WO2018227345A1 - 控制方法和无人机 - Google Patents

控制方法和无人机 Download PDF

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Publication number
WO2018227345A1
WO2018227345A1 PCT/CN2017/087955 CN2017087955W WO2018227345A1 WO 2018227345 A1 WO2018227345 A1 WO 2018227345A1 CN 2017087955 W CN2017087955 W CN 2017087955W WO 2018227345 A1 WO2018227345 A1 WO 2018227345A1
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WIPO (PCT)
Prior art keywords
model
flight
drone
motion information
pan
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Ceased
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PCT/CN2017/087955
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English (en)
French (fr)
Inventor
陈竞
赵丛
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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/CN2017/087955 priority Critical patent/WO2018227345A1/zh
Priority to CN201780004914.7A priority patent/CN108700883A/zh
Publication of WO2018227345A1 publication Critical patent/WO2018227345A1/zh
Anticipated expiration legal-status Critical
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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
    • G05D1/10—Simultaneous control of position or course in three dimensions
    • G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
    • G05D1/106—Change initiated in response to external conditions, e.g. avoidance of elevated terrain or of no-fly zones
    • 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
    • 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

Definitions

  • the invention relates to the technical field of drones, in particular to a control method and a drone.
  • the popularity of drones is growing, but many users are not professional flying hands.
  • the control technology of drones is poor. It is impossible to control drones to fly out of more professional flight trajectories to get a better shooting experience.
  • the automatic flight of the drone is mainly through the selection of waypoints, and then automatically flight based on the waypoints.
  • this flight plan automatically generates flight trajectories based on the waypoints, does not pay attention to the shooting effect during the flight, and cannot obtain high-quality shooting works.
  • the shooting value is low and the motivation for sharing is lacking.
  • Embodiments of the present invention provide a control method and a drone so that an ordinary user can also take a high-level photograph.
  • the control method of the embodiment of the present invention is applied to a drone.
  • the control method includes: collecting motion information during flight of the drone, determining model parameters of the flight model according to the motion information, and transmitting the model parameters to an external device.
  • the control method of the embodiment of the present invention is applied to a drone.
  • the drone communicates with an external device.
  • the control method includes: acquiring model parameters from the external device, determining a flight model according to the model parameters, and controlling the drone to fly according to the flight model.
  • the drone of the embodiment of the present invention includes a sensor, a processor, and a communication interface.
  • the sensor is configured to collect motion information during flight of the drone;
  • the processor is configured to determine model parameters of a flight model according to the motion information;
  • the communication interface is configured to send the model parameter to an external device .
  • the drone of the embodiment of the present invention communicates with an external device.
  • the drone includes a communication interface, a processor, the communication interface is configured to acquire model parameters from the external device, the processor is configured to determine a flight model according to the model parameter, and the processor is configured to control the The manned aircraft flies according to the flight model.
  • a drone includes a pan/tilt, a camera, one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be
  • the one or more processors execute, the program including instructions for executing the control method described above.
  • users of non-professional flying hands can directly use the recorded flight model to control the drone to perform flight and aerial photography to obtain a higher level of shooting work, thereby improving the user experience.
  • FIG. 1 is a flow chart of a control method of some embodiments of the present invention.
  • FIG. 2 is a block diagram of a drone of some embodiments of the present invention.
  • FIG. 3 is a schematic diagram of the state of a control method of some embodiments of the present invention.
  • 4 to 24 are schematic flow charts of a control method according to some embodiments of the present invention.
  • 25 is a block diagram of a drone of some embodiments of the present invention.
  • 26 to 28 are schematic diagrams of application scenarios of a control method according to some embodiments of the present invention.
  • Control methods include:
  • the control method of the embodiment of the present invention can be implemented by the drone 100 of the embodiment of the present invention.
  • UAV of the embodiment of the present invention 100 includes a sensor 10, a processor 20, and a communication interface 30.
  • the drone 100 is also carried by the pan/tilt head 40.
  • the step S12 can be implemented by the sensor 10, the step S14 can be implemented by the processor 20, and the step S16 can be implemented by the communication interface 30.
  • the senor 10 is used to collect motion information during flight of the drone 100; the processor 20 is configured to determine model parameters of the flight model based on the motion information; and the communication interface 30 is configured to transmit the model parameters to the external device.
  • the processor 20 may be a flight controller of the drone, or may be other dedicated or general-purpose processors, and is not specifically limited herein.
  • the motion information includes position information of the drone 100, speed information of the drone 100, acceleration information of the drone 100, attitude information of the drone 100, angular velocity information of the drone 100, One or more of the gimbal attitude information of the drone 100, the angular velocity information of the pan-tilt 40 motion, and the angular acceleration information of the pan-tilt 40 motion.
  • the location information may be absolute location information (longitude, latitude) or relative location information, and the relative location information is location information relative to a reference point.
  • the sensor 10 for collecting motion information during flight of the drone includes a compass, an electronic compass, an Inertial Measurement Unit (IMU), an acceleration sensor, a vision sensor (binocular, monocular, visual odometer), GNSS At least one of a receiver, a barometer, an airspeed meter, a compass, an ultrasonic wave, or the like.
  • IMU Inertial Measurement Unit
  • IMU Inertial Measurement Unit
  • an acceleration sensor an acceleration sensor
  • a vision sensor binocular, monocular, visual odometer
  • GNSS At least one of a receiver, a barometer, an airspeed meter, a compass, an ultrasonic wave, or the like.
  • the position information of the drone 100 can be collected by a GNSS receiver, an inertial measurement unit, a vision sensor, etc. configured by the drone, and the speed information of the drone 100 can be configured by the GNSS receiver of the drone, inertial measurement.
  • the unit, the visual sensor, the ultrasonic sensor or the airspeed meter collects, and the acceleration information of the drone 100 can be collected by the acceleration sensor, and the attitude information of the drone 100 can be collected by the inertial measurement unit, and the angular velocity information of the drone 100
  • the acquisition can be performed by the inertial measurement unit, and the attitude information of the head of the drone 100 can be collected by the inertial measurement unit, and the angular velocity information of the movement of the platform 40 of the drone 100 can be collected by the inertial measurement unit.
  • the external device includes one or more of the drone 200, the server 300, and the control terminal 400.
  • the control terminal 400 may be one or more of a remote controller, a smart phone, a tablet computer, a drone ground control station, a watch, a wristband, a video glasses, and the like.
  • control terminal 400 receives input from a user. The user can input by operating a pull wheel, a button, a button, a remote sensing, or the like on the remote controller or by controlling a user interface (UI) on the terminal 400.
  • UI user interface
  • the control method of the embodiment of the present invention obtains the model parameters of the flight model of the drone 100 by processing the motion information during the flight of the collected drone 100, and the model parameters may be sent to an external device such as the drone 200. Flight can be made directly from model parameters. In this way, the sharing of model parameters of the flight model can be achieved.
  • the non-professional flying hand may have a relatively uncomfortable operation skill on the drone 200, and therefore cannot skillfully control the drone 200 to perform aerial photography to obtain a higher level of shooting work.
  • the professional flying hand uploads the recorded model parameters to the server 300 or directly to the drone 200, and the non-professional flying hand can control the drone 200 to directly fly according to the flight model obtained by the model parameters recorded by the professional flying hand. Thereby obtaining high quality aerial works. In this way, the user experience can be improved.
  • step S12 collects motion information during flight of the drone 100, including:
  • Step S14 determines model parameters of the flight model according to the motion information, including:
  • Sending the model parameters to the external device in step S16 includes:
  • S161 Send the model parameters of the flight path model to an external device.
  • step S121 can be implemented by sensor 10
  • step S141 can be implemented by processor 20
  • step S161 can be implemented by communication interface 30.
  • the senor 10 can be used to collect first motion information during flight of the drone 100; the processor 20 can be used to determine model parameters of the flight trajectory model based on the first motion information; the communication interface 30 can be used to model the flight trajectory The model parameters are sent to the external device.
  • the first motion information may include at least one of position information, speed information, and acceleration information of the drone 100.
  • the sensor 10 collects only first motion information related to the flight trajectory model during flight of the drone 100 from position A to position B.
  • the processor 20 obtains model parameters of the flight trajectory model by processing one or more of position information, speed information, and acceleration information.
  • the processor 20 transmits the model parameters of the flight trajectory model to an external device, such as the drone 200, for sharing.
  • the drone 200 can determine the flight trajectory model based on the model parameters described above and fly according to the flight trajectory indicated by the flight trajectory model.
  • step S12 collects motion information during flight of the drone 100, including:
  • S122 collecting first motion information and second motion information during flight of the drone 100;
  • Step S14 determines model parameters of the flight model according to the motion information, including:
  • Sending the model parameters to the external device in step S16 includes:
  • S162 Send the model parameters of the flight path model and the model parameters of the flight speed model to an external device.
  • step S122 can be implemented by sensor 10
  • step S142 can be implemented by processor 20
  • step S162 can be implemented by communication interface 30.
  • the sensor 10 can be used to collect the first motion information and the second motion information during the flight of the drone 100; the processor 20 can be configured to determine the model parameters of the flight trajectory model according to the first motion information, and according to the second The motion information determines model parameters of the flight speed model; the communication interface 30 can be used to transmit model parameters of the flight speed model and model parameters of the flight speed model to an external device.
  • the first motion information may include at least one of position information, speed information, and acceleration information of the drone 100
  • the second motion information may include one of speed information and acceleration information of the drone 100
  • the sensor 10 simultaneously acquires first motion information associated with the flight trajectory model and second motion information associated with the flight speed model during one flight of the drone 100 from position A to position B.
  • the processor 20 can obtain the model parameters of the flight trajectory model by processing one or more of the position information, the speed information and the acceleration information, and obtain the flight speed model by processing one or more of the speed information and the acceleration information. Model parameters. Subsequently, the processor 20 transmits the flight trajectory model and the model parameters of the flight speed model to an external device, such as the drone 200, for sharing.
  • the drone 200 can not only fly according to the flight trajectory indicated by the flight trajectory model determined by the model parameters of the flight trajectory model, but also can perform the speed of the drone 100 according to the flight speed model determined by the model parameters of the flight speed model. Control, so as to more accurately restore the flight path and flight speed of the drone 100 during recording, and obtain better flight effects and aerial photography effects.
  • step S12 collects motion information during flight of the drone 100, including:
  • Step S14 determines model parameters of the flight model according to the motion information, including:
  • S143 Determine a model parameter of the flight trajectory model according to the first motion information, and determine a model parameter of the PTZ attitude model according to the third motion information;
  • Sending the model parameters to the external device in step S16 includes:
  • S163 Send the model parameters of the flight path model and the model parameters of the pan/tilt attitude model to an external device.
  • step S123 can be implemented by sensor 10
  • step S143 can be implemented by processor 20
  • step S163 can be implemented by communication interface 30.
  • the senor 10 can be used to collect the first motion information and the third motion information during the flight of the drone 100; the processor 20 can be configured to determine a model parameter of the flight trajectory model according to the first motion information, and according to the third The motion information determines model parameters of the pan/tilt attitude model; the communication interface 30 can be used to transmit the model parameters of the flight trajectory model and the model parameters of the pan/tilt attitude model to an external device.
  • the first motion information may include at least one of position information, speed information, and acceleration information of the drone 100.
  • the third motion information may include at least the pan-tilt attitude information of the drone 100 and the angular velocity information of the pan-tilt motion.
  • One of the angular acceleration information that is, the pitch angle information of the pan/tilt head 40 of the drone 100 on the Pitch axis, the yaw angle information on the Yaw axis, and the roll angle information on the Roll axis.
  • the sensor 10 simultaneously acquires first motion information related to the flight trajectory model and third motion information related to the pan/tilt attitude model during one flight of the drone 100 flying from the position A to the position B.
  • the processor 20 can obtain the model parameters of the flight trajectory model by processing one or more of the position information, the speed information, and the acceleration information, and process one of the angular motion information of the pan-tilt motion, the angular velocity information of the pan-tilt motion, and the angular acceleration information.
  • the model parameters of the gimbal attitude model can be obtained by one or more kinds.
  • the processor 20 transmits the flight trajectory model and the model parameters of the pan/tilt attitude model to an external device, such as the drone 200, for sharing.
  • the drone 200 can not only fly according to the flight trajectory indicated by the flight trajectory model determined by the model parameters of the flight trajectory model, but also can perform the drone 200 according to the pan/tilt attitude model determined by the model parameters of the pan/tilt attitude model.
  • the angle adjustment of the pan/tilt head 80 can more accurately restore the flight path and the attitude of the head of the drone 100 during recording, and obtain better flight effects and aerial photography effects.
  • step S12 collects motion information during flight of the drone 100, including:
  • S124 collecting first motion information, second motion information, and third motion information during flight of the drone 100;
  • Step S14 determines model parameters of the flight model according to the motion information, including:
  • S144 Determine a model parameter of the flight trajectory model according to the first motion information, determine a model parameter of the flight speed model according to the second motion information, and determine a model parameter of the PTZ attitude model according to the third motion information;
  • Sending the model parameters to the external device in step S16 includes:
  • S164 sending model parameters of the flight path model, model parameters of the flight speed model, and model parameters of the pan/tilt attitude model to external device.
  • step S124 can be implemented by sensor 10
  • step S144 can be implemented by processor 20
  • step S164 can be implemented by communication interface 30.
