WO2020037602A1 - 一种无人机的返航控制方法、设备、及无人机 - Google Patents

一种无人机的返航控制方法、设备、及无人机 Download PDF

Info

Publication number
WO2020037602A1
WO2020037602A1 PCT/CN2018/101958 CN2018101958W WO2020037602A1 WO 2020037602 A1 WO2020037602 A1 WO 2020037602A1 CN 2018101958 W CN2018101958 W CN 2018101958W WO 2020037602 A1 WO2020037602 A1 WO 2020037602A1
Authority
WO
WIPO (PCT)
Prior art keywords
drone
return
preset
state information
determined
Prior art date
Application number
PCT/CN2018/101958
Other languages
English (en)
French (fr)
Inventor
耿畅
刘新俊
彭昭亮
赖镇洲
Original Assignee
深圳市大疆创新科技有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 深圳市大疆创新科技有限公司 filed Critical 深圳市大疆创新科技有限公司
Priority to CN201880037310.7A priority Critical patent/CN110730933A/zh
Priority to PCT/CN2018/101958 priority patent/WO2020037602A1/zh
Publication of WO2020037602A1 publication Critical patent/WO2020037602A1/zh
Priority to US17/180,534 priority patent/US20210181766A1/en

Links

Images

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • 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
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64C—AEROPLANES; HELICOPTERS
    • B64C39/00—Aircraft not otherwise provided for
    • B64C39/02—Aircraft not otherwise provided for characterised by special use
    • B64C39/024—Aircraft not otherwise provided for characterised by special use of the remote controlled vehicle type, i.e. RPV
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U70/00—Launching, take-off or landing arrangements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20—Instruments for performing navigational calculations
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0017—Arrangements for implementing traffic-related aircraft activities, e.g. arrangements for generating, displaying, acquiring or managing traffic information
    • G08G5/0021—Arrangements for implementing traffic-related aircraft activities, e.g. arrangements for generating, displaying, acquiring or managing traffic information located in the aircraft
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0047—Navigation or guidance aids for a single aircraft
    • G08G5/0069—Navigation or guidance aids for a single aircraft specially adapted for an unmanned aircraft
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/02—Automatic approach or landing aids, i.e. systems in which flight data of incoming planes are processed to provide landing data
    • G08G5/025—Navigation or guidance aids
    • 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
    • B64U10/00—Type of UAV
    • B64U10/10—Rotorcrafts
    • B64U10/13—Flying platforms
    • B64U10/16—Flying platforms with five or more distinct rotor axes, e.g. octocopters
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U2201/00—UAVs characterised by their flight controls
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0004—Transmission of traffic-related information to or from an aircraft
    • G08G5/0013—Transmission of traffic-related information to or from an aircraft with a ground station

Definitions

  • the present invention relates to the field of control technology, and in particular, to a method, a device, and a drone for return control of a drone.
  • the embodiments of the present invention provide a drone return control method, device and drone, which can improve the accuracy and flight safety of the drone return.
  • an embodiment of the present invention provides a drone return control method, including:
  • the drone When it is determined that the remaining power of the drone is less than or equal to a preset return power threshold, the drone is controlled to fly to a preset cruising altitude, and the drone is controlled at the preset cruising altitude according to a first preset horizontal speed control amount.
  • the first preset horizontal speed control amount and the preset falling speed control amount are determined. Control the drone to return home.
  • an embodiment of the present invention provides a method for estimating a return power of a drone, including:
  • an embodiment of the present invention provides a method for establishing a unit time power consumption model of a drone, including:
  • an embodiment of the present invention provides a drone return control device, including a memory and a processor;
  • the memory is used to store program instructions
  • the processor is configured to call the program instructions, and when the program instructions are executed, perform the following operations:
  • the drone When it is determined that the remaining power of the drone is less than or equal to the preset return power threshold, the drone is controlled to fly to a preset cruise altitude, and the drone is controlled at the preset cruise altitude according to a first preset horizontal speed control amount.
