Pose determination method and system of underwater unmanned aerial vehicle

Abstract

The invention discloses a pose determination method and system of an underwater unmanned aerial vehicle, the method is applied to the underwater unmanned aerial vehicle, the underwater unmanned aerial vehicle is in radio communication connection with a receiver, and the underwater unmanned aerial vehicle is provided with a nine-axis gyroscope and a sensor; the pose determination method of the underwater unmanned aerial vehicle comprises the following steps: acquiring initial pose information of the nine-axis gyroscope and environment information of the sensor; obtaining intermediate attitude information of the underwater unmanned aerial vehicle according to the initial attitude information and the environment information; when the underwater unmanned aerial vehicle is located in a preset distance range of the receiver, receiving calibration information of the receiver; and performing pose calibration according to the calibration information and the intermediate pose information to obtain target pose information of the underwater unmanned aerial vehicle. According to the invention, the positioning accuracy of the underwater unmanned aerial vehicle is improved.

Description

Technical Field

[0001] The present application relates to the field of underwater UAV control technology, and in particular to a method and system for determining the position and posture of an underwater UAV. Background Art

[0002] The particularity of the underwater environment (such as limited light propagation, rapid attenuation of electromagnetic waves, etc.) makes traditional positioning technologies such as GPS and Wi-Fi unable to work properly underwater. In the existing technology, underwater positioning mostly relies on sonar systems, but sonar systems are expensive and highly dependent on the environment. At present, among the existing underwater drone positioning methods, inertial navigation combined with other auxiliary positioning methods is more common, such as correcting position and attitude through sensor fusion technology. However, in the absence of effective external reference information, the drift of the inertial navigation system is difficult to avoid.

[0003] Therefore, the prior art still needs to be improved and developed. Summary of the invention

[0004] The main purpose of the present application is to provide a method and system for determining the position and posture of an underwater UAV, aiming to solve the problem in the prior art that underwater UAV positioning using inertial navigation is difficult to avoid drift, resulting in low underwater UAV positioning accuracy.

[0005] A first aspect of an embodiment of the present application provides a method for determining the posture of an underwater drone, which is applied to an underwater drone, wherein the underwater drone is connected to a receiver via radio communication, and the underwater drone is provided with a nine-axis gyroscope and a sensor; the method for determining the posture of the underwater drone comprises: acquiring initial posture information of the nine-axis gyroscope and environmental information of the sensor; obtaining intermediate posture information of the underwater drone based on the initial posture information and the environmental information; receiving calibration information of the receiver when the underwater drone is within a preset distance range of the receiver; performing posture calibration based on the calibration information and the intermediate posture information to obtain target posture information of the underwater drone.

[0006] Optionally, in one embodiment of the present application, the nine-axis gyroscope includes an accelerometer, a gyroscope and a magnetometer, and the sensor includes a pressure sensor, a temperature sensor and a humidity sensor.

[0007] Optionally, in one embodiment of the present application, the obtaining of the initial posture information of the nine-axis gyroscope and the environmental information of the sensor specifically includes: obtaining the acceleration of the accelerometer, the angular velocity of the gyroscope and the azimuth of the magnetometer, and obtaining the pressure data of the pressure sensor, the temperature data of the temperature sensor and the humidity data of the humidity sensor; using a filtering method to fuse the acceleration, the angular velocity and the azimuth to obtain the initial posture information, and using a filtering method to fuse the pressure data, the temperature data and the humidity data to obtain the environmental information.

[0008] Optionally, in one embodiment of the present application, the intermediate posture information includes the current posture of the underwater drone; and obtaining the intermediate posture information of the underwater drone based on the initial posture information and the environmental information is specifically: obtaining the current posture of the underwater drone based on the initial posture information and the environmental information.

[0009] Optionally, in one embodiment of the present application, the underwater drone also includes an infrared transmitter, and the calibration information is the location information of the underwater drone; when the underwater drone is within a preset distance range of the receiver, receiving the calibration information of the receiver specifically includes: sending a calibration request to the receiver through the infrared transmitter; receiving the location information of the underwater drone generated by the receiver in response to the calibration request.

