Redundancy flight control system and method

Abstract

The invention discloses a redundancy flight control system and method, and relates to the technical field of flight control, the redundancy flight control system comprises an integrated control unit, and the integrated control unit comprises an inertial navigation sensor, a satellite positioning receiver, a navigation calculator, a power supply DC and a control calculator; at least two aviation-level J24-H connectors serve as external interfaces of the integrated control unit, the number of core points of the connectors in the integrated control unit is different to prevent wrong insertion, an airspeed meter interface is reserved to meet the subsequent measurement requirement for the airspeed, and the at least two aviation-level J24-H connectors serve as the external interfaces of the integrated control unit; by introducing a dual-IMU (inertial measurement unit) redundancy design and integrating a health judgment mechanism in a main controller, the system can monitor in real time and automatically switch to healthy IMU data as control input, so that the risk of out-of-control flight caused by a single IMU fault is effectively avoided, and the flight safety is improved. And the flight stability and safety of the unmanned aerial vehicle are obviously improved.

Description

Technical Field

[0001] The present invention relates to the field of flight control technology, and in particular to a redundant flight control system and method. Background Art

[0002] With the rapid development of drone technology, drones are increasingly used in aerial photography, agriculture, environmental monitoring, disaster assessment and other fields. However, the flight stability and safety of drones have always been the key factors restricting their widespread application. Especially in complex environments or extreme conditions, drones need to have higher reliability and robustness to cope with various unforeseen risks and challenges.

[0003] Traditional flight control systems mostly use a single inertial navigation unit (IMU) for attitude and position calculation. This design will seriously affect the flight stability of the drone when the sensor fails or is interfered with, and may even cause a crash. In addition, a single RTK (real-time kinematic differential positioning) module will also affect the positioning accuracy and flight safety of the drone when the signal is poor or fails.

[0004] In order to improve the flight stability and safety of drones, multi-redundant flight control systems have emerged. Multi-redundant flight control systems integrate multiple IMUs and multiple positioning methods to achieve data redundancy and backup, so that when a sensor fails, it can automatically switch to the backup sensor to ensure the continued stable flight of the drone. However, the existing multi-redundant flight control system still has some shortcomings in design, such as inefficient sensor data fusion algorithms, imperfect emergency handling mechanisms, and single flight modes.

[0005] Therefore, we propose a redundant flight control system and method to solve the above problems. Summary of the invention

[0006] The purpose of the present invention is to provide a redundant flight control system and method, which adopts a dual IMU design to ensure the reliability and accuracy of data through independent data collection and health status judgment. At the same time, an efficient Kalman filter algorithm is used for data fusion to improve the positioning accuracy and robustness of the drone. In addition, the system also has a complete emergency handling mechanism and a variety of flight mode options to meet the needs of different application scenarios.

[0007] To achieve the above object, the present invention provides the following technical solutions: a redundant flight control system, comprising an integrated control unit, wherein the integrated control unit comprises an inertial navigation sensor, a satellite positioning receiver, a navigation calculator, a power supply DC, and a control calculator;

[0008] At least two aviation-grade J24-H connectors are used as external interfaces of the integrated control unit. The number of connector cores in the integrated control unit is different to prevent wrong insertion, and an airspeed meter interface is reserved to meet the subsequent airspeed measurement requirements;

[0009] Dual IMU, the dual IMU includes a high-precision IMU and a low-precision IMU, both of which operate independently and input the solution results to the integrated control unit, and the integrated control unit selects healthy IMU posture data as control input through an internal health judgment mechanism;

[0010] A coprocessor, wherein the coprocessor is used to increase the ability of the flight control to connect to peripherals, wherein peripherals strongly related to flight control are connected to the integrated control unit, and peripherals weakly related to flight control are connected to the coprocessor;

[0011] RTK positioning and direction finding module, the RTK positioning and direction finding module has the ability to match the use of RTK mobile base station and network RTK;

[0012] A data fusion module, wherein the data fusion module uses a Kalman filter algorithm to fuse the dual IMU data and the RTK positioning data to improve the positioning accuracy and robustness of the UAV;

[0013] The Kalman filter algorithm continuously estimates the state of the system through two main steps: prediction and update. The following are the key formulas used in these two steps:

[0014] Prediction Steps:

[0015] State prediction equation:

[0016] hatxk∣k-1=Ax^k-1∣k-1+Buk-1

[0017] Among them, x^k|k-1 is the predicted state at time k, A is the state transfer matrix, x^k-1|k-1 is the optimal estimated state at time k-1, B is the control input matrix, and uk-1 is the control input at time k-1.