  • the first preset horizontal speed control amount and the preset falling speed control amount are determined. Control the drone to return home.
  • an embodiment of the present invention provides a drone return energy estimation device, including a memory and a processor;
  • the memory is used to store program instructions
  • the processor is configured to call the program instructions, and when the program instructions are executed, perform the following operations:
  • an embodiment of the present invention provides a device for establishing a unit time power consumption model of a drone, including a memory and a processor;
  • the memory is used to store program instructions
  • the processor is configured to call the program instructions, and when the program instructions are executed, perform the following operations:
  • an embodiment of the present invention provides a drone, including:
  • the power system configured on the fuselage is used to provide mobile power for the drone;
  • a processor to perform the following steps:
  • the drone When it is determined that the remaining power of the drone is less than or equal to a preset return power threshold, the drone is controlled to fly to a preset cruising altitude, and the drone is controlled at the preset cruising altitude according to a first preset horizontal speed control amount.
  • the first preset horizontal speed control amount and the preset falling speed control amount are determined. Control the drone to return home.
  • an embodiment of the present invention provides another drone, including:
  • the power system configured on the fuselage is used to provide mobile power for the drone;
  • a processor to perform the following steps:
  • an embodiment of the present invention provides another drone, including:
  • the power system configured on the fuselage is used to provide mobile power for the drone;
  • a processor to perform the following steps:
  • an embodiment of the present invention provides a computer-readable storage medium.
  • the computer-readable storage medium stores a computer program.
  • the computer program When the computer program is executed by a processor, the computer program implements the first aspect, the second aspect, or the third aspect. Aspect of the method.
  • the drone return control device determines that the remaining power of the drone is less than or equal to a preset return power threshold
  • the drone is controlled to fly to a preset cruising altitude, and according to the first preset
  • the horizontal speed control amount controls the drone to return horizontally at the preset cruise altitude.
  • the preset reduced power threshold controls the drone to return to home according to the first preset horizontal speed control amount and the preset descent speed control amount. In this way, the accuracy and flight safety of the drone return flight are improved.
  • FIG. 1 is a schematic structural diagram of a drone return control system according to an embodiment of the present invention.
  • 2a is a schematic diagram of a conventional drone return mode provided by the prior art
  • FIG. 2b is a schematic diagram of a drone return mode in which the estimated return power is relatively small provided by the prior art
  • FIG. 2c is a schematic diagram of a drone returning home mode provided by an embodiment of the present invention.
  • FIG. 3 is a schematic flowchart of a drone return control method according to an embodiment of the present invention.
  • FIG. 4a is a schematic diagram of another drone forced return home mode provided by an embodiment of the present invention.
  • FIG. 4b is a schematic diagram of another drone forced return home mode provided by an embodiment of the present invention.
  • FIG. 4c is a schematic diagram of another drone forced return home mode provided by an embodiment of the present invention.
  • FIG. 4d is a schematic diagram of another drone forced return home mode provided by an embodiment of the present invention.
  • FIG. 5 is a method for estimating a return power of a drone according to an embodiment of the present invention.
  • FIG. 6 is a method for establishing a unit time power consumption model of a UAV provided by an embodiment of the present invention
  • FIG. 7a is an effect diagram of power consumption per unit time estimated at a preset cruise altitude according to an embodiment of the present invention.
  • FIG. 7b is an effect diagram of power consumption per unit time estimated during a forced landing return in accordance with an embodiment of the present invention.
  • FIG. 8 is a schematic structural diagram of a drone return control device according to an embodiment of the present invention.
  • FIG. 9 is a schematic structural diagram of a drone return energy estimation device provided by an embodiment of the present invention.
  • FIG. 10 is a schematic structural diagram of a device for establishing a unit time power consumption model of a drone according to an embodiment of the present invention.
  • the drone return control method provided in the embodiment of the present invention may be executed by a drone return control system, and the drone return control device and the drone may perform two-way communication.
