WO2020107310A1 - 无人飞行器控制方法、控制装置及无人飞行器 - Google Patents

无人飞行器控制方法、控制装置及无人飞行器 Download PDF

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Publication number
WO2020107310A1
WO2020107310A1 PCT/CN2018/118099 CN2018118099W WO2020107310A1 WO 2020107310 A1 WO2020107310 A1 WO 2020107310A1 CN 2018118099 W CN2018118099 W CN 2018118099W WO 2020107310 A1 WO2020107310 A1 WO 2020107310A1
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WIPO (PCT)
Prior art keywords
uav
unmanned aerial
aerial vehicle
data
center
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PCT/CN2018/118099
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English (en)
French (fr)
Inventor
王凯
高翔
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SZ DJI Technology Co Ltd
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SZ DJI Technology Co Ltd
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Priority to PCT/CN2018/118099 priority Critical patent/WO2020107310A1/zh
Priority to CN201880042455.6A priority patent/CN110832418A/zh
Priority to US17/605,509 priority patent/US11920999B2/en
Publication of WO2020107310A1 publication Critical patent/WO2020107310A1/zh
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/08—Control of attitude, i.e. control of roll, pitch, or yaw
    • G05D1/0808—Control of attitude, i.e. control of roll, pitch, or yaw specially adapted for aircraft
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M1/00—Testing static or dynamic balance of machines or structures
    • G01M1/12—Static balancing; Determining position of centre of gravity
    • G01M1/122—Determining position of centre of gravity
    • G01M1/125—Determining position of centre of gravity of aircraft
    • G01M1/127—Determining position of centre of gravity of aircraft during the flight
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64C—AEROPLANES; HELICOPTERS
    • B64C17/00—Aircraft stabilisation not otherwise provided for
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/08—Control of attitude, i.e. control of roll, pitch, or yaw
    • G05D1/0808—Control of attitude, i.e. control of roll, pitch, or yaw specially adapted for aircraft
    • G05D1/0816—Control of attitude, i.e. control of roll, pitch, or yaw specially adapted for aircraft to ensure stability
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/10—Simultaneous control of position or course in three dimensions
    • G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/40—Control within particular dimensions
    • G05D1/49—Control of attitude, i.e. control of roll, pitch or yaw
    • G05D1/495—Control of attitude, i.e. control of roll, pitch or yaw to ensure stability
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/60—Intended control result
    • G05D1/606—Compensating for or utilising external environmental conditions, e.g. wind or water currents
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/60—Intended control result
    • G05D1/617—Safety or protection, e.g. defining protection zones around obstacles or avoiding hazards
    • G05D1/622—Obstacle avoidance
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U10/00—Type of UAV
    • B64U10/10—Rotorcrafts
    • B64U10/13—Flying platforms
    • B64U10/14—Flying platforms with four distinct rotor axes, e.g. quadcopters
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U2101/00—UAVs specially adapted for particular uses or applications
    • B64U2101/60—UAVs specially adapted for particular uses or applications for transporting passengers; for transporting goods other than weapons
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U2201/00—UAVs characterised by their flight controls
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U2201/00—UAVs characterised by their flight controls
    • B64U2201/20—Remote controls

Definitions

  • the present application relates to the technical field of aircraft, and in particular, to an unmanned aerial vehicle control method, an unmanned aerial vehicle control device, an unmanned aerial vehicle, an unmanned aerial vehicle system, and a computer storage medium.
  • the unmanned aerial vehicle when the load change causes the center of gravity of the entire unmanned aerial vehicle system to move more than a certain degree from the standard state, the unmanned aerial vehicle often has a "take-off nod" problem when the posture takes off from the ground. This phenomenon will also make the unmanned aircraft unmanned. After the aircraft leaves the ground, it will move a short distance relative to the take-off point, which may hit the surrounding objects, the crowd, or even the pilot himself.
  • This application aims to solve at least one of the technical problems existing in the prior art or related technologies.
  • the first aspect of the present application is to propose an unmanned aerial vehicle control method.
  • the second aspect of the present application is to propose an unmanned aerial vehicle control device.
  • the third aspect of this application is to propose an unmanned aerial vehicle.
  • the fourth aspect of this application is to propose a system for an unmanned aerial vehicle.
  • the fifth aspect of the present application is to propose a computer storage medium.
  • a method for controlling an unmanned aerial vehicle which includes: acquiring target flight data and current flight data, and determining the control state quantity based on the target flight data and current flight data; and according to Control the state quantity to calibrate the center of gravity of the UAV.
  • target flight data and current flight data of the unmanned aerial vehicle are acquired, and during the flight of the unmanned aerial vehicle, at least four control state quantities are given according to the target flight data and the current flight data: Total pull command, yaw axis torque command, pitch axis torque command, roll axis torque command, the above four control state quantities correspond to the force and torque received by the unmanned aerial vehicle due to each motor, that is, total pull force, yaw axis Torque, pitch axis torque, roll axis torque.
  • the center of gravity of the UAV is calibrated according to the control state quantity, that is, the deviation between the center of gravity of the UAV and the center of tension of the UAV is obtained.
  • the deviation of the actual position of the center of gravity of the current unmanned aerial vehicle from the standard position can be obtained, so that the degradation of flight quality caused by the deviation of the position of the center of gravity can be eliminated according to this deviation. It is simple, convenient, and operable, and it can greatly improve the load adaptability of unmanned aerial vehicles.
  • an unmanned aerial vehicle control device including: a processor for acquiring target flight data and current flight data, determining the control state quantity according to the target flight data and current flight data, and according to Control the state quantity to calibrate the center of gravity of the UAV.
  • the processor obtains target flight data and current flight data of the unmanned aerial vehicle, and during the flight of the unmanned aerial vehicle, at least four control states are given according to the target flight data and the current flight data Amount: total tension command, yaw axis torque command, pitch axis torque command, roll axis torque command, the above four control state quantities correspond to the force and torque received by the unmanned aerial vehicle due to each motor, that is, the total pull force, deviation Yaw axis torque, pitch axis torque, roll axis torque.
  • the processor performs calibration of the center of gravity of the unmanned aerial vehicle according to the control state quantity, that is, obtaining the deviation of the center of gravity of the unmanned aerial vehicle from the center of tension of the unmanned aerial vehicle.
  • the deviation of the actual position of the center of gravity of the current unmanned aerial vehicle from the standard position can be obtained through the unmanned aerial vehicle control device, so that the degradation of flight quality caused by the deviation of the position of the center of gravity can be eliminated according to this deviation.
  • the technical solution is simple and convenient for the user, has strong operability, and can improve the load adaptation capability of the unmanned aerial vehicle to a greater extent.
  • an unmanned aerial vehicle including a power device, and further comprising: a controller for acquiring target flight data and current flight data, and determining the control state according to the target flight data and current flight data And the center of gravity calibration of the UAV according to the control state quantity.
  • the controller obtains target flight data and current flight data of the unmanned aerial vehicle, and during the flight of the unmanned aerial vehicle, at least four control state quantities are given according to the target flight data and the current flight data: Total pull command, yaw axis torque command, pitch axis torque command, roll axis torque command, the above four control state quantities correspond to the force and torque received by the unmanned aerial vehicle due to each motor, that is, total pull force, yaw axis Torque, pitch axis torque, roll axis torque.
  • the controller performs calibration of the center of gravity of the unmanned aerial vehicle according to the control state quantity, that is, the deviation of the center of gravity of the unmanned aerial vehicle from the center of tension of the unmanned aerial vehicle is obtained.
  • the deviation of the actual position of the center of gravity of the current unmanned aerial vehicle from the standard position can be obtained through the unmanned aerial vehicle, so that the degradation of flight quality caused by the deviation of the position of the center of gravity can be eliminated according to this deviation. It is simple and convenient for the user, has strong operability, and can improve the load adaptability of the UAV to a greater extent.
  • a system for an unmanned aerial vehicle which includes: a control terminal for sending a center of gravity calibration command to the unmanned aerial vehicle; an unmanned aerial vehicle for center of gravity calibration according to the center of gravity calibration instruction to obtain Calibration results.
  • the system of the unmanned aerial vehicle proposed in this application includes a control terminal and an unmanned aerial vehicle.
  • the user When the user needs to use the unmanned aerial vehicle for loading, the user sends a center of gravity calibration command to the unmanned aerial vehicle through the control terminal, and the unmanned aerial vehicle receives the center of gravity calibration command.
  • the calibration result can be obtained by implementing the center of gravity calibration, and the calibration result may include: a successful calibration, a failed calibration, and calibration data.
  • a computer storage medium in which program instructions are stored in the computer storage medium.
  • the program instructions are used to achieve: acquiring target flight data and current flight data, and according to the target flight data and current flight data Determine the control state quantity; and calibrate the center of gravity of the UAV according to the control state quantity.
  • the computer storage medium proposed in this application stores program instructions, which are used to realize: acquiring target flight data and current flight data of the unmanned aerial vehicle, and in the process of controlling the flight of the unmanned aircraft, according to the target flight data and the current flight data At least four control state variables: total tension command, yaw axis torque command, pitch axis torque command, and roll axis torque command.
  • the above four control state variables correspond to the force and torque received by the UAV due to each motor. It is total tension, yaw axis torque, pitch axis torque, and roll axis torque.
  • the center of gravity of the UAV is calibrated according to the control state quantity, that is, the deviation between the center of gravity of the UAV and the center of tension of the UAV is obtained.
  • the deviation of the actual position of the center of gravity of the current unmanned aerial vehicle from the standard position can be obtained, so that the degradation of flight quality caused by the deviation of the position of the center of gravity can be eliminated according to this deviation. It is simple, convenient, and operable, and it can greatly improve the load adaptability of unmanned aerial vehicles.
  • FIG. 1 shows a schematic flowchart of an unmanned aerial vehicle control method according to an embodiment of the present application
  • FIG. 2 shows a schematic diagram of a gravity center offset of an unmanned aerial vehicle according to an embodiment of the present application
  • FIG. 3 shows a force analysis diagram of a single channel in the case where the center of gravity is offset according to an embodiment of the present application
  • FIG. 4 is a schematic diagram of an unmanned aerial vehicle control device according to an embodiment of the present application.
  • FIG. 5 shows a schematic diagram of an unmanned aerial vehicle according to an embodiment of the present application
  • FIG. 6 shows a schematic diagram of a flight control system of an unmanned aerial vehicle according to an embodiment of the present application
  • FIG. 7 shows a schematic diagram of a system of an unmanned aerial vehicle according to an embodiment of the present application.
  • FIG. 8 shows a schematic diagram of interactive implementation of a center of gravity calibration operation according to an embodiment of the present application.
  • FIG. 1 shows a schematic flowchart of a method for controlling an unmanned aerial vehicle according to an embodiment of the present application. Among them, the method includes:
  • Step 102 Obtain target flight data and current flight data, and determine the control state quantity according to the target flight data and current flight data.
  • the control state quantity includes at least four control state quantities: total tension command, yaw axis torque command, pitch axis torque command, and roll axis torque command.
  • the target flight data and current flight data of the unmanned aerial vehicle are obtained, and at least four control state quantities are given according to the target flight data and the current flight data during the flight of the unmanned aerial vehicle: total pull command, yaw axis torque Command, pitch axis torque command, roll axis torque command.
  • the unmanned aerial vehicle includes a power device, and the power device may be, for example, at least one electric motor.
  • the above-mentioned four control state quantities correspond to the forces and torques received by the unmanned aerial vehicle due to the respective electric motors, that is, the total pulling force and the yaw axis torque , Pitch axis torque, roll axis torque.
  • step 104 the center of gravity of the UAV is calibrated according to the control state quantity.
  • the center of gravity of the UAV is calibrated according to the control state quantity acquired in step 102. Further, the deviation of the center of gravity of the UAV from the center of tension of the UAV is obtained according to the control state quantity.
  • step 104 the step of calibrating the center of gravity of the unmanned aerial vehicle according to the control state quantity includes: calculating the offset data of the center of gravity of the unmanned aerial vehicle and the tension center of the unmanned aerial vehicle according to the control state quantity.
  • the offset data includes one or a combination of the following: offset position, offset mass, offset force, offset torque.
  • the offset data of the unmanned aerial vehicle's center of gravity and the unmanned aerial vehicle's tension center is calculated according to the control state quantity, that is, the deviation of the actual center of gravity position of the unmanned aerial vehicle from the standard position.
  • the offset data may be an offset Position, offset quality, offset force, offset torque and other data.
  • the flight controller of the UAV will continuously give at least four control state quantities during the flight of the UAV: total tension command T c , yaw axis torque command ⁇ zc , pitch axis Torque command ⁇ yc and roll axis torque command ⁇ xc , these four control state quantities correspond to the forces and moments that the drone will eventually receive due to the speed of each motor, that is, the total pulling force T and the yaw axis torque ⁇ z , Pitch axis torque ⁇ y , Roll axis torque ⁇ x .
  • the UAV's flight control system can use the above formula to calculate the horizontal position of the center of gravity of the UAV relative to the center of the paddle surface under the current mounting, that is, the offset distance.
  • the offset data is not limited to the offset distance.
  • the offset data may include one or a combination of the following: offset position, offset mass, offset force, offset torque.
  • the estimated center of gravity offset is not necessarily the true offset distance, but the control compensation value from the vertical channel to each rotation channel, such as offset mass, offset force, offset Set torque and other data. This embodiment is only an exemplary description and is not limited herein.
  • the method further includes: storing bias data.
  • the offset data can be saved to non-volatile memory such as Flash, EEPROM, etc.
  • non-volatile memory such as Flash, EEPROM, etc.
  • the UAV is loaded every time it is powered on
  • the offset data can be feedforwardly controlled by the unmanned aerial vehicle according to the offset data every time it takes off, so that the equivalent pulling center also acts on the actual center of gravity.
  • advance compensation can eliminate the aforementioned "take-off nod" problem.
  • it further includes: generating a control component based on the bias data, and controlling the power unit of the UAV according to the control component.
  • a control component is generated based on the offset data, and the power device of the UAV is controlled according to the control component, so as to reduce the offset data, make the UAV stable flight, and improve flight quality.
  • the flight control system can more accurately distribute the control amount of each control channel and reduce the amount of coupling between the channels.
  • the control system of an unmanned aerial vehicle can take forward feedforward control according to the stored bias data every time it takes off, and accurately distribute the pulling force of each power device, so that the equivalent pulling force center also acts on the actual center of gravity. Compensation can eliminate the aforementioned "take-off and nod" problem.
  • the tension of each power device is accurately distributed, so that the equivalent tension center also acts on the actual center of gravity to ensure the flight quality.
  • the method further includes: comparing the offset data with a preset threshold, and determining whether the load installation position of the UAV exceeds the specified installation range according to the comparison result.
  • the step of determining whether the load installation position of the UAV exceeds the specified installation range according to the comparison result includes: when the comparison result is that the offset data is greater than or equal to a preset threshold, determining the load installation of the UAV The position exceeds the specified installation range; when the comparison result is that the offset data is less than the preset threshold, it is determined that the load installation position of the UAV does not exceed the specified installation range.
  • whether the load installation position of the UAV exceeds the specified installation range may be determined according to the comparison result according to other suitable preset rules; for example, when the comparison result is that the offset data is greater than a preset threshold In the case of unmanned aerial vehicles, it is determined that the load installation position of the UAV exceeds the specified installation range; when the comparison result is that the offset data is less than or equal to the preset threshold, it is determined that the load installation position of the unmanned aircraft does not exceed the specified installation range. Not limited.
  • the user may be informed whether the installation position of the load exceeds the preset threshold by comparing with the preset threshold (ie, the offset range) supported by the UAV.
  • the unmanned aerial vehicle can detect whether the load installation is supported or whether the load installation location is reasonable.
  • the method further includes: recording the control state quantity within the preset time period, and performing the center of gravity calibration of the UAV according to the control state quantity within the preset time period.
  • each control state quantity output to eliminate the center-of-gravity offset is recorded for a period of time, and after calculating the control state quantity for a period of time, the random error of the control state quantity can be eliminated by averaging, etc. Eliminate the interference caused by wind or aircraft vibration, and then calculate the offset data to improve the accuracy of calculating the offset data.
  • the method before the step of calibrating the center of gravity of the UAV according to the control state quantity, the method further includes: acquiring the state data of the UAV, and judging whether the state data meets the center of gravity calibration condition; when the state data meets the center of gravity calibration condition Enter the step of calibrating the center of gravity of the UAV according to the control state quantity.
  • the state data includes one or a combination of the following: positioning data, image data, posture data, acceleration data, and angular velocity data.
  • the center of gravity calibration condition includes the unmanned aerial vehicle being in a balanced state.
  • the center of gravity calibration condition further includes that the inertial measurement unit of the UAV has performed data calibration.
  • the center of gravity calibration condition is whether the UAV is in a balanced state, only when the UAV is in a balanced state
  • the center-of-gravity calibration performed at the time is accurate, and the balance state includes a mode in which the horizontal position is stationary during the course rotation in the hovering mode and the positioning mode.
  • the gravity center calibration condition can also be that the inertial measurement unit of the unmanned aerial vehicle has performed data calibration, and the data obtained by the inertial measurement unit are accurate data on the basis of the unmanned aerial vehicle being in a balanced state, thereby improving the accuracy of the gravity center calibration.
  • the method further includes: acquiring surrounding environment data of the UAV, and judging whether the surrounding environment data meets the gravity center calibration conditions; when the surrounding environment data meets the gravity center calibration conditions, entering the unmanned aerial vehicle according to the control state quantity Steps for the calibration of the center of gravity.
  • the ambient data includes ambient airflow or ambient wind speed.
  • the center of gravity calibration condition includes that the wind speed of the environment where the UAV is located is less than the preset wind speed.
  • the surrounding environment data may be obtained according to the attitude of the drone, or may be obtained based on other external sensors, such as an anemometer or information obtained from a cloud weather station.
  • the surrounding environment is a windless environment, it will not cause external forces to interfere with the air flow of the unmanned aerial vehicle, so as to avoid interference in the calibration of the center of gravity of the unmanned aerial vehicle.
  • the gravity center calibration conditions may include:
  • Unmanned aerial vehicle has positioning hovering ability: In the above algorithm, it is assumed that the unmanned aerial vehicle is already in a balanced state, that is, the above-mentioned derivation process can only be established when the unmanned aerial vehicle is in a stationary state, because It is very difficult to rely on people to maintain the balance of multi-wing unmanned aerial vehicles. Therefore, it is required that the unmanned aerial vehicles must have positioning hovering capability without manual operation. Further, whether the unmanned aerial vehicle is in a balanced state can be determined by positioning data, image data, attitude data, etc.
  • the position information of the unmanned aerial vehicle can be obtained through a positioning device (such as global positioning system GPS, carrier phase differential technology RTK, etc.) ,
  • a positioning device such as global positioning system GPS, carrier phase differential technology RTK, etc.
  • the UAV can be considered to be in a hovering state; or multiple images of the surrounding environment of the unmanned aerial vehicle can be obtained through a visual sensor within a certain time interval.
  • the UAV can be considered to be in a hovering state; or the acceleration and speed information of the UAV can also be obtained through the inertial measurement unit (IMU).
  • IMU inertial measurement unit
  • the unmanned aerial vehicle can be considered to be in a hovering state.
  • one or more of the above judgment methods can be used to judge the data fusion to improve the judgment. Accuracy.
  • the surrounding airflow is stable and no wind:
  • the unmanned aerial vehicle will also be subject to the external force caused by the interference of the airflow, so that even if the unmanned aerial vehicle is in the positioning hover state, due to the introduction of new Ignoring the external force, the above formula derivation will also be invalid, so the environment that requires calibration must be a calm air environment without wind. It can be judged whether the UAV is in a windless environment based on the unmanned aerial vehicle's tilt angle data, etc., and can be obtained by setting a wind collecting device.
  • the IMU (Inertial Measurement Unit) calibration of the UAV is correct: the IMU must have been calibrated to eliminate the steady-state error due to temperature, etc., otherwise the error will be caused by the center of gravity offset by the above algorithm. Now common unmanned aerial vehicles are equipped with IMU calibration function, it is recommended to re-calibrate the IMU before the center of gravity calibration.
  • the distance from the UAV to the ground is greater than the preset distance. In this embodiment, it is ensured that the unmanned aerial vehicle is at a preset distance from the ground, for example, having a height of more than 2 meters from the ground, so as to reduce the influence of turbulence caused by the ground.
  • the calibration is stopped, and a first instruction is sent to the control terminal.
  • the first instruction includes the reason for not satisfying the gravity center calibration condition and the adjustment suggestion information.
  • the calibration when the calibration fails, the calibration is stopped, and a second instruction is sent to the control terminal.