[0018] Forecast error covariance matrix:

[0019] Pk|k-1=APk-1|k-1AT+Q

[0020] Among them, Pk|k-1 is the prediction error covariance matrix at time k, Pk-1|k-1 is the estimation error covariance matrix at time k-1, and Q is the process noise covariance matrix.

[0021] Update steps:

[0022] Kalman gain:

[0023] Kk=Pk∣k-1HT(HPk∣k-1HT+R)-1

[0024] Where Kk is the Kalman gain, H is the observation matrix, and R is the observation noise covariance matrix.

[0025] State update equation:

[0026] hatxk∣k=x^k∣k-1+Kk(zk-Hx^k∣k-1)

[0027] Among them, x^k|k is the optimal estimated state at time k, and zk is the observed value at time k;

[0028] Update the error covariance matrix:

[0029] Pk|k=(I-Kk H)Pk|k-1

[0030] Among them, Pk|k is the estimated error covariance matrix at time k, and I is the identity matrix.

[0031] Preferably, the dual IMU solution also includes an operation health monitoring mechanism for two sets of IMUs, which is used to monitor the health status of the IMUs in real time and transmit the health status to the main controller, which selects the healthy IMU as the navigation data source.

[0032] Preferably, the power supply DC supports a power supply range of 18 to 50V, and the system has vibration and impact resistance capabilities, meeting the requirements of three-axis 10g and three-axis 20g respectively. The integrated control unit also includes an emergency processing unit for executing corresponding emergency processing measures when sensor data is abnormal, RTK positioning data is abnormal, or joystick remote control data is abnormal, to ensure the safe flight of the drone.

[0033] Preferably, the integrated control unit also includes software design, which includes a gyroscope accelerometer acquisition unit, a barometer acquisition unit, a magnetometer acquisition unit, an RTK positioning data analysis module, an INS combined navigation solution unit, an AHRS solution unit, a posture control unit and a motor drive unit, and each unit works together to achieve stable flight and precise control of the UAV.

[0034] Preferably, the gyro-accelerometer acquisition unit uses the SPI bus for data acquisition, and the resolution of angular velocity and acceleration is less than 0.1 deg / s and 0.1 m / s respectively. 2 , and has the function of identifying the health status of data to ensure the accuracy and reliability of the collected data.

[0035] A method for using a redundant flight control system comprises the following steps:

[0036] S1, system initialization step, after the flight control system is powered on, the system is initialized, including hardware self-test, sensor calibration, and communication interface configuration;

[0037] S2, data collection step, independently collects gyroscope and accelerometer data from high-precision inertial measurement unit (IMU) and low-precision IMU, and obtains high-precision positioning data through RTK module, while collecting barometer, magnetometer and other sensor data;

[0038] S3, data health status judgment step, judging the health status of the collected sensor data to ensure the reliability and accuracy of the data;

[0039] S4, data fusion and integrated navigation solution step, using dual IMU data and RTK data for data fusion, and performing integrated navigation solution to calculate the precise position, speed and attitude of the UAV;

[0040] S5, a flight mode selection step, selecting a manual, automatic or route flight appropriate flight mode according to user needs or preset conditions;

[0041] S6, remote control and flight stick input processing step, receiving and processing input control instructions from the remote control or flight stick;

[0042] S7, posture control step, calculating the control amount according to the target posture and current posture information, and driving the motor through the PWM signal to adjust the posture and position of the UAV;

[0043] S8, emergency handling steps, monitoring the status of sensors, communications, and positioning modules. Once an abnormality is detected, the emergency handling mechanism is activated, including switching redundant sensors and autonomous return operations;

[0044] S9, data transmission and communication step, transmitting the status information and location information of the UAV to the ground station or other equipment in real time, and receiving control instructions or mission data from the ground station or other equipment.

[0045] Preferably, the control method of the combined navigation is:

[0046] S41. In the case of RTK positioning module failure or poor signal, high-precision IMU data is used for short-term inertial navigation to ensure that the drone can still maintain a certain navigation accuracy when it loses external positioning support;

[0047] S42. Post-process the RTK positioning data through software algorithms to further eliminate positioning errors and improve positioning accuracy during long-term flights.