  • the drone return control system includes a drone return control device and a drone.
  • the drone return control device may be installed on the drone, and in some cases In an embodiment, the drone return control device may be spatially independent of the drone.
  • the drone return control device may be a part of the drone, that is, the drone Drones include drone return control equipment.
  • the drone return control method can also be applied to other mobile devices, such as mobile devices such as robots, unmanned vehicles, and unmanned ships that can move autonomously.
  • the drone return control device in the drone return control system can obtain the remaining power of the drone in real time during the movement of the drone.
  • the drone return control device may control the drone to fly to a preset cruising altitude, and control the drone to return horizontally at the return altitude according to a first preset horizontal speed control amount.
  • the drone may Preset horizontal speed control amount and preset descent speed control amount control drone to return home.
  • FIG. 1 is a schematic structural diagram of a drone return control system according to an embodiment of the present invention.
  • the drone return control system includes a drone return control device 11 and a drone 12.
  • a communication connection may be established between the drone 12 and the drone return control device 11 through a wireless communication connection method.
  • a communication connection may also be established between the drone 12 and the drone return control device 11 by a wired communication connection.
  • the return flight control device 11 may be a flight controller.
  • the UAV 12 may be a rotor-type aircraft, for example, a quad-rotor, a six-rotor, an eight-rotor, or an aircraft such as a fixed-wing aircraft.
  • the drone 12 includes a power system 121, and the power system 121 is configured to provide power for the drone 12 to fly.
  • the drone return control device 11 can obtain the remaining power of the drone 12 in real time, and when it is determined that the remaining power of the drone 12 is less than or equal to a preset return power threshold, The UAV 12 is controlled to fly to a preset cruising altitude, so as to control the UAV 12 to return horizontally at the preset cruising altitude according to a first preset horizontal speed control amount.
  • the drone return control device 11 determines that the remaining power of the drone 12 is less than or equal to a preset falling power threshold, the drone is unmanned.
  • the home return control device 11 of the aircraft may control the drone 12 to return to the home according to the first preset horizontal speed control amount and the preset descent speed control amount.
  • the drone 12 can obtain the current position of the drone 12 in real time during flight, and calculate the return power required for the drone 12 to return from the current position to the return point, that is, the return power, and according to The return home power determines the preset return home power threshold.
  • the return home power can be calculated by the return home power estimation method provided in the later part of this article, and the drone home return control device 11 can execute the return home power estimation method in the later part of this article.
  • the drone 12 may obtain the current altitude of the drone 12 in real time, and calculate the amount of descending power required for the drone 12 to descend from the current altitude to the ground, that is, the amount of descending power, and determine the position according to the descending amount of electricity.
  • the preset power-down threshold is described. In some embodiments, the preset return power threshold and the preset reduced power threshold both retain a safety margin.
  • the drone 12 when it is determined that the remaining power of the drone 12 is less than or equal to the preset return power threshold, the drone 12 is triggered to return home, and the drone 12 is controlled to fly to a preset cruise altitude, and according to the first preset It is assumed that the horizontal speed control amount controls the drone 12 to return horizontally at the preset cruising altitude.
  • the drone return control device 11 may control the drone 12 to return to the home according to the first preset horizontal speed control amount and the preset descending speed control amount.
  • the drone when the drone is forced to return to the home, the drone may increase the downward speed component based on the first preset horizontal speed control amount, that is, the preset descending speed control amount, so that the drone 12 sides Return to level while descending to save time. After the drone 12 descends to a preset safe height, it may no longer descend, and the drone 12 returns horizontally at the preset safe height to prevent the drone from hitting the ground and improve the safety of the drone.
  • the drone 12 returns horizontally at a preset safe altitude, if the remaining power of the drone 12 is less than or equal to a preset landing power threshold, the drone can be controlled to fall, thereby further improving the safety of the drone.
  • the drone 12 may obtain the current altitude of the drone 12 in real time, and calculate the landing power required for the drone 12 to land from the current altitude, that is, the landing power, and according to the landing The power determines the preset falling power threshold. Wherein, the preset landing power threshold value retains a small safety margin.