  • the second instruction includes the cause of the calibration failure.
  • the deviation of the actual position of the center of gravity of the current unmanned aerial vehicle from the standard position can be obtained, so that the degradation of flight quality caused by the deviation of the position of the center of gravity can be eliminated according to this deviation.
  • Simple and convenient, strong maneuverability, and can improve the load adaptation ability of the unmanned aerial vehicle to a greater extent users can adapt their own load to the unmanned aerial vehicle frame without worrying about the deterioration of flight quality, making the unmanned aerial vehicle The ability to support third-party loads has been significantly improved.
  • FIG. 4 shows a schematic diagram of an unmanned aerial vehicle control device 40 according to an embodiment of the present application.
  • the control device 40 includes:
  • the processor 402 is configured to acquire target flight data and current flight data, determine the control state quantity according to the target flight data and current flight data, and perform the center of gravity calibration of the unmanned aerial vehicle according to the control state quantity.
  • the control state quantity includes at least four control state quantities: total tension command, yaw axis torque command, pitch axis torque command, and roll axis torque command.
  • the target flight data and current flight data of the unmanned aerial vehicle are obtained, and at least four control state quantities are given according to the target flight data and the current flight data during the flight of the unmanned aerial vehicle: total pull command, yaw axis torque Command, pitch axis torque command, roll axis torque command.
  • the unmanned aerial vehicle includes a power device, and the power device may be, for example, at least one electric motor.
  • the above-mentioned four control state quantities correspond to the force and torque received by the unmanned aerial vehicle due to the respective electric motors, that is, the total pulling force and the yaw axis torque , Pitch axis torque, roll axis torque. Further, the center of gravity of the UAV is calibrated according to the control state quantity. Further, the deviation of the center of gravity of the UAV from the center of tension of the UAV is obtained according to the control state quantity.
  • the processor 402 may include one or more microprocessors.
  • the processor 402 performing the calibration of the center of gravity of the UAV according to the control state quantity includes calculating offset data between the center of gravity of the UAV and the center of tension of the UAV according to the control state quantity.
  • the offset data includes one or a combination of the following: offset position, offset mass, offset force, offset torque.
  • the offset data of the unmanned aerial vehicle's center of gravity and the unmanned aerial vehicle's tension center is calculated according to the control state quantity, that is, the deviation of the actual center of gravity position of the unmanned aerial vehicle from the standard position.
  • the offset data may be an offset Position, offset quality, offset force, offset torque and other data.
  • the flight controller of the UAV will continuously give at least four control state quantities during the flight of the UAV: total tension command T c , yaw axis torque command ⁇ zc , pitch axis Torque command ⁇ yc and roll axis torque command ⁇ xc , these four control state quantities correspond to the forces and moments that the drone will eventually receive due to the speed of each motor, that is, the total pulling force T and the yaw axis torque ⁇ z , Pitch axis torque ⁇ y , Roll axis torque ⁇ x .
  • the UAV's flight control system can use the above formula to calculate the horizontal position of the center of gravity of the UAV relative to the center of the paddle surface under the current mounting, that is, the offset distance.
  • the offset data is not limited to the offset distance.
  • the offset data may include one or a combination of the following: offset position, offset mass, offset force, offset torque.
  • the estimated center of gravity offset is not necessarily the true offset distance, but the control compensation value from the vertical channel to each rotation channel, such as offset mass, offset force, offset Set torque and other data. This embodiment is only an exemplary description and is not limited herein.
  • it further includes a memory 404 for storing bias data.
  • the offset data can be saved to non-volatile memory such as Flash, EEPROM, etc.
  • non-volatile memory such as Flash, EEPROM, etc.
  • the UAV is loaded every time it is powered on
  • the offset data can be feedforwardly controlled by the unmanned aerial vehicle according to the offset data every time it takes off, so that the equivalent pulling center also acts on the actual center of gravity.
  • Such advance compensation can eliminate the aforementioned "take-off nod" problem.
  • the memory 404 may be a serial memory, or a parallel memory.
  • the memory 404 may be a RAM memory, or a ROM memory.
  • the processor 402 is further configured to generate a control component based on the bias data, and control the power unit of the UAV according to the control component.
  • a control component is generated based on the offset data, and the power device of the UAV is controlled according to the control component, so as to reduce the offset data, make the UAV stable flight, and improve flight quality.
  • the flight control system can more accurately distribute the control amount of each control channel and reduce the amount of coupling between the channels.
  • the control system of an unmanned aerial vehicle can take forward feedforward control according to the stored bias data every time it takes off, and accurately distribute the pulling force of each power device, so that the equivalent pulling force center also acts on the actual center of gravity. Compensation can eliminate the aforementioned "take-off and nod" problem.
  • the tension of each power device is accurately distributed, so that the equivalent tension center also acts on the actual center of gravity to ensure the flight quality.
  • the processor 402 is further configured to compare the offset data with a preset threshold, and determine whether the load installation location of the UAV exceeds the specified installation range according to the comparison result.
  • the processor 402 determines whether the load installation position of the unmanned aerial vehicle exceeds the specified installation range according to the comparison result includes: when the comparison result is that the offset data is greater than or equal to a preset threshold, determining the load installation of the unmanned aerial vehicle The position exceeds the specified installation range. If the result of the comparison is that the offset data is less than the preset threshold, it is determined that the load installation position of the UAV does not exceed the specified installation range.
  • whether the load installation position of the UAV exceeds the specified installation range may be determined according to the comparison result according to other suitable preset rules; for example, when the comparison result is that the offset data is greater than a preset threshold In the case of unmanned aerial vehicles, it is determined that the load installation position of the UAV exceeds the specified installation range; when the comparison result is that the offset data is less than or equal to the preset threshold, it is determined that the load installation position of the unmanned aircraft does not exceed the specified installation range. Not limited.
  • the user may be informed whether the installation position of the load exceeds the preset threshold by comparing with the preset threshold (ie, the offset range) supported by the UAV.
  • the unmanned aerial vehicle can detect whether the load installation is supported or whether the load installation location is reasonable.
  • the processor 402 is further configured to record the control state quantity within the preset time period, and perform the gravity center calibration of the UAV according to the control state quantity within the preset time period.
  • each control state quantity output to eliminate the center-of-gravity offset is recorded for a period of time, and after calculating the control state quantity for a period of time, the random error of the control state quantity can be eliminated by averaging, etc. Eliminate the interference caused by wind or aircraft vibration, and then calculate the offset data to improve the accuracy of calculating the offset data.
  • the processor 402 is further used to acquire the status data of the UAV and determine whether the status data meets the conditions of the center of gravity calibration. When the status data meets the conditions of the center of gravity calibration, perform the center of gravity calibration of the UAV according to the control state quantity .
  • the state data includes one or a combination of the following: positioning data, image data, posture data, acceleration data, and angular velocity data.
  • the center of gravity calibration condition includes the unmanned aerial vehicle being in a balanced state.
  • the center of gravity calibration condition further includes that the inertial measurement unit of the UAV has performed data calibration.
  • the center of gravity calibration condition is whether the UAV is in a balanced state, only when the UAV is in a balanced state
  • the center-of-gravity calibration performed at the time is accurate, and the balance state includes a mode in which the horizontal position is stationary during the course rotation in the hovering mode and the positioning mode.
  • the gravity center calibration condition can also be that the inertial measurement unit of the unmanned aerial vehicle has performed data calibration, and the data obtained by the inertial measurement unit are accurate data on the basis of the unmanned aerial vehicle being in a balanced state, thereby improving the accuracy of the gravity center calibration.
  • the processor 402 is further used to obtain the surrounding environment data of the unmanned aerial vehicle, and determine whether the surrounding environment data meets the gravity center calibration conditions; when the surrounding environment data meets the gravity center calibration conditions, enter according to the control state quantity Steps to calibrate the center of gravity of UAV.
  • the ambient data includes ambient airflow or ambient wind speed.
  • the center of gravity calibration condition includes that the wind speed of the environment where the UAV is located is less than the preset wind speed.
  • the surrounding environment data may be obtained according to the attitude of the drone, or may be obtained based on other external sensors, such as an anemometer or information obtained from a cloud weather station.
  • the surrounding environment is a windless environment, it will not bring external forces that interfere with the airflow of the unmanned aerial vehicle, and avoid interference in the calibration of the center of gravity of the unmanned aerial vehicle.
  • the gravity center calibration conditions may include:
  • Unmanned aerial vehicle has positioning hovering ability: In the above algorithm, it is assumed that the unmanned aerial vehicle is already in a balanced state, that is, the above-mentioned derivation process can only be established when the unmanned aerial vehicle is in a stationary state, because It is very difficult to rely on people to maintain the balance of multi-wing unmanned aerial vehicles. Therefore, it is required that the unmanned aerial vehicles must have positioning hovering capability without manual operation. Further, whether the unmanned aerial vehicle is in a balanced state can be determined by positioning data, image data, attitude data, etc.
  • the position information of the unmanned aerial vehicle can be obtained through a positioning device (such as global positioning system GPS, carrier phase differential technology RTK, etc.) ,
  • a positioning device such as global positioning system GPS, carrier phase differential technology RTK, etc.
  • the UAV can be considered to be in a hovering state; or multiple images of the surrounding environment of the unmanned aerial vehicle can be obtained through a visual sensor within a certain time interval.
  • the UAV can be considered to be in a hovering state; or the acceleration and speed information of the UAV can also be obtained through the inertial measurement unit (IMU).
  • IMU inertial measurement unit
  • the unmanned aerial vehicle can be considered to be in a hovering state.
  • one or more of the above judgment methods can be used to judge the data fusion to improve the judgment. Accuracy.
  • the surrounding airflow is stable and no wind:
  • the unmanned aerial vehicle will also be subject to the external force caused by the interference of the airflow, so that even if the unmanned aerial vehicle is in the positioning hover state, due to the introduction of new Ignoring the external force, the above formula derivation will also be invalid, so the environment that requires calibration must be a calm air environment without wind. It can be judged whether the UAV is in a windless environment based on the unmanned aerial vehicle's tilt angle data, etc., and can be obtained by setting a wind collecting device.
  • the IMU (Inertial Measurement Unit) calibration of the UAV is correct: the IMU must have been calibrated to eliminate the steady-state error due to temperature, etc., otherwise the error will be caused by the center of gravity offset by the above algorithm. Now common unmanned aerial vehicles are equipped with IMU calibration function, it is recommended to re-calibrate the IMU before the center of gravity calibration.
  • the distance from the UAV to the ground is greater than the preset distance. In this embodiment, it is ensured that the unmanned aerial vehicle is at a preset distance from the ground, for example, having a height of more than 2 meters from the ground, so as to reduce the influence of turbulence caused by the ground.
  • the processor 402 is further configured to stop calibration when the center of gravity calibration condition is not satisfied, and send a first instruction to the control terminal.
  • the first instruction includes the reason for not satisfying the gravity center calibration condition and the adjustment suggestion information.
  • the processor 402 is further configured to stop calibration when calibration fails, and send a second instruction to the control terminal.
  • the second instruction includes the cause of the calibration failure.
  • the deviation of the actual position of the center of gravity of the current unmanned aerial vehicle from the standard position can be obtained, so that the degradation of flight quality caused by the deviation of the position of the center of gravity can be eliminated according to this deviation.
  • Simple and convenient, strong maneuverability, and can improve the load adaptation ability of the unmanned aerial vehicle to a greater extent users can adapt their own load to the unmanned aerial vehicle frame without worrying about the deterioration of flight quality, making the unmanned aerial vehicle The ability to support third-party loads has been significantly improved.
  • FIG. 5 shows a schematic diagram of an unmanned aerial vehicle 50 according to an embodiment of the present application.
  • the UAV 50 includes:
  • the controller 502 is used for acquiring target flight data and current flight data, and determining the control state quantity according to the target flight data and current flight data; and performing the gravity center calibration of the unmanned aerial vehicle according to the control state quantity.
  • the control state quantity includes at least four control state quantities: total tension command, yaw axis torque command, pitch axis torque command, and roll axis torque command.
  • the controller 502 acquires target flight data and current flight data of the unmanned aerial vehicle 50, and during the flight of the unmanned aerial vehicle 50, at least four control state quantities are given based on the target flight data and the current flight data: total pull command , Yaw axis torque command, pitch axis torque command, roll axis torque command.
  • the unmanned aerial vehicle includes a power device, and the power device may be, for example, at least one electric motor.
  • the above-mentioned four control state quantities correspond to the forces and torques received by the unmanned aerial vehicle 50 due to the respective motors, that is, the total pulling force and the yaw axis Torque, pitch axis torque, roll axis torque. Further, the center of gravity of the UAV 50 is calibrated according to the control state quantity. Further, the deviation of the center of gravity of the UAV 50 from the center of tension of the UAV 50 is obtained according to the control state quantity.
  • the controller 502 may include one or more microprocessors.
  • the controller 502 performing the calibration of the center of gravity of the UAV according to the control state quantity includes calculating offset data between the center of gravity of the UAV and the center of tension of the UAV according to the control state quantity.
  • the offset data includes one or a combination of the following: offset position, offset mass, offset force, offset torque.
  • the offset data of the unmanned aerial vehicle's center of gravity and the unmanned aerial vehicle's tension center is calculated according to the control state quantity, that is, the deviation of the actual center of gravity position of the unmanned aerial vehicle from the standard position.
  • the offset data may be an offset Position, offset quality, offset force, offset torque and other data.
  • the flight control system of the unmanned aerial vehicle is shown in FIG. 6 and includes a flight controller 602, a motor 604, a propulsion mechanism 606 (such as a propeller), and a sensor 608.
  • Stability and control specifically, the speed command or position command of the remote controller or the host computer is input to the flight controller 602 as the target flight state, the sensor 608 acquires the current flight state and sends it to the flight controller 602, and the flight controller 602 according to the current flight
  • the state and target flight state are calculated and analyzed, and instructions are generated and sent to the motor 604, which drives the propulsion mechanism 606 to adjust the attitude of the UAV.
  • the sensor 608 may be a sensor of an unmanned aerial vehicle component such as a propulsion mechanism 606, a motor 604, or may be set at another suitable position of the unmanned aerial vehicle to obtain the current flight status of the unmanned aerial vehicle.
  • control state variables During the control of UAV flight, at least four control state variables will be continuously given: total tension command T c , yaw axis torque command ⁇ zc , pitch axis torque command ⁇ yc , roll axis torque command ⁇ xc , this
  • the four control state quantities correspond to the forces and moments that the UAV will ultimately receive due to the speed of each motor, that is, the total pulling force T, the yaw axis torque ⁇ z , the pitch axis torque ⁇ y , and the roll axis torque ⁇ x .
  • the UAV's flight control system can use the above formula to calculate the horizontal position of the center of gravity of the UAV relative to the center of the paddle surface under the current mounting, that is, the offset distance.
  • the offset data is not limited to the offset distance.
  • the offset data may include one or a combination of the following: offset position, offset mass, offset force, offset torque.
  • the estimated center of gravity offset is not necessarily the true offset distance, but the control compensation value from the vertical channel to each rotation channel, such as offset mass, offset force, offset Set torque and other data. This embodiment is only an exemplary description and is not limited herein.
  • the UAV 50 further includes a memory 504 for storing bias data.
  • the offset data can be saved to non-volatile memory such as Flash, EEPROM, etc.
  • non-volatile memory such as Flash, EEPROM, etc.
  • the UAV is loaded every time it is powered on
  • the offset data can be feedforwardly controlled by the unmanned aerial vehicle according to the offset data every time it takes off, so that the equivalent pulling center also acts on the actual center of gravity.
  • Such advance compensation can eliminate the aforementioned "take-off nod" problem.
  • the memory 504 may be a serial memory, or a parallel memory.
  • the memory 404 may be a RAM memory, or a ROM memory.
  • the controller 502 is also used to generate a control component based on the bias data and control the power unit of the UAV according to the control component.
  • a control component is generated based on the offset data, and the power device of the UAV is controlled according to the control component, so as to reduce the offset data, make the UAV stable flight, and improve flight quality.
  • the flight control system can more accurately allocate the control amount of each control channel and reduce the amount of coupling between the channels.
  • the controller 502 of the unmanned aerial vehicle 50 can use feedforward control according to the stored bias data to accurately distribute the pulling force of each power device, so that the equivalent pulling force center also acts on the actual center of gravity. Advance compensation can eliminate the aforementioned "take-off and nod" problem.
  • the pulling force of each power device is accurately distributed, so that the equivalent pulling force center also acts on the actual center of gravity to ensure flight quality.
  • the controller 502 is further used to compare the offset data with a preset threshold, and determine whether the load installation position of the UAV exceeds the specified installation range according to the comparison result.
  • the controller 502 determines whether the load installation position of the unmanned aerial vehicle exceeds the specified installation range according to the comparison result includes: when the comparison result is that the offset data is greater than or equal to a preset threshold, determining the load installation of the unmanned aerial vehicle The position exceeds the specified installation range; when the comparison result is that the offset data is less than the preset threshold, it is determined that the load installation position of the UAV does not exceed the specified installation range.
  • whether the load installation position of the UAV exceeds the specified installation range may be determined according to the comparison result according to other suitable preset rules; for example, when the comparison result is that the offset data is greater than a preset threshold In the case of unmanned aerial vehicles, it is determined that the load installation position of the UAV exceeds the specified installation range; when the comparison result is that the offset data is less than or equal to the preset threshold, it is determined that the load installation position of the unmanned aircraft does not exceed the specified installation range. Not limited.
  • the user may be informed whether the installation position of the load exceeds the preset threshold by comparing with the preset threshold (ie, the offset range) supported by the UAV.
  • the unmanned aerial vehicle can detect whether the load installation is supported or whether the load installation location is reasonable.
  • the controller 502 is further used to record the control state quantity within the preset time period, and perform the center of gravity calibration of the UAV according to the control state quantity within the preset time period.
  • each control state quantity output to eliminate the center-of-gravity offset is recorded for a period of time, and after calculating the control state quantity for a period of time, the random error of the control state quantity can be eliminated by averaging, etc. Eliminate the interference caused by wind or aircraft vibration, and then calculate the offset data to improve the accuracy of calculating the offset data.
  • the controller 502 is also used to obtain the status data of the UAV and determine whether the status data meets the gravity center calibration conditions; when the status data meets the gravity center calibration conditions, perform the gravity center calibration of the UAV according to the control state quantity .
  • the state data includes one or a combination of the following: positioning data, image data, posture data, acceleration data, and angular velocity data.
  • the gravity center calibration conditions include the unmanned aerial vehicle being in a balanced state, the wind speed of the environment where the unmanned aerial vehicle is located is less than a preset wind speed, and the inertial measurement unit of the unmanned aerial vehicle has performed data calibration.
  • the center of gravity calibration condition further includes that the inertial measurement unit of the UAV has performed data calibration.
  • the center of gravity calibration condition is whether the UAV is in a balanced state, only when the UAV is in a balanced state
  • the center-of-gravity calibration performed at the time is accurate, and the balance state includes a mode in which the horizontal position is stationary during the course rotation in the hovering mode and the positioning mode.
  • the gravity center calibration condition can also be that the inertial measurement unit of the unmanned aerial vehicle has performed data calibration, and the data obtained by the inertial measurement unit are accurate data on the basis of the unmanned aerial vehicle being in a balanced state, thereby improving the accuracy of the gravity center calibration.
  • the controller 502 is also used to obtain the surrounding environment data of the UAV and determine whether the surrounding environment data meets the gravity center calibration conditions; when the surrounding environment data meets the gravity center calibration conditions, enter according to the control state quantity Steps to calibrate the center of gravity of UAV.
  • the ambient data includes ambient airflow or ambient wind speed.
  • the center of gravity calibration condition includes that the wind speed of the environment where the UAV is located is less than the preset wind speed.
  • the surrounding environment data may be obtained according to the attitude of the drone, or may be obtained based on other external sensors, such as an anemometer or information obtained from a cloud weather station.
  • the surrounding environment is a windless environment, it will not cause external forces to interfere with the air flow of the unmanned aerial vehicle, so as to avoid interference in the calibration of the center of gravity of the unmanned aerial vehicle.
  • the gravity center calibration conditions may include:
  • Unmanned aerial vehicle has positioning hovering ability: In the above algorithm, it is assumed that the unmanned aerial vehicle is already in a balanced state, that is, the above-mentioned derivation process can only be established when the unmanned aerial vehicle is in a stationary state, because It is very difficult to rely on people to maintain the balance of multi-wing unmanned aerial vehicles. Therefore, it is required that the unmanned aerial vehicles must have positioning hovering capability without manual operation. Further, whether the unmanned aerial vehicle is in a balanced state can be determined by positioning data, image data, attitude data, etc.
