the motion control model and the sensor model.
Optionally, integrating the three-dimensional model, the motion control model and the sensor model to obtain the unmanned underwater vehicle model.
In the embodiment, modeling is carried out on the size, the material and the shape of the unmanned underwater vehicle by utilizing SolidWorks software to obtain a first model; layout is carried out on the executor of the first model to obtain a second model; processing the second model by using ANSYS software to obtain a first file; according to the first file, a three-dimensional model of the unmanned underwater vehicle is obtained; and obtaining the unmanned underwater vehicle model according to the three-dimensional model, the motion control model and the sensor model. The simulation precision of the unmanned underwater vehicle model obtained through the three-dimensional model, the motion control model and the sensor model is higher, so that the simulation precision of the unmanned underwater vehicle model when executing tasks in a simulation environment is higher.
In an exemplary embodiment, there is provided an unmanned submarine simulation method, and the flow is as shown in fig. 8, including:
step 801, based on a Gazebo platform in the simulation platform, sea surface waves are rendered by utilizing the sea wave world and a wave shader, and a sea surface environment is obtained.
Step 802, processing the electronic chart data to obtain raster data; the raster data includes blank areas and non-blank areas.
Step 803, interpolation processing is carried out on the blank area based on the non-blank area to obtain a terrain file.
And step 804, converting the topographic file and the non-blank area to obtain a digital elevation file.
Step 805, obtaining a subsea environment based on the digital elevation file.
Step 806, determining a simulation environment according to the sea surface environment and the seabed environment.
Step 807, modeling the size, material and shape of the unmanned submersible vehicle using SolidWorks software to obtain a first model.
Step 808, laying out the actuator of the first model to obtain a second model.
And step 809, processing the second model by utilizing ANSYS software to obtain a first file.
And step 810, obtaining a three-dimensional model of the unmanned underwater vehicle according to the first file.
And 811, obtaining the unmanned underwater vehicle model according to the three-dimensional model, the motion control model and the sensor model.
Step 812, determining the forces and torques experienced by the unmanned submarine model corresponding to the simulation task.
Step 813, determining a motion control model of the unmanned underwater vehicle model according to the force and the torque corresponding to the simulation task received by the unmanned underwater vehicle model.
Step 814, determining an error model corresponding to the simulation task of the unmanned submarine model.
Step 815, determining a sensor model of the unmanned submarine model according to the error model.
In step 816, the unmanned submersible module is determined based on the motion control model and the three-dimensional model of the unmanned submersible, and the sensor module is determined based on the sensor model.
In step 817, the path start point information corresponding to the simulation task is sent to the global planning module through the task scheduling module.
Step 818, obtaining each path point information corresponding to the simulation task through the global planning module according to the A-star algorithm and the path starting point information, and sending each path point information to the control module.
And step 819, obtaining, by the control module, second state information according to the pure tracking algorithm and the path point information.
Step 820, the second status information is sent to the local planning module by the control module.
In step 821, the state information of the obstacles around the unmanned underwater vehicle module is acquired through the sensor module, the state information of the obstacles is used as the first state information, and the first state information is sent to the local planning module.
In step 822, the first state information and the second state information are obtained by the local planning module.
Step 823, processing the first state information and the second state information by using a vector field histogram algorithm through the local planning module to obtain the state information of the unmanned underwater vehicle model.
Step 824, sending, by the local planning module, status information of the unmanned submersible vehicle model to the unmanned submersible vehicle module.
In step 825, the unmanned submersible vehicle module is controlled to move in the simulation environment according to the state information.
According to the unmanned submersible vehicle simulation method, different motion control models and sensor models can be built aiming at different simulation tasks, the state information of the unmanned submersible vehicle model is obtained based on the different motion control models and the sensor models, and then the unmanned submersible vehicle model is controlled to execute different simulation tasks in a simulation environment according to the state information.
In one exemplary embodiment, as shown in fig. 9, a schematic diagram of a framework developed based on the unmanned submersible simulation method of the present application is shown. Firstly, defining task requirements; step two, carrying out scheme design according to task requirements, including unmanned submarine model design and algorithm design; thirdly, developing related programming interfaces; fourth, setting up a simulation platform based on a Gazebo platform and an ROS platform; fifthly, burning the algorithm program into a hardware platform; sixthly, experimental testing; seventh, simulation and verification; eighth, analyze and model.
In one exemplary embodiment, a schematic diagram of the control platform interacting with the simulation platform is shown in FIG. 10. The control platform is constructed based on a Matlab platform and a Simulink platform, and the simulation platform is constructed based on a Gazebo platform and a ROS platform. The control platform comprises a task scheduling module, a global planning module, a control module and a local planning module, and the simulation platform comprises a sensor module and an unmanned underwater vehicle module. The control platform and the simulation platform can be distributed on different devices, and the control platform and the simulation platform can be distributed on the same device in a mode of creating a virtual machine.