  • the embodiment of the present invention may be based on the conventional home return mode in the prior art shown in FIG. 2a and FIG. 2b, and combine the home return mode shown in FIG. 2c provided by the embodiment of the present invention to the home return mode provided by the embodiment of the present invention. For comparison.
  • FIG. 2a is a schematic diagram of a conventional drone return mode provided by the prior art. As shown in FIG. 2a, it includes a start point 201, a cruise altitude point 202, a horizontal return route 203, a descending point 204, and a return point 205.
  • the usual way of returning by drone is generally straight-line return, and then descending above the return point. That is, as shown in FIG.
  • FIG. 2b is a schematic diagram of a drone returning method with a small estimated return power provided by the prior art, as shown in FIG. 2b, including a returning start point 211, a cruise altitude point 212, a horizontal return route 213, a descending point 214, and a return point. 215.
  • the drone ascends at the starting point 211 of the return flight to the cruise altitude point 212, and returns horizontally along the horizontal return path 213.
  • the drone returns horizontally to the descending point 214 and the remaining power is less than the preset descending power threshold, the drone starts to descend at the descending point 214 and descends to the landing point 215, wherein the landing point 215 is at the returning point 216 Ahead.
  • This return-to-home method uses the current return-to-home power estimation method to estimate the return-to-home power, which makes the estimated return-to-home power to be small, resulting in a preset return-to-home power threshold set to a smaller power threshold, so that when the drone enters the return-to-home mode, The remaining power is not enough to allow the drone to land early before flying above the home point, which can easily lead to the loss of the drone.
  • FIG. 2c is a schematic diagram of a drone returning approach provided by an embodiment of the present invention. As shown in FIG. 2c, it includes a starting point 221, a cruise altitude point 222, a horizontal return route 223, a descending point 224, a safe altitude point 225, Landing point 226, home point 226.
  • the embodiment of the present invention provides the return control method of the drone shown in FIG. 2c according to the above-mentioned situation. This method can control the drone to increase the downward return on the basis of the horizontal return when the drone returns to the home.
  • the speed component is the preset descent speed control amount to make the drone descend while returning to the sea, thereby saving the descending time, improving the flight safety of the drone, and the user experience.
  • the drone flies from the return home point 221 to the cruise altitude point 222, and controls the drone to return home on the horizontal return route 223. If the drone has a remaining power less than or equal to the By setting the power down threshold, you can control the drone to return home in the horizontal direction and downwards perpendicular to the horizontal direction. When the drone descends to a safe altitude point of 225, control the drone to return home horizontally. When the water bottle returns home, Landing point 226 landed at home point 227.
  • FIG. 3 is a schematic flowchart of a drone return control method according to an embodiment of the present invention.
  • the method may be executed by a drone return control device, wherein the drone return control
  • the specific explanation of the equipment is as described above.
  • the method according to the embodiment of the present invention includes the following steps.
  • S301 When it is determined that the remaining power of the drone is less than or equal to a preset return power threshold, control the drone to fly to a preset cruising altitude, and control the drone at the preset according to a first preset horizontal speed control amount. Return to level at cruising altitude.
  • the drone return control device can obtain the remaining power of the drone in real time. When it is determined that the remaining power of the drone is less than or equal to a preset return power threshold, the drone returns The control device may control the drone to fly to a preset cruising altitude, and control the drone to return horizontally at the preset cruising altitude according to a first preset horizontal speed control amount.
  • the drone's return control device determines that the remaining power of the drone is less than or equal to a preset reduced power threshold, it may be based on the The first preset horizontal speed control amount and the preset descent speed control amount control the drone to return home.
  • FIG. 4a can be used as an example for illustration.
  • FIG. 4a is a schematic diagram of another drone forced return home mode provided by an embodiment of the present invention.
  • the cruise altitude point 401 corresponds to a preset cruise altitude
  • the safe altitude point 403 corresponds to the preset safe altitude.