[0010] Optionally, in one embodiment of the present application, the posture calibration is performed according to the calibration information and the intermediate posture information to obtain the target posture information of the underwater drone, specifically including: obtaining the current position of the underwater drone according to the position information; obtaining the target posture of the underwater drone, and obtaining the control instruction of the underwater drone according to the current position, the current posture and the target posture; controlling the underwater drone to operate according to the control instruction to obtain the target posture information of the underwater drone.

[0011] Optionally, in one embodiment of the present application, the underwater drone is controlled to operate according to the control instruction to obtain the target posture information of the underwater drone, and then further includes: obtaining environmental update information of the sensor; processing the environmental update information to obtain status information of the underwater drone; according to the status information, modifying the control instruction to obtain a modified control instruction, controlling the underwater drone to operate according to the updated control instruction to obtain updated target posture information.

[0012] The second aspect of the embodiment of the present application further provides a system for determining the position and posture of an underwater drone, wherein the system for determining the position and posture of an underwater drone comprises:

[0013] A posture determination module, used to obtain intermediate posture information of the underwater drone according to the initial posture information and the environmental information;

[0014] A position calibration module, configured to receive calibration information of the receiver when the underwater drone is within a preset distance range of the receiver;

[0015] The attitude adjustment module is used to perform attitude calibration according to the calibration information and the intermediate attitude information to obtain the target attitude information of the underwater drone.

[0016] The third aspect of an embodiment of the present application also provides an underwater drone, wherein the underwater drone comprises: a memory, a processor, and an underwater drone posture determination program stored in the memory and executable on the processor, wherein the underwater drone posture determination program, when executed by the processor, implements the steps of the underwater drone posture determination method as described above.

[0017] The fourth aspect of an embodiment of the present application also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a posture determination program for an underwater drone, and when the posture determination program for an underwater drone is executed by a processor, the steps of the underwater drone posture determination method as described above are implemented.

[0018] Beneficial effect: The present application provides a method and system for determining the posture of an underwater UAV. The method achieves high-precision posture judgment and real-time positioning through a nine-axis gyroscope and 433MHz radio and infrared communication means, overcomes the shortcomings of the prior art in underwater positioning accuracy and communication distance, and improves the accuracy of underwater UAV positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 It is a flow chart of a preferred embodiment of the method for determining the position and posture of an underwater drone of the present application;

[0021] Figure 2 It is a structural diagram of a preferred embodiment of the position and posture determination system of the underwater drone of the present application;

[0022] Figure 3 This is a structural diagram of a preferred embodiment of the underwater drone of the present application.

[0023] Description of reference numerals:

[0024] 100, information acquisition module; 200, posture determination module; 300, position calibration module; 400, posture adjustment module. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical scheme and effect of the present application clearer and more specific, the technical scheme in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. The described embodiments are only possible technical implementations of the present application, not all possible implementations. Based on the embodiments in the present application, those skilled in the art can completely combine the embodiments of the present application to obtain other embodiments without creative work, and these embodiments are also within the scope of protection of the present application.

[0026] In the related technologies, there are problems with the accumulation of inertial navigation errors: in the case of long-term operation, relying solely on the nine-axis gyroscope for position calculation will lead to error accumulation, affecting positioning accuracy; limited communication: the underwater propagation distance of 433MHz radio is limited, and the propagation distance and directionality of infrared rays are strong, which cannot completely meet the needs of wide-area communications; insufficient calibration frequency: due to the complexity of the underwater environment, the equipment may be disturbed by various factors such as water flow and magnetic field during movement, and the accuracy of posture judgment is difficult to guarantee. Therefore, the long-term and precise navigation of underwater drones still relies on the input of more external auxiliary signals. The use of multimodal communication ensures that there is a redundant design to ensure tracking, solves the problem of drones tracking objects underwater, and can ensure continuous tracking of people in low visibility and complex environments.

[0027] This application adopts a nine-axis gyroscope combined with a dual auxiliary positioning method of 433MHz and infrared communication, and performs position synchronization and calibration through 433MHz radio and infrared communication. It is suitable for precise positioning and navigation in underwater environments. Through the collaborative work of the receiver and the drone, it solves the drift problem of the existing inertial navigation system and realizes real-time posture and position tracking of underwater drones.

[0028] The present application can be widely used in underwater exploration, search and rescue, marine research, etc. Especially in scenarios with high requirements for underwater communication and positioning, the technical solution of the present application can achieve high-precision real-time positioning and stable underwater communication.