  • the position information of the unmanned aerial vehicle can be obtained through a positioning device (such as global positioning system GPS, carrier phase differential technology RTK, etc.) ,
  • a positioning device such as global positioning system GPS, carrier phase differential technology RTK, etc.
  • the UAV can be considered to be in a hovering state; or multiple images of the surrounding environment of the unmanned aerial vehicle can be obtained through a visual sensor within a certain time interval.
  • the UAV can be considered to be in a hovering state; or the acceleration and speed information of the UAV can also be obtained through the inertial measurement unit (IMU).
  • IMU inertial measurement unit
  • the unmanned aerial vehicle can be considered to be in a hovering state.
  • one or more of the above judgment methods can be used to judge the data fusion to improve the judgment. Accuracy.
  • the surrounding airflow is stable and no wind:
  • the unmanned aerial vehicle will also be subject to the external force caused by the interference of the airflow, so that even if the unmanned aerial vehicle is in the positioning hover state, due to the introduction of new Ignoring the external force, the above formula derivation will also be invalid, so the environment that requires calibration must be a calm air environment without wind. It can be judged whether the UAV is in a windless environment based on the unmanned aerial vehicle's tilt angle data, etc., and can be obtained by setting a wind collecting device.
  • the IMU (Inertial Measurement Unit) calibration of the UAV is correct: the IMU must have been calibrated to eliminate the steady-state error due to temperature, etc., otherwise the error will be caused by the center of gravity offset by the above algorithm. Now common unmanned aerial vehicles are equipped with IMU calibration function, it is recommended to re-calibrate the IMU before the center of gravity calibration.
  • the distance from the UAV to the ground is greater than the preset distance. In this embodiment, it is ensured that the unmanned aerial vehicle is at a preset distance from the ground, for example, having a height of more than 2 meters from the ground, so as to reduce the influence of turbulence caused by the ground.
  • the controller 502 is further configured to stop calibration when the center of gravity calibration condition is not satisfied, and send a first instruction to the control terminal.
  • the first instruction includes the reason for not satisfying the gravity center calibration condition and the adjustment suggestion information.
  • the controller 502 is also used to stop calibration when calibration fails, and send a second instruction to the control terminal.
  • the second instruction includes the cause of the calibration failure.
  • the deviation of the actual position of the center of gravity of the current unmanned aerial vehicle from the standard position can be obtained, so that the degradation of flight quality caused by the deviation of the position of the center of gravity can be eliminated according to this deviation.
  • Simple and convenient, strong maneuverability, and can improve the load adaptation ability of the unmanned aerial vehicle to a greater extent users can adapt their own load to the unmanned aerial vehicle frame without worrying about the deterioration of flight quality, making the unmanned aerial vehicle The ability to support third-party loads has been significantly improved.
  • FIG. 7 shows a schematic diagram of a system 70 for an unmanned aerial vehicle according to an embodiment of the present application.
  • the UAV system 70 includes:
  • the control terminal 702 is used to send the gravity center calibration instruction to the unmanned aerial vehicle
  • the unmanned aerial vehicle 704 is used to perform the center of gravity calibration according to the center of gravity calibration instruction to obtain the calibration result.
  • the user when the user needs to use the unmanned aerial vehicle 704 for loading, the user sends a barycenter calibration instruction to the unmanned aerial vehicle 704 through the control terminal 702, and the unmanned aerial vehicle 704 receives the barycentric calibration instruction to achieve the barycenter calibration to obtain the calibration result
  • the results may include: successful calibration, failed calibration, calibration data, etc.
  • the UAV 704 is also used to send the calibration result to the control terminal.
  • control terminal 702 further includes a display device, which is used to display the calibration result.
  • the calibration result can be displayed on the display device of the control terminal 702 to ensure that the user intuitively obtains the calibration result.
  • the UAV 704 performing the center of gravity calibration according to the center of gravity calibration instruction includes: acquiring the target flight data and current flight data according to the center of gravity calibration instruction, and determining the control state quantity according to the target flight data and current flight data, and according to the control state quantity The center of gravity of the UAV 704 is calibrated.
  • the control state quantity includes at least four control state quantities: total tension command, yaw axis torque command, pitch axis torque command, roll axis torque command.
  • the target flight data and current flight data of the unmanned aerial vehicle 704 are obtained, and during the flight of the unmanned aerial vehicle 704, at least four control state quantities are given according to the target flight data and the current flight data: total pull command, yaw Axis torque command, pitch axis torque command, roll axis torque command.
  • the unmanned aerial vehicle 704 includes a power device, which may be, for example, at least one electric motor.
  • the above-mentioned four control state quantities correspond to the force and torque received by the unmanned aerial vehicle 704 due to the rotation speed of each motor, that is, the total pulling force, Yaw axis torque, pitch axis torque, roll axis torque.
  • the center of gravity of the UAV 704 is calibrated according to the control state quantity.
  • the deviation of the center of gravity of the unmanned aerial vehicle 704 and the center of tension of the unmanned aerial vehicle 704 is obtained according to the control state quantity, so that the decrease in flight quality caused by the deviation of the position of the center of gravity can be eliminated based on the deviation.
  • the UAV 704 calibrating the center of gravity of the UAV according to the control state quantity includes: calculating the offset data of the UAV's center of gravity and the UAV's tension center according to the control state quantity.
  • the offset data includes one or a combination of the following: offset position, offset mass, offset force, offset torque.
  • the offset data of the unmanned aerial vehicle's center of gravity and the unmanned aerial vehicle's tension center is calculated according to the control state quantity, that is, the deviation of the actual center of gravity position of the unmanned aerial vehicle from the standard position.
  • the offset data may be an offset Position, offset quality, offset force, offset torque and other data.
  • the flight controller of the UAV will continuously give at least four control state quantities during the flight of the UAV: total tension command T c , yaw axis torque command ⁇ zc , pitch axis Torque command ⁇ yc and roll axis torque command ⁇ xc , these four control state quantities correspond to the forces and moments that the drone will eventually receive due to the speed of each motor, that is, the total pulling force T and the yaw axis torque ⁇ z , Pitch axis torque ⁇ y , Roll axis torque ⁇ x .
  • the UAV's flight control system can use the above formula to calculate the horizontal position of the center of gravity of the UAV relative to the center of the paddle surface under the current mounting, that is, the offset distance.
  • the offset data is not limited to the offset distance.
  • the offset data may include one or a combination of the following: offset position, offset mass, offset force, offset torque.
  • the estimated center of gravity offset is not necessarily the true offset distance, but the control compensation value from the vertical channel to each rotation channel, such as offset mass, offset force, offset Set torque and other data. This embodiment is only an exemplary description and is not limited herein.
  • the UAV 704 is also used to store bias data.
  • the offset data of the center of gravity of the unmanned aerial vehicle 704 and the tension center of the unmanned aerial vehicle 704 can be saved to a non-volatile memory such as Flash, EEPROM, etc.
  • the unmanned aerial vehicle 704 loads the offset data every time it is powered on.
  • the unmanned aerial vehicle can feedforward the control according to the offset data, so that the equivalent tension center also acts on the actual At the center of gravity, such advance compensation can eliminate the aforementioned "take-off and nod" problem.
  • control terminal 702 is also used to store offset data and send the offset data to the UAV.
  • the offset data may also be stored on the control terminal 702, and the control terminal 702 may directly send the offset data to the unmanned aerial vehicle 704 when sending the center of gravity calibration instruction.
  • the UAV 704 is also used to generate a control component based on the bias data, and control the power unit of the UAV 704 according to the control component.
  • a control component is generated based on the offset data, and the power device of the UAV is controlled according to the control component, so as to reduce the offset data, make the UAV stable flight, and improve flight quality.
  • the unmanned aerial vehicle 704 can more accurately allocate the control amount of each control channel and reduce the coupling amount between the channels.
  • the control system of unmanned aerial vehicle 704 can accurately allocate the pulling force of each power device according to the stored offset data during each take-off, so that the equivalent pulling force center also acts on the actual center of gravity. Early compensation can eliminate the aforementioned "take-off and nod" problem. Or, during the flight of the UAV 704, the pulling force of each power device is accurately distributed, so that the equivalent pulling force center also acts on the actual center of gravity to ensure the flying quality.
  • the UAV 704 is also used to compare the offset data with a preset threshold, and determine whether the load installation location of the UAV exceeds the specified installation range according to the comparison result.
  • the unmanned aerial vehicle 704 determines whether the load installation position of the unmanned aerial vehicle exceeds the specified installation range according to the comparison result includes: if the comparison result is that the offset data is greater than or equal to a preset threshold, determining the unmanned aerial vehicle 704 Of the load installation position exceeds the specified installation range; if the result of the comparison is that the offset data is less than the preset threshold, it is determined that the load installation position of the UAV 704 does not exceed the specified installation range.
  • whether the load installation position of the UAV exceeds the specified installation range may be determined according to the comparison result according to other suitable preset rules; for example, when the comparison result is that the offset data is greater than a preset threshold In the case of unmanned aerial vehicles, it is determined that the load installation position of the UAV exceeds the specified installation range; when the comparison result is that the offset data is less than or equal to the preset threshold, it is determined that the load installation position of the unmanned aircraft does not exceed the specified installation range. Not limited.
  • the user may be informed whether the installation position of the load exceeds the preset threshold by comparing with the preset threshold (ie, offset range) supported by the UAV 704, This enables the UAV 704 to detect whether the load installation is supported or whether the load installation location is reasonable.
  • the preset threshold ie, offset range
  • the UAV 704 is also used to send the result of whether the load installation position exceeds the specified installation range to the control terminal 702; the display device is also used to display the result of whether the load installation position exceeds the specified installation range.
  • control terminal 702 displays the result of whether the load installation position exceeds the specified installation range to remind the user to adjust the load installation position.
  • the UAV 704 is also used to record the control state quantity within the preset time period, and perform the center of gravity calibration of the UAV 704 according to the control state quantity within the preset time period.
  • each control state quantity output to eliminate the center-of-gravity offset is recorded for a period of time, and after calculating the control state quantity for a period of time, the random error of the control state quantity can be eliminated by averaging, etc. Eliminate the interference caused by wind or aircraft vibration, and then calculate the offset data to improve the accuracy of calculating the offset data.
  • the prompting device of the UAV 704 issues calibration prompting information during the process of performing the center of gravity calibration according to the center of gravity calibration instruction.
  • the status in order to let the user know the progress in real time, the status can be reported to the user by flashing a special color of the UAV status light and making a set sound.
  • the UAV 704 is also used to obtain status data and determine whether the status data meets the gravity center calibration conditions. When the status data meets the gravity center calibration conditions, perform the gravity center calibration according to the gravity center calibration instructions.
  • the UAV 704 is also used to send calibration progress information to the control terminal 702. For example, the calibration status is reported to the user by displaying a progress bar on the app of the control terminal 702.
  • the state data includes one or a combination of the following: positioning data, image data, posture data, acceleration data, and angular velocity data.
  • the center of gravity calibration condition includes the unmanned aerial vehicle being in a balanced state.
  • the center of gravity calibration condition further includes that the inertial measurement unit of the UAV has performed data calibration.
  • the center of gravity calibration condition is whether the UAV is in a balanced state, only when the UAV is in a balanced state
  • the center-of-gravity calibration performed at the time is accurate, and the balance state includes a mode in which the horizontal position is stationary during the course rotation in the hovering mode and the positioning mode.
  • the gravity center calibration condition can also be that the inertial measurement unit of the unmanned aerial vehicle has performed data calibration, and the data obtained by the inertial measurement unit are accurate data on the basis of the unmanned aerial vehicle being in a balanced state, thereby improving the accuracy of the gravity center calibration.
  • the UAV 704 is also used to obtain the surrounding environment data of the UAV and determine whether the surrounding environment data meets the gravity center calibration conditions.
  • the unmanned aerial vehicle performs unmanned vehicles according to the control state quantity.
  • the center of gravity of the aircraft is calibrated.
  • the ambient data includes ambient airflow or ambient wind speed.
  • the center of gravity calibration condition includes that the wind speed of the environment where the UAV is located is less than the preset wind speed.
  • the surrounding environment data may be obtained according to the attitude of the drone, or may be obtained based on other external sensors, such as an anemometer or information obtained from a cloud weather station.
  • the surrounding environment is a windless environment, it will not cause external forces to interfere with the air flow of the unmanned aerial vehicle, so as to avoid interference in the calibration of the center of gravity of the unmanned aerial vehicle.
  • the gravity center calibration conditions may include:
  • Unmanned aerial vehicle has positioning hovering ability: In the above algorithm, it is assumed that the unmanned aerial vehicle is already in a balanced state, that is, the above-mentioned derivation process can only be established when the unmanned aerial vehicle is in a stationary state, because It is very difficult to rely on people to maintain the balance of multi-wing unmanned aerial vehicles. Therefore, it is required that the unmanned aerial vehicles must have positioning hovering capability without manual operation. Further, whether the unmanned aerial vehicle is in a balanced state can be determined by positioning data, image data, attitude data, etc.
  • the position information of the unmanned aerial vehicle can be obtained through a positioning device (such as global positioning system GPS, carrier phase differential technology RTK, etc.) ,
  • a positioning device such as global positioning system GPS, carrier phase differential technology RTK, etc.
  • the UAV can be considered to be in a hovering state; or multiple images of the surrounding environment of the unmanned aerial vehicle can be obtained through a visual sensor within a certain time interval.
  • the UAV can be considered to be in a hovering state; or the acceleration and speed information of the UAV can also be obtained through the inertial measurement unit (IMU).
  • IMU inertial measurement unit
  • the unmanned aerial vehicle can be considered to be in a hovering state.
  • one or more of the above judgment methods can be used to judge the data fusion to improve the judgment. Accuracy.
  • the IMU (Inertial Measurement Unit) calibration of the UAV is correct: the IMU must have been calibrated to eliminate the steady-state error due to temperature, etc., otherwise the error will be caused by the center of gravity offset by the above algorithm. Now common unmanned aerial vehicles are equipped with IMU calibration function, it is recommended to re-calibrate the IMU before the center of gravity calibration.
  • the distance of the UAV 704 from the ground is greater than the preset distance. In this embodiment, it is ensured that the unmanned aerial vehicle is at a preset distance from the ground, for example, having a height of more than 2 meters from the ground, so as to reduce the influence of turbulence caused by the ground.
  • the UAV 704 is also used to stop calibration when the status data does not satisfy the gravity center calibration condition, and send a first instruction to the control terminal 702.
  • the display device of the control terminal 702 may display information that the status data does not satisfy the gravity center calibration conditions (for example, the UAV is not in a balanced state) and adjustment suggestion information (for example, please adjust the hovering state of the UAV).
  • the first instruction includes the reason for not satisfying the gravity center calibration condition and the adjustment suggestion information.
  • the UAV 704 is also used to stop calibration and send a second instruction to the control terminal 702 when the calibration fails.
  • the second instruction includes the cause of the calibration failure.
  • the calibration is stopped, and the first instruction is sent to the control terminal 702.
  • the calibration operation may be interrupted in advance, and the calibration failure and the failed the reason.
  • the deviation of the actual position of the center of gravity of the current unmanned aerial vehicle from the standard position can be obtained, so that the degradation of flight quality caused by the deviation of the position of the center of gravity can be eliminated according to this deviation.
  • Simple and convenient, strong maneuverability and can improve the load adaptation ability of the UAV to a greater extent. Users can adapt their load to the UAV rack without worrying about the deterioration of flight quality, making the UAV The ability to support third-party loads has been significantly improved.
  • FIG. 8 shows a schematic diagram of interactive implementation of a center of gravity calibration operation according to an embodiment of the present application.
  • the interaction realization steps include:
  • the user operates the unmanned aerial vehicle to complete the take-off operation, and puts the unmanned aerial vehicle into the positioning hovering mode, while ensuring that the unmanned aerial vehicle is at least 2 meters above the ground to reduce the turbulence caused by the ground;
  • the UAV After receiving the trigger command, the UAV will check whether the current state and environment can be calibrated for the center of gravity. For example, if the UAV detects that the attitude output is not 0 when hovering, the UAV will apply to the terminal Feedback that the center of gravity calibration is currently not possible, and remind the user to perform IMU calibration and move to a windless environment to restart the operation. If all checks are passed, the UAV will automatically enter the center of gravity calibration process;
  • the unmanned aerial vehicle will record the amount of control output by the controller to eliminate the center of gravity offset within a period of time. After calculating the data within a period of time, the random error can be eliminated by averaging and other methods, and then use the above algorithm to calculate the center of gravity Estimated horizontal offset. In order to let the user understand the progress in real time, the status can be reported to the user by flashing the special color light of the UAV status light or displaying the progress bar on the terminal app in real time;
  • the calibration operation may be interrupted in advance, and the calibration failure and the reason for the failure will be fed back to the user through the terminal app.
  • the algorithm estimates the center of gravity offset value, it can compare with the offset range supported by the UAV during the center of gravity calibration process to inform the user whether the installation position exceeds the specified range, so that the UAV can Check if the load is supported.
  • the interactive terminal for the calibration of the center of gravity may be a terminal app, a remote controller, a host computer, and the like, which is not limited in this application.
  • the center of gravity of the unmanned aerial vehicle can also be calibrated indoors or in a non-open scene.
  • the embodiments of the present application are applicable to unmanned aerial vehicles with real-time load changes.
  • the flight controller of the unmanned aerial vehicle can perform center of gravity calibration in real time to adapt to The changing load ensures the stability and safety of the flight and improves the user experience.
  • the current center-of-gravity offset level is updated and calculated, and the user can be alerted in a dangerous situation.
  • a computer storage medium in which program instructions are stored in the computer storage medium, and the program instructions are used to achieve: acquiring target flight data and current flight data, and according to the target flight data and current flight data Determine the control state quantity; and calibrate the center of gravity of the UAV according to the control state quantity.
  • control state quantity includes at least four control state quantities: total tension command, yaw axis torque command, pitch axis torque command, roll axis torque command.
  • the target flight data and current flight data of the unmanned aerial vehicle are obtained, and at least four control state quantities are given according to the target flight data and the current flight data during the flight of the unmanned aerial vehicle: total pull command, yaw axis torque Command, pitch axis torque command, roll axis torque command.
  • the unmanned aerial vehicle includes a power device, and the power device may be, for example, at least one electric motor.
  • the above-mentioned four control state quantities correspond to the force and torque received by the unmanned aerial vehicle due to the respective electric motors, that is, the total pulling force and the yaw axis torque , Pitch axis torque, roll axis torque. Further, the center of gravity of the UAV is calibrated according to the control state quantity. Further, the deviation of the center of gravity of the UAV from the center of tension of the UAV is obtained according to the control state quantity.
  • the computer storage medium may be volatile memory, or non-volatile memory.
  • the computer storage medium may also be a serial memory or a parallel memory.
  • the computer storage medium may be a RAM memory or a ROM memory.
  • the program instructions to perform the calibration of the center of gravity of the UAV according to the control state quantity include: calculating the offset data of the center of gravity of the UAV and the pulling center of the UAV according to the control state quantity.
  • the offset data includes one or a combination of the following: offset position, offset mass, offset force, offset torque.
  • the offset data of the unmanned aerial vehicle's center of gravity and the unmanned aerial vehicle's tension center is calculated according to the control state quantity, that is, the deviation of the actual center of gravity position of the unmanned aerial vehicle from the standard position.
  • the offset data may be an offset Position, offset quality, offset force, offset torque and other data.
  • the flight controller of the UAV will continuously give at least four control state quantities during the flight of the UAV: total tension command T c , yaw axis torque command ⁇ zc , pitch axis Torque command ⁇ yc and roll axis torque command ⁇ xc , these four control state quantities will correspond to the forces and moments that the drone will eventually receive due to the speed of each motor, that is, the total pulling force T and the yaw axis torque ⁇ z , pitch axis torque ⁇ y , roll axis torque ⁇ x .
  • the UAV's flight control system can use the above formula to calculate the horizontal position of the center of gravity of the UAV relative to the center of the paddle surface under the current mounting, that is, the offset distance.
  • the offset data is not limited to the offset distance.
  • the offset data may include one or a combination of the following: offset position, offset mass, offset force, offset torque.
  • the estimated center of gravity offset is not necessarily the true offset distance, but the control compensation value from the vertical channel to each rotation channel, such as offset mass, offset force, offset Set torque and other data. This embodiment is only an exemplary description and is not limited herein.
  • the program instructions are also used to implement: store bias data.
  • the offset data can be saved to non-volatile memory such as Flash, EEPROM, etc.
  • non-volatile memory such as Flash, EEPROM, etc.
  • the UAV is loaded every time it is powered on
  • the offset data can be feedforwardly controlled by the unmanned aerial vehicle according to the offset data every time it takes off, so that the equivalent pulling center also acts on the actual center of gravity.