  • the senor 10 can be used to collect the first motion information, the second motion information and the third motion information during the flight of the drone 100; the processor 20 can be configured to determine the model parameters of the flight trajectory model according to the first motion information. Determining a model parameter of the flight speed model according to the second motion information, and determining a model parameter of the pan/tilt attitude model according to the third motion information; the communication interface 30 may be configured to use the model parameter of the flight trajectory model, the model parameter of the flight speed model, and The model parameters of the pan/tilt attitude model are sent to an external device.
  • the first motion information may include at least one of position information, speed information, and acceleration information of the drone 100.
  • the second motion information may include at least one of speed information and acceleration information of the drone 100.
  • the three motion information may include at least one of the pan/tilt attitude information of the drone 100, the angular velocity information of the pan-tilt motion, and the angular acceleration information, that is, the attitude of the pan-tilt is the pan/tilt head 40 of the drone 100 on the Pitch axis.
  • the sensor 10 simultaneously acquires first motion information related to the flight trajectory model, second motion information related to the flight speed model, and related to the gimbal attitude model during a flight of the drone 100 from the position A to the position B.
  • the processor 20 can obtain the model parameters of the flight trajectory model by processing one or more of the position information, the speed information and the acceleration information, and obtain the flight speed model by processing one or more of the speed information and the acceleration information.
  • the model parameters can be obtained by processing one or more of the attitude information of the gimbal, the angular velocity information of the gimbal motion, and the angular acceleration information.
  • the processor 20 transmits the flight trajectory model, the flight speed model, and the model parameters of the pan/tilt attitude model to an external device, such as the drone 200, for sharing.
  • the drone 200 can not only fly according to the flight trajectory indicated by the flight trajectory model determined by the model parameters of the flight trajectory model, but also can control the speed of the drone 100 by the flight speed model determined by the model parameters of the flight speed model.
  • the angle adjustment of the pan/tilt head 80 of the drone 200 can be performed according to the pan/tilt attitude model determined by the model parameters of the gimbal attitude model, thereby more accurately restoring the flight trajectory, flight speed and the flying speed of the drone 100 during recording. PTZ attitude for better flight performance and aerial photography.
  • control method of the embodiment of the present invention further includes:
  • S11 controlling the drone 100 to fly on the flight trajectory indicated by the flight path model according to the model parameters of the flight trajectory model;
  • S125 collecting second motion information of the drone 100 during flight along the indicated flight trajectory
  • S165 Send model parameters of the flight speed model to an external device.
  • step 11 can be implemented by processor 20, step S125 can be implemented by sensor 10, step S145 can be implemented by processor 20, and step S165 can be implemented by communication interface 30.
  • the processor 20 can be used to control the drone 100 to fly on the flight trajectory indicated by the flight trajectory model according to the model parameters of the flight trajectory model; the sensor 10 can be used to collect the drone 100 to fly along the indicated flight trajectory The second motion information during flight; the processor is further configured to determine a model parameter of the flight speed model according to the second motion information; the communication interface 30 is configured to send the model parameter of the flight speed model to the external device.
  • the drone 100 first acquires first motion information during the first flight from position A to position B to determine model parameters of the flight trajectory model. Subsequently, the drone 100 performs the second flight based on the flight trajectory indicated by the flight trajectory model, starting from the position A and ending at the position B.
  • the drone 100 During the second flight, the drone 100 only collects the second motion information. Subsequently, the drone 100 processes the second motion information to determine model parameters of the flight speed model, and transmits the model parameters of the flight speed model to the external device. Thus, the drone 100 separately records the flight trajectory model and the flight speed model in the form of multiple flight recordings. In each recording, the user's focus is different, such as the first flight focuses on the flight trajectory, and the second flight focuses on the flight speed. In this way, the user's control of the drone 100 is more perfect, and the quality of the recorded flight model is better.
  • control method of the embodiment of the present invention further includes:
  • S11 controlling the drone 100 to fly on the flight trajectory indicated by the flight path model according to the model parameters of the flight trajectory model;
  • S126 Collecting third motion information of the drone 100 during flight along the indicated flight trajectory
  • S166 Send the model parameters of the PTZ attitude model to an external device.
  • step S11 can be implemented by processor 20
  • step S125 can be implemented by sensor 10
  • step S146 can be implemented by processor 20
  • step S166 can be implemented by communication interface 30.
  • the processor 10 can be used to control the drone 100 to fly on the flight path indicated by the flight path model according to the model parameters of the flight trajectory model; the sensor 20 can be used to collect the drone 100 to fly along the indicated flight path.
  • the third motion information during flight; the processor 20 is further configured to determine model parameters of the pan/tilt attitude model according to the third motion information; the communication interface 30 is configured to send the model parameters of the pan/tilt attitude model to the external device.
  • the drone 100 first acquires first motion information during the first flight from position A to position B to determine model parameters of the flight trajectory model. Subsequently, the drone 100 performs the second flight based on the flight trajectory indicated by the flight trajectory model, starting from the position A and ending at the position B. During the second flight, the drone 100 only collects third motion information. Subsequently, the drone 100 processes the third motion information to determine model parameters of the pan/tilt attitude model, and transmits the model parameters of the pan/tilt attitude model to the external device. In this way, the drone 100 separately records the flight path model and the pan/tilt attitude model in the form of multiple flight recordings. In each recording, the user's focus is different. For example, the first flight focuses on the flight trajectory, and the second flight focuses on the attitude of the gimbal. In this way, the user's control of the drone 100 is more perfect, and the quality of the recorded flight model is better.
  • control method of the embodiment of the present invention further includes:
  • S11 controlling the drone 100 to fly on the flight trajectory indicated by the flight path model according to the model parameters of the flight trajectory model;
  • S127 collecting second motion information and third motion information of the drone 100 during flight along the indicated flight trajectory
  • S167 Send the model parameters of the flight speed model and the model parameters of the pan/tilt attitude model to an external device.
  • step S11 can be implemented by processor 20
  • step S127 can be implemented by sensor 10
  • step S147 can be implemented by processor 20
  • step S167 can be implemented by communication interface 30.
  • the processor 20 can also be used to control the drone 100 to fly on the flight trajectory indicated by the flight trajectory model according to the model parameters of the flight trajectory model; the sensor 20 can also be used to collect the drone 100 along the indicated flight.
  • the second motion information and the third motion information during the flight of the trajectory flight; the processor 20 is further configured to determine a model parameter of the flight speed model according to the second motion information, and determine a model parameter of the pan/tilt attitude model according to the third motion information
  • the communication interface 30 can also be used to transmit model parameters of the flight speed model and model parameters of the pan/tilt attitude model to an external device.
  • the drone 100 first acquires first motion information during the first flight from position A to position B to determine model parameters of the flight trajectory model. Subsequently, the drone 100 performs the second flight based on the flight trajectory indicated by the flight trajectory model, starting from the position A and ending at the position B. During the second flight, the drone 100 simultaneously acquires the second motion information and the third motion information. Subsequently, the drone 100 processes the second motion information to determine the model parameters of the flight speed model, processes the third motion information to determine the model parameters of the pan-tilt attitude model, and models the parameters of the flight speed model and the pan/tilt The model parameters of the attitude model are sent to an external device.
  • the drone 100 separately records the flight trajectory model, the flight speed model, and the gimbal attitude model in the form of multiple flight recordings.
  • the user's focus is different.
  • the first flight focuses on the flight trajectory
  • the second flight focuses on the flight speed and the attitude of the gimbal.
  • the user's control of the drone 100 is more perfect, and the quality of the recorded flight model is better.
  • the drone 100 first acquires first motion information during the first flight from position A to position B to determine model parameters of the flight trajectory model. Subsequently, the drone 100 performs the second flight based on the flight trajectory indicated by the flight trajectory model, starting from the position A and ending at the position B. During the second flight, the drone 100 collects second motion information. Subsequently, the drone 100 processes the second motion information to determine the model parameters of the flight speed model, and transmits the model parameters of the flight speed model to the external device. Then, the drone 100 performs the third flight according to the flight speed model, starting from the position A and ending with the position B according to the flight trajectory indicated by the flight trajectory model. During the third flight, the drone 100 collects third motion information.
  • the UAV 100 processes the third motion information to determine the model parameters of the PTZ attitude model, and transmits the model parameters of the PTZ attitude model to the external device.
  • the drone 100 separately records the flight path model, the flight speed model, and the gimbal attitude model in the form of multiple flight recordings.
  • the user's attention points are different. For example, the first flight focuses on the flight trajectory, the second flight focuses on the flight speed, and the third flight focuses on the attitude of the gimbal. In this way, the user's control of the drone 100 is more perfect, and the quality of the recorded flight model is better.
  • the flight model includes one or more flight model segments that are segmented at time intervals.
  • Step S14 determines model parameters of the flight model according to the motion information, including:
  • S1482 Determine model parameters corresponding to the flight model segment according to motion information of each of the plurality of segments.
  • step S1481 and step S1482 can be implemented by processor 20.
  • the processor 20 can also be used to divide the flight process of the drone 100 into a plurality of segments according to time intervals, and determine the corresponding flight model segments according to the motion information of each of the plurality of segments. Model parameters.
  • the flight model includes a plurality of flight model segments, and the flight model segments are divided at time intervals, and each flight model segment corresponds to a functional formula. Therefore, the flight model is a segmentation function that segments at time intervals.
  • the entire flight process of the drone 100 is divided into segments at intervals of time, and each segment corresponds to a motion information and a functional formula, and each of the motion information and the functional formula can determine each The model parameters corresponding to a segment.
  • segmenting the flight model at time intervals allows the corresponding function of the flight model to better fit the flight path, flight speed, or pan/tilt attitude of the drone 100 throughout the flight. As such, the flight model is more accurate.
  • step S14 determines model parameters of the flight model based on the motion information, including:
  • S1491 Determine expected motion information corresponding to the motion information according to a time when the motion information is collected and a preset flight model;
  • step S1491, step S1492, and step S1493 can be implemented by processor 20.
  • the processor 20 is configured to: determine expected motion information corresponding to the motion information according to the time when the motion information is collected and the preset flight model, determine an error between the collected motion information and the expected motion information, and determine an error according to the error Determine the model parameters of the flight model.
  • the preset flight model includes a preset flight trajectory model indicating the flight of the drone 100, a preset flight speed model indicating the flight of the drone 100, and a preset pan-tilt attitude indicating the attitude of the pan/tilt head 40 of the drone 100.
  • the preset flight model has the same piecewise function expression as the flight model. The difference between the two is that the model parameter p in the preset flight model is unknown and needs to be obtained by the error equation.
  • the flight trajectory model is taken as an example for description.
  • the flight path model is a piecewise function f(p,t) about the model parameter p and time t, and the function is as follows:
  • [t 0 , t 1 ), [t 1 , t 2 ), ..., [t m-1 , t m ) represent flight model segments at intervals of time
  • m represents the corresponding segment of each flight model segment
  • the number, such as [t 0 , t 1 ), represents the first flight model segment
  • [t 1 , t 2 ) represents the second flight model segment
  • n represents the number of model parameters p in each flight model segment or the number of coefficients of the function corresponding to each flight model segment.
  • the model parameter p in the preset flight trajectory model is an unknown number and needs to be determined by the acquired first motion information.
  • the first motion information includes position information x, speed information v, and acceleration information a of the drone 100.
  • the model parameter p can be solved by an error equation.
  • the expression of the error equation is as follows:
  • the following label j distinguishes the position information x j , the speed information v j and the acceleration information a j collected at different time points.
  • the position information x j , the speed information v j and the acceleration information a j are the position information, the speed information and the acceleration information collected by the sensor 10 at the corresponding time point, that is, the motion information collected by the sensor 10 .
  • f(p,t j ) with Corresponding expected motion information of the position information x j , the speed information v j , and the acceleration information a j , respectively.
  • w x , w v , and w a are weights corresponding to position information, speed information, and acceleration information, respectively.
  • the error equation weights the position, velocity and acceleration calculated by the preset flight path model at each time point with the acquired position, velocity and acceleration.
  • a p value needs to be selected such that the value of the error equation, ie, the value of error(p), is minimized.
  • the value of error(p) should be zero.
  • the value of error(p) cannot reach zero.
  • the method for obtaining the p value is as follows: First, a p value is selected and substituted into the error equation for calculation to obtain the value of error(p), and the accuracy of the current flight trajectory model is measured according to the value of the error(p). If the value of error(p) is large, the value of p calculated by substituting the error equation above is based on re-selecting a new p-value into the error equation to obtain the value of the new error(p), and according to the new error. The value of (p) measures the accuracy of the new flight path model. This cycle is repeated until a p value is chosen such that the value of error(p) is as small as possible, ie the corresponding p value is taken as the model parameter of the final flight trajectory model.
  • model parameters of the flight speed model and the model parameters of the pan/tilt attitude model can also be obtained by referring to the above calculation method, and will not be described herein.
  • control methods include:
  • S26 Control the drone 200 to fly according to the flight model.
  • the control method of the embodiment of the present invention can be implemented by the drone 200 of the embodiment of the present invention.
  • the drone 200 of an embodiment of the present invention includes a processor 60 and a communication interface 70.
  • Step 22 can be implemented by communication interface 70.
  • Step S24 and step S26 can be implemented by the processor 60.
  • the communication interface 70 is used to acquire model parameters from an external device; the processor 60 is configured to: determine a flight model based on the model parameters, and control the drone 200 to fly according to the flight model.