[0029] First, the following will be combined with the attached Figure 1 , the architecture of the underwater drone of the embodiment of the present application is introduced.

[0030] Nine-axis gyroscope posture judgment: Both the drone and the receiver are equipped with a nine-axis gyroscope (including a 1-axis accelerometer, a 3-axis gyroscope, and a 3-axis magnetometer) to obtain the device's posture information in real time, including the device's acceleration, angular velocity, and orientation. By integrating these sensor data, the drone can autonomously determine the current posture (i.e., position and direction) and adjust the motion state in real time as needed. This design obtains the device's mobile posture based on quaternions to ensure that both motion trajectories are in one dimension.

[0031] 433MHz radio communication: The position and status of the drone and the receiver are synchronized via 433MHz radio. The 433MHz frequency band has relatively good underwater penetration and can communicate effectively within a certain distance (several meters to tens of meters). The drone regularly sends its position information to the receiver via 433MHz radio and obtains calibration information from the receiver to ensure the accuracy of position calculation.

[0032] Infrared short-distance calibration: To further improve positioning accuracy, infrared communication is used to perform short-distance posture calibration when the drone is close to the receiver. Infrared has strong directionality and precise signal transmission characteristics, and can be used to fine-tune the drone's attitude to reduce the cumulative error in inertial navigation. At regular intervals or when the communication signal is poor, the drone will actively approach the receiver for infrared calibration.

[0033] Attitude calibration and position estimation: The drone uses the attitude calibration information provided by the receiver and the data from its own nine-axis gyroscope to make precise attitude adjustments and position estimation. The inertial navigation system (INS) is used for real-time attitude tracking and periodic precision correction with the help of infrared signals to solve the error accumulation problem of inertial navigation.

[0034] Motion control and navigation algorithm: The drone uses its own motion control algorithm (such as PID control or adaptive control algorithm) to achieve autonomous navigation and attitude control based on the received posture calibration information. This algorithm combines the sensor data of the nine-axis gyroscope and the calibration data of the receiver, allowing the drone to maintain a stable flight or swimming posture in complex underwater environments.

[0035] Pressure sensor: Choose a high-precision underwater pressure sensor that can accurately measure the pressure distribution around the underwater drone and help assess water depth and environmental pressure changes.

[0036] Temperature sensor: Use a highly sensitive underwater temperature sensor to monitor the temperature changes of the water area where the drone is located in real time and optimize the working status of the drone.

[0037] Humidity Sensor: Use a waterproof humidity sensor to monitor the humidity level inside the drone to ensure that the electronic equipment is protected from moisture.

[0038] Inertial Measurement Unit (IMU): Integrated high-precision IMU (accelerometer, gyroscope) to track the drone's attitude and motion trajectory.

[0039] Sonar sensor: Install high-resolution sonar to detect the relative position of the drone and the environment, and assist in trajectory tracking.

[0040] Data acquisition device: Microcontroller unit (MCU): Choose a high-performance, low-power MCU to control data acquisition and processing of all sensors, such as STM32 or ESP32, which is suitable for underwater operations.

[0041] Data storage: Integrated flash memory or SD card to store data collected by the sensor, ensuring that the data can be read after communication is interrupted or the task is completed.

[0042] Communication module: Integrate underwater wireless communication module (such as acoustic communication or optical communication) to realize data interaction between the UAV and the transmitter and transmit trajectory data in real time.

[0043] Software system: Data acquisition algorithm: Develop data acquisition algorithms for different sensors to ensure the accuracy and real-time performance of data in complex underwater environments.

[0044] Trajectory tracking and prediction: Design trajectory tracking and prediction algorithms to accurately model the motion trajectory of the drone based on sensor data such as pressure, IMU, and sonar.

[0045] Data processing and analysis: Develop underwater data processing and analysis systems to analyze the UAV's motion, environmental parameters and positioning data in real time.

[0046] Sensor placement: Pressure, temperature, humidity, sonar, and IMU sensors are evenly placed on the drone and receiver to ensure comprehensive data collection and support accurate trajectory tracking.

[0047] MCU and memory integration: The MCU and data storage device are safely integrated inside the drone, and waterproof treatment ensures its stability and safety in complex underwater environments.

[0048] In a data acquisition system, the analog signal measured by the sensor needs to be converted into a digital signal by an ADC (Analog-to-Digital Converter) so that a microcontroller (MCU) or other processing unit can read and analyze the data.