  • the drone return control device determines that the remaining power of the drone 40 is less than or equal to the preset descending power threshold, the drone may be controlled according to the first preset horizontal speed control amount V1 and the preset descending speed control amount Vx. Man-machine forced landing and returned.
  • the drone may be controlled according to the second preset horizontal speed control amount.
  • the drone returns horizontally at the preset safe altitude.
  • the first preset speed control amount may be the same as the second preset horizontal speed control amount. In other embodiments, the first preset speed control amount may be the same as the second preset speed control amount.
  • the horizontal speed control amounts are different, and are not specifically limited in the embodiment of the present invention.
  • FIG. 4b can be used as an example for illustration.
  • FIG. 4b is a schematic diagram of another drone forced return home mode provided by an embodiment of the present invention, as shown in FIG. 4b, including: drone 41, cruise altitude point 411, and descent point. 412. A safe altitude point 413, a landing point 414, and a home point 415, wherein the cruise altitude point 411 corresponds to a preset cruise altitude, and the safe altitude point 413 corresponds to the preset safe altitude.
  • the second preset horizontal speed control amount is V2.
  • the drone 41 makes a forced landing return from the descent point 412, if the drone return control device determines that the altitude of the drone 41 drops to a safe altitude point 413, then The drone 41 may be controlled to return horizontally at the preset safe altitude from the safe altitude point 413 according to the second preset horizontal speed control amount V2.
  • the drone return control device determines that the remaining power of the drone is less than or equal to the preset landing power threshold, the drone can be controlled.
  • the drone landed.
  • the position where the remaining power of the UAV is less than or equal to a preset landing power threshold may be any position on a horizontal course on the preset safe altitude.
  • FIG. 4b when the drone 41 returns home at a second preset horizontal speed control amount V2 from the safe altitude point 413 along the preset safe altitude, if the drone return control device is determined at the landing point 414 If the remaining power of the drone 41 is less than or equal to the preset landing power threshold, the drone can be controlled to start landing from the landing point 414.
  • the drone return control device determines that the drone reaches above the home point, the drone can be controlled to land at the home point .
  • the drone 41 when the drone 41 returns home at a second preset horizontal speed control amount V2 from the safe height point 413 along the preset safe altitude, if the drone return control device determines the drone When 41 reaches the landing point 416 above the home point 415, the drone 41 can be controlled to land from the landing point 416 to the home point 415.
  • the drone when the drone returns home during the forced landing, if the drone return control device determines that the drone reaches above the home point, the drone can be controlled to land to the home point. In some embodiments, when the drone returns to the home, if the drone return control device determines that the drone reaches the home point when the drone descends to a preset safe height, the drone may be controlled. Land to the home point.
  • FIG. 4c can be used as an example for illustration.
  • FIG. 4c is a schematic diagram of another drone forced return home mode provided by an embodiment of the present invention.
  • a landing point 423, and a home point 424 wherein the cruise height point 421 corresponds to a preset cruise height, and the landing point 423 is located at a preset safe height above the home point.
  • the drone return control device determines that the drone descends to the landing point 423 at a preset safe height, the drone 42 can be controlled to descend to the returning point 424 .
  • the drone return control device determines that the remaining power of the drone is less than or equal to a preset landing power threshold, the drone can be controlled to land.
  • FIG. 4d may be taken as an example.
  • FIG. 4d is a schematic diagram of another drone forced return home mode provided by an embodiment of the present invention. As shown in FIG. Landing point 433, home point 434. When the drone 43 returns from the descent point 432 and returns to the home, if the drone return control device determines that the remaining power of the drone is less than or equal to a preset landing power threshold, the drone 43 can be controlled from the landing point 433 Began to land.
  • the drone return control device determines that the remaining power of the drone is less than or equal to a preset return power threshold
  • the drone is controlled to fly to a preset cruising altitude, and according to the first preset
  • the horizontal speed control amount controls the drone to return horizontally at the preset cruise altitude.