It should be understood that, although the steps in the flowcharts related to the above embodiments are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides an unmanned underwater vehicle simulation device for realizing the unmanned underwater vehicle simulation method. The implementation scheme of the solution provided by the device is similar to the implementation scheme described in the method, so the specific limitation in the embodiments of one or more unmanned underwater vehicle simulation devices provided below can be referred to as the limitation of the unmanned underwater vehicle simulation method hereinabove, and the description thereof is omitted here.
In one embodiment, as shown in FIG. 11, an unmanned submersible vehicle simulation apparatus 1100 is provided, comprising: a model building module 1120, a first determination module 1140, a status information acquisition module 1160, and a movement control module 1180, wherein:
the model construction module 1120 is used for constructing a motion control model and a sensor model of the unmanned underwater vehicle model on a simulation platform according to a simulation task of the unmanned underwater vehicle model of the unmanned underwater vehicle;
a first determination module 1140 for determining an unmanned submersible vehicle module based on the motion control model and the unmanned submersible vehicle model, and for determining a sensor module based on the sensor model;
the state information obtaining module 1160 is configured to obtain state information of the unmanned underwater vehicle model through the unmanned underwater vehicle module; the state information is determined according to the first state information sent by the sensor module and the second state information sent by the control platform;
the movement control module 1180 is configured to control, by using the unmanned underwater vehicle module, the unmanned underwater vehicle model to move in the simulation environment according to the state information.
In one embodiment, the state information obtaining module 1160 is further configured to obtain the first state information and the second state information through the local planning module; processing the first state information and the second state information by using a vector field histogram algorithm through a local planning module to obtain the state information of the unmanned underwater vehicle model; and sending state information of the unmanned underwater vehicle model to the unmanned underwater vehicle module through the local planning module.
In one embodiment, the state information obtaining module 1160 is further configured to send, to the global planning module through the task scheduling module, path start point information corresponding to the simulation task; obtaining each path point information corresponding to the simulation task through a global planning module according to the A-star algorithm and the path starting point information, and sending each path point information to a control module; obtaining second state information according to a pure tracking algorithm and the information of each path point through a control module; sending second state information to the local planning module through the control module; the method comprises the steps of obtaining state information of obstacles around an unmanned submarine module through a sensor module, taking the state information of the obstacles as first state information, and sending the first state information to a local planning module.
In one embodiment, the model building module 1120 is further configured to determine a force and torque to which the unmanned submersible model is subjected corresponding to the simulation task; determining a motion control model of the unmanned underwater vehicle model according to the force and torque, corresponding to the simulation task, of the unmanned underwater vehicle model; determining an error model corresponding to a simulation task of the unmanned submarine model; and determining a sensor model of the unmanned submarine model according to the error model.
The modules in the unmanned aerial vehicle simulation device can be fully or partially realized by software, hardware and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, and the internal structure of which may be as shown in fig. 12. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is for storing data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program when executed by the processor implements an unmanned aerial vehicle simulation method.
In one embodiment, a computer device is provided, which may be a terminal, and the internal structure thereof may be as shown in fig. 13. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program when executed by the processor implements an unmanned aerial vehicle simulation method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those skilled in the art that the structures shown in fig. 12 and 13 are block diagrams of only some of the structures associated with the present application and are not intended to limit the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of:
according to the simulation task of the unmanned underwater vehicle model of the unmanned underwater vehicle, a motion control model and a sensor model of the unmanned underwater vehicle model are built on a simulation platform;
determining an unmanned submarine module according to the motion control model and the three-dimensional model of the unmanned submarine, and determining a sensor module according to the sensor model;
acquiring state information of an unmanned underwater vehicle model through the unmanned underwater vehicle module; the state information is determined according to the first state information sent by the sensor module and the second state information sent by the control platform;
and controlling the unmanned underwater vehicle model to move in the simulation environment according to the state information through the unmanned underwater vehicle module.
In an embodiment, there is also provided a computer device comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the method embodiments described above when the computer program is executed.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
according to the simulation task of the unmanned underwater vehicle model of the unmanned underwater vehicle, a motion control model and a sensor model of the unmanned underwater vehicle model are built on a simulation platform;
determining an unmanned submarine module according to the motion control model and the three-dimensional model of the unmanned submarine, and determining a sensor module according to the sensor model;
acquiring state information of an unmanned underwater vehicle model through the unmanned underwater vehicle module; the state information is determined according to the first state information sent by the sensor module and the second state information sent by the control platform;
and controlling the unmanned underwater vehicle model to move in the simulation environment according to the state information through the unmanned underwater vehicle module.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, carries out the steps of the method embodiments described above.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in accordance with the embodiments may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples represent only a few embodiments of the present application, which are described in more detail and are not thereby to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.