[0049] The following describes the method and system for determining the position and posture of an underwater drone in an embodiment of the present application with reference to the accompanying drawings. In view of the problem that it is difficult to avoid drift when using inertial navigation to locate underwater drones in the above-mentioned related technologies, resulting in low accuracy in positioning underwater drones, the present application provides a method for determining the position and posture of an underwater drone. In this method, a nine-axis gyroscope and 433MHz radio and infrared communication methods are used to achieve high-precision position and posture judgment and real-time positioning, thereby overcoming the deficiencies of the prior art in underwater positioning accuracy and communication distance, and improving the accuracy of underwater drone positioning. Thus, the technical problem that it is difficult to avoid drift when using inertial navigation to locate underwater drones in the related technologies, resulting in low accuracy in positioning underwater drones, is solved.

[0050] The technical solution of the present application is described in detail with specific embodiments below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0051] The method for determining the position and posture of an underwater drone described in a preferred embodiment of the present application is as follows: Figure 1 As shown, the method for determining the position and posture of the underwater drone includes the following steps:

[0052] In step S101, initial posture information of the nine-axis gyroscope and environmental information of the sensor are obtained.

[0053] The present application uses radio (such as 433MHz) and optical communication (such as infrared) for underwater communication, and combines an inertial navigation system (INS) for posture judgment.

[0054] In a possible implementation, the acceleration of the accelerometer, the angular velocity of the gyroscope, and the orientation of the magnetometer are obtained, and the pressure data of the pressure sensor, the temperature data of the temperature sensor, and the humidity data of the humidity sensor are obtained; the acceleration, the angular velocity, and the orientation are fused by a filtering method to obtain initial posture information, and the pressure data, the temperature data, and the humidity data are fused by a filtering method to obtain environmental information.

[0055] Specifically, data fusion: the data of gyroscope, accelerometer and magnetometer are integrated to obtain the initial attitude information of the UAV; sensor data (such as pressure, sonar, etc.) are integrated with the preliminary attitude information to further improve the accuracy of attitude determination. Kalman filter or extended Kalman filter: the fused data is processed using Kalman filter or extended Kalman filter algorithm to eliminate noise and error. These algorithms can predict the attitude of the UAV based on the system model and sensor data, and update the prediction results in real time.

[0056] In one embodiment of the present application, the sensor obtains an analog signal: the physical quantity detected by various sensors (such as pressure, temperature, and humidity sensors) is usually a continuously changing analog signal. These signals may be changes in voltage, current, or resistance, indicating specific environmental parameters. Pressure sensor: outputs a voltage proportional to the measured pressure; temperature sensor: outputs a voltage or resistance change proportional to the temperature; humidity sensor: outputs a voltage signal that changes with humidity. Select a high-precision, low-power ADC chip to ensure accurate collection of sensor data, consider factors such as sampling rate, resolution, and power consumption, and select an ADC device suitable for the application scenario; encode the digital signal output by the ADC in hexadecimal for easy data transmission and storage. Hexadecimal encoding can effectively reduce the number of bits in data transmission and improve data transmission efficiency. Processing and computing technology: When designing an efficient analog-to-digital conversion (ADC) system, combining innovative data acquisition and processing technologies can significantly improve the quality, stability, and accuracy of the data.

[0057] Furthermore, dynamic range adjustment: by designing an adaptive dynamic range adjustment algorithm, the reference voltage (Vref) or gain of the ADC is dynamically adjusted according to the signal strength measured by the sensor to improve the dynamic range and accuracy of data acquisition. Dynamic reference voltage adjustment: adjust the reference voltage range of the ADC according to the real-time strength of the signal. For example, when the sensor signal is small, reduce the reference voltage so that the ADC has higher resolution within a smaller voltage range and improves accuracy. Adaptive gain control: adjust the gain of the preamplifier according to the amplitude of the signal so that the signal input to the ADC is always in the optimal range to avoid overload or loss of accuracy. It is suitable for nonlinear applications and alternating strong and weak signals. It can ensure that accurate digitized signals can be obtained within a wide range of signal strengths, improving the robustness of the system.