  • Such advance compensation can eliminate the aforementioned "take-off nod" problem.
  • the program instructions are also used to achieve: obtain a control component based on the offset data, and control the power unit of the UAV according to the control component.
  • a control component is generated based on the offset data, and the power device of the UAV is controlled according to the control component, so as to reduce the offset data, make the UAV stable flight, and improve flight quality.
  • the flight control system can more accurately distribute the control amount of each control channel and reduce the amount of coupling between the channels.
  • the control system of an unmanned aerial vehicle can take forward feedforward control according to the stored bias data every time it takes off, and accurately distribute the pulling force of each power device, so that the equivalent pulling force center also acts on the actual center of gravity. Compensation can eliminate the aforementioned "take-off and nod" problem.
  • the tension of each power device is accurately distributed, so that the equivalent tension center also acts on the actual center of gravity to ensure the flight quality.
  • the program instructions are also used to realize: compare the offset data with a preset threshold, and determine whether the load installation position of the UAV exceeds the specified installation range according to the comparison result.
  • the program instructions implement to determine whether the load installation position of the unmanned aerial vehicle exceeds the specified installation range according to the comparison result: when the comparison result is that the offset data is greater than or equal to a preset threshold, determine the load installation of the unmanned aerial vehicle The position exceeds the specified installation range; when the comparison result is that the offset data is less than the preset threshold, it is determined that the load installation position of the UAV does not exceed the specified installation range.
  • whether the load installation position of the UAV exceeds the specified installation range may be determined according to the comparison result according to other suitable preset rules; for example, when the comparison result is that the offset data is greater than a preset threshold In the case of unmanned aerial vehicles, it is determined that the load installation position of the UAV exceeds the specified installation range; when the comparison result is that the offset data is less than or equal to the preset threshold, it is determined that the load installation position of the unmanned aircraft does not exceed the specified installation range. Not limited.
  • the user may be informed whether the installation position of the load exceeds the preset threshold by comparing with the preset threshold (ie, the offset range) supported by the UAV.
  • the unmanned aerial vehicle can detect whether the load installation is supported or whether the load installation location is reasonable.
  • the program instructions are also used to realize: record the control state quantity within the preset time period, and perform the center of gravity calibration of the UAV according to the control state quantity within the preset time period.
  • each control state quantity output to eliminate the center-of-gravity offset is recorded for a period of time, and after calculating the control state quantity for a period of time, the random error of the control state quantity can be eliminated by averaging, etc. Eliminate the interference caused by wind or aircraft vibration, and then calculate the offset data to improve the accuracy of calculating the offset data.
  • the program instructions are also used to achieve: before the step of calibrating the center of gravity of the UAV according to the control state quantity, obtain the state data of the UAV and determine whether the state data meets the conditions of the center of gravity calibration; when the state data When the center of gravity calibration conditions are satisfied, the procedure for performing the center of gravity calibration of the UAV according to the control state quantity is entered.
  • the state data includes one or a combination of the following: positioning data, image data, posture data, acceleration data, and angular velocity data.
  • the center of gravity calibration condition includes the unmanned aerial vehicle being in a balanced state.
  • the center of gravity calibration condition further includes that the inertial measurement unit of the UAV has performed data calibration.
  • the center of gravity calibration condition is whether the UAV is in a balanced state, only when the UAV is in a balanced state
  • the calibration of the center of gravity is accurate.
  • the balance state includes the hover mode and the positioning mode during the course rotation in the positioning mode.
  • the gravity center calibration condition can also be that the inertial measurement unit of the unmanned aerial vehicle has performed data calibration, and the data obtained by the inertial measurement unit are accurate data on the basis of the unmanned aerial vehicle being in a balanced state, thereby improving the accuracy of the gravity center calibration.
  • the program instructions are also used to achieve: obtain the surrounding environment data of the UAV, and determine whether the surrounding environment data meets the gravity center calibration conditions; when the surrounding environment data meets the gravity center calibration conditions, enter the control state quantity Steps to calibrate the center of gravity of the UAV.
  • the ambient data includes ambient airflow or ambient wind speed.
  • the center of gravity calibration condition includes that the wind speed of the environment where the UAV is located is less than the preset wind speed.
  • the surrounding environment data may be obtained according to the attitude of the drone, or may be obtained based on other external sensors, such as an anemometer or information obtained from a cloud weather station.
  • the surrounding environment is a windless environment, it will not cause external forces to interfere with the air flow of the unmanned aerial vehicle, so as to avoid interference in the calibration of the center of gravity of the unmanned aerial vehicle.
  • the gravity center calibration conditions may include:
  • Unmanned aerial vehicle has positioning hovering ability: In the above algorithm, it is assumed that the unmanned aerial vehicle is already in a balanced state, that is, the above-mentioned derivation process can only be established when the unmanned aerial vehicle is in a stationary state, because It is very difficult to rely on people to maintain the balance of multi-wing unmanned aerial vehicles. Therefore, it is required that the unmanned aerial vehicles must have positioning hovering capability without manual operation. Further, whether the unmanned aerial vehicle is in a balanced state can be determined by positioning data, image data, attitude data, etc.
  • the position information of the unmanned aerial vehicle can be obtained through a positioning device (such as global positioning system GPS, carrier phase differential technology RTK, etc.) ,
  • a positioning device such as global positioning system GPS, carrier phase differential technology RTK, etc.
  • the UAV can be considered to be in a hovering state; or multiple images of the surrounding environment of the unmanned aerial vehicle can be obtained through a visual sensor within a certain time interval.
  • the UAV can be considered to be in a hovering state; or the acceleration and speed information of the UAV can also be obtained through the inertial measurement unit (IMU).
  • IMU inertial measurement unit
  • the unmanned aerial vehicle can be considered to be in a hovering state.
  • one or more of the above judgment methods can be used to judge the data fusion to improve the judgment. Accuracy.
  • the IMU (Inertial Measurement Unit) calibration of the UAV is correct: the IMU must have been calibrated to eliminate the steady-state error due to temperature, etc., otherwise the error will be caused by the center of gravity offset by the above algorithm. Now common unmanned aerial vehicles are equipped with IMU calibration function, it is recommended to re-calibrate the IMU before the center of gravity calibration.
  • the distance from the UAV to the ground is greater than the preset distance. In this embodiment, it is ensured that the unmanned aerial vehicle is at a preset distance from the ground, for example, having a height of more than 2 meters from the ground, so as to reduce the influence of turbulence caused by the ground.
  • the program instructions are also used to realize: when the gravity center calibration conditions are not satisfied, stop the calibration and send the first instruction to the control terminal.
  • the first instruction includes the reason for not satisfying the gravity center calibration condition and the adjustment suggestion information.
  • the program instructions are also used to implement: when the calibration fails, stop the calibration and send a second instruction to the control terminal.
  • the second instruction includes the cause of the calibration failure.
  • the deviation of the actual position of the center of gravity of the current unmanned aerial vehicle from the standard position can be obtained, so that the degradation of flight quality caused by the deviation of the position of the center of gravity can be eliminated according to this deviation.