[0048] Preferably, the specific control method for selecting the flight mode is:

[0049] Manual flight mode, control the drone flight according to the real-time input instructions of the remote controller or flight joystick;

[0050] S51, automatic flight mode, autonomous navigation flight according to the preset flight path and altitude;

[0051] S52, route flight mode, combines waypoint planning and RTK positioning data to achieve precise route tracking flight;

[0052] S53, obstacle avoidance flight mode, monitors and avoids obstacles in real time through integrated forward and backward obstacle avoidance sensors.

[0053] Preferably, the method further includes the following user interaction and monitoring steps:

[0054] S10, transmitting the real-time flight status, sensor data and flight video of the UAV to a ground station or mobile device through a wireless communication module for real-time monitoring by an operator;

[0055] S11. Provide a graphical user interface (GUI) that allows operators to set flight parameters, view flight logs, and adjust flight strategies on a ground station or mobile device;

[0056] S12, integrated voice prompt function, which issues voice warnings or instructions to the operator during specific flight phases or abnormal situations.

[0057] Compared with the prior art, the present invention has the following beneficial effects:

[0058] Improve flight stability and safety: By introducing a dual IMU (inertial measurement unit) redundant design and integrating a health judgment mechanism in the main controller, the system can monitor in real time and automatically switch to healthy IMU data as control input, thereby effectively avoiding the risk of flight loss of control due to a single IMU failure and significantly improving the flight stability and safety of the drone.

[0059] Improve positioning accuracy: Combining the high-precision RTK (real-time dynamic differential positioning) module and using the Kalman filter algorithm to fuse the dual IMU data and RTK positioning data can further optimize the positioning accuracy of the drone, allowing it to maintain accurate flight trajectory and attitude control in complex environments or dynamically changing conditions.

[0060] Enhanced environmental adaptability and robustness: The system supports multiple flight mode options (such as manual flight, automatic flight, route flight, etc.), and has the ability to detect ground height and avoid obstacles in the front and back directions, so that the drone can better adapt to different scenarios and mission requirements. At the same time, the emergency processing module can execute the preset emergency processing process when the sensor fails or the positioning data is abnormal, ensuring that the drone can still operate safely and stably in various emergency situations.

[0061] Reduce maintenance costs and improve efficiency: Through highly integrated hardware design and optimized control algorithms, the present invention reduces system complexity and failure points, and reduces maintenance and upkeep costs. At the same time, efficient data processing capabilities and precise flight control enable drones to complete tasks more quickly, improving work efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 It is a schematic diagram of the main structure of a redundant flight control system of the present invention;

[0063] Figure 2 is a system block diagram of the redundant flight control system of the present invention;

[0064] Figure 3 For the present invention Figure 2 Specific system block diagram of the output module;

[0065] Figure 4 For the present invention Figure 1 The internal structure block diagram of the integrated control unit;

[0066] Figure 5 Schematic diagram of the method flow in the present invention.

[0067] In the figure: 1. integrated control unit; 11. inertial navigation sensor; 12. satellite positioning receiver; 13. navigation calculator; 14. power supply DC; 15. control calculator; 2. main controller; 3. input module; 4. output module; 5. communication module; 6. emergency processing unit. DETAILED DESCRIPTION

[0068] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0069] like Figure 1 - Figure 4 As shown, the present invention provides a technical solution: a redundant flight control system, comprising an integrated control unit 1, wherein the integrated control unit 1 comprises an inertial navigation sensor 11, a satellite positioning receiver 12, a navigation calculator 13, a power supply DC 14, and a control calculator 15;

[0070] At least two aviation-grade J24-H connectors are used as external interfaces of the integrated control unit 1. The number of connector cores in the integrated control unit 1 is different to prevent wrong insertion, and an airspeed meter interface is reserved to meet the subsequent airspeed measurement requirements;

[0071] Dual IMU, the dual IMU includes a high-precision IMU and a low-precision IMU, both of which operate independently and input the solution results to the integrated control unit 1, and the integrated control unit 1 selects healthy IMU posture data as control input through an internal health judgment mechanism;

[0072] A coprocessor, wherein the coprocessor is used to increase the ability of the flight control to connect to peripherals, wherein the peripherals strongly related to the flight control are connected to the integrated control unit 1, and the peripherals weakly related to the flight control are connected to the coprocessor;

[0073] RTK positioning and direction finding module, the RTK positioning and direction finding module has the ability to match the use of RTK mobile base station and network RTK;