[0058] Noise suppression: Using digital filters and signal processing algorithms to suppress noise interference in ADC output is a key means to improve data quality. The following measures can be taken: Low-pass filter (LPF): Low-pass filter the sampled data to eliminate high-frequency noise and maintain valid signals; Kalman filter: For dynamically changing signals, the Kalman filter can predict the signal based on the system model and eliminate unwanted noise interference.

[0059] Sensor calibration: Implementing real-time calibration is necessary to ensure the stability and accuracy of the ADC in long-term use. The main methods include: Periodic automatic calibration: The system calibrates the ADC regularly to compensate for deviations caused by factors such as temperature changes and voltage drift. Reference voltage correction: Dynamically correct ADC measurement deviations by comparing the built-in precise reference voltage source with the actual reference voltage. Self-calibration mechanism: Using the known reference signal in the system, periodic self-calibration is performed to ensure the long-term stability of the data output. This mechanism can significantly reduce the error drift of the system and make data acquisition more reliable.

[0060] Adaptive sampling rate: The adaptive sampling rate algorithm dynamically adjusts the ADC sampling rate by monitoring the signal changes of the sensor to optimize data acquisition efficiency and reduce power consumption. When the sensor detects frequent signal changes, the system automatically increases the sampling rate to ensure accurate capture of rapidly changing signals; when the signal changes slowly, the system reduces the sampling rate to reduce power consumption and optimize resource utilization. This adaptive sampling technology can not only reduce power consumption, but also optimize the use of system resources while ensuring data accuracy, which is particularly suitable for battery-powered devices.

[0061] In step S102, the intermediate posture information of the underwater drone is obtained according to the initial posture information and the environmental information.

[0062] In a possible implementation, the intermediate posture information includes the current posture of the underwater drone. The current posture of the underwater drone is obtained according to the initial posture information and the environmental information.

[0063] Specifically, the data from the nine-axis gyroscope is combined with the fused data from other sensors to calculate the current posture of the drone (such as pitch angle, roll angle, and heading angle).

[0064] It should be noted that the data collected by the sensor, the attitude information obtained by the gyroscope, and the calibration information sent by the receiver are interrelated and complementary. Attitude information obtained by the gyroscope: The gyroscope mainly provides the angular velocity and direction information of the drone; combined with the data of the accelerometer and magnetometer, the gyroscope can calculate the real-time attitude of the drone (pitch angle, yaw angle, roll angle); Calibration information sent by the receiver: The receiver receives the attitude information of the drone through radio or infrared, and may provide calibration information based on external references (such as GPS or other positioning devices). These calibration information is used to correct the cumulative error of the drone's attitude and improve positioning accuracy. Data collected by sensors: The data collected by sensors (such as pressure, temperature, humidity, sonar, etc.) provide the environmental parameters and motion status of the drone. These data are crucial for the drone's perception of depth, temperature, humidity and surrounding environment underwater. Sensor data can also be used to assist in attitude determination. For example, a pressure sensor can provide information about the depth of the drone underwater, which helps to infer the vertical attitude of the drone. The role of sensors in collecting data: Environmental perception: sensor data provides detailed information about the environment around the drone, such as water depth, temperature, humidity, etc.; attitude assisted determination: the water depth information provided by the pressure sensor can assist in determining the vertical attitude of the drone; the sonar sensor provides relative position information with the environment, which helps the drone to accurately locate in complex environments; motion state monitoring: sensor data can be used to monitor the motion state of the drone, such as speed, acceleration, etc.; fault diagnosis: sensor data can be used to detect abnormal conditions of the drone, such as motor failure, sensor failure, etc.

[0065] In step S103, when the underwater drone is within a preset distance range of the receiver, calibration information of the receiver is received.

[0066] In a possible implementation, the underwater drone further includes an infrared transmitter, and the calibration information is the position information of the underwater drone. A calibration request is sent to the receiver via the infrared transmitter; and the position information of the underwater drone generated by the receiver in response to the calibration request is received.

[0067] Specifically, the receiver periodically sends calibration information to the drone to correct the accumulated error of the attitude information. When the drone is close to the receiver, infrared communication can be used for short-distance attitude calibration to further improve positioning accuracy.

[0068] In step S104, posture calibration is performed according to the calibration information and the intermediate posture information to obtain target posture information of the underwater drone.

[0069] In one possible implementation, the current position of the underwater drone is obtained based on the position information; the target posture of the underwater drone is acquired, and the control instruction of the underwater drone is obtained based on the current position, the current posture and the target posture; the underwater drone is controlled to operate according to the control instruction to obtain the target posture information of the underwater drone.