  • the preset reduced power threshold when it is determined that the remaining power of the drone is less than or equal to the preset reduced power threshold And controlling the drone to return to home according to the first preset horizontal speed control amount and the preset descent speed control amount. In this way, the probability of the drone being lost is reduced, the descent time is saved, and the accuracy and flight safety of the drone returning are improved.
  • FIG. 5 is a method for estimating a return power of an unmanned aerial vehicle according to an embodiment of the present invention.
  • the method for estimating a return power of an unmanned aerial vehicle may be performed by a device for estimating a return power of the unmanned aerial vehicle.
  • a two-way communication can be performed between the return power estimation device of the human machine and the drone.
  • the return power estimation device of the drone can be installed on the drone.
  • the return power of the drone The estimation device may be spatially independent of the drone.
  • the drone return energy estimation device may be a part of the drone, that is, the drone includes the drone return energy.
  • Estimation equipment which may be a flight controller of a drone.
  • the method for estimating the return power of the drone may also be applied to other mobile devices, such as mobile devices that can move autonomously, such as robots, unmanned vehicles, and unmanned ships.
  • This embodiment of the present invention does not Be specific.
  • the method according to the embodiment of the present invention includes the following steps.
  • S501 Determine the motion status information of the drone during the return flight.
  • the drone's return power estimation device needs to estimate the drone's return power in real time during the flight of the drone, and the return power is required for the drone to return from the current position to the return point. Power.
  • the drone's return power estimation device can determine the movement status information of the drone during the return flight. Specifically, during the flight of the drone, the drone return power estimation device can determine in real time from the current position to Home point information of the drone's movement status during home.
  • the motion status information may include at least one of horizontal flying speed, vertical flying speed, and altitude information of the drone, wherein the altitude information of the drone may include The altitude at which the drone is located or the altitude of the drone.
  • the returning process is a process in which the drone returns from the current position to the return point.
  • the return home process is a process in which the drone 40 returns home from the return home point 221 to the return home point 227.
  • S502 Estimate the returning power amount according to the determined exercise state information.
  • the return power estimation device for the drone may estimate the return power according to the determined motion state information.
  • the current return home power estimation often uses the power consumption per unit time obtained from experience to multiply the time required for home return to make a rough estimate. Because the current return home power estimate does not take into account the movement status information of the drone during the return home, Failure to correctly reflect the impact on power consumption, unable to cover various flight scenarios, causing large deviations between estimated results and actual conditions in some scenarios, poor accuracy, especially when the flight distance is far from the actual return flight battery More obvious.
  • the return flight power is estimated based on the motion state information determined by the drone during the return flight, which can truly reflect the impact of the drone's motion status information on the power consumption during the return flight, and can accurately estimate the return flight. Battery.
  • the drone's returning power estimation device when the drone's returning power estimation device estimates the returning power according to the determined motion state information, it can determine the power consumption per unit time of the drone during the returning process according to the determined motion state information.
  • the return home power is estimated based on the power consumption per unit time.
  • the motion status information of the drone may be different, and the drone may determine the power consumption per unit time of the drone according to the motion status information. It can be understood that, since the motion status information of the drone may be different at different moments, the unit power consumption of the drone at different moments may be different.
  • the return flight power can be determined according to the power consumption per unit time. For example, the power consumption of each unit time can be accumulated during the return flight. According to the accumulation operation, the power consumption during the entire return flight can be estimated, that is, the return flight power.
  • the drone return power estimation device may substitute the determined motion state information into a unit time power consumption model of the drone to determine the unit time power consumption.
  • the unit power consumption model of the drone is as follows:
  • ⁇ bat resume R1 + R2V vert + R3h + R4V horz
  • V vert , h, and V horz represent vertical flight speed, altitude, and horizontal flight speed, respectively.
  • R1, R2, R3, and R4 are model coefficients, wherein the model coefficients are parameters other than the independent variables in the unit time power consumption model of the UAV, and ⁇ bat resume is the power consumption per unit time.