[0074] A data fusion module, wherein the data fusion module uses a Kalman filter algorithm to fuse the dual IMU data and the RTK positioning data to improve the positioning accuracy and robustness of the UAV;

[0075] The Kalman filter algorithm continuously estimates the state of the system through two main steps: prediction and update. The following are the key formulas used in these two steps:

[0076] Prediction Steps:

[0077] State prediction equation:

[0078] hatxk∣k-1=Ax^k-1∣k-1+Buk-1

[0079] Among them, x^k|k-1 is the predicted state at time k, A is the state transfer matrix, x^k-1|k-1 is the optimal estimated state at time k-1, B is the control input matrix, and uk-1 is the control input at time k-1.

[0080] Forecast error covariance matrix:

[0081] Pk|k-1=APk-1|k-1AT+Q

[0082] Among them, Pk|k-1 is the prediction error covariance matrix at time k, Pk-1|k-1 is the estimation error covariance matrix at time k-1, and Q is the process noise covariance matrix.

[0083] Update steps:

[0084] Kalman gain:

[0085] Kk=Pk∣k-1HT(HPk∣k-1HT+R)-1

[0086] Where Kk is the Kalman gain, H is the observation matrix, and R is the observation noise covariance matrix.

[0087] State update equation:

[0088] hatxk∣k=x^k∣k-1+Kk(zk-Hx^k∣k-1)

[0089] Among them, x^k|k is the optimal estimated state at time k, and zk is the observed value at time k;

[0090] Update the error covariance matrix:

[0091] Pk|k=(I-KkH)Pk|k-1

[0092] Where Pk|k is the estimated error covariance matrix at time k, and I is the identity matrix;

[0093] The dual IMU solution also includes two sets of IMU operation health monitoring mechanisms for real-time monitoring of the health status of the IMU and transmitting the health status to the main controller 2, which selects the healthy IMU as the navigation data source. The power supply DC14 supports a power supply range of 18 to 50V, and the system has vibration and impact resistance, meeting the requirements of three-axis 10g and three-axis 20g respectively. The integrated control unit 1 also includes an emergency processing unit 6, which is used to execute corresponding emergency processing measures when sensor data is abnormal, RTK positioning data is abnormal, or joystick remote control data is abnormal, to ensure the safe flight of the UAV. The integrated control unit 1 also includes software design, which includes a gyroscope accelerometer acquisition unit, a barometer acquisition unit, a magnetometer acquisition unit, an RTK positioning data analysis module, an INS combined navigation solution unit, an AHRS solution unit, a posture control unit and a motor drive unit. Each unit works together to achieve stable flight and precise control of the UAV. The gyroscope accelerometer acquisition unit uses the SPI bus for data acquisition, and the resolutions of angular velocity and acceleration are less than 0.1deg / s and 0.1m / s respectively. 2 , and has the function of identifying the health status of data to ensure the accuracy and reliability of the collected data.

[0094] Specifically, after the system design is completed, strict testing and verification work is required to ensure the stability and reliability of the system. The test content includes but is not limited to:

[0095] Functional test: Verify whether all functions of the system are operating normally, including dual IMU switching, RTK positioning, multiple flight modes, etc.

[0096] Performance test: evaluate the system's key performance indicators such as positioning accuracy, flight stability, and response speed.

[0097] Environmental adaptability test: Test the stability and reliability of the system under different environmental conditions (such as high temperature, low temperature, strong wind, etc.).

[0098] Fault simulation test: artificially create system failures (such as disconnecting the IMU, simulating RTK signal loss, etc.) to verify the effectiveness of the emergency response mechanism.

[0099] like Figure 5 As shown, a method for using a redundant flight control system, S1, system initialization step, after the flight control system is powered on, the system is initialized, including hardware self-check, sensor calibration, and communication interface configuration;

[0100] S2, data collection step, independently collects gyroscope and accelerometer data from high-precision inertial measurement unit (IMU) and low-precision IMU, and obtains high-precision positioning data through RTK module, while collecting barometer, magnetometer and other sensor data;

[0101] S3, data health status judgment step, judging the health status of the collected sensor data to ensure the reliability and accuracy of the data;

[0102] S4, data fusion and integrated navigation solution step, using dual IMU data and RTK data for data fusion, and performing integrated navigation solution to calculate the precise position, speed and attitude of the UAV;