  • Simple and convenient, strong maneuverability, and can improve the load adaptation ability of the unmanned aerial vehicle to a greater extent users can adapt their own load to the unmanned aerial vehicle frame without worrying about the deterioration of flight quality, making the unmanned aerial vehicle The ability to support third-party loads has been significantly improved.
  • connection can be a fixed connection, a detachable connection, or an integral connection; it can be directly connected or indirectly connected through an intermediate medium.

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Abstract

一种无人飞行器控制方法、无人飞行器控制装置、无人飞行器、无人飞行器的系统以及计算机存储介质。其中，无人飞行器控制方法包括：获取目标飞行数据和当前飞行数据，并根据目标飞行数据和当前飞行数据确定控制状态量；以及根据控制状态量进行无人飞行器的重心校准。采用该技术方案，可获得当前无人飞行器的实际重心位置与标准位置的偏差，从而能根据这一偏差消除重心位置偏差造成的飞行品质的下降，该技术方案对于用户来说简单方便，可操作性强，并且能够更大限度地提升无人飞行器的负载适配能力。

Description

无人飞行器控制方法、控制装置及无人飞行器 技术领域
本申请涉及飞行器技术领域，具体而言，涉及一种无人飞行器控制方法、无人飞行器控制装置、无人飞行器、无人飞行器的系统以及计算机存储介质。
背景技术
目前，多旋翼无人飞行器被大范围的应用于工业、农业等行业领域，这些领域中无人飞行器往往利用其挂载的设备而执行不同的工作任务，因此无人飞行器上所挂载的设备呈现多样化的趋势，有的负载是无人飞行器厂商配套提供的可用该型无人飞行器使用的设备，有的负载是用户自行设计或者购买的第三方设备。而这些负载的变动会使该无人飞行器的动力学模型与无人飞行器飞行控制系统设计时所依赖的模型相差较大，即使通过控制系统的鲁棒性设计能够保证无人飞行器可以进行正常的飞行操作，但在负载与标准负载差别较大时，无人飞行器的飞行品质还是难免会有不同程度的下降。例如当负载的变动导致整个无人飞行器系统的重心较标准状态移动超过一定程度后，无人飞行器在起飞离地瞬间往往出现姿态抖一下的“起飞点头”问题，这种现象还会使得无人飞行器离地后立刻相对起飞点横移一小段距离，这可能会撞上周围的物体、人群甚至飞手自己。
针对上述问题，一些无人飞行器厂商通过声明对负载的要求来限制负载的安装位置以及重量来减弱重心偏置的影响，这样会牺牲一定的负载能力；一些无人飞行器会要求用户手动测量重心的位置并将其输入进无人飞行器的模型系统中来解决该问题，这样的操作对于大部分用户来说都过于复杂且不实际，也影响用户体验；一些会通过对控制器进行改进，提高控制器的自适应性，但是在每次起飞离地时仍然会因为尚未来得及对模型进行估计而造成起飞姿态“点头”、位置“横漂”的现象。
发明内容
本申请旨在至少解决现有技术或相关技术中存在的技术问题之一。
为此，本申请的第一个方面在于提出了一种无人飞行器控制方法。
本申请的第二个方面在于提出了一种无人飞行器控制装置。
本申请的第三个方面在于提出了一种无人飞行器。
本申请的第四个方面在于提出了一种无人飞行器的系统。
本申请的第五个方面在于提出了一种计算机存储介质。
有鉴于此，根据本申请的第一个方面，提出了一种无人飞行器控制方法，包括：获取目标飞行数据和当前飞行数据，并根据目标飞行数据和当前飞行数据确定控制状态量；以及根据控制状态量进行无人飞行器的重心校准。
本申请提出的无人飞行器控制方法中，获取无人飞行器的目标飞行数据和当前飞行数据，在控制无人飞行器飞行过程中，根据目标飞行数据和当前飞行数据给出至少四个控制状态量：总拉力命令、偏航轴扭矩命令、俯仰轴扭矩命令、横滚轴扭矩命令，上述四个控制状态量对应于无人飞行器因为各个电机而受到的力和力矩，也就是总拉力、偏航轴扭矩、俯仰轴扭矩、横滚轴扭矩。进一步地，根据控制状态量进行无人飞行器的重心校准，即获得无人飞行器的重心与无人飞行器的拉力中心的偏差。采用本申请的技术方案，可获得当前无人飞行器的实际重心位置与标准位置的偏差，从而能根据这一偏差而消除重心位置偏差造成的飞行品质的下降，本申请的技术方案对于用户来说简单方便，可操作性强，并且能够更大限度地提升无人飞行器的负载适配能力。
根据本申请的第二个方面，提出了一种无人飞行器控制装置，包括：处理器，用于获取目标飞行数据和当前飞行数据，根据目标飞行数据和当前飞行数据确定控制状态量，并根据控制状态量进行无人飞行器的重心校准。
本申请提出的无人飞行器控制装置中，处理器获取无人飞行器的目标飞行数据和当前飞行数据，在控制无人飞行器飞行过程中，根据目标飞行数据和当前飞行数据给出至少四个控制状态量：总拉力命令、偏航轴扭矩 命令、俯仰轴扭矩命令、横滚轴扭矩命令，上述四个控制状态量对应于无人飞行器因为各个电机而受到的力和力矩，也就是总拉力、偏航轴扭矩、俯仰轴扭矩、横滚轴扭矩。进一步地，处理器根据控制状态量进行无人飞行器的重心校准，即获得无人飞行器的重心与无人飞行器的拉力中心的偏差。采用本申请的技术方案，可通过无人飞行器控制装置获得当前无人飞行器的实际重心位置与标准位置的偏差，从而能根据这一偏差而消除重心位置偏差造成的飞行品质的下降，本申请的技术方案对于用户来说简单方便，可操作性强，并且能够更大限度地提升无人飞行器的负载适配能力。
根据本申请的第三个方面，提出了一种无人飞行器，包括动力装置，还包括：控制器，用于获取目标飞行数据和当前飞行数据，并根据目标飞行数据和当前飞行数据确定控制状态量；以及根据控制状态量进行无人飞行器的重心校准。
本申请提出的无人飞行器中，控制器获取无人飞行器的目标飞行数据和当前飞行数据，在控制无人飞行器飞行过程中，根据目标飞行数据和当前飞行数据给出至少四个控制状态量：总拉力命令、偏航轴扭矩命令、俯仰轴扭矩命令、横滚轴扭矩命令，上述四个控制状态量对应于无人飞行器因为各个电机而受到的力和力矩，也就是总拉力、偏航轴扭矩、俯仰轴扭矩、横滚轴扭矩。进一步地，控制器根据控制状态量进行无人飞行器的重心校准，即获得无人飞行器的重心与无人飞行器的拉力中心的偏差。采用本申请的技术方案，可通过无人飞行器获得当前无人飞行器的实际重心位置与标准位置的偏差，从而能根据这一偏差而消除重心位置偏差造成的飞行品质的下降，本申请的技术方案对于用户来说简单方便，可操作性强，并且能够更大限度地提升无人飞行器的负载适配能力。
根据本申请的第四个方面，提出了一种无人飞行器的系统，包括：控制终端，用于向无人飞行器发送重心校准指令；无人飞行器，用于根据重心校准指令进行重心校准，得到校准结果。
本申请提出的无人飞行器的系统中包括控制终端和无人飞行器，用户在需要使用无人飞行器进行负载时，通过控制终端向无人飞行器发送重心校准指令，无人飞行器接收该重心校准指令，实现重心校准得到校准结果， 校准结果可包括：校准成功、校准失败、校准数据等。采用本申请的技术方案，可获得当前无人飞行器的实际重心位置与标准位置的偏差，从而能根据这一偏差而消除重心位置偏差造成的飞行品质的下降，本申请的技术方案对于用户来说简单方便，可操作性强，并且能够更大限度地提升无人飞行器的负载适配能力。
根据本申请的第五个方面，提出了一种计算机存储介质，计算机存储介质中存储有程序指令，程序指令用于实现：获取目标飞行数据和当前飞行数据，并根据目标飞行数据和当前飞行数据确定控制状态量；以及根据控制状态量进行无人飞行器的重心校准。
本申请提出的计算机存储介质存储有程序指令，程序指令用于实现：获取无人飞行器的目标飞行数据和当前飞行数据，在控制无人飞行器飞行过程中，根据目标飞行数据和当前飞行数据给出至少四个控制状态量：总拉力命令、偏航轴扭矩命令、俯仰轴扭矩命令、横滚轴扭矩命令，上述四个控制状态量对应于无人飞行器因为各个电机而受到的力和力矩，也就是总拉力、偏航轴扭矩、俯仰轴扭矩、横滚轴扭矩。进一步地，根据控制状态量进行无人飞行器的重心校准，即获得无人飞行器的重心与无人飞行器的拉力中心的偏差。采用本申请的技术方案，可获得当前无人飞行器的实际重心位置与标准位置的偏差，从而能根据这一偏差而消除重心位置偏差造成的飞行品质的下降，本申请的技术方案对于用户来说简单方便，可操作性强，并且能够更大限度地提升无人飞行器的负载适配能力。
本申请的附加方面和优点将在下面的描述部分中变得明显，或通过本申请的实践了解到。
附图说明
本申请的上述和/或附加的方面和优点从结合下面附图对实施例的描述中将变得明显和容易理解，其中：
图1示出了本申请的一个实施例的无人飞行器控制方法的流程示意图；
图2示出了本申请的一个实施例的无人飞行器重心偏置示意图；
图3示出了本申请的一个实施例的重心偏置情况下的单通道的受力分析图；
图4示出了本申请的一个实施例的无人飞行器控制装置的示意图；
图5示出了本申请的一个实施例的无人飞行器的示意图；
图6示出了本申请的一个实施例的无人飞行器的飞行控制系统示意图；
图7示出了本申请的一个实施例的无人飞行器的系统的示意图；
图8示出了本申请的一个实施例的重心校准操作的交互实现示意图。
具体实施方式
为了能够更清楚地理解本申请的上述目的、特征和优点，下面结合附图和具体实施方式对本申请进行进一步的详细描述。需要说明的是，在不冲突的情况下，本申请的实施例及实施例中的特征可以相互组合。
在下面的描述中阐述了很多具体细节以便于充分理解本申请，但是，本申请还可以采用其他不同于在此描述的其他方式来实施，因此，本申请的保护范围并不限于下面公开的具体实施例的限制。
本申请第一方面的实施例，提出一种无人飞行器控制方法，图1示出了本申请的一个实施例的无人飞行器控制方法的流程示意图。其中，该方法包括：
步骤102，获取目标飞行数据和当前飞行数据，并根据目标飞行数据和当前飞行数据确定控制状态量。
在一种实施例中，所述控制状态量包括至少四个控制状态量：总拉力命令、偏航轴扭矩命令、俯仰轴扭矩命令、横滚轴扭矩命令。具体地，获取无人飞行器的目标飞行数据和当前飞行数据，在控制无人飞行器飞行过程中，根据目标飞行数据和当前飞行数据给出至少四个控制状态量：总拉力命令、偏航轴扭矩命令、俯仰轴扭矩命令、横滚轴扭矩命令。进一步地，无人飞行器包括动力装置，该动力装置可以诸如是至少一个电机，上述四个控制状态量对应于无人飞行器因为各个电机而受到的力和力矩，也就是总拉力、偏航轴扭矩、俯仰轴扭矩、横滚轴扭矩。
步骤104，根据控制状态量进行无人飞行器的重心校准。
进一步地，根据步骤102中获取的控制状态量进行无人飞行器的重心校准。进一步地，根据控制状态量获得无人飞行器的重心与无人飞行器的拉力中心的偏差。
在一些实施例中，步骤104，根据控制状态量进行无人飞行器的重心校准的步骤包括：根据控制状态量，计算无人飞行器的重心与无人飞行器的拉力中心的偏置数据。
在一些实施例中，偏置数据包括以下一种或其组合：偏置位置、偏置质量、偏置力、偏置力矩。
在该实施例中，根据控制状态量计算得到无人飞行器的重心与无人飞行器的拉力中心的偏置数据，即无人飞行器的实际重心位置与标准位置的偏差，偏置数据可以为偏置位置、偏置质量、偏置力、偏置力矩等数据。
在一种实施例中，无人飞行器的飞行控制器在控制无人飞行器飞行过程中会持续的给出至少四个控制状态量：总拉力命令T c、偏航轴扭矩命令τ zc、俯仰轴扭矩命令τ yc、横滚轴扭矩命令τ xc，这四个控制状态量对应于无人机最终将因为各个电机的转速而受到的力和力矩，也就是总拉力T、偏航轴扭矩τ z、俯仰轴扭矩τ y、横滚轴扭矩τ x。
定义所有电机位置围绕出的正多边形的外接圆的圆心为等效拉力中心。如图2所示，以四旋翼无人飞行器为例，包括四个电机，O点即为该四旋翼无人飞行器的等效拉力中心，根据力的平移定理，可以将所有电机的拉力等效于作用等效拉力中心上的总拉力T加上两个绕水平轴的力矩τ x、τ y。
当无人飞行器的重心与拉力重心完全重合时，根据二力平衡法则，只需要满足拉力等于重力，即T＝G，可以维持无人飞行器的平衡，此时无人飞行器的两个水平旋转轴上的力矩将接近于零。但是若无人飞行器的重心与等效拉力中心不重合，则用户还需手动调节无人飞行器力矩才能维持平衡。以横滚方向上的不重合为例，可做受力分析图如图3所示，根据刚体受力平衡法则，当无人飞行器维持悬停的稳定状态时，必然有
T＝G                (1)
T×d y+τ x＝0            (2)
在无人飞行器已达到稳定状态时，有
T＝T c                  (3)
τ x＝τ xc              (4)
因此可以得到d y＝-τ xc/T c，同理可得d x＝-τ yc/T c。因此，在无人飞行器保持悬停的情况下，无人飞行器的飞控系统可以利用上述公式计算出当前挂载下无人飞行器重心相对桨面中心的水平位置，即偏置距离。
当然，偏置数据不限于偏置距离，在其他实施例中，偏置数据可以包括以下一种或其组合：偏置位置、偏置质量、偏置力、偏置力矩。例如，对于一些建模不够准确的无人飞行器，估计的重心偏置量不一定是真实偏置距离，而是垂直通道到各转动通道的控制补偿值，例如偏置质量、偏置力、偏置力矩等数据。本实施例仅为示例性说明，在此不作限定。
在一些实施例中，还包括：存储偏置数据。
在该实施例中，在标定出偏置数据后，可将该偏置数据保存到Flash、EEPROM等非易失存储器，在承载相同负载的情况下，无人飞行器每次在上电后都加载该偏置数据，在每次起飞时无人飞行器都能根据该偏置数据前馈控制，使得等效拉力中心也作用于实际的重心上，这样的提前补偿就能消除前述的“起飞点头”问题。在一些实施例中，还包括：根据偏置数据生成控制分量，并根据控制分量控制无人飞行器的动力装置。
在该实施例中，根据偏置数据生成控制分量，根据控制分量控制无人飞行器的动力装置，以减小偏置数据，使无人飞行器稳定飞行，提升飞行品质。飞控系统能更加准确的分配各个控制通道的控制量，降低通道间的耦合量。例如，在每次起飞时无人飞行器的控制系统就能根据存储的偏置数据通过前馈控制，准确分配各个动力装置的拉力，使得等效拉力中心也作用于实际的重心上，这样的提前补偿就能消除前述的“起飞点头”问题。或者在无人飞行器飞行的过程中准确分配各个动力装置的拉力，使得等效拉力中心也作用于实际的重心上，保证飞行品质。
在一些实施例中，还包括：将偏置数据与预设阈值进行比较，根据比较结果确定无人飞行器的负载安装位置是否超过规定安装范围。
在一些实施例中，根据比较结果确定无人飞行器的负载安装位置是否超过规定安装范围的步骤包括：在比较结果为偏置数据大于或等于预设阈值的情况下，确定无人飞行器的负载安装位置超过规定安装范围；在比较结果为偏置数据小于预设阈值的情况下，确定无人飞行器的负载安装位置未超过规定安装范围。可以理解，在其他实施方式中，也可以按照其他合适的预先设置的规则来根据比较结果确定无人飞行器的负载安装位置是否超过规定安装范围；例如，在比较结果为偏置数据大于预设阈值的情况下，确定无人飞行器的负载安装位置超过规定安装范围；在比较结果为偏置数据小于或等于预设阈值的情况下，确定无人飞行器的负载安装位置未超过规定安装范围，在此不作限定。
在一种实施例中，计算出偏置数据后，可以通过跟该款无人飞行器所支持的预设阈值(即偏置范围)进行比较，告知用户负载的安装位置是否超过预设阈值，使得无人飞行器能够自行检测是否支持该负载安装，或者负载安装的位置是否合理。
在一些实施例中，还包括：记录预设时间段内的控制状态量，并根据预设时间段内的控制状态量进行无人飞行器的重心校准。
在该实施例中，在一段时间内记录为消除重心偏置而输出的各控制状态量，统计一段时间内的控制状态量后可通过求取平均值等方法消除控制状态量的随机误差，以消除诸如风或飞机振动而引入的干扰，然后再计算出偏置数据，提高计算偏置数据的准确性。
在一些实施例中，在根据控制状态量进行无人飞行器的重心校准的步骤之前还包括：获取无人飞行器的状态数据，并判断状态数据是否满足重心校准条件；当状态数据满足重心校准条件时，进入根据控制状态量进行无人飞行器的重心校准的步骤。
在一些实施例中，状态数据包括以下一种或其组合：定位数据、图像数据、姿态数据、加速度数据、角速度数据。
在一些实施例中，重心校准条件包括无人飞行器处于平衡状态。
在一些实施例中，重心校准条件还包括无人飞行器的惯性测量单元已进行数据校准。
在该实施例中，在进行无人飞行器的重心校准前，需判断状态数据是否满足允许重心校准的条件，例如，重心校准条件为无人飞行器是否处于平衡状态，只有在无人飞行器处于平衡状态时进行的重心校准才是准确的，其中平衡状态包括悬停模式、定位模式下航向转动过程中水平位置静止的模式。重心校准条件还可以为无人飞行器的惯性测量单元已进行数据校准，在无人飞行器处于平衡状态的基础上保证惯性测量单元获取的数据均为准确数据，由此提高重心校准的准确性。
在一些实施例中，还包括：获取无人飞行器的周围环境数据，并判断周围环境数据是否满足重心校准条件；当周围环境数据满足重心校准条件时，进入根据所述控制状态量进行无人飞行器的重心校准的步骤。
在一些实施例中，周围环境数据包括周围环境气流或周围环境风速。
在一些实施例中，重心校准条件包括无人飞行器所处环境的风速小于预设风速。
在该实施例中，周围环境数据可以根据无人机的姿态得到，也可以根据其他外部传感器，例如风力计或者从云端气象站得到的信息获取。在周围环境为无风环境时不会给无人飞行器带来气流干扰的外力，避免无人飞行器的重心校准出现干扰。
在具体实施例中，重心校准条件可以包括：
(1)无人飞行器具备定位悬停能力：在上述的算法中，都是在假设无人飞行器已经处于平衡状态，也就是只有当无人飞行器处于静止状态时，上述推导过程才能够成立，由于依靠人来维持多选翼的无人飞行器的平衡十分困难，因此要求无人飞行器必须具备无需手动操作的定位悬停能力。进一步地，可通过定位数据、图像数据、姿态数据等判断无人飞行器是否处于平衡状态，例如，可以通过定位装置(如全球定位系统GPS、载波相位差分技术RTK等)获取无人飞行器的位置信息，当获取的无人飞行器的位置未发生变化时可以认为无人飞行器处于悬停状态；或者也可以在一定时间间隔内通过视觉传感器获取无人飞行器的周围环境的多张图像，并对获取的多张图像进行图像处理，当获取的图像中的物体位置未发生变化时可以认为无人飞行器处于悬停状态；或者还可以通过惯性测量单元(IMU) 获取无人飞行器的加速度、速度信息，当无人飞行器的加速度与速度为零时，可以认为无人飞行器处于悬停状态，在其他实施方式中，也可以通过上述判断方式中的一种或几种的数据融合进行判断，以提高判断的准确度。
(2)周围气流稳定且无风：当周围环境风速较大，无人飞行器还会受到气流干扰带来的外力，使得无人飞行器即使处于定位悬停状态，由于引入了新的难以估算且无法忽视的外力，上述的公式推导也将失效，因此要求进行校准的环境必须是无风的平静气流环境。可根据无人飞行器倾斜角度数据等判断无人飞行器是否处于无风环境，获取设置风力采集装置来判断。
(3)无人飞行器的IMU(惯性测量单元)校准正确：IMU必须已经通过校准消除了由于温度等带来的稳态误差，否则该误差会被上述算法认为是重心偏置引发的。现在常见的无人飞行器都具备IMU校准功能，推荐在每次进行重心校准之前，进行IMU的重新校准。
在一些实施例中，无人飞行器距离地面的距离大于预设距离。在该实施例中，保证无人飞行器距离地面预设距离，例如距离地面有2米以上的高度，以减小地面所带来的紊流影响。
在一些实施例中，当不满足重心校准条件时，停止校准，并发送第一指令至控制终端。在该实施例中，第一指令包括不满足重心校准条件的原因和调整建议信息。
在一些实施例中，当校准失败时，停止校准，并发送第二指令至控制终端。在该实施例中，在该实施例中，第二指令包括校准失败原因。
采用本申请的技术方案，可获得当前无人飞行器的实际重心位置与标准位置的偏差，从而能根据这一偏差而消除重心位置偏差造成的飞行品质的下降，本申请的技术方案对于用户来说简单方便，可操作性强，并且能够更大限度地提升无人飞行器的负载适配能力，用户可以适配自己的负载到无人飞行器机架上而不用担心飞行品质的恶化，使得无人飞行器支持第三方负载的能力有明显的提高。
本申请第二方面的实施例，提出一种无人飞行器控制装置，图4示出了本申请的一个实施例的无人飞行器控制装置40的示意图。其中，该控制 装置40包括：
处理器402，用于获取目标飞行数据和当前飞行数据，根据目标飞行数据和当前飞行数据确定控制状态量，并根据控制状态量进行无人飞行器的重心校准。
在一种实施例中，所述控制状态量包括至少四个控制状态量：总拉力命令、偏航轴扭矩命令、俯仰轴扭矩命令、横滚轴扭矩命令。具体地，获取无人飞行器的目标飞行数据和当前飞行数据，在控制无人飞行器飞行过程中，根据目标飞行数据和当前飞行数据给出至少四个控制状态量：总拉力命令、偏航轴扭矩命令、俯仰轴扭矩命令、横滚轴扭矩命令。进一步地，无人飞行器包括动力装置，该动力装置可以诸如是至少一个电机，上述四个控制状态量对应于无人飞行器因为各个电机而受到的力和力矩，也就是总拉力、偏航轴扭矩、俯仰轴扭矩、横滚轴扭矩。进一步地，根据控制状态量进行无人飞行器的重心校准。进一步地，根据控制状态量获得无人飞行器的重心与无人飞行器的拉力中心的偏差。
在一些实施例中，处理器402可以包括一个或多个微处理器。
在一些实施例中，处理器402根据控制状态量进行无人飞行器的重心校准包括：根据控制状态量，计算无人飞行器的重心与无人飞行器的拉力中心的偏置数据。
在一些实施例中，偏置数据包括以下一种或其组合：偏置位置、偏置质量、偏置力、偏置力矩。
在该实施例中，根据控制状态量计算得到无人飞行器的重心与无人飞行器的拉力中心的偏置数据，即无人飞行器的实际重心位置与标准位置的偏差，偏置数据可以为偏置位置、偏置质量、偏置力、偏置力矩等数据。
在一种实施例中，无人飞行器的飞行控制器在控制无人飞行器飞行过程中会持续的给出至少四个控制状态量：总拉力命令T c、偏航轴扭矩命令τ zc、俯仰轴扭矩命令τ yc、横滚轴扭矩命令τ xc，这四个控制状态量对应于无人机最终将因为各个电机的转速而受到的力和力矩，也就是总拉力T、偏航轴扭矩τ z、俯仰轴扭矩τ y、横滚轴扭矩τ x。