  • the drone 200 according to the embodiment of the present invention also carries a pan/tilt head 80 on which the camera 90 is mounted.
  • the external device includes one or more of the drone 100, the server 300, and the control terminal 400.
  • the control terminal 400 may be one or more of a remote controller, a smart phone, a tablet computer, a drone ground control station, a watch, a wristband, a video glasses, and the like.
  • the control terminal receives input from the user. The user can input by operating a pull wheel, a button, a button, a remote sensing, or the like on the remote controller or by controlling a user interface (UI) on the terminal 400.
  • UI user interface
  • the control method of the embodiment of the present invention first processes the model parameter p acquired from the external device to obtain the flight model f(p, t). Specifically, the drone 200 acquires the model parameter p from the external device and substitutes the model parameter p into the flight.
  • the function of the model is in f(p,t).
  • the flight model f(p,t) is a piecewise function that is segmented at time intervals. Wherein, the model parameter p and the time t are both known quantities, and thus, the value of f(p, t) can be determined.
  • the drone 200 is then controlled to perform autonomous flight in accordance with the flight model described above.
  • the flying model recorded by the professional flying hand can be used to control the drone 200 to fly, and on the other hand, the flying process of the drone 200 can be ensured.
  • the safety in the middle can help non-professional flying hands to obtain higher-quality aerial photographs and enhance the user experience.
  • the flight model includes at least a flight trajectory model
  • step S26 controls the drone 200 to fly according to the flight model, including:
  • S261 Control the drone 200 to fly according to the flight trajectory indicated by the flight trajectory model.
  • step S261 can be implemented by processor 60. That is, the processor 60 is further configured to control the drone 200 to fly in accordance with the flight trajectory indicated by the flight trajectory model.
  • the drone 200 flies from position A to position B by learning the flight path model in accordance with the flight trajectory indicated by the flight trajectory model, or from position C to position D according to the flight trajectory indicated by the flight trajectory model.
  • position A and position C refer to two different starting positions
  • position B and position D refer to two different ending positions.
  • the location information collected by the drone 100 may be absolute location information or relative location information.
  • the position information collected by the drone is absolute location information
  • the position information collected by the drone 100 is absolute position information from the position A to the position B
  • the drone 200 flies from the position A to the position B by learning the flight trajectory model according to the flight trajectory indicated by the flight trajectory model, and is completely repeated at this time.
  • the flight path flies from position C to position D. At this time, the drone 200 determines the position C and the position D according to the reference point, wherein the reference point can receive the control terminal A time position of UAV 200 to send a replay instruction.
  • the flight environment in which the drone 200 learns the flight model does not need to be the same as the flight environment when the drone 100 records the flight model.
  • the drone 200 can fly autonomously according to the indicated flight path of the flight path model, and the user does not need to manually control to change the flight position of the drone 200, and the intelligence and convenience of the drone 200 are greatly improved.
  • the flight environment when the drone 200 learns the flight model need not be the same as the flight environment when the drone 100 records the flight model, and the flight model has high portability.
  • the flight model further includes a flight speed model, and step S26 controls the drone 200 to fly according to the flight model, including:
  • S262 Control the drone 200 to fly according to the flight trajectory indicated by the flight trajectory model and the flight speed indicated by the flight speed model.
  • step S262 can be implemented by processor 60. That is, the processor 60 is further configured to control the drone 200 to fly in accordance with the flight trajectory indicated by the flight trajectory model and the flight speed indicated by the flight speed model.
  • the drone 200 learns the flight trajectory model and the flight speed model, and flies from position A to position according to the flight trajectory indicated by the flight trajectory model and the flight speed indicated by the flight speed model. B, or flight from position C to position D according to the flight trajectory indicated by the flight path model and the flight speed indicated by the flight speed. In this way, the drone 200 can more accurately restore the flight process of the drone 100 during recording, and improve the flight effect of the drone 200.
  • the posture of the pan/tilt head 80 of the drone 200 can be automatically controlled by the user, and the flexibility of the shooting angle of the camera 90 at the time of aerial photography is improved.
  • the flight model further includes a pan/tilt attitude model, and step S26 controls the drone 200 to fly according to the flight model, including:
  • S263 Control the drone 200 to fly according to the flight trajectory indicated by the flight trajectory model and the flight speed indicated by the flight speed model, and simultaneously adjust the attitude of the pan/tilt head 80 according to the pan/tilt attitude model.
  • step S263 can be implemented by processor 60. That is to say, the processor 60 is further configured to control the drone 200 to fly according to the flight trajectory indicated by the flight trajectory model and the flight speed indicated by the flight speed model, and simultaneously adjust the attitude of the pan-tilt 80 according to the pan-tilt attitude model.
  • the drone 200 learns the flight path model, the flight speed model, and the pan/tilt attitude model, and flies from the position A to the position B according to the flight trajectory indicated by the flight trajectory model and the flight speed indicated by the flight speed model, while simultaneously following the gimbal attitude model.
  • the attitude of the pan/tilt head 80 is adjusted; or the flight trajectory indicated by the flight path model and the flight speed indicated by the flight speed model are flighted from the position C to the position D, while the attitude of the pan/tilt head 80 is adjusted according to the pan/tilt attitude model.
  • the drone 200 can more accurately restore the flight trajectory, the flight speed, and the attitude of the gimbal 80 when the drone 100 records the flight model, and the flight effect and aerial photography effect of the drone 200 are better.
  • the flight model further includes a pan/tilt attitude model, and step S26 controls the drone 200 to fly according to the flight model:
  • S264 Control the drone 200 to fly according to the flight trajectory indicated by the flight trajectory model, and simultaneously adjust the attitude of the pan/tilt head 80 according to the pan/tilt attitude model.
  • step S264 can be implemented by processor 60. That is to say, the processor 60 is further configured to control the drone 200 to fly according to the flight trajectory indicated by the flight trajectory model, and simultaneously adjust the attitude of the pan/tilt head 80 according to the pan/tilt attitude model.
  • the drone 200 learns the flight path model and the pan/tilt attitude model, and flies from the position A to the position B according to the flight trajectory indicated by the flight trajectory model, while adjusting the attitude of the pan/tilt head 80 according to the gimbal attitude model, or according to the flight trajectory model.
  • the indicated flight path flies from position C to position D, during which the attitude of the pan/tilt head 80 is adjusted according to the pan/tilt attitude model.
  • the drone 200 can restore the flight trajectory and the attitude of the head of the drone 100 when recording the flight model, and improve the flight effect and aerial photography effect of the drone 200.
  • the speed of the drone 200 can be controlled by the user, which increases the degree of freedom of control of the drone 200.
  • the drone 200 is in communication with the control terminal 400.
  • the control method of the embodiment of the present invention further includes:
  • S251 Receive a speed control instruction sent by the control terminal 400.
  • Step S26 controls the drone 200 to fly according to the flight model including:
  • S265 controlling the drone 200 to fly according to the flight trajectory indicated by the flight trajectory model
  • S266 The drone 200 is controlled to adjust the flight speed of the drone 200 in accordance with the speed control command.
  • step S251 can be implemented by communication interface 70, and step S265 and step S266 can be implemented by processor 60.
  • the communication interface 70 is for receiving the speed control command sent by the control terminal 400; the processor 60 is for controlling the drone 200 to fly according to the flight trajectory indicated by the flight trajectory model, and controlling the drone 200 to follow the speed control command. The flight speed of the drone 200 is adjusted.
  • the user can input a speed control command for adjusting the flight speed of the drone 200 at the control terminal 400, and the control terminal 400 transmits the speed control command to the drone 200. Thereafter, the drone 200 performs speed adjustment based on the speed control command.
  • the drone 200 has a high degree of freedom of operation, and the drone 200 can optimize the flight effect and the aerial shooting effect by changing the flight speed during flight along the flight path.
  • the drone 200 is in communication with the control terminal 400.
  • the control method of the embodiment of the present invention further includes:
  • S252 Receive a PTZ control command sent by the control terminal 400.
  • Step S26 controls the drone 200 to fly according to the flight model including:
  • S265 controlling the drone 200 to fly according to the flight trajectory indicated by the flight trajectory model
  • S267 The drone 200 is controlled to adjust the posture of the pan/tilt head 80 carried by the drone 200 according to the pan/tilt control command.
  • step S252 can be implemented by communication interface 70, and step S265 and step S267 can be implemented by processor 60.
  • the communication interface 70 is for receiving the PTZ control command sent by the control terminal 400; the processor 60 is for controlling the UAV 200 to fly according to the flight trajectory indicated by the flight trajectory model, and controlling the UAV 200 to follow the PTZ
  • the control command adjusts the attitude of the pan/tilt head 80 carried by the drone 200.
  • the user can input a PTZ control command for adjusting the posture of the PTZ 80 at the control terminal 400, and the control terminal 400 transmits the PTZ control command to the UAV.
  • the drone 200 performs the attitude adjustment of the pan/tilt head 80 according to the pan/tilt control command.
  • the drone 200 uses the flight model for autonomous flight, the flight location of the drone 200 and the flight location when the drone 100 records the flight model may be the same or different.
  • the user can change the shooting angle of the camera 90 mounted on the pan/tilt by adjusting the posture of the pan/tilt head 80, so as to put the main body of the user's attention into the shooting image of the camera 90, thereby obtaining a higher-level aerial photography. works.
  • the drone 200 is in communication with the control terminal 400.
  • the control method of the embodiment of the present invention further includes:
  • S254 Control the drone 200 to fly to the starting position point
  • Step S26 controls the drone 200 to fly according to the flight model including:
  • step S253 can be implemented by communication interface 70, and step S254 and step S268 can be implemented by processor 60.
  • the communication interface 70 is configured to receive a home position point indication command sent by the control terminal 400; the processor 60 is configured to control the drone 200 to fly to the home position point, and the drone 200 arrives After the start position point, the drone 200 is controlled to fly in accordance with the flight trajectory indicated by the flight trajectory model.
  • the user can input the starting position point by controlling the UI interface of the terminal 400.
  • the drone 200 flies to the starting position point, the drone 200 performs the flight according to the flight trajectory indicated by the flight model. In this way, the interaction between the drone 200 and the user is enhanced to meet the user's use requirements.
  • control method of the embodiment of the present invention further includes:
  • step S27 can be implemented by processor 60. That is to say, the processor 60 is further configured to control the attitude of the gimbal 80 during the flight trajectory indicated by the drone 200 in accordance with the flight trajectory model so that the photographic subject is always located in the photographic image of the camera 90.
  • the drone 200 controls the attitude of the pan/tilt head 80 during the learning of the flight model.
  • the object is always located in the shooting screen of the camera 90 to achieve the effect of surrounding the self-timer, thereby further improving the intelligence of the drone 200 and improving the user experience.
  • step S27 controls the attitude of the gimbal 80 during the flight of the drone 200 in accordance with the flight trajectory indicated by the flight trajectory model so that the photographic subject is always located at the camera 90.
  • the shooting screen includes:
  • S272 Determine a shooting object according to the determination instruction.
  • step S271 can be implemented by communication interface 70, which can be implemented by processor 60. That is to say, the communication interface 70 is further configured to receive the photographic subject determination instruction sent by the control terminal 400; the processor 60 is further configured to determine the photographic subject according to the determination instruction.
  • the drone 200 can transmit the image transmission data to the UI interface of the control terminal to 400.
  • the user can select the shooting object to be tracked in the UI interface, and then the control terminal 400 sends the shooting object determination instruction to the drone. 200.
  • the processor 60 adjusts the attitude of the pan/tilt head 80 by an algorithm of real-time tracking detection so that the subject is always within the photographing screen of the camera 90.
  • the drone 200 includes a sensor 50, and the control method of the embodiment of the present invention controls the drone 200 to fly after the flight trajectory indicated by the flight trajectory model in step S261. Also includes:
  • step S28 can be implemented by processor 60. That is to say, the processor 60 can also be used to control the drone 200 to avoid obstacles detected by the sensor 50 during the process of controlling the drone 200 to fly in accordance with the flight trajectory indicated by the flight trajectory model.
  • the sensor 50 includes an ultrasonic sensor, a TOF (time of flight) ranging sensor, a visual distance avoidance sensor, and the like.
  • the flight location of the drone 200 may be different from the flight location when the drone 100 records the flight trajectory model.
  • the starting position and the ending position are position A and position, respectively.
  • the starting position and the ending position are position C and position D, respectively.
  • the drone 200 may have a risk of hitting an obstacle during the flight from the position C to the position D in accordance with the flight trajectory indicated by the flight trajectory model. Therefore, when the sensor 50 of the drone 200 detects an obstacle, it needs to perform autonomous avoidance to ensure the safety of the drone 200 in flight.
  • the drone 100 and the drone 200 of the embodiment of the present invention may be the same type of drone. That is to say, the drone 100 can not only have a function of recording a flight model but also a function of flying in accordance with a flight model acquired from an external device.
  • the drone 200 not only has a function of flying in accordance with a flight model acquired from an external device, but also has a function of recording a flight model.
  • a drone 1000 of an embodiment of the present invention includes a pan/tilt head 500, a camera 600, one or more processors 700, a memory 800, and one or more programs 810.
  • One or more of the programs 810 are stored in the memory 800 and are configured to be executed by one or more processors 700.
  • the program 810 includes a control method for performing any of the above embodiments.