[0103] S5, a flight mode selection step, selecting a manual, automatic or route flight appropriate flight mode according to user needs or preset conditions;

[0104] S6, remote control and flight stick input processing step, receiving and processing input control instructions from the remote control or flight stick;

[0105] S7, posture control step, calculating the control amount according to the target posture and current posture information, and driving the motor through the PWM signal to adjust the posture and position of the UAV;

[0106] S8, emergency handling steps, monitoring the status of sensors, communications, and positioning modules. Once an abnormality is detected, the emergency handling mechanism is activated, including switching redundant sensors and autonomous return operations;

[0107] S9, data transmission and communication step, transmitting the status information and location information of the UAV to the ground station or other equipment in real time, and receiving control instructions or mission data from the ground station or other equipment.

[0108] The control method of the combined navigation is:

[0109] S41. In the case of RTK positioning module failure or poor signal, high-precision IMU data is used for short-term inertial navigation to ensure that the drone can still maintain a certain navigation accuracy when it loses external positioning support;

[0110] S42. Post-process the RTK positioning data through software algorithms to further eliminate positioning errors and improve positioning accuracy during long-term flights.

[0111] Preferably, the specific control method for selecting the flight mode is:

[0112] Manual flight mode, control the drone flight according to the real-time input instructions of the remote controller or flight joystick;

[0113] S51, automatic flight mode, autonomous navigation flight according to the preset flight path and altitude;

[0114] S52, route flight mode, combines waypoint planning and RTK positioning data to achieve precise route tracking flight;

[0115] S53, obstacle avoidance flight mode, real-time monitoring and obstacle avoidance through integrated forward and backward obstacle avoidance sensors;

[0116] The following user interaction and monitoring steps are also included:

[0117] S10, transmitting the real-time flight status, sensor data and flight video of the UAV to a ground station or mobile device through a wireless communication module for real-time monitoring by an operator;

[0118] S11. Provide a graphical user interface (GUI) that allows operators to set flight parameters, view flight logs, and adjust flight strategies on a ground station or mobile device;

[0119] S12, integrated voice prompt function, which issues voice warnings or instructions to the operator during specific flight phases or abnormal situations.

[0120] Specifically, the system collects data from various sensors in real time and performs preprocessing:

[0121] IMU data acquisition: Gyroscope and accelerometer data are collected from high-precision and low-precision IMUs via the SPI bus.

[0122] Barometer data collection: Collect air pressure data from the barometer via SPI and convert it into altitude information.

[0123] Magnetometer data acquisition: Collect geomagnetic data from the magnetometer via the CAN bus.

[0124] RTK positioning data collection: Receive positioning data from the RTK module through the TTL serial port.

[0125] Identify the health status and determine the availability of all collected data to ensure the accuracy and validity of the data;

[0126] According to the position information and ground instructions sent by the navigation software, position-attitude-angular velocity series PID control is performed:

[0127] Set target position: Set the target position, attitude and angular velocity of the drone according to the flight mission.

[0128] Calculate the control amount: According to the deviation between the current posture and the target posture, the control amount is calculated by the PID controller.

[0129] Output control signal: convert the control quantity into PWM signal and output it to the motor drive unit to control the flight of the drone.

[0130] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A redundant flight control system, characterized in that: The invention comprises an integrated control unit (1), wherein the integrated control unit (1) comprises an inertial navigation sensor (11), a satellite positioning receiver (12), a navigation calculator (13), a power supply DC (14), and a control calculator (15); At least two aviation-grade J24-H connectors are used as external interfaces of the integrated control unit (1), the number of connector cores in the integrated control unit (1) is different to prevent wrong insertion, and an airspeed meter interface is reserved to meet subsequent airspeed measurement requirements; A dual IMU, wherein the dual IMU includes a high-precision IMU and a low-precision IMU, the two operate independently and input the solution results to an integrated control unit (1), and the integrated control unit (1) selects healthy IMU posture data as control input through an internal health judgment mechanism; A coprocessor, the coprocessor is used to increase the ability of the flight control to interface with peripherals, wherein the peripherals strongly related to the flight control are connected to the integrated control unit (1), and the peripherals weakly related to the flight control are connected to the coprocessor; RTK positioning and direction finding module, the RTK positioning and direction finding module has the ability to match the use of RTK mobile base station and network RTK; The data fusion module uses a Kalman filter algorithm to fuse the dual IMU data and the RTK positioning data to improve the positioning accuracy and robustness of the UAV.