定义所有电机位置围绕出的正多边形的外接圆的圆心为等效拉力中 心。如图2所示，以四旋翼无人飞行器为例，包括四个电机，O点即为该四旋翼无人飞行器的等效拉力中心，根据力的平移定理，可以将所有电机的拉力等效于作用等效拉力中心上的总拉力T加上两个绕水平轴的力矩τ x、τ y。
当无人飞行器的重心与拉力重心完全重合时，根据二力平衡法则，只需要满足拉力等于重力，即T＝G，可以维持无人飞行器的平衡，此时无人飞行器的两个水平旋转轴上的力矩将接近于零。但是若无人飞行器的重心与等效拉力中心不重合，则用户还需手动调节无人飞行器力矩才能维持平衡。以横滚方向上的不重合为例，可做受力分析图如图3所示，根据刚体受力平衡法则，当无人飞行器维持悬停的稳定状态时，同样地，必然有
T＝G                     (1)
T×d y+τ x＝0             (2)
在无人飞行器已达到稳定状态时，有
T＝T c                   (3)
τ x＝τ xc               (4)
因此可以得到d y＝-τ xc/T c，同理可得d x＝-τ yc/T c。因此，在无人飞行器保持悬停的情况下，无人飞行器的飞控系统可以利用上述公式计算出当前挂载下无人飞行器重心相对桨面中心的水平位置，即偏置距离。
当然，偏置数据不限于偏置距离，在其他实施例中，偏置数据可以包括以下一种或其组合：偏置位置、偏置质量、偏置力、偏置力矩。例如，对于一些建模不够准确的无人飞行器，估计的重心偏置量不一定是真实偏置距离，而是垂直通道到各转动通道的控制补偿值，例如偏置质量、偏置力、偏置力矩等数据。本实施例仅为示例性说明，在此不作限定。
在一些实施例中，还包括：存储器404，用于存储偏置数据。
在该实施例中，在标定出偏置数据后，可将该偏置数据保存到Flash、EEPROM等非易失存储器，在承载相同负载的情况下，无人飞行器每次在上电后都加载该偏置数据，在每次起飞时无人飞行器都能根据该偏置数据前馈控制，使得等效拉力中心也作用于实际的重心上，这样的提前补偿就能消除前述的“起飞点头”问题。
在一些实施例中，存储器404可以为串行存储器，或者并行存储器。存储器404可以为RAM存储器，或者ROM存储器。
在一些实施例中，处理器402还用于根据偏置数据生成控制分量，并根据控制分量控制无人飞行器的动力装置。
在该实施例中，根据偏置数据生成控制分量，根据控制分量控制无人飞行器的动力装置，以减小偏置数据，使无人飞行器稳定飞行，提升飞行品质。飞控系统能更加准确的分配各个控制通道的控制量，降低通道间的耦合量。例如，在每次起飞时无人飞行器的控制系统就能根据存储的偏置数据通过前馈控制，准确分配各个动力装置的拉力，使得等效拉力中心也作用于实际的重心上，这样的提前补偿就能消除前述的“起飞点头”问题。或者在无人飞行器飞行的过程中准确分配各个动力装置的拉力，使得等效拉力中心也作用于实际的重心上，保证飞行品质。
在一些实施例中，处理器402还用于将偏置数据与预设阈值进行比较，根据比较结果确定无人飞行器的负载安装位置是否超过规定安装范围。
在一些实施例中，处理器402根据比较结果确定无人飞行器的负载安装位置是否超过规定安装范围包括：在比较结果为偏置数据大于等于预设阈值的情况下，确定无人飞行器的负载安装位置超过规定安装范围，在比较结果为偏置数据小于预设阈值的情况下，确定无人飞行器的负载安装位置未超过规定安装范围。可以理解，在其他实施方式中，也可以按照其他合适的预先设置的规则来根据比较结果确定无人飞行器的负载安装位置是否超过规定安装范围；例如，在比较结果为偏置数据大于预设阈值的情况下，确定无人飞行器的负载安装位置超过规定安装范围；在比较结果为偏置数据小于或等于预设阈值的情况下，确定无人飞行器的负载安装位置未超过规定安装范围，在此不作限定。
在一种实施例中，计算出偏置数据后，可以通过跟该款无人飞行器所支持的预设阈值(即偏置范围)进行比较，告知用户负载的安装位置是否超过预设阈值，使得无人飞行器能够自行检测是否支持该负载安装，或者负载安装的位置是否合理。
在一些实施例中，处理器402还用于记录预设时间段内的控制状态量， 并根据预设时间段内的控制状态量进行无人飞行器的重心校准。
在该实施例中，在一段时间内记录为消除重心偏置而输出的各控制状态量，统计一段时间内的控制状态量后可通过求取平均值等方法消除控制状态量的随机误差，以消除诸如风或飞机振动而引入的干扰，然后再计算出偏置数据，提高计算偏置数据的准确性。
在一些实施例中，处理器402还用于获取无人飞行器的状态数据，并判断状态数据是否满足重心校准条件，当状态数据满足重心校准条件时，根据控制状态量进行无人飞行器的重心校准。
在一些实施例中，状态数据包括以下一种或其组合：定位数据、图像数据、姿态数据、加速度数据、角速度数据。
在一些实施例中，重心校准条件包括无人飞行器处于平衡状态。
在一些实施例中，重心校准条件还包括无人飞行器的惯性测量单元已进行数据校准。
在该实施例中，在进行无人飞行器的重心校准前，需判断状态数据是否满足允许重心校准的条件，例如，重心校准条件为无人飞行器是否处于平衡状态，只有在无人飞行器处于平衡状态时进行的重心校准才是准确的，其中平衡状态包括悬停模式、定位模式下航向转动过程中水平位置静止的模式。重心校准条件还可以为无人飞行器的惯性测量单元已进行数据校准，在无人飞行器处于平衡状态的基础上保证惯性测量单元获取的数据均为准确数据，由此提高重心校准的准确性。
在一些实施例中，处理器402还用于获取无人飞行器的周围环境数据，并判断周围环境数据是否满足重心校准条件；当周围环境数据满足重心校准条件时，进入根据所述控制状态量进行无人飞行器的重心校准的步骤。
在一些实施例中，周围环境数据包括周围环境气流或周围环境风速。
在一些实施例中，重心校准条件包括无人飞行器所处环境的风速小于预设风速。
在该实施例中，周围环境数据可以根据无人机的姿态得到，也可以根据其他外部传感器，例如风力计或者从云端气象站得到的信息获取。在周围环境为无风环境时不会给无人飞行器带来气流干扰的外力，避免无人飞 行器的重心校准出现干扰。
在具体实施例中，重心校准条件可以包括：
(1)无人飞行器具备定位悬停能力：在上述的算法中，都是在假设无人飞行器已经处于平衡状态，也就是只有当无人飞行器处于静止状态时，上述推导过程才能够成立，由于依靠人来维持多选翼的无人飞行器的平衡十分困难，因此要求无人飞行器必须具备无需手动操作的定位悬停能力。进一步地，可通过定位数据、图像数据、姿态数据等判断无人飞行器是否处于平衡状态，例如，可以通过定位装置(如全球定位系统GPS、载波相位差分技术RTK等)获取无人飞行器的位置信息，当获取的无人飞行器的位置未发生变化时可以认为无人飞行器处于悬停状态；或者也可以在一定时间间隔内通过视觉传感器获取无人飞行器的周围环境的多张图像，并对获取的多张图像进行图像处理，当获取的图像中的物体位置未发生变化时可以认为无人飞行器处于悬停状态；或者还可以通过惯性测量单元(IMU)获取无人飞行器的加速度、速度信息，当无人飞行器的加速度与速度为零时，可以认为无人飞行器处于悬停状态，在其他实施方式中，也可以通过上述判断方式中的一种或几种的数据融合进行判断，以提高判断的准确度。
(2)周围气流稳定且无风：当周围环境风速较大，无人飞行器还会受到气流干扰带来的外力，使得无人飞行器即使处于定位悬停状态，由于引入了新的难以估算且无法忽视的外力，上述的公式推导也将失效，因此要求进行校准的环境必须是无风的平静气流环境。可根据无人飞行器倾斜角度数据等判断无人飞行器是否处于无风环境，获取设置风力采集装置来判断。
(3)无人飞行器的IMU(惯性测量单元)校准正确：IMU必须已经通过校准消除了由于温度等带来的稳态误差，否则该误差会被上述算法认为是重心偏置引发的。现在常见的无人飞行器都具备IMU校准功能，推荐在每次进行重心校准之前，进行IMU的重新校准。
在一些实施例中，无人飞行器距离地面的距离大于预设距离。在该实施例中，保证无人飞行器距离地面预设距离，例如距离地面有2米以上的高度，以减小地面所带来的紊流影响。
在一些实施例中，处理器402还用于当不满足重心校准条件时，停止校准，并发送第一指令至控制终端。在该实施例中，第一指令包括不满足重心校准条件的原因和调整建议信息。
在一些实施例中，处理器402还用于当校准失败时，停止校准，并发送第二指令至控制终端。在该实施例中，在该实施例中，第二指令包括校准失败原因。
采用本申请的技术方案，可获得当前无人飞行器的实际重心位置与标准位置的偏差，从而能根据这一偏差而消除重心位置偏差造成的飞行品质的下降，本申请的技术方案对于用户来说简单方便，可操作性强，并且能够更大限度地提升无人飞行器的负载适配能力，用户可以适配自己的负载到无人飞行器机架上而不用担心飞行品质的恶化，使得无人飞行器支持第三方负载的能力有明显的提高。
本申请第三方面的实施例，提出了一种无人飞行器，图5示出了本申请的一个实施例的无人飞行器50的示意图。其中，该无人飞行器50包括：
控制器502，用于获取目标飞行数据和当前飞行数据，并根据目标飞行数据和当前飞行数据确定控制状态量；以及根据控制状态量进行无人飞行器的重心校准。
在一种实施例中，所述控制状态量包括至少四个控制状态量：总拉力命令、偏航轴扭矩命令、俯仰轴扭矩命令、横滚轴扭矩命令。具体地，控制器502获取无人飞行器50的目标飞行数据和当前飞行数据，在控制无人飞行器50飞行过程中，根据目标飞行数据和当前飞行数据给出至少四个控制状态量：总拉力命令、偏航轴扭矩命令、俯仰轴扭矩命令、横滚轴扭矩命令。进一步地，无人飞行器包括动力装置，该动力装置可以诸如是至少一个电机，上述四个控制状态量对应于无人飞行器50因为各个电机而受到的力和力矩，也就是总拉力、偏航轴扭矩、俯仰轴扭矩、横滚轴扭矩。进一步地，根据控制状态量进行无人飞行器50的重心校准。进一步地，根据控制状态量获得无人飞行器50的重心与无人飞行器50的拉力中心的偏差。
在一些实施例中，控制器502可以包括一个或多个微处理器。
在一些实施例中，控制器502根据控制状态量进行无人飞行器的重心 校准包括：根据控制状态量，计算无人飞行器的重心与无人飞行器的拉力中心的偏置数据。
在一些实施例中，偏置数据包括以下一种或其组合：偏置位置、偏置质量、偏置力、偏置力矩。
在该实施例中，根据控制状态量计算得到无人飞行器的重心与无人飞行器的拉力中心的偏置数据，即无人飞行器的实际重心位置与标准位置的偏差，偏置数据可以为偏置位置、偏置质量、偏置力、偏置力矩等数据。
在一种实施例中，无人飞行器的飞行控制系统如图6所示，包括飞行控制器602、电机604、推进机构606(例如螺旋桨)、传感器608，通过飞行控制系统来实现无人飞行器的稳定与操纵，具体地，遥控器或者上位机的速度指令或者位置指令作为目标飞行状态输入至飞行控制器602，传感器608获取当前飞行状态并发送至飞行控制器602，飞行控制器602根据当前飞行状态和目标飞行状态进行计算分析，生成指令并发送至电机604，电机604带动推进机构606对无人飞行器姿态进行调整。其中，传感器608可以为推进机构606、电机604等无人飞行器部件的传感器，也可以设置在无人飞行器其他合适位置，用于获取无人飞行器的当前飞行状态。
在控制无人飞行器飞行过程中会持续的给出至少四个控制状态量：总拉力命令T c、偏航轴扭矩命令τ zc、俯仰轴扭矩命令τ yc、横滚轴扭矩命令τ xc，这四个控制状态量对应于无人机最终将因为各个电机的转速而受到的力和力矩，也就是总拉力T、偏航轴扭矩τ z、俯仰轴扭矩τ y、横滚轴扭矩τ x。
定义所有电机位置围绕出的正多边形的外接圆的圆心为等效拉力中心。如图2所示，以四旋翼无人飞行器为例，包括四个电机，O点即为该四旋翼无人飞行器的等效拉力中心，根据力的平移定理，可以将所有电机的拉力等效于作用等效拉力中心上的总拉力T加上两个绕水平轴的力矩τ x、τ y。
当无人飞行器的重心与拉力重心完全重合时，根据二力平衡法则，只需要满足拉力等于重力，即T＝G，可以维持无人飞行器的平衡，此时无人飞行器的两个水平旋转轴上的力矩将接近于零。但是若无人飞行器的重心与等效拉力中心不重合，则用户还需手动调节无人飞行器力矩才能维持平 衡。以横滚方向上的不重合为例，可做受力分析图如图3所示，根据刚体受力平衡法则，当无人飞行器维持悬停的稳定状态时，同样地，必然有
T＝G                   (1)
T×d y+τ x＝0           (2)
在无人飞行器已达到稳定状态时，有
T＝T c                    (3)
τ x＝τ xc                (4)
因此可以得到d y＝-τ xc/T c，同理可得d x＝-τ yc/T c。因此，在无人飞行器保持悬停的情况下，无人飞行器的飞控系统可以利用上述公式计算出当前挂载下无人飞行器重心相对桨面中心的水平位置，即偏置距离。
当然，偏置数据不限于偏置距离，在其他实施例中，偏置数据可以包括以下一种或其组合：偏置位置、偏置质量、偏置力、偏置力矩。例如，对于一些建模不够准确的无人飞行器，估计的重心偏置量不一定是真实偏置距离，而是垂直通道到各转动通道的控制补偿值，例如偏置质量、偏置力、偏置力矩等数据。本实施例仅为示例性说明，在此不作限定。
在一些实施例中，无人飞行器50还包括：存储器504，用于存储偏置数据。
在该实施例中，在标定出偏置数据后，可将该偏置数据保存到Flash、EEPROM等非易失存储器，在承载相同负载的情况下，无人飞行器每次在上电后都加载该偏置数据，在每次起飞时无人飞行器都能根据该偏置数据前馈控制，使得等效拉力中心也作用于实际的重心上，这样的提前补偿就能消除前述的“起飞点头”问题。
在一些实施例中，存储器504可以为串行存储器，或者并行存储器。存储器404可以为RAM存储器，或者ROM存储器。
在一些实施例中，控制器502还用于根据偏置数据生成控制分量，并根据控制分量控制无人飞行器的动力装置。
在该实施例中，根据偏置数据生成控制分量，根据控制分量控制无人飞行器的动力装置，以减小偏置数据，使无人飞行器稳定飞行，提升飞行品质。飞控系统能更加准确的分配各个控制通道的控制量，降低通道间的 耦合量。例如，在每次起飞时无人飞行器50的控制器502就能根据存储的偏置数据通过前馈控制，准确分配各个动力装置的拉力，使得等效拉力中心也作用于实际的重心上，这样的提前补偿就能消除前述的“起飞点头”问题。或者在无人飞行器50飞行的过程中准确分配各个动力装置的拉力，使得等效拉力中心也作用于实际的重心上，保证飞行品质。
在一些实施例中，控制器502还用于将偏置数据与预设阈值进行比较，根据比较结果确定无人飞行器的负载安装位置是否超过规定安装范围。
在一些实施例中，控制器502根据比较结果确定无人飞行器的负载安装位置是否超过规定安装范围包括：在比较结果为偏置数据大于等于预设阈值的情况下，确定无人飞行器的负载安装位置超过规定安装范围；在比较结果为偏置数据小于预设阈值的情况下，确定无人飞行器的负载安装位置未超过规定安装范围。可以理解，在其他实施方式中，也可以按照其他合适的预先设置的规则来根据比较结果确定无人飞行器的负载安装位置是否超过规定安装范围；例如，在比较结果为偏置数据大于预设阈值的情况下，确定无人飞行器的负载安装位置超过规定安装范围；在比较结果为偏置数据小于或等于预设阈值的情况下，确定无人飞行器的负载安装位置未超过规定安装范围，在此不作限定。
在一种实施例中，计算出偏置数据后，可以通过跟该款无人飞行器所支持的预设阈值(即偏置范围)进行比较，告知用户负载的安装位置是否超过预设阈值，使得无人飞行器能够自行检测是否支持该负载安装，或者负载安装的位置是否合理。
在一些实施例中，控制器502还用于记录预设时间段内的控制状态量，并根据预设时间段内的控制状态量进行无人飞行器的重心校准。
在该实施例中，在一段时间内记录为消除重心偏置而输出的各控制状态量，统计一段时间内的控制状态量后可通过求取平均值等方法消除控制状态量的随机误差，以消除诸如风或飞机振动而引入的干扰，然后再计算出偏置数据，提高计算偏置数据的准确性。
在一些实施例中，控制器502还用于获取无人飞行器的状态数据，并判断状态数据是否满足重心校准条件；当状态数据满足重心校准条件时， 根据控制状态量进行无人飞行器的重心校准。
在一些实施例中，状态数据包括以下一种或其组合：定位数据、图像数据、姿态数据、加速度数据、角速度数据。
在一些实施例中，重心校准条件包括无人飞行器处于平衡状态、无人飞行器所处环境的风速小于预设风速、无人飞行器的惯性测量单元已进行数据校准。
在一些实施例中，重心校准条件还包括无人飞行器的惯性测量单元已进行数据校准。
在该实施例中，在进行无人飞行器的重心校准前，需判断状态数据是否满足允许重心校准的条件，例如，重心校准条件为无人飞行器是否处于平衡状态，只有在无人飞行器处于平衡状态时进行的重心校准才是准确的，其中平衡状态包括悬停模式、定位模式下航向转动过程中水平位置静止的模式。重心校准条件还可以为无人飞行器的惯性测量单元已进行数据校准，在无人飞行器处于平衡状态的基础上保证惯性测量单元获取的数据均为准确数据，由此提高重心校准的准确性。
在一些实施例中，控制器502还用于获取无人飞行器的周围环境数据，并判断周围环境数据是否满足重心校准条件；当周围环境数据满足重心校准条件时，进入根据所述控制状态量进行无人飞行器的重心校准的步骤。
在一些实施例中，周围环境数据包括周围环境气流或周围环境风速。
在一些实施例中，重心校准条件包括无人飞行器所处环境的风速小于预设风速。
在该实施例中，周围环境数据可以根据无人机的姿态得到，也可以根据其他外部传感器，例如风力计或者从云端气象站得到的信息获取。在周围环境为无风环境时不会给无人飞行器带来气流干扰的外力，避免无人飞行器的重心校准出现干扰。
在具体实施例中，重心校准条件可以包括：
(1)无人飞行器具备定位悬停能力：在上述的算法中，都是在假设无人飞行器已经处于平衡状态，也就是只有当无人飞行器处于静止状态时，上述推导过程才能够成立，由于依靠人来维持多选翼的无人飞行器的平衡 十分困难，因此要求无人飞行器必须具备无需手动操作的定位悬停能力。进一步地，可通过定位数据、图像数据、姿态数据等判断无人飞行器是否处于平衡状态，例如，可以通过定位装置(如全球定位系统GPS、载波相位差分技术RTK等)获取无人飞行器的位置信息，当获取的无人飞行器的位置未发生变化时可以认为无人飞行器处于悬停状态；或者也可以在一定时间间隔内通过视觉传感器获取无人飞行器的周围环境的多张图像，并对获取的多张图像进行图像处理，当获取的图像中的物体位置未发生变化时可以认为无人飞行器处于悬停状态；或者还可以通过惯性测量单元(IMU)获取无人飞行器的加速度、速度信息，当无人飞行器的加速度与速度为零时，可以认为无人飞行器处于悬停状态，在其他实施方式中，也可以通过上述判断方式中的一种或几种的数据融合进行判断，以提高判断的准确度。
(2)周围气流稳定且无风：当周围环境风速较大，无人飞行器还会受到气流干扰带来的外力，使得无人飞行器即使处于定位悬停状态，由于引入了新的难以估算且无法忽视的外力，上述的公式推导也将失效，因此要求进行校准的环境必须是无风的平静气流环境。可根据无人飞行器倾斜角度数据等判断无人飞行器是否处于无风环境，获取设置风力采集装置来判断。
(3)无人飞行器的IMU(惯性测量单元)校准正确：IMU必须已经通过校准消除了由于温度等带来的稳态误差，否则该误差会被上述算法认为是重心偏置引发的。现在常见的无人飞行器都具备IMU校准功能，推荐在每次进行重心校准之前，进行IMU的重新校准。
在一些实施例中，无人飞行器距离地面的距离大于预设距离。在该实施例中，保证无人飞行器距离地面预设距离，例如距离地面有2米以上的高度，以减小地面所带来的紊流影响。
在一些实施例中，控制器502还用于当不满足所述重心校准条件时，停止校准，并发送第一指令至控制终端。在该实施例中，第一指令包括不满足重心校准条件的原因和调整建议信息。
在一些实施例中，控制器502还用于当校准失败时，停止校准，并发送第二指令至控制终端。在该实施例中，在该实施例中，第二指令包括校 准失败原因。
采用本申请的技术方案，可获得当前无人飞行器的实际重心位置与标准位置的偏差，从而能根据这一偏差而消除重心位置偏差造成的飞行品质的下降，本申请的技术方案对于用户来说简单方便，可操作性强，并且能够更大限度地提升无人飞行器的负载适配能力，用户可以适配自己的负载到无人飞行器机架上而不用担心飞行品质的恶化，使得无人飞行器支持第三方负载的能力有明显的提高。
本申请第四方面的实施例，提出了一种无人飞行器的系统，图7示出了本申请的一个实施例的无人飞行器的系统70的示意图。其中，该无人飞行器的系统70包括：
控制终端702，用于向无人飞行器发送重心校准指令；
无人飞行器704，用于根据重心校准指令进行重心校准，得到校准结果。
在该实施例中，用户在需要使用无人飞行器704进行负载时，通过控制终端702向无人飞行器704发送重心校准指令，无人飞行器704接收该重心校准指令，实现重心校准得到校准结果，校准结果可包括：校准成功、校准失败、校准数据等。
在一些实施例中，无人飞行器704还用于将校准结果发送至控制终端。
在一些实施例中，控制终端702还包括显示装置，显示装置用于对校准结果进行显示。
在该实施例中，控制终端702的显示装置上可显示出校准结果，保证用户直观地获取到该校准结果。
在一些实施例中，无人飞行器704根据重心校准指令进行重心校准包括：根据重心校准指令获取目标飞行数据和当前飞行数据，并根据目标飞行数据和当前飞行数据确定控制状态量，根据控制状态量进行无人飞行器704的重心校准。
在该实施例中，所述控制状态量包括至少四个控制状态量：总拉力命令、偏航轴扭矩命令、俯仰轴扭矩命令、横滚轴扭矩命令。具体地，获取无人飞行器704的目标飞行数据和当前飞行数据，在控制无人飞行器704 飞行过程中，根据目标飞行数据和当前飞行数据给出至少四个控制状态量：总拉力命令、偏航轴扭矩命令、俯仰轴扭矩命令、横滚轴扭矩命令。进一步地，无人飞行器704包括动力装置，该动力装置可以诸如是至少一个电机，上述四个控制状态量对应于无人飞行器704因为各个电机的转速而受到的力和力矩，也就是总拉力、偏航轴扭矩、俯仰轴扭矩、横滚轴扭矩。进一步地，根据控制状态量进行无人飞行器704的重心校准。进一步地，根据控制状态量获得无人飞行器704的重心与无人飞行器704的拉力中心的偏差，从而能根据这一偏差而消除重心位置偏差造成的飞行品质的下降。
在一些实施例中，无人飞行器704根据控制状态量进行无人飞行器的重心校准包括：根据控制状态量，计算无人飞行器的重心与无人飞行器的拉力中心的偏置数据。
在一些实施例中，偏置数据包括以下一种或其组合：偏置位置、偏置质量、偏置力、偏置力矩。
在该实施例中，根据控制状态量计算得到无人飞行器的重心与无人飞行器的拉力中心的偏置数据，即无人飞行器的实际重心位置与标准位置的偏差，偏置数据可以为偏置位置、偏置质量、偏置力、偏置力矩等数据。