  • the program 810 can be used to execute instructions of the control method described in the following steps:
  • the program 810 can also be used to execute instructions of the control method described in the following steps:
  • S26 Control the drone 200 to fly according to the flight model.
  • a computer readable storage medium in accordance with an embodiment of the present invention includes a computer program for use in conjunction with a flight capable electronic device, which can be executed by processor 800 to perform the control method described in any of the above embodiments.
  • a computer program can be executed by processor 800 to perform the control methods described in the following steps:
  • the computer program can also be executed by processor 800 to perform the control methods described in the following steps:
  • S26 Control the drone 200 to fly according to the flight model.
  • a "computer-readable medium” can be any apparatus that can contain, store, communicate, propagate, or transport a program for use in an instruction execution system, apparatus, or device, or in conjunction with the instruction execution system, apparatus, or device.
  • computer readable media include the following: electrical connections (electronic devices) having one or more wires, portable computer disk cartridges (magnetic devices), random access memory (RAM), Read only memory (ROM), erasable editable read only memory (EPROM or flash memory), fiber optic devices, and portable compact disk read only memory (CDROM).
  • the computer readable medium may even be a paper or other suitable medium on which the program can be printed, as it may be optically scanned, for example by paper or other medium, followed by editing, interpretation or, if appropriate, other suitable The method is processed to obtain the program electronically and then stored in computer memory.
  • portions of the invention may be implemented in hardware, software, firmware or a combination thereof.
  • multiple steps or methods may be performed by software or firmware stored in a memory and executed by a suitable instruction execution system.
  • the hardware is executed, as in another embodiment, and can be performed by any one or combination of the following techniques well known in the art: discrete logic circuits having logic gates for performing logic functions on data signals, An application specific integrated circuit with a suitable combination of logic gates, a programmable gate array (PGA), a field programmable gate array (FPGA), and the like.
  • PGA programmable gate array
  • FPGA field programmable gate array
  • each functional unit in each embodiment of the present invention may be integrated into one processing module, or each unit may exist physically separately, or two or more units may be integrated into one module.
  • the above integrated modules can be executed in the form of hardware or in the form of software functional modules.
  • the integrated modules, if executed in the form of software functional modules and sold or used as separate products, may also be stored in a computer readable storage medium.
  • the above mentioned storage medium may be a read only memory, a magnetic disk or an optical disk or the like.

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Abstract

一种用于无人机(100)的控制方法及一种无人机(100)。控制方法包括：(S12)采集无人机(100)飞行过程中的运动信息；(S14)根据运动信息确定飞行模型的模型参数；(S16)将模型参数发送至外部设备。

Description

控制方法和无人机 技术领域
本发明涉及无人机技术领域，特别涉及一种控制方法和无人机。
背景技术
无人机的普及度正日益增长，但许多用户不是专业飞手，对无人机的操控技术较差，不能控制无人机飞出较为专业的飞行轨迹以获得较好的拍摄体验。而目前无人机的自动飞行主要是通过选取航点，然后基于航点产生航线自动飞行。但这一飞行方案基于航点自动产生飞行轨迹，没有关注飞行过程中的拍摄效果，无法获得高水准的拍摄作品，拍摄价值较低，缺乏分享的动机。
发明内容
本发明的实施例提供一种控制方法和无人机，以使普通用户也能拍摄出高水准的拍摄作品。
本发明实施方式的控制方法用于无人机。所述控制方法包括：采集所述无人机飞行过程中的运动信息，根据所述运动信息确定飞行模型的模型参数，以及将所述模型参数发送至外部设备。
本发明实施方式的控制方法用于无人机。所述无人机与外部设备通信。所述控制方法包括：从所述外部设备获取模型参数，根据所述模型参数确定飞行模型以及控制所述无人机按照所述飞行模型飞行。
本发明实施方式的无人机包括传感器、处理器和通信接口。所述传感器用于采集所述无人机飞行过程中的运动信息；所述处理器用于根据所述运动信息确定飞行模型的模型参数；所述通信接口用于将所述模型参数发送至外部设备。
本发明实施方式的无人机与外部设备通信。所述无人机包括通信接口、处理器，所述通信接口用于从所述外部设备获取模型参数；所述处理器用于根据所述模型参数确定飞行模型；所述处理器用于控制所述无人机按照所述飞行模型飞行。
本发明实施方式的无人机包括云台、摄像头、一个或多个处理器、存储器和一个或多个程序，其中所述一个或多个程序被存储在所述存储器中，并且被配置成由所述一个或多个处理器执行，所述程序包括用于执行上述的控制方法的指令。
本发明实施方式的控制方法和无人机和在录制好飞行模型后，将上述飞行模型分享给其他无人机进行使用。如此，非专业飞手的用户可以直接使用录制好的飞行模型控制无人机进行飞行和航拍以得到较高水准的拍摄作品，提升用户的使用体验。
本发明的实施方式的附加方面和优点将在下面的描述中部分给出，部分将从下面的描述中变得明显，或通过本发明的实施方式的实践了解到。
附图说明
本发明的上述和/或附加的方面和优点从结合下面附图对实施方式的描述中将变得明显和容易理解，其中：
图1是本发明某些实施方式的控制方法的流程示意图。
图2是本发明某些实施方式的无人机的模块示意图。
图3是本发明某些实施方式的控制方法的状态示意图。
图4至图24是本发明某些实施方式的控制方法的流程示意图。
图25是本发明某些实施方式的无人机的模块示意图。
图26至28是本发明某些实施方式的控制方法的应用场景示意图。
具体实施方式
下面详细描述本发明的实施方式，所述实施方式的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施方式是示例性的，仅用于解释本发明，而不能理解为对本发明的限制。
请一并参阅图1至3，本发明实施方式的控制方法用于无人机100。控制方法包括：
S12：采集无人机100飞行过程中的运动信息；
S14：根据运动信息确定飞行模型的模型参数；和
S16：将模型参数发送至外部设备。
本发明实施方式的控制方法可以由本发明实施方式的无人机100实现。本发明实施方式的无人机 100包括传感器10、处理器20和通信接口30。此外，无人机100还承载由云台40。其中，步骤S12可以由传感器10实现，步骤S14可以由处理器20实现，步骤S16可以由通信接口30实现。
也即是说，传感器10用于采集无人机100飞行过程中的运动信息；处理器20用于根据运动信息确定飞行模型的模型参数；通信接口30用于将模型参数发送至外部设备。
其中，所述处理器20可以是无人机的飞行控制器，也可以是其他专用或者通用的处理器，在这里不作具体的限定。
在某些实施方式中，运动信息包括无人机100的位置信息、无人机100的速度信息、无人机100的加速度信息、无人机100的姿态信息、无人机100的角速度信息、无人机100的云台姿态信息、云台40运动的角速度信息、云台40运动的角加速度信息中的一种或多种。其中，所述位置信息可以是绝对位置信息(经度、纬度)，也可以是相对位置信息，相对位置信息是相对于参考点的位置信息。用于采集无人机飞行过程中的运动信息的传感器10包括指南针、电子罗盘、惯性测量单元(Inertial Measurement Unit,IMU)、加速度传感器、视觉传感器(双目、单目、视觉里程计)、GNSS接收机、气压计、空速计、指南针、超声波等传感器中的至少一种。
其中，无人机100的位置信息可以由无人机配置的GNSS接收机、惯性测量单元、视觉传感器等进行采集，无人机100的速度信息可以由无人机配置的GNSS接收机、惯性测量单元、视觉传感器、超声波传感器或空速计进行采集，无人机100的加速度信息可以由加速度传感器进行采集，无人机100的姿态信息可以由惯性测量单元进行采集，无人机100的角速度信息可以由惯性测量单元进行采集，无人机100的云台姿态信息可以由惯性测量单元进行采集，无人机100的云台40运动的角速度信息可以由惯性测量单元进行采集。
在某些实施方式中，外部设备包括无人机200、服务器300、控制终端400中的一种或多种。其中控制终端400可以是遥控器、智能手机、平板电脑、无人机地面控制站、手表、手环、视频眼镜等中的一种或多种。在本发明的实施例中，控制终端400接收用户的输入。其中，用户可以通过操作遥控器上的拔轮、按钮、按键、遥感等进行输入或者通过控制终端400上的用户界面(UI)进行输入。
本发明实施方式的控制方法通过处理采集到的无人机100飞行过程中的运动信息得到无人机100的飞行模型的模型参数，上述模型参数可以发送至外部设备，外部设备如无人机200可直接根据模型参数进行飞行。如此，可实现飞行模型的模型参数的共享。尤其对于非专业飞手来说，非专业飞手对无人机200的操作技能可能较为生疏，因此无法熟练地操控无人机200进行航拍以得到较高水准的拍摄作品。而专业飞手将录制的模型参数上传至服务器300或直接发送给无人机200，则非专业飞手可以控制无人机200直接根据专业飞手录制的模型参数处理得到的飞行模型进行飞行，从而获得高质量的航拍作品。如此，可以提升用户的使用体验。