[0070] Specifically, position calculation: the current position of the UAV is calculated based on the absolute position information provided by the receiver (such as GPS coordinates) and the relative motion information of the UAV (such as speed, acceleration, etc.); attitude adjustment: according to the difference between the calculated attitude and the target attitude (provided by the autonomous navigation algorithm or manual control instructions), the attitude is adjusted by controlling the motor or other actuators of the UAV; according to the current position, attitude and target position of the UAV (provided by the navigation algorithm or mission planning), the required control instructions (such as speed, acceleration, steering angle, etc.) are calculated; the calculated control instructions are passed to the actuators of the UAV (such as motors, servos, etc.) to realize autonomous navigation and attitude control of the UAV.

[0071] In one possible implementation, environmental update information of the sensor is obtained; the environmental update information is processed to obtain status information of the underwater drone; the control instruction is corrected according to the status information to obtain a corrected control instruction, and the underwater drone is controlled to operate according to the updated control instruction to obtain updated target posture information.

[0072] Specifically, in the process of executing control instructions, the drone continuously collects new sensor data and updates the status of the drone through data fusion and posture calculation; based on the new status information, the control instructions are corrected to ensure that the drone can fly or swim accurately and stably according to the predetermined trajectory.

[0073] This application significantly improves the accuracy of underwater drone posture judgment by integrating a nine-axis gyroscope and multiple communication technologies. Through 433MHz radio and infrared communication, it solves the bottleneck of underwater communication distance and accuracy, and can perform real-time communication and posture calibration at a long distance. The periodic attitude calibration mechanism effectively solves the error accumulation problem in the inertial navigation system and improves the positioning accuracy during long-term operation. The system adapts to complex underwater environments and can dynamically adjust the posture and position according to the current communication and sensor status to ensure the stable operation of the drone.

[0074] Next, the position and posture determination system of an underwater drone proposed in an embodiment of the present application is described with reference to the accompanying drawings.

[0075] Figure 2 It is a structural diagram of the position and posture determination system of the underwater drone according to an embodiment of the present application.

[0076] like Figure 2 As shown, the position and posture determination system of the underwater drone includes: an information acquisition module 100, a posture determination module 200, a position calibration module 300 and a posture adjustment module 400.

[0077] Specifically, the information acquisition module is used to obtain the initial posture information of the nine-axis gyroscope and the environmental information of the sensor;

[0078] A posture determination module, used to obtain intermediate posture information of the underwater drone according to the initial posture information and the environmental information;

[0079] A position calibration module, configured to receive calibration information of the receiver when the underwater drone is within a preset distance range of the receiver;

[0080] The attitude adjustment module is used to perform attitude calibration according to the calibration information and the intermediate attitude information to obtain the target attitude information of the underwater drone.

[0081] Figure 3 This is a structural diagram of an underwater drone provided in an embodiment of the present application. The underwater drone may include:

[0082] A memory 501 , a processor 502 , and a computer program stored in the memory 501 and executable on the processor 502 .

[0083] When the processor 502 executes the program, the method for determining the position and posture of the underwater drone provided in the above embodiment is implemented.

[0084] Furthermore, the underwater drone also includes:

[0085] The communication interface 503 is used for communication between the memory 501 and the processor 502 .

[0086] The memory 501 is used to store computer programs that can be executed on the processor 502 .

[0087] The memory 501 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0088] If the memory 501, the processor 502 and the communication interface 503 are implemented independently, the communication interface 503, the memory 501 and the processor 502 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus or an Extended Industry Standard Architecture (EIS) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0089] Optionally, in a specific implementation, if the memory 501, the processor 502 and the communication interface 503 are integrated on a chip, the memory 501, the processor 502 and the communication interface 503 can communicate with each other through an internal interface.

[0090] The processor 502 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0091] This embodiment also provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the above method for determining the position and posture of an underwater drone is implemented.

[0092] One embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the present application Figure 1 A method for determining the position and posture of an underwater drone provided in any of the corresponding embodiments.

[0093] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0094] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0095] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0096] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable storage medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, a "computer-readable storage medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples (non-exhaustive list) of computer-readable storage media include the following: an electrical connection with one or N wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable storage medium may even be paper or other suitable medium on which the program is printed, since the program can be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways as necessary, and then storing it in a computer memory.