在一种实施例中，无人飞行器的飞行控制器在控制无人飞行器飞行过程中会持续的给出至少四个控制状态量：总拉力命令T c、偏航轴扭矩命令τ zc、俯仰轴扭矩命令τ yc、横滚轴扭矩命令τ xc，这四个控制状态量对应于无人机最终将因为各个电机的转速而受到的力和力矩，也就是总拉力T、偏航轴扭矩τ z、俯仰轴扭矩τ y、横滚轴扭矩τ x。
定义所有电机位置围绕出的正多边形的外接圆的圆心为等效拉力中心。如图2所示，以四旋翼无人飞行器为例，包括四个电机，O点即为该四旋翼无人飞行器的等效拉力中心，根据力的平移定理，可以将所有电机的拉力等效于作用等效拉力中心上的总拉力T加上两个绕水平轴的力矩τ x、τ y。
当无人飞行器的重心与拉力重心完全重合时，根据二力平衡法则，只需要满足拉力等于重力，即T＝G，可以维持无人飞行器的平衡，此时无人飞行器的两个水平旋转轴上的力矩将接近于零。但是若无人飞行器的重心 与等效拉力中心不重合，则用户还需手动调节无人飞行器力矩才能维持平衡。以横滚方向上的不重合为例，可做受力分析图如图3所示，根据刚体受力平衡法则，当无人飞行器维持悬停的稳定状态时，同样地，必然有
T＝G                     (1)
T×d y+τ x＝0             (2)
在无人飞行器已达到稳定状态时，有
T＝T c                     (3)
τ x＝τ xc                 (4)
因此可以得到d y＝-τ xc/T c，同理可得d x＝-τ yc/T c。因此，在无人飞行器保持悬停的情况下，无人飞行器的飞控系统可以利用上述公式计算出当前挂载下无人飞行器重心相对桨面中心的水平位置，即偏置距离。
当然，偏置数据不限于偏置距离，在其他实施例中，偏置数据可以包括以下一种或其组合：偏置位置、偏置质量、偏置力、偏置力矩。例如，对于一些建模不够准确的无人飞行器，估计的重心偏置量不一定是真实偏置距离，而是垂直通道到各转动通道的控制补偿值，例如偏置质量、偏置力、偏置力矩等数据。本实施例仅为示例性说明，在此不作限定。
在一些实施例中，无人飞行器704还用于存储偏置数据。
在该实施例中，在计算得到无人飞行器704的重心与无人飞行器704的拉力中心的偏置数据后，可将该偏置数据保存到Flash、EEPROM等非易失存储器中，在承载相同负载的情况下，无人飞行器704每次在上电后都加载该偏置数据，在每次起飞时无人飞行器都能根据该偏置数据前馈控制，使得等效拉力中心也作用于实际的重心上，这样的提前补偿就能消除前述的“起飞点头”问题。
在一些实施例中，控制终端702还用于存储偏置数据，以及将偏置数据发送至所述无人飞行器。在该实施例中，偏置数据也可以存储在控制终端702上，控制终端702在发送重心校准指令的时候，可直接发送偏置数据至无人飞行器704。
在一些实施例中，无人飞行器704还用于根据偏置数据生成控制分量，并根据控制分量控制无人飞行器704的动力装置。
在该实施例中，根据偏置数据生成控制分量，根据控制分量控制无人飞行器的动力装置，以减小偏置数据，使无人飞行器稳定飞行，提升飞行品质。无人飞行器704能更加准确的分配各个控制通道的控制量，降低通道间的耦合量。例如，在每次起飞时无人飞行器704的控制系统就能根据存储的偏置数据通过前馈控制，准确分配各个动力装置的拉力，使得等效拉力中心也作用于实际的重心上，这样的提前补偿就能消除前述的“起飞点头”问题。或者在无人飞行器704飞行的过程中准确分配各个动力装置的拉力，使得等效拉力中心也作用于实际的重心上，保证飞行品质。
在一些实施例中，无人飞行器704还用于将偏置数据与预设阈值进行比较，根据比较结果确定无人飞行器的负载安装位置是否超过规定安装范围。
在一些实施例中，无人飞行器704根据比较结果确定无人飞行器的负载安装位置是否超过规定安装范围包括：在比较结果为偏置数据大于或等于预设阈值的情况下，确定无人飞行器704的负载安装位置超过规定安装范围；在比较结果为偏置数据小于预设阈值的情况下，确定无人飞行器704的负载安装位置未超过规定安装范围。可以理解，在其他实施方式中，也可以按照其他合适的预先设置的规则来根据比较结果确定无人飞行器的负载安装位置是否超过规定安装范围；例如，在比较结果为偏置数据大于预设阈值的情况下，确定无人飞行器的负载安装位置超过规定安装范围；在比较结果为偏置数据小于或等于预设阈值的情况下，确定无人飞行器的负载安装位置未超过规定安装范围，在此不作限定。
在一种实施例中，计算出偏置数据后，可以通过跟该款无人飞行器704所支持的预设阈值(即偏置范围)进行比较，告知用户负载的安装位置是否超过预设阈值，使得无人飞行器704能够自行检测是否支持该负载安装，或者负载安装的位置是否合理。
在一些实施例中，无人飞行器704还用于将负载安装位置是否超过规定安装范围的结果发送至控制终端702；显示装置还用于对负载安装位置是否超过规定安装范围的结果进行显示。
在该实施例中，控制终端702对负载安装位置是否超过规定安装范围 的结果进行显示，以提醒用户调整负载安装位置。
在一些实施例中，无人飞行器704还用于记录预设时间段内的控制状态量，并根据预设时间段内的控制状态量进行无人飞行器704的重心校准。
在该实施例中，在一段时间内记录为消除重心偏置而输出的各控制状态量，统计一段时间内的控制状态量后可通过求取平均值等方法消除控制状态量的随机误差，以消除诸如风或飞机振动而引入的干扰，然后再计算出偏置数据，提高计算偏置数据的准确性。
在一些实施例中，无人飞行器704的提示装置在根据重心校准指令进行重心校准的过程中发出校准提示信息。
在该实施例中，为了让用户实时了解进度，可以通过无人飞行器状态灯闪特殊颜色、发出设定的声音等方式来向用户报告状态。
在一些实施例中，无人飞行器704还用于获取状态数据，并判断状态数据是否满足重心校准条件，当状态数据满足重心校准条件时根据重心校准指令进行重心校准。
在一些实施例中，无人飞行器704还用于向控制终端702发送校准进度信息。例如，通过在控制终端702的app上显示进度条的方法来向用户报告校准状态。
在一些实施例中，状态数据包括以下一种或其组合：定位数据、图像数据、姿态数据、加速度数据、角速度数据。
在一些实施例中，重心校准条件包括无人飞行器处于平衡状态。
在一些实施例中，重心校准条件还包括无人飞行器的惯性测量单元已进行数据校准。
在该实施例中，在进行无人飞行器的重心校准前，需判断状态数据是否满足允许重心校准的条件，例如，重心校准条件为无人飞行器是否处于平衡状态，只有在无人飞行器处于平衡状态时进行的重心校准才是准确的，其中平衡状态包括悬停模式、定位模式下航向转动过程中水平位置静止的模式。重心校准条件还可以为无人飞行器的惯性测量单元已进行数据校准，在无人飞行器处于平衡状态的基础上保证惯性测量单元获取的数据均为准确数据，由此提高重心校准的准确性。
在一些实施例中，无人飞行器704还用于获取无人飞行器的周围环境数据，并判断周围环境数据是否满足重心校准条件，当周围环境数据满足重心校准条件时，根据控制状态量进行无人飞行器的重心校准。
在一些实施例中，周围环境数据包括周围环境气流或周围环境风速。
在一些实施例中，重心校准条件包括无人飞行器所处环境的风速小于预设风速。
在该实施例中，周围环境数据可以根据无人机的姿态得到，也可以根据其他外部传感器，例如风力计或者从云端气象站得到的信息获取。在周围环境为无风环境时不会给无人飞行器带来气流干扰的外力，避免无人飞行器的重心校准出现干扰。
在具体实施例中，重心校准条件可以包括：
(1)无人飞行器具备定位悬停能力：在上述的算法中，都是在假设无人飞行器已经处于平衡状态，也就是只有当无人飞行器处于静止状态时，上述推导过程才能够成立，由于依靠人来维持多选翼的无人飞行器的平衡十分困难，因此要求无人飞行器必须具备无需手动操作的定位悬停能力。进一步地，可通过定位数据、图像数据、姿态数据等判断无人飞行器是否处于平衡状态，例如，可以通过定位装置(如全球定位系统GPS、载波相位差分技术RTK等)获取无人飞行器的位置信息，当获取的无人飞行器的位置未发生变化时可以认为无人飞行器处于悬停状态；或者也可以在一定时间间隔内通过视觉传感器获取无人飞行器的周围环境的多张图像，并对获取的多张图像进行图像处理，当获取的图像中的物体位置未发生变化时可以认为无人飞行器处于悬停状态；或者还可以通过惯性测量单元(IMU)获取无人飞行器的加速度、速度信息，当无人飞行器的加速度与速度为零时，可以认为无人飞行器处于悬停状态，在其他实施方式中，也可以通过上述判断方式中的一种或几种的数据融合进行判断，以提高判断的准确度。
(2)周围气流稳定且无风：当周围环境风速较大，无人飞行器还会受到气流干扰带来的外力，使得无人飞行器即使处于定位悬停状态，由于引入了新的难以估算且无法忽视的外力，上述的公式推导也将失效，因此要求进行校准的环境必须是无风的平静气流环境。可根据无人飞行器倾斜角 度数据等判断无人飞行器是否处于无风环境，获取设置风力采集装置来判断。
(3)无人飞行器的IMU(惯性测量单元)校准正确：IMU必须已经通过校准消除了由于温度等带来的稳态误差，否则该误差会被上述算法认为是重心偏置引发的。现在常见的无人飞行器都具备IMU校准功能，推荐在每次进行重心校准之前，进行IMU的重新校准。
在一些实施例中，无人飞行器704距离地面的距离大于预设距离。在该实施例中，保证无人飞行器距离地面预设距离，例如距离地面有2米以上的高度，以减小地面所带来的紊流影响。
在一些实施例中，无人飞行器704还用于当状态数据不满足重心校准条件时，停止校准，并发送第一指令至所述控制终端702。可通过控制终端702的显示装置显示状态数据不满足重心校准条件的信息(例如无人飞行器未处于平衡状态)和调整建议信息(例如请调整无人飞行器悬停状态)。
在一些实施例中，第一指令包括不满足所述重心校准条件的原因和调整建议信息。
在一些实施例中，无人飞行器704还用于当校准失败时，停止校准，并发送第二指令至所述控制终端702。
在一些实施例中，第二指令包括校准失败原因。
在一些实施例中，无人飞行器704在根据重心校准指令进行重心校准的过程中，若状态数据不满足重心校准条件，则停止校准，并发送第一指令至控制终端702。
在该实施例中，如果在校准过程中用户进行了操作或者因为传感器精度有限导致数据收敛性很差，将可能会提前中断校准操作，并通过控制终端702的app向用户反馈校准失败以及失败的原因。
采用本申请的技术方案，可获得当前无人飞行器的实际重心位置与标准位置的偏差，从而能根据这一偏差而消除重心位置偏差造成的飞行品质的下降，本申请的技术方案对于用户来说简单方便，可操作性强，并且能够更大限度地提升无人飞行器的负载适配能力，用户可以适配自己的负载到无人飞行器机架上而不用担心飞行品质的恶化，使得无人飞行器支持第 三方负载的能力有明显的提高。
图8示出了本申请的一个实施例的重心校准操作的交互实现示意图。其中，该交互实现步骤包括：
(1)用户操作无人飞行器完成起飞操作，并使无人飞行器进入定位悬停模式，同时要保证无人飞行器距离地面有2米以上的高度，以减小地面所带来的紊流影响；
(2)无人飞行器在收到触发命令后，将检查当前状态与环境是否可以进行重心校准操作，例如如果无人飞行器检测到悬停时姿态输出不为0，则无人飞行器将向终端app反馈当前无法进行重心校准，并提醒用户进行IMU校准并移至无风环境下重新出发操作。如果通过所有检查，无人飞行器将自动进入重心校准过程；
(3)无人飞行器将在一段时间内，记录控制器为消除重心偏置而输出的各控制量，统计一段时间内的数据后可通过平均等方法消除随机误差，然后利用上述算法计算出重心水平偏置估计值。为了让用户实时了解进度，可以通过无人飞行器状态灯闪特殊颜色灯或者终端app上实时显示进度条的方法来向用户报告状态；
(4)如果在校准过程中用户进行了操作或者因为传感器精度有限导致数据收敛性很差，将可能会提前中断校准操作，并通过终端app向用户反馈校准失败以及失败的原因。
(5)在飞控系统计算出收敛的估计值后，将通过终端app向用户告知校准成功，并将该值保存在非易失存储器中以供之后承载相同负载时的飞行继续使用。
(6)至此，完成整个重心校准过程。
其中，该算法估计出重心偏置值后，可以通过跟重心校准过程中的该款无人飞行器所支持的偏置范围进行比较，告知用户的安装位置是否超过规定范围，使得无人飞行器能够自行检测是否支持该负载。
重心校准的交互终端可以是终端app、遥控器、上位机等终端，本申请不做限制。
在其他实施例中，如果无人飞行器的定位精度非常高，也可以在室内 或非空旷场景下进行该无人飞行器的重心校准。
本申请实施例适用于负载实时变化的无人飞行器，例如对于油动无人飞行器、植保无人飞行器等负载实时变动的情况，无人飞行器的飞行控制器可以实时进行重心校准，以适配实时变动的负载，确保飞行的平稳与安全，并提高用户的使用体验。进一步地，当无人飞行器处于悬停状态时，更新计算出当前的重心偏置水平，在危险情况下可以提醒用户。
本申请第五方面的实施例，提出了一种计算机存储介质，计算机存储介质中存储有程序指令，程序指令用于实现：获取目标飞行数据和当前飞行数据，并根据目标飞行数据和当前飞行数据确定控制状态量；以及根据控制状态量进行无人飞行器的重心校准。
在该实施例中，所述控制状态量包括至少四个控制状态量：总拉力命令、偏航轴扭矩命令、俯仰轴扭矩命令、横滚轴扭矩命令。具体地，获取无人飞行器的目标飞行数据和当前飞行数据，在控制无人飞行器飞行过程中，根据目标飞行数据和当前飞行数据给出至少四个控制状态量：总拉力命令、偏航轴扭矩命令、俯仰轴扭矩命令、横滚轴扭矩命令。进一步地，无人飞行器包括动力装置，该动力装置可以诸如是至少一个电机，上述四个控制状态量对应于无人飞行器因为各个电机而受到的力和力矩，也就是总拉力、偏航轴扭矩、俯仰轴扭矩、横滚轴扭矩。进一步地，根据控制状态量进行无人飞行器的重心校准。进一步地，根据控制状态量获得无人飞行器的重心与无人飞行器的拉力中心的偏差。
在一些实施例中，所述计算机存储介质可以为易失性存储器，或者非易失性存储器。所述计算机存储介质也可以为串行存储器，或者并行存储器。所述计算机存储介质可以为RAM存储器，或者ROM存储器。
在一些实施例中，程序指令实现根据控制状态量进行无人飞行器的重心校准包括：根据控制状态量，计算无人飞行器的重心与无人飞行器的拉力中心的偏置数据。
在一些实施例中，偏置数据包括以下一种或其组合：偏置位置、偏置质量、偏置力、偏置力矩。
在该实施例中，根据控制状态量计算得到无人飞行器的重心与无人飞 行器的拉力中心的偏置数据，即无人飞行器的实际重心位置与标准位置的偏差，偏置数据可以为偏置位置、偏置质量、偏置力、偏置力矩等数据。
在一种实施例中，无人飞行器的飞行控制器在控制无人飞行器飞行过程中会持续的给出至少四个控制状态量：总拉力命令T c、偏航轴扭矩命令τ zc、俯仰轴扭矩命令τ yc、横滚轴扭矩命令τ xc，这四个控制状态量将对应于无人机最终将因为各个电机的转速而受到的力和力矩，也就是总拉力T、偏航轴扭矩τ z、俯仰轴扭矩τ y、横滚轴扭矩τ x。
定义所有电机位置围绕出的正多边形的外接圆的圆心为等效拉力中心。如图2所示，以四旋翼无人飞行器为例，包括四个电机，O点即为该四旋翼无人飞行器的等效拉力中心，根据力的平移定理，可以将所有电机的拉力等效于作用等效拉力中心上的总拉力T加上两个绕水平轴的力矩τ x、τ y。
当无人飞行器的重心与拉力重心完全重合时，根据二力平衡法则，只需要满足拉力等于重力，即T＝G，可以维持无人飞行器的平衡，此时无人飞行器的两个水平旋转轴上的力矩将接近于零。但是若无人飞行器的重心与等效拉力中心不重合，则用户还需手动调节无人飞行器力矩才能维持平衡。以横滚方向上的不重合为例，可做受力分析图如图3所示，根据刚体受力平衡法则，当无人飞行器维持悬停的稳定状态时，同样地，必然有
T＝G                      (1)
T×d y+τ x＝0              (2)
在无人飞行器已达到稳定状态时，有
T＝T c                    (3)
τ x＝τ xc                (4)
因此可以得到d y＝-τ xc/T c，同理可得d x＝-τ yc/T c。因此，在无人飞行器保持悬停的情况下，无人飞行器的飞控系统可以利用上述公式计算出当前挂载下无人飞行器重心相对桨面中心的水平位置，即偏置距离。
当然，偏置数据不限于偏置距离，在其他实施例中，偏置数据可以包括以下一种或其组合：偏置位置、偏置质量、偏置力、偏置力矩。例如，对于一些建模不够准确的无人飞行器，估计的重心偏置量不一定是真实偏 置距离，而是垂直通道到各转动通道的控制补偿值，例如偏置质量、偏置力、偏置力矩等数据。本实施例仅为示例性说明，在此不作限定。
在一些实施例中，程序指令还用于实现：存储偏置数据。
在该实施例中，在标定出偏置数据后，可将该偏置数据保存到Flash、EEPROM等非易失存储器，在承载相同负载的情况下，无人飞行器每次在上电后都加载该偏置数据，在每次起飞时无人飞行器都能根据该偏置数据前馈控制，使得等效拉力中心也作用于实际的重心上，这样的提前补偿就能消除前述的“起飞点头”问题。
在一些实施例中，程序指令还用于实现：根据偏置数据得到控制分量，并根据控制分量控制无人飞行器的动力装置。
在该实施例中，根据偏置数据生成控制分量，根据控制分量控制无人飞行器的动力装置，以减小偏置数据，使无人飞行器稳定飞行，提升飞行品质。飞控系统能更加准确的分配各个控制通道的控制量，降低通道间的耦合量。例如，在每次起飞时无人飞行器的控制系统就能根据存储的偏置数据通过前馈控制，准确分配各个动力装置的拉力，使得等效拉力中心也作用于实际的重心上，这样的提前补偿就能消除前述的“起飞点头”问题。或者在无人飞行器飞行的过程中准确分配各个动力装置的拉力，使得等效拉力中心也作用于实际的重心上，保证飞行品质。
在一些实施例中，程序指令还用于实现：将偏置数据与预设阈值进行比较，根据比较结果确定无人飞行器的负载安装位置是否超过规定安装范围。
在一些实施例中，程序指令实现根据比较结果确定无人飞行器的负载安装位置是否超过规定安装范围包括：在比较结果为偏置数据大于等于预设阈值的情况下，确定无人飞行器的负载安装位置超过规定安装范围；在比较结果为偏置数据小于预设阈值的情况下，确定无人飞行器的负载安装位置未超过规定安装范围。可以理解，在其他实施方式中，也可以按照其他合适的预先设置的规则来根据比较结果确定无人飞行器的负载安装位置是否超过规定安装范围；例如，在比较结果为偏置数据大于预设阈值的情况下，确定无人飞行器的负载安装位置超过规定安装范围；在比较结果为 偏置数据小于或等于预设阈值的情况下，确定无人飞行器的负载安装位置未超过规定安装范围，在此不作限定。
在一种实施例中，计算出偏置数据后，可以通过跟该款无人飞行器所支持的预设阈值(即偏置范围)进行比较，告知用户负载的安装位置是否超过预设阈值，使得无人飞行器能够自行检测是否支持该负载安装，或者负载安装的位置是否合理。
在一些实施例中，程序指令还用于实现：记录预设时间段内的控制状态量，并根据预设时间段内的控制状态量进行无人飞行器的重心校准。
在该实施例中，在一段时间内记录为消除重心偏置而输出的各控制状态量，统计一段时间内的控制状态量后可通过求取平均值等方法消除控制状态量的随机误差，以消除诸如风或飞机振动而引入的干扰，然后再计算出偏置数据，提高计算偏置数据的准确性。
在一些实施例中，程序指令还用于实现：在根据控制状态量进行无人飞行器的重心校准的步骤之前，获取无人飞行器的状态数据，并判断状态数据是否满足重心校准条件；当状态数据满足重心校准条件时，进入根据控制状态量进行无人飞行器的重心校准的步骤。
在一些实施例中，状态数据包括以下一种或其组合：定位数据、图像数据、姿态数据、加速度数据、角速度数据。
在一些实施例中，重心校准条件包括无人飞行器处于平衡状态。
在一些实施例中，重心校准条件还包括无人飞行器的惯性测量单元已进行数据校准。
在该实施例中，在进行无人飞行器的重心校准前，需判断状态数据是否满足允许重心校准的条件例如，重心校准条件为无人飞行器是否处于平衡状态，只有在无人飞行器处于平衡状态时进行的重心校准才是准确的，其中平衡状态包括悬停模式、定位模式下航向转动过程中水平位置静止的模式。重心校准条件还可以为无人飞行器的惯性测量单元已进行数据校准，在无人飞行器处于平衡状态的基础上保证惯性测量单元获取的数据均为准确数据，由此提高重心校准的准确性。
在一些实施例中，程序指令还用于实现：获取无人飞行器的周围环境 数据，并判断周围环境数据是否满足重心校准条件；当周围环境数据满足重心校准条件时，进入根据所述控制状态量进行无人飞行器的重心校准的步骤。
在一些实施例中，周围环境数据包括周围环境气流或周围环境风速。
在一些实施例中，重心校准条件包括无人飞行器所处环境的风速小于预设风速。
在该实施例中，周围环境数据可以根据无人机的姿态得到，也可以根据其他外部传感器，例如风力计或者从云端气象站得到的信息获取。在周围环境为无风环境时不会给无人飞行器带来气流干扰的外力，避免无人飞行器的重心校准出现干扰。
在具体实施例中，重心校准条件可以包括：
(1)无人飞行器具备定位悬停能力：在上述的算法中，都是在假设无人飞行器已经处于平衡状态，也就是只有当无人飞行器处于静止状态时，上述推导过程才能够成立，由于依靠人来维持多选翼的无人飞行器的平衡十分困难，因此要求无人飞行器必须具备无需手动操作的定位悬停能力。进一步地，可通过定位数据、图像数据、姿态数据等判断无人飞行器是否处于平衡状态，例如，可以通过定位装置(如全球定位系统GPS、载波相位差分技术RTK等)获取无人飞行器的位置信息，当获取的无人飞行器的位置未发生变化时可以认为无人飞行器处于悬停状态；或者也可以在一定时间间隔内通过视觉传感器获取无人飞行器的周围环境的多张图像，并对获取的多张图像进行图像处理，当获取的图像中的物体位置未发生变化时可以认为无人飞行器处于悬停状态；或者还可以通过惯性测量单元(IMU)获取无人飞行器的加速度、速度信息，当无人飞行器的加速度与速度为零时，可以认为无人飞行器处于悬停状态，在其他实施方式中，也可以通过上述判断方式中的一种或几种的数据融合进行判断，以提高判断的准确度。
(2)周围气流稳定且无风：当周围环境风速较大，无人飞行器还会受到气流干扰带来的外力，使得无人飞行器即使处于定位悬停状态，由于引入了新的难以估算且无法忽视的外力，上述的公式推导也将失效，因此要求进行校准的环境必须是无风的平静气流环境。可根据无人飞行器倾斜角 度数据等判断无人飞行器是否处于无风环境，获取设置风力采集装置来判断。
(3)无人飞行器的IMU(惯性测量单元)校准正确：IMU必须已经通过校准消除了由于温度等带来的稳态误差，否则该误差会被上述算法认为是重心偏置引发的。现在常见的无人飞行器都具备IMU校准功能，推荐在每次进行重心校准之前，进行IMU的重新校准。