Claims (10)
1. An unmanned submarine simulation method, comprising:
according to a simulation task of an unmanned underwater vehicle model of the unmanned underwater vehicle, a motion control model and a sensor model of the unmanned underwater vehicle model are built on a simulation platform;
determining an unmanned underwater vehicle module according to the motion control model and a three-dimensional model of the unmanned underwater vehicle, and determining a sensor module according to the sensor model;
Acquiring state information of the unmanned underwater vehicle model through the unmanned underwater vehicle module; the state information is determined according to the first state information sent by the sensor module and the second state information sent by the control platform;
and controlling the unmanned underwater vehicle model to move in a simulation environment according to the state information through the unmanned underwater vehicle module.
2. The method of claim 1, wherein the control platform comprises a local planning module; the obtaining, by the unmanned submersible vehicle module, the status information of the unmanned submersible vehicle model includes:
acquiring the first state information and the second state information through the local planning module;
processing the first state information and the second state information by the local planning module through a vector field histogram algorithm to obtain state information of the unmanned underwater vehicle model;
and sending state information of the unmanned underwater vehicle model to the unmanned underwater vehicle module through the local planning module.
3. The method of claim 2, wherein the control platform further comprises a task scheduling module, a global planning module, and a control module; the obtaining, by the local planning module, the first state information and the second state information includes:
Transmitting path starting point information corresponding to the simulation task to the global planning module through the task scheduling module;
obtaining each path point information corresponding to the simulation task through the global planning module according to an A-star algorithm and the path starting point information, and sending each path point information to the control module;
obtaining the second state information by the control module according to a pure tracking algorithm and the path point information;
sending the second state information to the local planning module through the control module;
and acquiring the state information of the obstacles around the unmanned underwater vehicle module through the sensor module, taking the state information of the obstacles as the first state information, and sending the first state information to the local planning module.
4. The method of claim 1, wherein constructing the motion control model and the sensor model of the unmanned submersible model on a simulation platform based on the simulation tasks of the unmanned submersible model of the unmanned submersible comprises:
determining the force and torque corresponding to the simulation task, which the unmanned submarine model receives;
Determining a motion control model of the unmanned underwater vehicle model according to the force and the torque, corresponding to the simulation task, of the unmanned underwater vehicle model;
determining an error model corresponding to a simulation task of the unmanned submarine model;
and determining a sensor model of the unmanned submarine model according to the error model.
5. The method according to any one of claims 1-4, further comprising:
based on the Gazebo platform in the simulation platform, sea surface waves are rendered by utilizing the sea wave world and the wave coloring device, so that a sea surface environment is obtained;
obtaining a submarine environment based on the Gazebo platform and the electronic chart data;
and determining the simulation environment according to the sea surface environment and the seabed environment.
6. The method of claim 5, wherein the deriving a subsea environment based on the Gazebo platform and electronic chart data comprises:
processing the electronic chart data to obtain raster data; the raster data comprises blank areas and non-blank areas;
performing interpolation processing on the blank area based on the non-blank area to obtain a terrain file;
performing file conversion on the topographic file and the non-blank area to obtain a digital elevation file;
And obtaining the submarine environment based on the digital elevation file.
7. The method according to any one of claims 1-4, further comprising:
modeling the size, material and shape of the unmanned underwater vehicle by utilizing SolidWorks software to obtain a first model;
layout is carried out on the executor of the first model to obtain a second model;
processing the second model by using ANSYS software to obtain a first file;
according to the first file, a three-dimensional model of the unmanned underwater vehicle is obtained;
and obtaining the unmanned underwater vehicle model according to the three-dimensional model, the motion control model and the sensor model.
8. An unmanned submarine simulator, the device comprising:
the model construction module is used for constructing a motion control model and a sensor model of the unmanned underwater vehicle model on a simulation platform according to a simulation task of the unmanned underwater vehicle model of the unmanned underwater vehicle;
the first determining module is used for determining an unmanned underwater vehicle module according to the motion control model and the unmanned underwater vehicle model and determining a sensor module according to the sensor model;
The state information acquisition module is used for acquiring the state information of the unmanned underwater vehicle model through the unmanned underwater vehicle module; the state information is determined according to the first state information sent by the sensor module and the second state information sent by the control platform;
and the movement control module is used for controlling the unmanned underwater vehicle model to move in a simulation environment according to the state information through the unmanned underwater vehicle module.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 7 when the computer program is executed.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.
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