请一并参阅图2和图4，在某些实施方式中，步骤S12采集无人机100飞行过程中的运动信息包括：
S121：采集无人机100飞行过程中的第一运动信息；
步骤S14根据运动信息确定飞行模型的模型参数包括：
S141：根据第一运动信息确定飞行轨迹模型的模型参数；
步骤S16将模型参数发送至外部设备包括：
S161：将飞行轨迹模型的模型参数发送至外部设备。
在某些实施方式中，步骤S121可以由传感器10实现，步骤S141可以由处理器20实现，步骤S161可以由通信接口30实现。
也即是说，传感器10可用于采集无人机100飞行过程中的第一运动信息；处理器20可用于根据第一运动信息确定飞行轨迹模型的模型参数；通信接口30可用于将飞行轨迹模型的模型参数发送至外部设备。
具体地，请参阅图26所示的应用场景一。其中，第一运动信息可以至少包括无人机100的位置信息、速度信息和加速度信息中的一种。传感器10在无人机100的从位置A飞行至位置B的飞行过程中仅采集与飞行轨迹模型相关的第一运动信息。处理器20通过处理位置信息、速度信息和加速度信息中的一种或多种即可得到飞行轨迹模型的模型参数。处理器20将飞行轨迹模型的模型参数发送至外部设备，如无人机200，以进行共享。如此，无人机200可根据上述模型参数确定飞行轨迹模型并根据飞行轨迹模型指示的飞行轨迹进行飞行。
请一并参阅图2和图5，在某些实施方式中，步骤S12采集无人机100飞行过程中的运动信息包括：
S122：采集无人机100飞行过程中的第一运动信息与第二运动信息；
步骤S14根据运动信息确定飞行模型的模型参数包括：
S142：根据第一运动信息确定飞行轨迹模型的模型参数，及根据第二运动信息确定飞行速度模型的 模型参数；
步骤S16将模型参数发送至外部设备包括：
S162：将飞行轨迹模型的模型参数及飞行速度模型的模型参数发送至外部设备。
在某些实施方式中，步骤S122可以由传感器10实现，步骤S142可以由处理器20实现，步骤S162可以由通信接口30实现。
也即是说，传感器10可用于采集无人机100飞行过程中的第一运动信息与第二运动信息；处理器20可用于根据第一运动信息确定飞行轨迹模型的模型参数，及根据第二运动信息确定飞行速度模型的模型参数；通信接口30可用于将飞行速度模型的模型参数及飞行速度模型的模型参数发送至外部设备。
具体地，请参阅图26所示的应用场景二。其中，第一运动信息可以至少包括无人机100的位置信息、速度信息和加速度信息中的一种，第二运动信息可以包括无人机100的速度信息和加速度信息中一种。传感器10在无人机100从位置A飞行至位置B的一次飞行过程中同时采集与飞行轨迹模型相关的第一运动信息和与飞行速度模型相关的第二运动信息。处理器20通过处理位置信息、速度信息和加速度信息中的一种或多种即可得到飞行轨迹模型的模型参数，通过处理速度信息和加速度信息中的一种或多种即可得到飞行速度模型的模型参数。随后，处理器20将飞行轨迹模型及飞行速度模型的模型参数均发送至外部设备，如无人机200，以进行共享。如此，无人机200不仅可以根据由飞行轨迹模型的模型参数确定的飞行轨迹模型指示的飞行轨迹进行飞行，还可以根据由飞行速度模型的模型参数确定的飞行速度模型进行无人机100的速度控制，从而更加精确地还原录制时无人机100的飞行轨迹及飞行速度，可获得更好的飞行效果和航拍效果。
请一并参阅图2、图6和图7，在某些实施方式中，步骤S12采集无人机100飞行过程中的运动信息包括：
S123：采集无人机100飞行过程中的第一运动信息与第三运动信息；
步骤S14根据运动信息确定飞行模型的模型参数包括：
S143：根据第一运动信息确定飞行轨迹模型的模型参数，及根据第三运动信息确定云台姿态模型的模型参数；
步骤S16将模型参数发送至外部设备包括：
S163：将飞行轨迹模型的模型参数及云台姿态模型的模型参数发送至外部设备。
在某些实施方式中，步骤S123可以由传感器10实现，步骤S143可以由处理器20实现，步骤S163可以由通信接口30实现。
也即是说，传感器10可用于采集无人机100飞行过程中的第一运动信息与第三运动信息；处理器20可用于根据第一运动信息确定飞行轨迹模型的模型参数，及根据第三运动信息确定云台姿态模型的模型参数；通信接口30可用于将飞行轨迹模型的模型参数及云台姿态模型的模型参数发送至外部设备。
具体地，请参阅图26所示的应用场景三。其中，第一运动信息可以至少包括无人机100的位置信息、速度信息和加速度信息中的一种，第三运动信息可以至少包括无人机100的云台姿态信息、云台运动的角速度信息、角加速度信息中的一种，即无人机100的云台40在Pitch轴上的俯仰角信息、在Yaw轴上的偏航角信息和在Roll轴上的翻滚角信息。传感器10在无人机100从位置A飞行至位置B的一次飞行过程中同时采集与飞行轨迹模型相关的第一运动信息和与云台姿态模型相关的第三运动信息。处理器20通过处理位置信息、速度信息和加速度信息中的一种或多种即可得到飞行轨迹模型的模型参数，通过处理云台姿态信息、云台运动的角速度信息、角加速度信息中的一种或多种即可得到云台姿态模型的模型参数。随后，处理器20将飞行轨迹模型及云台姿态模型的模型参数均发送至外部设备，如无人机200，以进行共享。如此，无人机200不仅可以根据由飞行轨迹模型的模型参数确定的飞行轨迹模型指示的飞行轨迹进行飞行，还可以根据由云台姿态模型的模型参数确定的云台姿态模型进行无人机200的云台80的角度调整，从而更加精确地还原录制时无人机100的飞行轨迹及云台姿态，可获得更好的飞行效果和航拍效果。
请一并参阅图2、图7和图8，在某些实施方式中，步骤S12采集无人机100飞行过程中的运动信息包括：
S124：采集无人机100飞行过程中的第一运动信息、第二运动信息和第三运动信息；
步骤S14根据运动信息确定飞行模型的模型参数包括：
S144：根据第一运动信息确定飞行轨迹模型的模型参数，根据第二运动信息确定飞行速度模型的模型参数，及根据第三运动信息确定云台姿态模型的模型参数；
步骤S16将模型参数发送至外部设备包括：
S164：将飞行轨迹模型的模型参数、飞行速度模型的模型参数、及云台姿态模型的模型参数发送至 外部设备。
在某些实施方式中，步骤S124可以由传感器10实现，步骤S144可以由处理器20实现，步骤S164可以由通信接口30实现。
也即是说，传感器10可用于采集无人机100飞行过程中的第一运动信息、第二运动信息和第三运动信息；处理器20可用于根据第一运动信息确定飞行轨迹模型的模型参数，根据第二运动信息确定飞行速度模型的模型参数，及根据第三运动信息确定云台姿态模型的模型参数；通信接口30可用于将飞行轨迹模型的模型参数、飞行速度模型的模型参数、及云台姿态模型的模型参数发送至外部设备。
具体地，请参阅图26所示的应用场景四。其中，第一运动信息可以至少包括无人机100的位置信息、速度信息和加速度信息中的一种，第二运动信息可以至少包括无人机100的速度信息、加速度信息中的一种，第三运动信息可以至少包括无人机100的云台姿态信息、云台运动的角速度信息、角加速度信息中的一种，即云台的姿态即为无人机100的云台40在Pitch轴上的俯仰角信息、在Yaw轴上的偏航角信息和在Roll轴上的翻滚角信息。传感器10在无人机100从位置A飞行至位置B的一次飞行过程中同时采集与飞行轨迹模型相关的第一运动信息、与飞行速度模型相关的第二运动信息、及与云台姿态模型相关的第三运动信息。处理器20通过处理位置信息、速度信息和加速度信息中的一种或多种即可得到飞行轨迹模型的模型参数，通过处理速度信息、加速度信息中的一种或多种即可得到飞行速度模型的模型参数，通过处理云台姿态信息、云台运动的角速度信息、角加速度信息中的一种或多种即可得到云台姿态模型的模型参数。随后，处理器20将飞行轨迹模型、飞行速度模型及云台姿态模型的模型参数均发送至外部设备，如无人机200，以进行共享。如此，无人机200不仅可以根据由飞行轨迹模型的模型参数确定的飞行轨迹模型指示的飞行轨迹进行飞行，还可以由飞行速度模型的模型参数确定的飞行速度模型进行无人机100的速度控制，同时还能根据由云台姿态模型的模型参数确定的云台姿态模型进行无人机200的云台80的角度调整，从而更加精确地还原录制时无人机100的飞行轨迹、飞行速度及云台姿态，可获得更好的飞行效果和航拍效果。
请一并参阅图2和图9，在某些实施方式中，本发明实施方式的控制方法还包括：
S11：根据飞行轨迹模型的模型参数控制无人机100在飞行轨迹模型指示的飞行轨迹上飞行；
S125：采集无人机100在沿着指示的飞行轨迹飞行的飞行过程中的第二运动信息；
S145：根据第二运动信息确定飞行速度模型的模型参数；
S165：将飞行速度模型的模型参数发送至外部设备。
在某些实施方式中，步骤11可以由处理器20实现，步骤S125可以由传感器10实现，步骤S145可以由处理器20实现，步骤S165可以由通信接口30实现。
也即是说，处理器20可用于根据飞行轨迹模型的模型参数控制无人机100在飞行轨迹模型指示的飞行轨迹上飞行；传感器10可用于采集无人机100在沿着指示的飞行轨迹飞行的飞行过程中的第二运动信息；处理器还可用于根据第二运动信息确定飞行速度模型的模型参数；通信接口30可用于将飞行速度模型的模型参数发送至外部设备。具体地，请参阅图26的应用场景五。无人机100在第一次从位置A飞行至位置B的飞行过程中首先采集第一运动信息以确定飞行轨迹模型的模型参数。随后，无人机100根据飞行轨迹模型指示的飞行轨迹，以位置A为起点，以位置B为终点，进行第二次飞行。在第二次飞行过程中，无人机100仅采集第二运动信息。随后，无人机100对第二运动信息进行处理以确定飞行速度模型的模型参数，并将飞行速度模型的模型参数发送至外部设备。如此，无人机100采用多次飞行录制的形式分别录制飞行轨迹模型和飞行速度模型。在每一次录制中，用户的关注点有所不同，如第一次飞行重点关注飞行轨迹，第二次飞行重点关注飞行速度。如此，用户对无人机100的操控更加完美，录制出的飞行模型的质量更佳。
请一并参阅图2和图10，在某些实施方式中，本发明实施方式的控制方法还包括：
S11：根据飞行轨迹模型的模型参数控制无人机100在飞行轨迹模型指示的飞行轨迹上飞行；
S126：采集无人机100在沿着指示的飞行轨迹飞行的飞行过程中的第三运动信息；
S146：根据第三运动信息确定云台姿态模型的模型参数；和
S166：将云台姿态模型的模型参数发送至外部设备。
在某些实施方式中，步骤S11可以由处理器20实现，步骤S125可以由传感器10实现，步骤S146可以由处理器20实现，步骤S166可以由通信接口30实现。
也即是说，处理器10可用于根据飞行轨迹模型的模型参数控制无人机100在飞行轨迹模型指示的飞行轨迹上飞行；传感器20可用于采集无人机100才沿着指示的飞行轨迹飞行的飞行过程中的第三运动信息；处理器20还可用于根据第三运动信息确定云台姿态模型的模型参数；通信接口30可用于将云台姿态模型的模型参数发送至外部设备。
具体地，请参阅图26所述的应用场景六。无人机100在第一次从位置A飞行至位置B的飞行过程中首先采集第一运动信息以确定飞行轨迹模型的模型参数。随后，无人机100根据飞行轨迹模型指示的飞行轨迹，以位置A为起点，以位置B为终点，进行第二次飞行。在第二次飞行过程中，无人机100仅采集第三运动信息。随后，无人机100对第三运动信息进行处理以确定云台姿态模型的模型参数，并将云台姿态模型的模型参数发送至外部设备。如此，无人机100采用多次飞行录制的形式分别录制飞行轨迹模型和云台姿态模型。在每一次录制中，用户的关注点有所不同，如第一次飞行重点关注飞行轨迹，第二次飞行重点关注云台姿态。如此，用户对无人机100的操控更加完美，录制出的飞行模型的质量更佳。
请一并参阅图2和图11，在某些实施方式中，本发明实施方式的控制方法还包括：
S11：根据飞行轨迹模型的模型参数控制无人机100在飞行轨迹模型指示的飞行轨迹上飞行；
S127：采集无人机100在沿着指示的飞行轨迹飞行的飞行过程中的第二运动信息和第三运动信息；
S147：根据第二运动信息确定飞行速度模型的模型参数，并根据第三运动信息确定云台姿态模型的模型参数；和
S167：将飞行速度模型的模型参数和云台姿态模型的模型参数发送至外部设备。
在某些实施方式中，步骤S11可以由处理器20实现，步骤S127可以由传感器10实现，步骤S147可以由处理器20实现，步骤S167可以由通信接口30实现。
也即是说，处理器20还可用于根据飞行轨迹模型的模型参数控制无人机100在飞行轨迹模型指示的飞行轨迹上飞行；传感器20还可用于采集无人机100在沿着指示的飞行轨迹飞行的飞行过程中的第二运动信息和第三运动信息；处理器20还可用于根据第二运动信息确定飞行速度模型的模型参数，并根据第三运动信息确定云台姿态模型的模型参数；通信接口30还可用于将飞行速度模型的模型参数和云台姿态模型的模型参数发送至外部设备。
具体地，请参阅图26所示的应用场景七。无人机100在第一次从位置A飞行至位置B的飞行过程中首先采集第一运动信息以确定飞行轨迹模型的模型参数。随后，无人机100根据飞行轨迹模型指示的飞行轨迹，以位置A为起点，以位置B为终点，进行第二次飞行。在第二次飞行过程中，无人机100同时采集第二运动信息和第三运动信息。随后，无人机100对第二运动信息进行处理已确定飞行速度模型的模型参数，对第三运动信息进行处理以确定云台姿态模型的模型参数，并将飞行速度模型的模型参数和云台姿态模型的模型参数发送至外部设备。如此，无人机100采用多次飞行录制的形式分别录制飞行轨迹模型、飞行速度模型和云台姿态模型。在每一次录制中，用户的关注点有所不同，如第一次飞行重点关注飞行轨迹，第二次飞行重点关注飞行速度和云台姿态。如此，用户对无人机100的操控更加完美，录制出的飞行模型的质量更佳。