2. A redundant flight control system according to claim 1, characterized in that: The dual IMU solution also includes two sets of IMU operation health monitoring mechanisms, which are used to monitor the health status of the IMUs in real time and transmit the health status to the main controller (2), and the main controller (2) selects the healthy IMU as the navigation data source.

3. A redundant flight control system according to claim 1, characterized in that: The power supply DC (14) supports a power supply range of 18 to 50 V, and the system has anti-vibration and anti-impact capabilities, meeting the requirements of three-axis 10g and three-axis 20g respectively. The integrated control unit (1) also includes an emergency processing unit (6) for executing corresponding emergency processing measures when sensor data is abnormal, RTK positioning data is abnormal, or joystick remote control data is abnormal, so as to ensure the safe flight of the drone.

4. A redundant flight control system according to claim 1, characterized in that: The integrated control unit (1) further comprises a software design, wherein the software design comprises a gyroscope accelerometer acquisition unit, a barometer acquisition unit, a magnetometer acquisition unit, an RTK positioning data analysis module, an INS integrated navigation solution unit, an AHRS solution unit, a posture control unit and a motor drive unit, wherein the units work in coordination to achieve stable flight and precise control of the UAV.

5. A redundant flight control system according to claim 4, characterized in that: The gyro-accelerometer acquisition unit uses the SPI bus for data acquisition, and the resolution of angular velocity and acceleration is less than 0.1 deg / s and 0.1 m / s respectively. 2 , and has the function of identifying the health status of data to ensure the accuracy and reliability of the collected data.

6. A method for using a redundant flight control system, characterized in that: The following steps are involved: S1, system initialization step, after the flight control system is powered on, the system is initialized, including hardware self-test, sensor calibration, and communication interface configuration; S2, data collection step, independently collects gyroscope and accelerometer data from high-precision inertial measurement unit (IMU) and low-precision IMU, and obtains high-precision positioning data through RTK module, while collecting barometer, magnetometer and other sensor data; S3, data health status judgment step, judging the health status of the collected sensor data to ensure the reliability and accuracy of the data; S4, data fusion and integrated navigation solution step, using dual IMU data and RTK data for data fusion and integrated navigation solution to calculate the precise position, speed and attitude of the UAV; S5, a flight mode selection step, selecting a manual, automatic or route flight appropriate flight mode according to user needs or preset conditions; S6, remote control and flight stick input processing step, receiving and processing input control instructions from the remote control or flight stick; S7, posture control step, calculating the control amount according to the target posture and current posture information, and driving the motor through the PWM signal to adjust the posture and position of the UAV; S8, emergency handling steps, monitoring the status of sensors, communications, and positioning modules. Once an abnormality is detected, the emergency handling mechanism is activated, including switching redundant sensors and autonomous return operations; S9, data transmission and communication step, transmitting the status information and location information of the UAV to the ground station or other equipment in real time, and receiving control instructions or mission data from the ground station or other equipment.

7. The method for using a redundant flight control system according to claim 6, characterized in that: The control method of the combined navigation is: S41. In the case of RTK positioning module failure or poor signal, high-precision IMU data is used for short-term inertial navigation to ensure that the drone can still maintain a certain navigation accuracy when it loses external positioning support; S42. Post-process the RTK positioning data through software algorithms to further eliminate positioning errors and improve positioning accuracy during long-term flights.

8. The method for using a redundant flight control system according to claim 6, characterized in that: The specific control method for selecting the flight mode is: Manual flight mode, control the drone flight according to the real-time input instructions of the remote controller or flight joystick; S51, automatic flight mode, autonomous navigation flight according to the preset flight path and altitude; S52, route flight mode, combines waypoint planning and RTK positioning data to achieve precise route tracking flight; S53, obstacle avoidance flight mode, monitors and avoids obstacles in real time through integrated forward and backward obstacle avoidance sensors.

9. The method for using a redundant flight control system according to claim 6, characterized in that: The following user interaction and monitoring steps are also included: S10, transmitting the real-time flight status, sensor data and flight video of the UAV to a ground station or mobile device through a wireless communication module for real-time monitoring by an operator; S11. Provide a graphical user interface (GUI) that allows operators to set flight parameters, view flight logs, and adjust flight strategies on a ground station or mobile device; S12, integrated voice prompt function, which issues voice warnings or instructions to the operator during specific flight phases or abnormal situations.

Images