[0097] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0098] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0099] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0100] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

[0101] It should be understood that the application of the present application is not limited to the above examples. For ordinary technicians in this field, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to this application.

[0102] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for determining the position and posture of an underwater drone, characterized in that: Applied to an underwater drone, the underwater drone is connected to a receiver via radio communication, and the underwater drone is provided with a nine-axis gyroscope and a sensor; The method for determining the position and posture of the underwater drone comprises: Acquiring initial attitude information of the nine-axis gyroscope and environmental information of the sensor; Obtaining intermediate posture information of the underwater drone according to the initial posture information and the environmental information; When the underwater drone is within a preset distance range of the receiver, receiving calibration information of the receiver; Perform posture calibration according to the calibration information and the intermediate posture information to obtain target posture information of the underwater drone.

2. The method for determining the position and posture of an underwater drone according to claim 1, characterized in that: The nine-axis gyroscope includes an accelerometer, a gyroscope and a magnetometer, and the sensor includes a pressure sensor, a temperature sensor and a humidity sensor.

3. The method for determining the position and posture of an underwater drone according to claim 2, characterized in that: The obtaining of the initial attitude information of the nine-axis gyroscope and the environmental information of the sensor specifically includes: Acquire the acceleration of the accelerometer, the angular velocity of the gyroscope, and the orientation of the magnetometer, and acquire the pressure data of the pressure sensor, the temperature data of the temperature sensor, and the humidity data of the humidity sensor; The acceleration, the angular velocity and the orientation are fused by a filtering method to obtain initial posture information, and the pressure data, the temperature data and the humidity data are fused by a filtering method to obtain environmental information.

4. The method for determining the position and posture of an underwater drone according to claim 1, characterized in that: The intermediate posture information includes the current posture of the underwater drone; The intermediate posture information of the underwater drone is obtained according to the initial posture information and the environmental information, specifically: The current posture of the underwater drone is obtained according to the initial posture information and the environmental information.

5. The method for determining the position and posture of an underwater drone according to claim 4, characterized in that: The underwater drone also includes an infrared transmitter, and the calibration information is the position information of the underwater drone; When the underwater drone is within a preset distance range of the receiver, receiving calibration information of the receiver specifically includes: sending a calibration request to the receiver via the infrared transmitter; Receive position information of the underwater drone generated by the receiver in response to the calibration request.

6. The method for determining the position and posture of an underwater drone according to claim 5, characterized in that: The performing posture calibration according to the calibration information and the intermediate posture information to obtain the target posture information of the underwater drone specifically includes: According to the position information, obtaining the current position of the underwater drone; Acquire the target posture of the underwater drone, and obtain a control instruction of the underwater drone according to the current position, the current posture and the target posture; The underwater drone is controlled to run according to the control instruction to obtain target position information of the underwater drone.

7. The method for determining the position and posture of an underwater drone according to claim 6, characterized in that: The controlling the underwater drone to operate according to the control instruction to obtain target position information of the underwater drone further includes: Obtaining environmental update information of the sensor; Processing the environmental update information to obtain status information of the underwater drone; According to the state information, the control instruction is corrected to obtain a corrected control instruction, and the underwater drone is controlled to operate according to the updated control instruction to obtain updated target posture information.

8. A position determination system for an underwater drone, characterized in that: The position and posture determination system of the underwater drone comprises: An information acquisition module is used to obtain the initial attitude information of the nine-axis gyroscope and the environmental information of the sensor; A posture determination module, used to obtain intermediate posture information of the underwater drone according to the initial posture information and the environmental information; A position calibration module, configured to receive calibration information of the receiver when the underwater drone is within a preset distance range of the receiver; The attitude adjustment module is used to perform attitude calibration according to the calibration information and the intermediate attitude information to obtain the target attitude information of the underwater drone.

9. An underwater drone, characterized in that: The underwater drone includes: a memory, a processor, and an underwater drone posture determination program stored in the memory and executable on the processor. When the underwater drone posture determination program is executed by the processor, the steps of the underwater drone posture determination method as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a posture determination program for an underwater drone, and when the posture determination program for an underwater drone is executed by a processor, the steps of the posture determination method for an underwater drone as described in any one of claims 1 to 7 are implemented.

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