在一些实施例中，无人飞行器距离地面的距离大于预设距离。在该实施例中，保证无人飞行器距离地面预设距离，例如距离地面有2米以上的高度，以减小地面所带来的紊流影响。
在一些实施例中，程序指令还用于实现：当不满足重心校准条件时，停止校准，并发送第一指令至控制终端。在该实施例中，第一指令包括不满足重心校准条件的原因和调整建议信息。
在一些实施例中，程序指令还用于实现：当校准失败时，停止校准，并发送第二指令至控制终端。在该实施例中，在该实施例中，第二指令包括校准失败原因。
采用本申请的技术方案，可获得当前无人飞行器的实际重心位置与标准位置的偏差，从而能根据这一偏差而消除重心位置偏差造成的飞行品质的下降，本申请的技术方案对于用户来说简单方便，可操作性强，并且能够更大限度地提升无人飞行器的负载适配能力，用户可以适配自己的负载到无人飞行器机架上而不用担心飞行品质的恶化，使得无人飞行器支持第三方负载的能力有明显的提高。
在本说明书的描述中，术语“第一”、“第二”仅用于描述的目的，而不能理解为指示或暗示相对重要性，除非另有明确的规定和限定；术语“连接”、“安装”、“固定”等均应做广义理解，例如，“连接”可以是固定连接，也可以是可拆卸连接，或一体地连接；可以是直接相连，也可以通过中间媒介间接相连。对于本领域的普通技术人员而言，可以根据具体情况理解上述术语在本申请中的具体含义。
在本说明书的描述中，术语“一个实施例”、“一些实施例”、“具体实施例”等的描述意指结合该实施例或示例描述的具体特征、结构、材 料或特点包含于本申请的至少一个实施例或示例中。在本说明书中，对上述术语的示意性表述不一定指的是相同的实施例或实例。而且，描述的具体特征、结构、材料或特点可以在任何的一个或多个实施例或示例中以合适的方式结合。
以上所述仅为本申请的优选实施例而已，并不用于限制本申请，对于本领域的技术人员来说，本申请可以有各种更改和变化。凡在本申请的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本申请的保护范围之内。

Claims (101)

  1. 一种无人飞行器控制方法，其中，包括：
    获取目标飞行数据和当前飞行数据，并根据所述目标飞行数据和所述当前飞行数据确定控制状态量；以及
    根据所述控制状态量进行无人飞行器的重心校准。
  2. 根据权利要求1所述的无人飞行器控制方法，其中，所述根据所述控制状态量进行无人飞行器的重心校准的步骤包括：
    根据所述控制状态量，计算所述无人飞行器的重心与所述无人飞行器的拉力中心的偏置数据。
  3. 根据权利要求2所述的无人飞行器控制方法，其中，还包括：
    存储所述偏置数据。
  4. 根据权利要求2所述的无人飞行器控制方法，其中，还包括：
    根据所述偏置数据生成控制分量，并根据所述控制分量控制所述无人飞行器的动力装置。
  5. 根据权利要求2所述的无人飞行器控制方法，其中，还包括：
    将所述偏置数据与预设阈值进行比较，根据比较结果确定所述无人飞行器的负载安装位置是否超过规定安装范围。
  6. 根据权利要求5所述的无人飞行器控制方法，其中，所述根据比较结果确定所述无人飞行器的负载安装位置是否超过规定安装范围的步骤包括：
    在所述比较结果为所述偏置数据大于或等于所述预设阈值的情况下，确定所述无人飞行器的负载安装位置超过所述规定安装范围；
    在所述比较结果为所述偏置数据小于所述预设阈值的情况下，确定所述无人飞行器的负载安装位置未超过所述规定安装范围。
  7. 根据权利要求1所述的无人飞行器控制方法，其中，还包括：
    记录预设时间段内的控制状态量，并根据所述预设时间段内的控制状态量进行所述无人飞行器的重心校准。
  8. 根据权利要求1至7中任一项所述的无人飞行器控制方法，其中， 在所述根据所述控制状态量进行所述无人飞行器的重心校准的步骤之前还包括：
    获取所述无人飞行器的状态数据，并判断所述状态数据是否满足重心校准条件；
    当所述状态数据满足所述重心校准条件时，进入所述根据所述控制状态量进行所述无人飞行器的重心校准的步骤。
  9. 根据权利要求8所述的无人飞行器控制方法，其中，
    所述状态数据包括以下一种或其组合：定位数据、图像数据、姿态数据、加速度数据、角速度数据。
  10. 根据权利要求8所述的无人飞行器控制方法，其中，
    所述重心校准条件包括所述无人飞行器处于平衡状态。
  11. 根据权利要求10所述的无人飞行器控制方法，其中，
    所述重心校准条件还包括所述无人飞行器的惯性测量单元已进行数据校准。
  12. 根据权利要求8所述的无人飞行器控制方法，其中，还包括：
    获取所述无人飞行器的周围环境数据，并判断所述周围环境数据是否满足重心校准条件；
    当所述周围环境数据满足所述重心校准条件时，进入所述根据所述控制状态量进行所述无人飞行器的重心校准的步骤。
  13. 根据权利要求12所述的无人飞行器控制方法，其中，
    所述周围环境数据包括周围环境气流或周围环境风速。
  14. 根据权利要求12所述的无人飞行器控制方法，其中，
    所述重心校准条件包括所述无人飞行器所处环境的风速小于预设风速。
  15. 根据权利要求10所述的无人飞行器控制方法，其中，所述无人飞行器距离地面的距离大于预设距离。
  16. 根据权利要求8或12所述的无人飞行器控制方法，其中，当不满足所述重心校准条件时，停止校准，并发送第一指令至控制终端。
  17. 根据权利要求8或12所述的无人飞行器控制方法，其中，当校准 失败时，停止校准，并发送第二指令至控制终端。
  18. 根据权利要求2至6中任一项所述的无人飞行器控制方法，其中，所述偏置数据包括以下一种或其组合：偏置位置、偏置质量、偏置力、偏置力矩。
  19. 一种无人飞行器控制装置，其中，包括：
    处理器，用于获取目标飞行数据和当前飞行数据，根据所述目标飞行数据和所述当前飞行数据确定控制状态量，并根据所述控制状态量进行无人飞行器的重心校准。
  20. 根据权利要求19所述的无人飞行器控制装置，其中，所述处理器根据所述控制状态量进行无人飞行器的重心校准包括：
    根据所述控制状态量，计算所述无人飞行器的重心与所述无人飞行器的拉力中心的偏置数据。
  21. 根据权利要求20所述的无人飞行器控制装置，其中，还包括：
    存储器，用于存储所述偏置数据。
  22. 根据权利要求20所述的无人飞行器控制装置，其中，
    所述处理器还用于根据所述偏置数据生成控制分量，并根据所述控制分量控制所述无人飞行器的动力装置。
  23. 根据权利要求20所述的无人飞行器控制装置，其中，
    所述处理器还用于将所述偏置数据与预设阈值进行比较，根据比较结果确定所述无人飞行器的负载安装位置是否超过规定安装范围。
  24. 根据权利要求23所述的无人飞行器控制装置，其中，所述处理器根据比较结果确定所述无人飞行器的负载安装位置是否超过规定安装范围包括：
    在所述比较结果为所述偏置数据大于或等于所述预设阈值的情况下，确定所述无人飞行器的负载安装位置超过所述规定安装范围，在所述比较结果为所述偏置数据小于所述预设阈值的情况下，确定所述无人飞行器的负载安装位置未超过所述规定安装范围。
  25. 根据权利要求19所述的无人飞行器控制装置，其中，
    所述处理器还用于记录预设时间段内的控制状态量，并根据所述预设 时间段内的控制状态量进行所述无人飞行器的重心校准。
  26. 根据权利要求19至25中任一项所述的无人飞行器控制装置，其中，
    所述处理器还用于获取所述无人飞行器的状态数据，并判断所述状态数据是否满足重心校准条件，当所述状态数据满足所述重心校准条件时，根据所述控制状态量进行所述无人飞行器的重心校准。
  27. 根据权利要求26所述的无人飞行器控制装置，其中，
    所述状态数据包括以下一种或其组合：定位数据、图像数据、姿态数据、加速度数据、角速度数据。
  28. 根据权利要求26所述的无人飞行器控制装置，其中，
    所述重心校准条件包括所述无人飞行器处于平衡状态。
  29. 根据权利要求28所述的无人飞行器控制装置，其中，
    所述重心校准条件还包括所述无人飞行器的惯性测量单元已进行数据校准。
  30. 根据权利要求26所述的无人飞行器控制装置，其中，
    所述处理器还用于获取所述无人飞行器的周围环境数据，并判断所述周围环境数据是否满足重心校准条件，当所述周围环境数据满足所述重心校准条件时，进入所述根据所述控制状态量进行所述无人飞行器的重心校准的步骤。
  31. 根据权利要求30所述的无人飞行器控制装置，其中，
    所述周围环境数据包括周围环境气流或周围环境风速。
  32. 根据权利要求30所述的无人飞行器控制装置，其中，
    所述重心校准条件包括所述无人飞行器所处环境的风速小于预设风速。
  33. 根据权利要求28所述的无人飞行器控制装置，其中，所述无人飞行器距离地面的距离大于预设距离。
  34. 根据权利要求26或30所述的无人飞行器控制装置，其中，所述处理器还用于当不满足所述重心校准条件时，停止校准，并发送第一指令至控制终端。
  35. 根据权利要求26或30所述的无人飞行器控制装置，其中，所述处理器还用于当校准失败时，停止校准，并发送第二指令至控制终端。
  36. 根据权利要求20至24中任一项所述的无人飞行器控制装置，其中，所述偏置数据包括以下一种或其组合：偏置位置、偏置质量、偏置力、偏置力矩。
  37. 一种无人飞行器，包括动力装置，其中，还包括：
    控制器，用于获取目标飞行数据和当前飞行数据，并根据所述目标飞行数据和所述当前飞行数据确定控制状态量；以及根据所述控制状态量进行所述无人飞行器的重心校准。
  38. 根据权利要求37所述的无人飞行器，其中，所述控制器根据所述控制状态量进行无人飞行器的重心校准包括：
    根据所述控制状态量，计算所述无人飞行器的重心与所述无人飞行器的拉力中心的偏置数据。
  39. 根据权利要求37所述的无人飞行器，其中，还包括：
    提示装置，用于在所述控制器根据所述控制状态量进行所述无人飞行器的重心校准的过程中发出校准提示信息。
  40. 根据权利要求38所述的无人飞行器，其中，还包括：
    存储器，用于存储所述偏置数据。
  41. 根据权利要求38所述的无人飞行器，其中，
    所述控制器还用于根据所述偏置数据生成控制分量，并根据所述控制分量控制所述动力装置。
  42. 根据权利要求38所述的无人飞行器，其中，
    所述控制器还用于将所述偏置数据与预设阈值进行比较，根据比较结果确定所述无人飞行器的负载安装位置是否超过规定安装范围。
  43. 根据权利要求42所述的无人飞行器，其中，所述控制器根据比较结果确定所述无人飞行器的负载安装位置是否超过规定安装范围包括：
    在所述比较结果为所述偏置数据大于或等于所述预设阈值的情况下，确定所述无人飞行器的负载安装位置超过所述规定安装范围；在所述比较结果为所述偏置数据小于所述预设阈值的情况下，确定所述无人飞行器的 负载安装位置未超过所述规定安装范围。
  44. 根据权利要求37所述的无人飞行器，其中，
    所述控制器还用于记录预设时间段内的控制状态量，并根据所述预设时间段内的控制状态量进行所述无人飞行器的重心校准。
  45. 根据权利要求37至44中任一项所述的无人飞行器，其中，
    所述控制器还用于获取所述无人飞行器的状态数据，并判断所述状态数据是否满足重心校准条件；当所述状态数据满足所述重心校准条件时，根据所述控制状态量进行所述无人飞行器的重心校准。
  46. 根据权利要求45所述的无人飞行器，其中，
    所述状态数据包括以下一种或其组合：定位数据、图像数据、姿态数据、加速度数据、角速度数据。
  47. 根据权利要求45所述的无人飞行器，其中，
    所述重心校准条件包括所述无人飞行器处于平衡状态。
  48. 根据权利要求47所述的无人飞行器，其中，
    所述重心校准条件还包括所述无人飞行器的惯性测量单元已进行数据校准。
  49. 根据权利要求45所述的无人飞行器，其中，
    所述控制器还用于获取所述无人飞行器的周围环境数据，并判断所述周围环境数据是否满足重心校准条件，当所述周围环境数据满足所述重心校准条件时，进入所述根据所述控制状态量进行所述无人飞行器的重心校准的步骤。
  50. 根据权利要求49所述的无人飞行器，其中，
    所述周围环境数据包括周围环境气流或周围环境风速。
  51. 根据权利要求49所述的无人飞行器，其中，
    所述重心校准条件包括所述无人飞行器所处环境的风速小于预设风速。
  52. 根据权利要求47所述的无人飞行器，其中，所述无人飞行器距离地面的距离大于预设距离。
  53. 根据权利要求45或49所述的无人飞行器，其中，所述控制器还 用于当不满足所述重心校准条件时，停止校准，并发送第一指令至控制终端。
  54. 根据权利要求45或49所述的无人飞行器，其中，所述控制器还用于当校准失败时，停止校准，并发送第二指令至控制终端。
  55. 根据权利要求38至42中任一项所述的无人飞行器，其中，所述偏置数据包括以下一种或其组合：偏置位置、偏置质量、偏置力、偏置力矩。
  56. 一种无人飞行器的系统，其中，包括：
    控制终端，用于向无人飞行器发送重心校准指令；
    所述无人飞行器，用于根据所述重心校准指令进行重心校准，得到校准结果。
  57. 根据权利要求56所述的无人飞行器的系统，其中，
    所述无人飞行器还用于将所述校准结果发送至所述控制终端。
  58. 根据权利要求57所述的无人飞行器的系统，其中，
    所述控制终端还包括显示装置，所述显示装置用于对所述校准结果进行显示。
  59. 根据权利要求58所述的无人飞行器的系统，其中，所述无人飞行器根据所述重心校准指令进行重心校准包括：
    根据所述重心校准指令获取目标飞行数据和当前飞行数据，并根据所述目标飞行数据和所述当前飞行数据确定控制状态量，根据所述控制状态量进行无人飞行器的重心校准。
  60. 根据权利要求59所述的无人飞行器的系统，其中，所述无人飞行器根据所述控制状态量进行无人飞行器的重心校准包括：
    根据所述控制状态量，计算所述无人飞行器的重心与所述无人飞行器的拉力中心的偏置数据。
  61. 根据权利要求60所述的无人飞行器的系统，其中，
    所述无人飞行器还用于存储所述偏置数据。
  62. 根据权利要求60所述的无人飞行器的系统，其中，
    所述控制终端还用于存储所述偏置数据。
  63. 根据权利要求60所述的无人飞行器的系统，其中，
    所述无人飞行器还用于根据所述偏置数据生成控制分量，并根据所述控制分量控制所述无人飞行器的动力装置。
  64. 根据权利要求60所述的无人飞行器的系统，其中，
    所述无人飞行器还用于将所述偏置数据与预设阈值进行比较，根据比较结果确定所述无人飞行器的负载安装位置是否超过规定安装范围。
  65. 根据权利要求64所述的无人飞行器的系统，其中，所述无人飞行器根据比较结果确定所述无人飞行器的负载安装位置是否超过规定安装范围包括：
    在所述比较结果为所述偏置数据大于或等于所述预设阈值的情况下，确定所述无人飞行器的负载安装位置超过所述规定安装范围；在所述比较结果为所述偏置数据小于所述预设阈值的情况下，确定所述无人飞行器的负载安装位置未超过所述规定安装范围。
  66. 根据权利要求64所述的无人飞行器的系统，其中，
    所述无人飞行器还用于将所述负载安装位置是否超过规定安装范围的结果发送至所述控制终端；
    所述显示装置还用于对所述负载安装位置是否超过规定安装范围的结果进行显示。
  67. 根据权利要求59所述的无人飞行器的系统，其中，
    所述无人飞行器还用于记录预设时间段内的控制状态量，并根据所述预设时间段内的控制状态量进行所述无人飞行器的重心校准。
  68. 根据权利要求56至67中任一项所述的无人飞行器的系统，其中，
    所述无人飞行器的提示装置在根据所述重心校准指令进行重心校准的过程中发出校准提示信息。
  69. 根据权利要求56至67中任一项所述的无人飞行器的系统，其中，
    所述无人飞行器还用于获取状态数据，并判断所述状态数据是否满足重心校准条件，当所述状态数据满足所述重心校准条件时根据所述重心校准指令进行重心校准。
  70. 根据权利要求69所述的无人飞行器的系统，其中，
    所述无人飞行器还用于向所述控制终端发送校准进度信息。
  71. 根据权利要求69所述的无人飞行器的系统，其中，
    所述状态数据包括以下一种或其组合：定位数据、图像数据、姿态数据、加速度数据、角速度数据。
  72. 根据权利要求69所述的无人飞行器的系统，其中，
    所述重心校准条件包括所述无人飞行器处于平衡状态。
  73. 根据权利要求72所述的无人飞行器的系统，其中，
    所述重心校准条件还包括所述无人飞行器的惯性测量单元已进行数据校准。
  74. 根据权利要求69所述的无人飞行器的系统，其中，
    所述无人飞行器还用于获取所述无人飞行器的周围环境数据，并判断所述周围环境数据是否满足重心校准条件，当所述周围环境数据满足所述重心校准条件时，根据所述控制状态量进行所述无人飞行器的重心校准。
  75. 根据权利要求74所述的无人飞行器的系统，其中，
    所述周围环境数据包括周围环境气流或周围环境风速。
  76. 根据权利要求74所述的无人飞行器的系统，其中，
    所述重心校准条件包括所述无人飞行器所处环境的风速小于预设风速。
  77. 根据权利要求72所述的无人飞行器的系统，其中，所述无人飞行器距离地面的距离大于预设距离。
  78. 根据权利要求69或74所述的无人飞行器的系统，其中，
    所述无人飞行器还用于当不满足所述重心校准条件时，停止校准，并发送第一指令至所述控制终端。
  79. 根据权利要求78所述的无人飞行器的系统，其中，
    所述第一指令包括不满足所述重心校准条件的原因和调整建议信息。
  80. 根据权利要求69或74所述的无人飞行器的系统，其中，
    所述无人飞行器还用于当校准失败时，停止校准，并发送第二指令至所述控制终端。
  81. 根据权利要求80所述的无人飞行器的系统，其中，
    所述第二指令包括校准失败原因。
  82. 根据权利要求69或74所述的无人飞行器的系统，其中，
    所述无人飞行器在根据所述重心校准指令进行重心校准的过程中，若不满足所述重心校准条件，则停止校准，并发送第一指令至所述控制终端。
  83. 根据权利要求60至66中任一项所述的无人飞行器的系统，其中，所述偏置数据包括以下一种或其组合：偏置位置、偏置质量、偏置力、偏置力矩。
  84. 一种计算机存储介质，其中，所述计算机存储介质中存储有程序指令，所述程序指令用于实现：
    获取目标飞行数据和当前飞行数据，并根据所述目标飞行数据和所述当前飞行数据确定控制状态量；以及
    根据所述控制状态量进行无人飞行器的重心校准。
  85. 根据权利要求84所述的计算机存储介质，其中，所述程序指令实现所述根据所述控制状态量进行无人飞行器的重心校准包括：
    根据所述控制状态量，计算所述无人飞行器的重心与所述无人飞行器的拉力中心的偏置数据。
  86. 根据权利要求85所述的计算机存储介质，其中，所述程序指令还用于实现：
    存储所述偏置数据。
  87. 根据权利要求85所述的计算机存储介质，其中，所述程序指令还用于实现：
    根据所述偏置数据得到控制分量，并根据所述控制分量控制所述无人飞行器的动力装置。
  88. 根据权利要求85所述的计算机存储介质，其中，所述程序指令还用于实现：
    将所述偏置数据与预设阈值进行比较，根据比较结果确定所述无人飞行器的负载安装位置是否超过规定安装范围。
  89. 根据权利要求88所述的计算机存储介质，其中，所述程序指令实现所述根据比较结果确定所述无人飞行器的负载安装位置是否超过规定安 装范围包括：
    在所述比较结果为所述偏置数据大于或等于所述预设阈值的情况下，确定所述无人飞行器的负载安装位置超过所述规定安装范围；
    在所述比较结果为所述偏置数据小于所述预设阈值的情况下，确定所述无人飞行器的负载安装位置未超过所述规定安装范围。
  90. 根据权利要求84所述的计算机存储介质，其中，所述程序指令还用于实现：
    记录预设时间段内的控制状态量，并根据所述预设时间段内的控制状态量进行所述无人飞行器的重心校准。
  91. 根据权利要求84至90中任一项所述的计算机存储介质，其中，所述程序指令还用于实现：
    获取所述无人飞行器的状态数据，并判断所述状态数据是否满足重心校准条件；
    当所述状态数据满足所述重心校准条件时，进入所述根据所述控制状态量进行所述无人飞行器的重心校准的步骤。
  92. 根据权利要求91所述的计算机存储介质，其中，
    所述状态数据包括以下一种或其组合：定位数据、图像数据、姿态数据、加速度数据、角速度数据。
  93. 根据权利要求91所述的计算机存储介质，其中，
    所述重心校准条件包括所述无人飞行器处于平衡状态。
  94. 根据权利要求93所述的计算机存储介质，其中，
    所述重心校准条件还包括所述无人飞行器的惯性测量单元已进行数据校准。
  95. 根据权利要求91所述的计算机存储介质，其中，所述程序指令还用于实现：
    获取所述无人飞行器的周围环境数据，并判断所述周围环境数据是否满足重心校准条件；
    当所述周围环境数据满足所述重心校准条件时，进入所述根据所述控制状态量进行所述无人飞行器的重心校准的步骤。
  96. 根据权利要求95所述的计算机存储介质，其中，
    所述周围环境数据包括周围环境气流或周围环境风速。
  97. 根据权利要求95所述的计算机存储介质，其中，
    所述重心校准条件包括所述无人飞行器所处环境的风速小于预设风速。
  98. 根据权利要求93所述的计算机存储介质，其中，所述无人飞行器距离地面的距离大于预设距离。
  99. 根据权利要求91或95所述的计算机存储介质，其中，所述程序指令还用于实现：当不满足所述重心校准条件时，停止校准，并发送第一指令至控制终端。
  100. 根据权利要求91或95所述的计算机存储介质，其中，所述程序指令还用于实现：当校准失败时，停止校准，并发送第二指令至控制终端。
  101. 根据权利要求85至89中任一项所述的计算机存储介质，其中，所述偏置数据包括以下一种或其组合：偏置位置、偏置质量、偏置力、偏置力矩。
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