或者，请参阅图26所示的应用场景八。无人机100在第一次从位置A飞行至位置B的飞行过程中首先采集第一运动信息以确定飞行轨迹模型的模型参数。随后，无人机100根据飞行轨迹模型指示的飞行轨迹，以位置A为起点，以位置B为终点，进行第二次飞行。在第二次飞行过程中，无人机100采集第二运动信息。随后，无人机100对第二运动信息进行处理已确定飞行速度模型的模型参数，并将飞行速度模型的模型参数发送至外部设备。再接着，无人机100根据飞行轨迹模型指示的飞行轨迹，以位置A为起点，以位置B为终点，按照飞行速度模型进行第三次飞行。在第三次飞行过程中，无人机100采集第三运动信息。最后，无人机100对第三运动信息进行处理已确定云台姿态模型的模型参数，并将云台姿态模型的模型参数发送至外部设备。如此，无人机100采用多次飞行录制的形式分别录制飞行轨迹模型、飞行速度模型、云台姿态模型。在每一次录制中，用户的关注点有所不同，如第一次飞行重点关注飞行轨迹，第二次飞行重点关注飞行速度、第三次飞行重点关注云台姿态。如此，用户对无人机100的操控更加完美，录制出的飞行模型的质量更佳。
请一并参阅图2和图12，在某些实施方式中，飞行模型包括一个或多个以时间间隔分段的飞行模型段。步骤S14根据运动信息确定飞行模型的模型参数包括：
S1481：根据时间间隔将无人机100的飞行过程划分为多个航段；和
S1482：根据多个航段中每一个航段的运动信息确定与飞行模型段对应的模型参数。
在某些实施方式中，步骤S1481和步骤S1482可以由处理器20实现。
也即是说，处理器20还可用于根据时间间隔将无人机100的飞行过程划分为多个航段，以及根据多个航段中每一个航段的运动信息确定与飞行模型段对应的模型参数。
具体地，飞行模型包括多个飞行模型段，飞行模型段以时间间隔进行划分，每一个飞行模型段对应一个函数式，因此，飞行模型是一个以时间间隔进行分段的分段函数。将无人机100的整个飞行过程以时间为间隔进行航段划分，每一个航段对应一个运动信息及函数式，由上述运动信息和函数式可确定每 一个航段对应的模型参数。如此，将飞行模型以时间间隔进行分段，可以使得飞行模型对应的函数更好地拟合无人机100在整个飞行过程中的飞行轨迹、飞行速度或云台姿态。如此，飞行模型的精确度更高。
请一并参阅图2和图13，在某些实施方式中，步骤S14根据运动信息确定飞行模型的模型参数包括：
S1491：根据采集运动信息时的时间和预设飞行模型确定与运动信息对应的预期运动信息；
S1492：确定采集的运动信息与预期运动信息之间的误差；和
S1493：根据误差确定飞行模型的模型参数。
在某些实施方式中，步骤S1491、步骤S1492和步骤S1493可以由处理器20实现。
也即是说，处理器20用于：根据采集运动信息时的时间和预设飞行模型确定与运动信息对应的预期运动信息，确定采集的运动信息与预期运动信息之间的误差，以及根据误差确定飞行模型的模型参数。
其中，预设飞行模型包括指示无人机100飞行的预设飞行轨迹模型、指示无人机100飞行的预设飞行速度模型、指示无人机100的云台40的姿态的预设云台姿态模型中的一种或多种。预设飞行模型与飞行模型具有相同的分段函数表达式，两者区别之处在于预设飞行模型中的模型参数p为未知量，需要通过误差方程进行求取。
具体地，以飞行轨迹模型为例进行说明。飞行轨迹模型是一个关于模型参数p和时间t的分段函数f(p,t)，函数式如下所示：
Figure PCTCN2017087955-appb-000001
其中，[t0,t1),[t1,t2),...,[tm-1,tm)表示以时间为间隔的飞行模型段，m表示每个飞行模型段对应的编号，如[t0,t1)表示第一个飞行模型段，[t1,t2)表示第二个飞行模型段，以此类推。n表示每一个飞行模型段中模型参数p的个数或者说每一个飞行模型段对应的函数的系数个数。
预设飞行轨迹模型中的模型参数p是未知数，需要通过采集的第一运动信息进行确定。其中，第一运动信息包括无人机100的位置信息x、速度信息v和加速度信息a。具体地，模型参数p可通过一个误差方程进行求解。误差方程的表达式如下：
Figure PCTCN2017087955-appb-000002
其中，以下标j来区分不同时间点搜集到的位置信息xj、速度信息vj和加速度信息aj。位置信息xj、速度信息vj和加速度信息aj分别为对应时间点下传感器10采集到的位置信息、速度信息和加速度信息，即传感器10采集到的运动信息。f(p,tj)、
Figure PCTCN2017087955-appb-000003
和
Figure PCTCN2017087955-appb-000004
分别为位置信息xj、速度信息vj和加速度信息aj的对应的预期运动信息。wx、wv、wa分别为位置信息、速度信息及加速度信息对应的权重。
误差方程将飞行轨迹模型在各个时间点上由预设飞行轨迹模型计算得到的位置、速度和加速度与采集到的位置、速度和加速度进行偏差加权求和。如此，为使飞行轨迹模型的函数能够更加准确地描述无人机100的飞行轨迹，需要选出一个p值使得误差方程的值即error(p)的值最小。在理想情况下，error(p)的值应该为零。但在实际操作中，由于传感器10采集的第一运动信息存在一定偏差，因此，error(p)的值无法达到零。具体地，p值的求取方法如下：首先选择一个p值代入误差方程进行计算以得到error(p)的值，根据error(p)的值的大小衡量当前的飞行轨迹模型的精准度。如果error(p)的值较大，则以上述已代入误差方程进行计算的p值为依据重新选取一个新的p值代入误差方程以得到新的error(p)的值，并根据新的error(p)的值衡量新的飞行轨迹模型的精准度。如此循环往复，直至选取到一个p值使得error(p)的值尽可能小，即将对应的p值作为最终的飞行轨迹模型的模型参数。
同样地，飞行速度模型的模型参数及云台姿态模型的模型参数同样可以参照上述的计算方式进行模型参数的求取，在此不再赘述。
请一并参阅图7和图14，本发明实施方式的控制方法用于无人机200。无人机200与外部设备通信。控制方法包括：
S22：从外部设备获取模型参数；
S24：根据模型参数确定飞行模型；和
S26：控制无人机200按照飞行模型飞行。
本发明实施方式的控制方法可以由本发明实施方式的无人机200实现。本发明实施方式的无人机200包括处理器60和通信接口70。步骤22可以由通信接口70实现。步骤S24和步骤S26可以由处理器60实现。
也即是说，通信接口70用于从外部设备获取模型参数；处理器60用于：根据模型参数确定飞行模型，以及控制无人机200按照飞行模型飞行。
本发明实施方式的无人机200还承载有云台80，云台80搭载有摄像头90。
在某些实施方式中，外部设备包括无人机100、服务器300、控制终端400中的一种或多种。其中控制终端400可以是遥控器、智能手机、平板电脑、无人机地面控制站、手表、手环、视频眼镜等中的一种或多种。在本发明的实施例中，控制终端接收用户的输入。其中，用户可以通过操作遥控器上的拔轮、按钮、按键、遥感等进行输入或者通过控制终端400上的用户界面(UI)进行输入。
本发明实施方式的控制方法首先处理从外部设备获取到的模型参数p以得到飞行模型f(p,t)，具体地，无人机200从外部设备获取模型参数p并将模型参数p代入飞行模型的函数式f(p,t)中。飞行模型f(p,t)是以时间为间隔进行分段的分段函数。其中，模型参数p和时间t均为已知量，如此，即可确定f(p,t)的值。随后根据上述飞行模型控制无人机200进行自主飞行。尤其对于非专业飞手来说，在非专业飞手使用无人机200时，可以直接使用专业飞手录制好的飞行模型操控无人机200进行飞行，一方面可以确保无人机200飞行过程中的安全性，另一方面可以帮助非专业飞手获取到水准较高的航拍作品，提升用户的使用体验。
请一并参阅图7和图15，在某些实施方式中，飞行模型至少包括飞行轨迹模型，步骤S26控制无人机200按照飞行模型飞行包括：
S261：控制无人机200按照飞行轨迹模型指示的飞行轨迹飞行。
在某些实施方式中，步骤S261可以由处理器60实现。也即是说，处理器60进一步用于控制无人机200按照飞行轨迹模型指示的飞行轨迹飞行。
具体地，请参阅图27所示的应用场景一和应用场景二。无人机200通过学习飞行轨迹模型按照飞行轨迹模型指示的飞行轨迹从位置A飞行至位置B，或者按照飞行轨迹模型指示的飞行轨迹从位置C飞行至位置D。其中，位置A与位置C指代两个不同的起点位置，位置B和位置D指代两个不同的终点位置。具体地，如前所述，无人机100在获取模型参数的期间，采集的位置信息可以是绝对位置信息，也可以是相对位置信息，当无人机采集的位置信息是绝对位置信息时，例如无人机100采集的位置信息是从位置A至位置B的绝对位置信息，无人机200通过学习飞行轨迹模型按照飞行轨迹模型指示的飞行轨迹从位置A飞行至位置B，此时完全重复无人机100从位置A飞行至位置B的飞行轨迹；当无人机采集的位置信息是相对位置信息时，例如无人机100采集的位置信息是从位置A至位置B的相对位置信息，即从位置A至位置B的位置信息相对于参考点的位置信息，其中参考点可以接收到控制终端发送的录制指令时无人机100所处的位置，无人机200按照飞行轨迹模型指示的飞行轨迹从位置C飞行至位置D，此时，无人机200根据参考点确定位置C和位置D，其中参考点可以接收到控制终端发送的重播指令时无人机200所处的位置。也即是说，无人机200学习飞行模型时所处的飞行环境无需与无人机100录制飞行模型时的飞行环境相同。如此，无人机200可依照飞行轨迹模型的指示的飞行轨迹自主飞行，用户无需手动操控以改变无人机200的飞行位置，无人机200的智能性和便利性得到极大提升。此外，无人机200学习飞行模型时的飞行环境与无人机100录制飞行模型时的飞行环境无需相同，飞行模型的可移植性较高。
需要说明的是，本文只是给出参考点的一种选择方式，本领域技术人员可以选择其他位置作为参考点，在这里不作具体的限定。
请一并参阅图7和图16，在某些实施方式中，飞行模型还包括飞行速度模型，步骤S26控制无人机200按照飞行模型飞行包括：
S262：控制无人机200按照飞行轨迹模型指示的飞行轨迹及飞行速度模型指示的飞行速度飞行。
在某些实施方式中，步骤S262可以由处理器60实现。也即是说，处理器60进一步用于控制无人机200按照飞行轨迹模型指示的飞行轨迹及飞行速度模型指示的飞行速度飞行。
具体地，请参阅图27所示的应用场景一和应用场景二。无人机200通过学习飞行轨迹模型和飞行速度模型，按照飞行轨迹模型指示的飞行轨迹及按照飞行速度模型指示的飞行速度从位置A飞行至位置 B，或者按照飞行轨迹模型指示的飞行轨迹及按照飞行速度指示的飞行速度从位置C飞行至位置D。如此，无人机200能更加准确地还原录制时无人机100的飞行过程，提升无人机200的飞行效果。此时无人机200的云台80的姿态可由用户自主操控，提升航拍时摄像头90的拍摄角度的灵活性。
请一并参阅图7和图17，在某些实施方式中，飞行模型还包括云台姿态模型，步骤S26控制无人机200按照飞行模型飞行包括：
S263：控制无人机200按照飞行轨迹模型指示的飞行轨迹及飞行速度模型指示的飞行速度飞行，并同时按照云台姿态模型调整云台80的姿态。
在某些实施方式中，步骤S263可以由处理器60实现。也即是说，处理器60进一步用于控制无人机200按照飞行轨迹模型指示的飞行轨迹及飞行速度模型指示的飞行速度飞行，并同时按照云台姿态模型调整云台80的姿态。
具体地，请参阅图27所示的应用场景一和应用场景二。无人机200通过学习飞行轨迹模型、飞行速度模型和云台姿态模型，按照飞行轨迹模型指示的飞行轨迹及飞行速度模型指示的飞行速度从位置A飞行至位置B，期间同时按照云台姿态模型调整云台80的姿态；或者按照飞行轨迹模型指示的飞行轨迹及飞行速度模型指示的飞行速度从位置C飞行至位置D，期间同时按照云台姿态模型调整云台80的姿态。如此，无人机200可以更为准确地还原出无人机100在录制飞行模型时的飞行轨迹、飞行速度以及云台80的姿态，无人机200的飞行效果和航拍效果更佳。
请一并参阅图7和图18，在某些实施方式中，飞行模型还包括云台姿态模型，步骤S26控制无人机200按照飞行模型飞行包括：
S264：控制无人机200按照飞行轨迹模型指示的飞行轨迹飞行，并同时按照云台姿态模型调整云台80的姿态。
在某些实施方式中，步骤S264可以由处理器60实现。也即是说，处理器60进一步用于控制无人机200按照飞行轨迹模型指示的飞行轨迹飞行，并同时按照云台姿态模型调整云台80的姿态。
具体地，请参阅图27所示的应用场景一和应用场景二。无人机200通过学习飞行轨迹模型和云台姿态模型，按照飞行轨迹模型指示的飞行轨迹从位置A飞行至位置B，期间同时按照云台姿态模型调整云台80的姿态，或者按照飞行轨迹模型指示的飞行轨迹从位置C飞行至位置D，期间同时按照云台姿态模型调整云台80的姿态。如此，无人机200可以还原出无人机100在录制飞行模型时的飞行轨迹及云台姿态，提升无人机200的飞行效果和航拍效果。此时，无人机200的速度可以由用户自行控制，增加了无人机200的操控自由度。
请一并参阅图7和图19，在某些实施方式中，无人机200与控制终端400通信。本发明实施方式的控制方法还包括：
S251：接收控制终端400发送的速度控制指令；
步骤S26控制无人机200按照飞行模型飞行包括：
S265：控制无人机200按照飞行轨迹模型指示的飞行轨迹飞行；和
S266：控制无人机200按照速度控制指令调整无人机200的飞行速度。
在某些实施方式中，步骤S251可以由通信接口70实现，步骤S265和步骤S266可以由处理器60实现。
也即是说，通信接口70用于接收控制终端400发送的速度控制指令；处理器60用于控制无人机200按照飞行轨迹模型指示的飞行轨迹飞行，以及控制无人机200按照速度控制指令调整无人机200的飞行速度。
具体地，无人机200按照飞行轨迹模型指示的飞行轨迹飞行时，用户可以在控制终端400输入调整无人机200飞行速度的速度控制指令，控制终端400将速度控制指令发送至无人机200后，无人机200根据速度控制指令进行速度调整。如此，无人机200的操作自由度较高，无人机200通过改变沿飞行轨迹飞行过程中的飞行速度可以对飞行效果和航拍效果进行优化。
请一并参阅图7和图20，在某些实施方式中，无人机200与控制终端400通信。本发明实施方式的控制方法还包括：
S252：接收控制终端400发送的云台控制指令；
步骤S26控制无人机200按照飞行模型飞行包括：
S265：控制无人机200按照飞行轨迹模型指示的飞行轨迹飞行；和
S267：控制无人机200按照云台控制指令调整无人机200承载的云台80的姿态。
在某些实施方式中，步骤S252可以由通信接口70实现，步骤S265和步骤S267可以由处理器60实现。
也即是说，通信接口70用于接收控制终端400发送的云台控制指令；处理器60用于控制无人机200按照飞行轨迹模型指示的飞行轨迹飞行，以及控制无人机200按照云台控制指令调整无人机200承载的云台80的姿态。
具体地，无人机200按照飞行轨迹模型指示的飞行轨迹飞行时，用户可以在控制终端400输入调整云台80的姿态的云台控制指令，控制终端400将云台控制指令发送至无人机200后，无人机200根据云台控制指令进行云台80的姿态调整。在实际应用中，无人机200在使用飞行模型进行自主飞行时，无人机200的飞行地点和无人机100录制飞行模型时的飞行地点可以是相同的，也可以是不同的。而当飞行地点不同时，用户通过调整云台80的姿态可以改变云台上搭载的摄像头90的拍摄角度，以将用户关注的主体放入摄像头90的拍摄画面中，从而获得水准较高的航拍作品。
请一并参阅图7和图21，在某些实施方式中，无人机200与控制终端400通信。本发明实施方式的控制方法还包括：
S253：接收控制终端400发送的起始位置点指示指令；和
S254：控制无人机200飞行至所述起始位置点；
步骤S26控制无人机200按照飞行模型飞行包括：
S268：在无人机200到达起始位置点后，控制无人机200按照飞行轨迹模型指示的飞行轨迹飞行。
在某些实施方式中，步骤S253可以由通信接口70实现，步骤S254和步骤S268可以由处理器60实现。
也即是说，通信接口70用于接收控制终端400发送的起始位置点指示指令；处理器60用于控制无人机200飞行至所述起始位置点，以及在无人机200到达起始位置点后，控制无人机200按照飞行轨迹模型指示的飞行轨迹飞行。
具体地，用户可以通过控制终端400的UI界面进行起始位置点的输入，待无人机200飞行至起始位置点时无人机200自行根据飞行模型指示的飞行轨迹进行飞行。如此，增强无人机200与用户之间的交互，满足用户的使用需求。
请一并参阅图7和图22，在某些实施方式中，本发明实施方式的控制方法还包括：
S27：在无人机200按照飞行轨迹模型指示的飞行轨迹飞行过程中，控制云台80的姿态以使拍摄对象始终位于摄像头90的拍摄画面中。
在某些实施方式中，步骤S27可以由处理器60实现。也即是说，处理器60进一步用于在无人机200按照飞行轨迹模型指示的飞行轨迹飞行过程中，控制云台80的姿态以使拍摄对象始终位于摄像头90的拍摄画面中。
具体地，请参阅图28，若无人机100录制的飞行模型指示的飞行轨迹为圆形状或椭圆形状，则无人机200在学习上述飞行模型的过程中，控制云台80的姿态使拍摄对象始终位于摄像头90的拍摄画面中即可实现环绕自拍的效果，从而进一步提升无人机200的智能性，提升用户的使用体验。
请一并参阅图7和图23，在某些实施方式中，步骤S27在无人机200按照飞行轨迹模型指示的飞行轨迹飞行过程中，控制云台80的姿态以使拍摄对象始终位于摄像头90的拍摄画面中包括：
S271：接收控制终端400发送的拍摄对象确定指令；和
S272：根据确定指令确定拍摄对象。
在某些实施方式中，步骤S271可以由通信接口70实现，步骤S272可以由处理器60实现。也即是说，通信接口70还用于接收控制终端400发送的拍摄对象确定指令；处理器60还用于根据确定指令确定拍摄对象。
具体地，无人机200可以发送图传数据至控制终端到400的UI界面，用户可以在UI界面中点选需要跟踪的拍摄对象，随后由控制终端400将拍摄对象确定指令发送至无人机200。处理器60通过实时跟踪检测的算法调整云台80的姿态以使拍摄对象始终位于摄像头90的拍摄画面内。
请一并参阅图7和图24，在某些实施方式中，无人机200包括传感器50，本发明实施方式的控制方法在步骤S261控制无人机200按照飞行轨迹模型指示的飞行轨迹飞行后还包括：
S28：在控制无人机200按照所述飞行轨迹模型指示的飞行轨迹飞行的过程中，控制无人机200对传感器50探测到的障碍物进行避绕。
在某些实施方式中，步骤S28可以由处理器60实现。也即是说，处理器60还可用于在控制无人机200按照所述飞行轨迹模型指示的飞行轨迹飞行的过程中，控制无人机200对传感器50探测到的障碍物进行避绕。
其中，传感器50包括超声波传感器、TOF(time of flight)测距传感器、视觉测距避障传感器等。
具体地，请参阅图27所示的应用场景三。由于无人机200在按照飞行轨迹模型指示的飞行轨迹飞 行的过程中，无人机200的飞行地点与无人机100录制飞行轨迹模型时的飞行地点可能不同，比如，无人机100录制飞行轨迹模型时起点位置和终点位置分别为位置A和位置B，无人机200学习飞行轨迹模型时起点位置和终点位置分别为位置C和位置D。此时无人机200在按照飞行轨迹模型指示的飞行轨迹从位置C向位置D飞行的过程中可能会有撞上障碍物的危险。因此，当无人机200的传感器50探测到障碍物时需要进行自主避让以保证无人机200飞行中安全性。
需要说明的是，本发明实施方式的无人机100和无人机200可以是同种类型的无人机。也即是说，无人机100不仅可以具有录制飞行模型的功能，也具有按照从外部设备获取的飞行模型进行飞行的功能。无人机200不仅具有按照从外部设备获取的飞行模型进行飞行的功能，也具有录制飞行模型的功能。
请参阅图25，本发明实施方式的无人机1000包括云台500、摄像头600、一个或多个处理器700、存储器800和一个或多个程序810。其中一个或多个程序810被存储在存储器800中，并且被配置成由一个或多个处理器700执行。程序810包括用于执行上述任意一项实施方式所述的控制方法。
举例来说，程序810可用于执行以下步骤所述的控制方法的指令：
S12：采集无人机100飞行过程中的运动信息；
S14：根据运动信息确定飞行模型的模型参数；和
S16：将模型参数发送至外部设备。
程序810还可以用于执行以下步骤所述的控制方法的指令：
S22：从外部设备获取模型参数；
S24：根据模型参数确定飞行模型；和
S26：控制无人机200按照飞行模型飞行。
本发明实施方式的计算机可读存储介质包括与能够飞行的电子装置结合使用的计算机程序，上述计算机程序可被处理器800执行以完成上述任意一项实施方式所述的控制方法。
举例来说，计算机程序可被处理器800执行以完成以下步骤所述的控制方法：
S12：采集无人机100飞行过程中的运动信息；
S14：根据运动信息确定飞行模型的模型参数；和
S16：将模型参数发送至外部设备。
计算机程序还可被处理器800执行以完成以下步骤所述的控制方法：
S22：从外部设备获取模型参数；
S24：根据模型参数确定飞行模型；和
S26：控制无人机200按照飞行模型飞行。
在本说明书的描述中，参考术语“一个实施方式”、“一些实施方式”、“示意性实施方式”、“示例”、“具体示例”、或“一些示例”等的描述意指结合所述实施方式或示例描述的具体特征、结构、材料或者特点包含于本发明的至少一个实施方式或示例中。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方式或示例。而且，描述的具体特征、结构、材料或者特点可以在任何的一个或多个实施方式或示例中以合适的方式结合。
流程图中或在此以其他方式描述的任何过程或方法描述可以被理解为，表示包括一个或更多个用于执行特定逻辑功能或过程的步骤的可执行指令的代码的模块、片段或部分，并且本发明的优选实施方式的范围包括另外的执行，其中可以不按所示出或讨论的顺序，包括根据所涉及的功能按基本同时的方式或按相反的顺序，来执行功能，这应被本发明的实施例所属技术领域的技术人员所理解。
在流程图中表示或在此以其他方式描述的逻辑和/或步骤，例如，可以被认为是用于执行逻辑功能的可执行指令的定序列表，可以具体执行在任何计算机可读介质中，以供指令执行系统、装置或设备(如基于计算机的系统、包括处理器的系统或其他可以从指令执行系统、装置或设备取指令并执行指令的系统)使用，或结合这些指令执行系统、装置或设备而使用。就本说明书而言，"计算机可读介质"可以是任何可以包含、存储、通信、传播或传输程序以供指令执行系统、装置或设备或结合这些指令执行系统、装置或设备而使用的装置。计算机可读介质的更具体的示例(非穷尽性列表)包括以下：具有一个或多个布线的电连接部(电子装置)，便携式计算机盘盒(磁装置)，随机存取存储器(RAM)，只读存储器(ROM)，可擦除可编辑只读存储器(EPROM或闪速存储器)，光纤装置，以及便携式光盘只读存储器(CDROM)。另外，计算机可读介质甚至可以是可在其上打印所述程序的纸或其他合适的介质，因为可以例如通过对纸或其他介质进行光学扫描，接着进行编辑、解译或必要时以其他合适方式进行处理来以电子方式获得所述程序，然后将其存储在计算机存储器中。
应当理解，本发明的各部分可以用硬件、软件、固件或它们的组合来执行。在上述实施方式中，多个步骤或方法可以用存储在存储器中且由合适的指令执行系统执行的软件或固件来执行。例如，如果用 硬件来执行，和在另一实施方式中一样，可用本领域公知的下列技术中的任一项或他们的组合来执行：具有用于对数据信号执行逻辑功能的逻辑门电路的离散逻辑电路，具有合适的组合逻辑门电路的专用集成电路，可编程门阵列(PGA)，现场可编程门阵列(FPGA)等。
本技术领域的普通技术人员可以理解执行上述实施方法携带的全部或部分步骤是可以通过程序来指令相关的硬件完成，所述的程序可以存储于一种计算机可读存储介质中，该程序在执行时，包括方法实施例的步骤之一或其组合。
此外，在本发明各个实施例中的各功能单元可以集成在一个处理模块中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个模块中。上述集成的模块既可以采用硬件的形式执行，也可以采用软件功能模块的形式执行。所述集成的模块如果以软件功能模块的形式执行并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。
上述提到的存储介质可以是只读存储器，磁盘或光盘等。尽管上面已经示出和描述了本发明的实施例，可以理解的是，上述实施例是示例性的，不能理解为对本发明的限制，本领域的普通技术人员在本发明的范围内可以对上述实施例进行变化、修改、替换和变型。

Claims (49)

  1. 一种控制方法，用于无人机，其特征在于，所述控制方法包括：
    采集所述无人机飞行过程中的运动信息；
    根据所述运动信息确定飞行模型的模型参数；和
    将所述模型参数发送至外部设备。
  2. 根据权利要求1所述的控制方法，其特征在于，
    所述采集所述无人机飞行过程中的运动信息包括：
    采集所述无人机飞行过程中的第一运动信息；
    所述根据所述运动信息确定飞行模型的模型参数包括：
    根据所述第一运动信息确定飞行轨迹模型的模型参数；
    所述将所述模型参数发送至外部设备包括：
    将所述飞行轨迹模型的模型参数发送至外部设备。
  3. 根据权利要求1所述的控制方法，其特征在于，
    所述采集所述无人机飞行过程中的运动信息还包括：
    采集所述无人机飞行过程中的第一运动信息与第二运动信息；
    所述根据所述运动信息确定飞行模型的模型参数还包括：
    根据所述第一运动信息确定飞行轨迹模型的模型参数，及根据所述第二运动信息确定飞行速度模型的模型参数；
    所述将所述模型参数发送至外部设备包括：
    将所述飞行轨迹模型的模型参数及所述飞行速度模型的模型参数发送至外部设备。
  4. 根据权利要求1所述的控制方法，所述无人机承载有云台，其特征在于，
    所述采集所述无人机飞行过程中的运动信息还包括：
    采集所述无人机飞行过程中的第一运动信息与第三运动信息；
    所述根据所述运动信息确定飞行模型的模型参数还包括：
    根据所述第一运动信息确定飞行轨迹模型的模型参数，及根据所述第三运动信息确定云台姿态模型的模型参数；
    所述将所述模型参数发送至外部设备包括：
    将所述飞行轨迹模型的模型参数及所述云台姿态模型的模型参数发送至外部设备。
  5. 根据权利要求1所述的控制方法，其特征在于，所述无人机承载有云台，
    所述采集所述无人机飞行过程中的运动信息还包括：
    采集所述无人机飞行过程中的第一运动信息、第二运动信息及第三运动信息；
    所述根据所述运动信息确定飞行模型的模型参数还包括：
    根据所述第一运动信息确定飞行轨迹模型的模型参数，根据所述第二运动信息确定飞行速度模型的模型参数，及根据所述第三运动信息确定云台姿态模型的模型参数；
    所述将所述模型参数发送至外部设备包括：
    将所述飞行轨迹模型的模型参数、所述飞行速度模型的模型参数、及所述云台姿态模型的模型参数发送至外部设备。
  6. 根据权利要求2所述的控制方法，其特征在于，所述控制方法还包括：
    根据所述飞行轨迹模型的模型参数控制所述无人机在所述飞行轨迹模型指示的飞行轨迹上飞行；
    采集所述无人机在沿着所述指示的飞行轨迹飞行的飞行过程中的第二运动信息和/或第三运动信息；
    根据所述第二运动信息确定飞行速度模型的模型参数，和/或根据所述第三运动信息确定云台姿态模型的模型参数；和
    将所述飞行速度模型的模型参数和/或所述云台姿态模型的模型参数发送至外部设备。
  7. 根据权利要求1所述的控制方法，其特征在于，所述根据所述运动信息确定飞行模型的模型参数包括：
    根据采集所述运动信息时的时间和预设飞行模型确定与所述运动信息对应的预期运动信息；
    确定所述采集的运动信息与所述预期运动信息之间的误差；和
    根据所述误差确定所述飞行模型的模型参数。
  8. 根据权利要求1所述的控制方法，其特征在于，所述飞行模型包括一个或多个以时间间隔分段的飞行模型段。
  9. 根据权利要求8所述的控制方法，其特征在于，所述根据所述运动信息确定飞行模型的模型参数 包括：
    根据所述时间间隔将所述无人机的飞行过程划分为多个航段；和
    根据所述多个航段中每一个航段的运动信息确定与所述飞行模型段对应的模型参数。
  10. 根据权利要求1所述的控制方法，其特征在于，所述运动信息包括所述无人机的位置信息、所述无人机的速度信息、所述无人机的加速度信息、所述无人机的姿态信息、所述无人机的角速度信息、所述无人机的云台姿态信息、云台运动的角速度信息、云台运动的角加速度信息中的一种或多种。
  11. 根据权利要求7所述的控制方法，其特征在于，所述预设飞行模型包括指示所述无人机飞行的预设飞行轨迹模型、指示所述无人机飞行的预设飞行速度模型、指示所述无人机的云台的姿态的预设云台姿态模型中的一种或多种。
  12. 根据权利要求1所述的控制方法，其特征在于，所述外部设备包括无人机、服务器、控制终端中的一种或多种。
  13. 一种控制方法，用于无人机，所述无人机与外部设备通信，其特征在于，所述控制方法包括：
    从所述外部设备获取模型参数；
    根据所述模型参数确定飞行模型；和
    控制所述无人机按照所述飞行模型飞行。
  14. 根据权利要求13所述的控制方法，其特征在于，所述飞行模型至少包括飞行轨迹模型；所述控制所述无人机按照所述飞行模型飞行包括：
    控制所述无人机按照所述飞行轨迹模型指示的飞行轨迹飞行。
  15. 根据权利要求14所述的控制方法，其特征在于，所述飞行模型还包括飞行速度模型；所述控制所述无人机按照所述飞行模型飞行包括：
    控制所述无人机按照所述飞行轨迹模型指示的飞行轨迹及所述飞行速度模型指示的飞行速度飞行。
  16. 根据权利要求15所述的控制方法，其特征在于，所述无人机承载有云台，所述飞行模型还包括云台姿态模型；所述控制所述无人机按照所述飞行模型飞行包括：
    控制所述无人机按照所述飞行轨迹模型指示的飞行轨迹及所述飞行速度模型指示的飞行速度飞行，并同时按照所述云台姿态模型调整所述云台的姿态。
  17. 根据权利要求15所述的控制方法，其特征在于，所述无人机承载有云台，所述飞行模型还包括云台姿态模型；所述控制所述无人机按照所述飞行模型飞行包括：
    控制所述无人机按照所述飞行轨迹模型指示的飞行轨迹飞行，并同时按照所述云台姿态模型调整所述云台的姿态。
  18. 根据权利要求14所述的控制方法，其特征在于，所述无人机与控制终端通信，所述控制方法还包括：
    接收所述控制终端发送的速度控制指令；
    所述控制所述无人机按照所述飞行模型飞行包括：
    控制所述无人机按照所述飞行轨迹模型指示的飞行轨迹飞行；和
    控制所述无人机按照所述速度控制指令调整所述无人机的飞行速度。
  19. 根据权利要求14所述的控制方法，其特征在于，所述无人机承载有云台，所述无人机与控制终端通信，所述控制方法还包括：
    接收所述控制终端发送的云台控制指令；
    所述控制所述无人机按照所述飞行模型飞行包括：
    控制所述无人机按照所述飞行轨迹模型指示的飞行轨迹飞行；和
    控制所述无人机按照所述云台控制指令调整所述无人机承载的云台的姿态。
  20. 根据权利要求14所述的控制方法，其特征在于，所述无人机与控制终端通信，所述控制方法还包括：
    接收所述控制终端发送的起始位置点指示指令；和
    控制所述无人机飞行至所述起始位置点；
    所述控制所述无人机按照所述飞行模型飞行包括：
    在所述无人机到达所述起始位置点后，控制所述无人机按照所述飞行轨迹模型指示的飞行轨迹飞行。
  21. 根据权利要求14所述的控制方法，其特征在于，所述无人机承载有云台，所述云台搭载有摄像头，所述控制方法还包括：
    在所述无人机按照所述飞行轨迹模型指示的飞行轨迹飞行过程中，控制所述云台的姿态以使拍摄对 象始终位于所述摄像头的拍摄画面中。
  22. 根据权利要求21所述的控制方法，其特征在于，所述无人机与控制终端通信，所述在所述无人机按照所述飞行轨迹模型指示的飞行轨迹飞行过程中，控制所述云台的姿态以使拍摄对象始终位于所述摄像头的拍摄画面中包括：
    接收所述控制终端发送的拍摄对象确定指令；和
    根据所述确定指令确定拍摄对象。
  23. 根据权利要求14所述的控制方法，其特征在于，所述无人机包括传感器，所述控制方法在所述控制所述无人机按照所述飞行轨迹模型指示的飞行轨迹飞行的步骤后还包括：
    在控制所述无人机按照所述飞行轨迹模型指示的飞行轨迹飞行的过程中，控制所述无人机对所述传感器探测到的障碍物进行避绕。
  24. 根据权利要求13所述的控制方法，其特征在于，所述外部设备包括无人机、服务器、控制终端中的一种或多种。
  25. 一种无人机，其特征在于，所述无人机包括传感器、处理器和通信接口，
    所述传感器用于：
    采集所述无人机飞行过程中的运动信息；
    所述处理器用于：
    根据所述运动信息确定飞行模型的模型参数；
    所述通信接口用于：
    将所述模型参数发送至外部设备。
  26. 根据权利要求25所述的无人机，其特征在于，
    所述传感器进一步用于：
    采集所述无人机飞行过程中的第一运动信息；
    所述处理器进一步用于：
    根据所述第一运动信息确定飞行轨迹模型的模型参数；
    所述通信接口进一步用于：
    将所述飞行轨迹模型的模型参数发送至外部设备。
  27. 根据权利要求25所述的无人机，其特征在于，
    所述传感器进一步用于：
    采集所述无人机飞行过程中的第一运动信息与第二运动信息；
    所述处理器进一步用于：
    根据所述第一运动信息确定飞行轨迹模型的模型参数，及根据所述第二运动信息确定飞行速度模型的模型参数；
    所述通信接口进一步用于：
    将所述飞行轨迹模型的模型参数及所述飞行速度模型的模型参数发送至外部设备。
  28. 根据权利要求25所述的无人机，其特征在于，所述无人机承载有云台，
    所述传感器进一步用于：
    采集所述无人机飞行过程中的第一运动信息与第三运动信息；
    所述处理器进一步用于：
    根据所述第一运动信息确定飞行轨迹模型的模型参数，及根据所述第三运动信息确定云台姿态模型的模型参数；
    所述通信接口进一步用于：
    将所述飞行轨迹模型的模型参数及所述云台姿态模型的模型参数发送至外部设备。
  29. 根据权利要求25所述的无人机，其特征在于，所述无人机承载有云台，
    所述传感器进一步用于：
    采集所述无人机飞行过程中的第一运动信息、第二运动信息及第三运动信息；
    所述处理器进一步用于：
    根据所述第一运动信息确定飞行轨迹模型的模型参数，根据所述第二运动信息确定飞行速度模型的模型参数，及根据所述第三运动信息确定云台姿态模型的模型参数；
    所述通信接口进一步用于：
    将所述飞行轨迹模型的模型参数、所述飞行速度模型的模型参数、及所述云台姿态模型的模型参数发送至外部设备。
  30. 根据权利要求26所述的无人机，其特征在于，所述处理器还用于：
    根据所述飞行轨迹模型的模型参数控制所述无人机在所述飞行轨迹模型指示的飞行轨迹上飞行；
    所述传感器进一步用于：
    采集所述无人机在沿着所述指示的飞行轨迹飞行的飞行过程中的第二运动信息和/或第三运动信息；
    所述处理器进一步用于：
    根据所述第二运动信息确定飞行速度模型的模型参数，和/或根据所述第三运动信息确定云台姿态模型的模型参数；
    所述通信接口进一步用于：
    将所述飞行速度模型的模型参数和/或所述云台姿态模型的模型参数发送至外部设备。
  31. 根据权利要求25所述的无人机，其特征在于，所述处理器进一步用于：
    根据采集所述运动信息时的时间和预设飞行模型确定与所述运动信息对应的预期运动信息；
    确定所述采集的运动信息与所述预期运动信息之间的误差；和
    根据所述误差确定所述飞行模型的模型参数。
  32. 根据权利要求25所述的无人机，其特征在于，所述预设飞行模型包括一个或多个以时间间隔分段的飞行模型段。
  33. 根据权利要求32所述的无人机，其特征在于，所述处理器进一步用于：
    根据所述时间间隔将所述无人机的飞行过程划分为多个航段；和
    根据所述多个航段中每一个航段的运动信息确定与所述飞行模型段对应的模型参数。
  34. 根据权利要求25所述的无人机，其特征在于，所述运动信息包括所述无人机的位置信息、所述无人机的速度信息、所述无人机的加速度信息、所述无人机的姿态信息、所述无人机的角速度信息、所述无人机的云台姿态信息、所述无人机的云台的角速度信息中的一种或多种。
  35. 根据权利要求31所述的无人机，其特征在于，所述预设飞行模型包括指示所述无人机飞行的预设飞行轨迹模型、指示所述无人机飞行的预设飞行速度模型、指示所述无人机的云台的姿态的预设云台姿态模型中的一种或多种。
  36. 根据权利要求25所述的无人机，其特征在于，所述外部设备包括无人机、服务器、控制终端中的一种或多种。
  37. 一种无人机，所述无人机与外部设备通信，其特征在于，所述无人机包括通信接口和处理器，所述通信接口用于：
    从所述外部设备获取模型参数；
    所述处理器用于：
    根据所述模型参数确定飞行模型；和
    控制所述无人机按照所述飞行模型飞行。
  38. 根据权利要求37所述的无人机，其特征在于，所述飞行模型至少包括飞行轨迹模型；所述处理器进一步用于：
    控制所述无人机按照所述飞行轨迹模型指示的飞行轨迹飞行。
  39. 根据权利要求38所述的无人机，其特征在于，所述飞行模型还包括飞行速度模型；所述处理器进一步用于：
    控制所述无人机按照所述飞行轨迹模型指示的飞行轨迹及所述飞行速度模型指示的飞行速度飞行。
  40. 根据权利要求39所述的无人机，其特征在于，所述无人机承载有云台，所述飞行模型还包括云台姿态模型；所述处理器进一步用于：
    控制所述无人机按照所述飞行轨迹模型指示的飞行轨迹及所述飞行速度模型指示的飞行速度飞行，并同时按照所述云台姿态模型调整所述云台的姿态。
  41. 根据权利要求39所述的无人机，其特征在于，所述无人机承载有云台，所述飞行模型还包括云台姿态模型；所述处理器进一步用于：
    控制所述无人机按照所述飞行轨迹模型指示的飞行轨迹飞行，并同时按照所述云台姿态模型调整所述云台的姿态。
  42. 根据权利要求38所述的无人机，其特征在于，所述无人机与控制终端通信，所述通信接口进一步用于：
    接收所述控制终端发送的速度控制指令；
    所述处理器进一步用于：
    控制所述无人机按照所述飞行轨迹模型指示的飞行轨迹飞行；和
    控制所述无人机按照所述速度控制指令调整所述无人机的飞行速度。
  43. 根据权利要求38所述的无人机，其特征在于，所述无人机承载有云台，所述无人机与控制终端通信，所述通信接口进一步用于：
    接收所述控制终端发送的云台控制指令；
    所述处理器进一步用于：
    控制所述无人机按照所述飞行轨迹模型指示的飞行轨迹飞行；和
    控制所述无人机按照所述云台控制指令调整所述无人机承载的云台的姿态。
  44. 根据权利要求38所述的无人机，其特征在于，所述无人机与控制终端通信，所述通信接口进一步用于：
    接收所述控制终端发送的起始位置点指示指令；
    所述处理器进一步用于：
    控制所述无人机飞行至所述起始位置点；和
    在所述无人机到达所述起始位置点后，控制所述无人机按照所述飞行轨迹模型指示的飞行轨迹飞行。
  45. 根据权利要求38所述的无人机，其特征在于，所述无人机承载有云台，所述云台搭载有摄像头，所述处理器进一步用于：
    在所述无人机按照所述飞行轨迹模型指示的飞行轨迹飞行过程中，控制所述云台的姿态以使拍摄对象始终位于所述摄像头的拍摄画面中。
  46. 根据权利要求45所述的无人机，其特征在于，所述无人机与控制终端通信，所述通信接口进一步用于：
    接收所述控制终端发送的拍摄对象确定指令；
    所述处理器进一步用于：
    根据所述确定指令确定拍摄对象。
  47. 根据权利要求38所述的无人机，其特征在于，所述处理器还用于：
    在控制所述无人机按照所述飞行轨迹模型指示的飞行轨迹飞行的过程中，控制所述无人机对所述传感器探测到的障碍物进行避绕。
  48. 根据权利要求37所述的无人机，其特征在于，所述外部设备包括无人机、服务器、控制终端中的一种或多种。
  49. 一种无人机，其特征在在于，所述无人机包括：
    云台；
    摄像头；
    一个或多个处理器；
    存储器；
    一个或多个程序，其中所述一个或多个程序被存储在所述存储器中，并且被配置成由所述一个或多个处理器执行，所述程序包括用于执行权利要求1至12和/或权利要求13至24中任意一项所述的控制方法的指令。
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CN105652891A (zh) * 2016-03-02 2016-06-08 中山大学 一种旋翼无人机移动目标自主跟踪装置及其控制方法

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