  • the drone's return energy estimation device can execute the method for establishing the unit time power consumption model of the drone later in this article. .
  • the return power estimation device of the drone may determine the motion state information of the drone during the return flight, and estimate the return flight power based on the determined motion state information. By estimating the return flight power in this way, Reduced power estimation errors and improved drone flight safety and user experience.
  • FIG. 6 is a method for establishing a unit time power consumption model of a drone according to an embodiment of the present invention.
  • the method for establishing a unit time power consumption model of a drone may be implemented by The device execution of the unit time power consumption model is performed.
  • the device for establishing the unit time power consumption model of the drone and the drone can perform two-way communication.
  • the device for establishing the unit time power consumption model of the drone can be installed.
  • the device for establishing a unit time power consumption model of the drone may be spatially independent of the drone.
  • the device for establishing a drone may be a part of the drone, that is, the drone includes a device for establishing the unit time power consumption model of the drone, and the device for establishing the unit time power consumption model of the drone may Flight controller for drone.
  • the method for establishing a unit time power consumption model of a drone may also be applied to other mobile devices, such as mobile devices capable of autonomous movement such as robots, unmanned vehicles, and unmanned ships. The embodiments of the invention are not specifically limited.
  • the device for establishing a unit time power consumption model of the drone may be a terminal device, wherein the terminal device includes at least one of a smartphone, a tablet computer, a laptop computer, and a desktop computer. Species. Specifically, the method according to the embodiment of the present invention includes the following steps.
  • S601 Acquire the motion state information of the drone during flight and the actual power consumption per unit time corresponding to the motion state information.
  • the device that establishes a unit time power consumption model of the drone can obtain the movement state information of the drone during flight, and obtain the actual unit time electricity consumption corresponding to the movement state information, that is, A sample of exercise state information and a sample of power consumption per unit time.
  • the motion state information includes motion state information of the drone in a plurality of different flight states.
  • the plurality of different flight states include at least two of hovering, uniform flight, accelerated flight, and decelerated flight.
  • the motion state information includes motion state information of the drone in a plurality of different flight environments.
  • the plurality of different flight environments may include any one of a plurality of different locations, a plurality of different flight altitudes, a plurality of different temperature environments, a plurality of different wind speed environments, or the like Multiple environments.
  • the exercise state information may include a degree of dispersion, and the degree of dispersion of the exercise state information is greater than or equal to a preset dispersion degree threshold.
  • the motion state information includes at least one of horizontal flying speed, vertical flying speed, and altitude information of the drone.
  • the exercise state information sample and the unit time power consumption sample are obtained based on a large amount of sample data, and the drone's return power estimation device may be effective on the sample data before collecting the sample data. Judgment.
  • the drone's return power estimation device may detect whether the flight status of the drone from which the sample data is obtained is normal, and if it is detected that the flight status of the drone is not significantly faulty, the drone may be determined. The drone is flying normally.
  • the drone's return power estimation device can detect whether the drone's flight status remains stable during hovering, horizontal uniform flight, or vertical uniform flight, and if the detection result is yes, it can determine the The drone is flying normally. In one embodiment, after the drone's return power estimation device detects that the drone's flight status is normal, it starts collecting sample data.
  • S602 Substituting the motion state information into the unit time power consumption model to obtain an expected unit time power consumption of the drone.
  • the unit time power consumption model includes one or more model coefficients to be determined. After the one or more model coefficients to be determined are determined, the unit time power consumption model has been successfully established.
  • the independent variable of the unit time power consumption model is the independent variable of the motion state information.
  • a device that establishes a unit time power consumption model of a drone may substitute the motion state information into the unit time power consumption model to obtain an expected unit time power consumption of the drone.
  • the device for establishing a unit time power consumption model of the drone may be based on the current altitude and the set safe return point. Position, comprehensively preset return altitude information such as cruise altitude, cruise speed, and descent speed, and calculate the return time to obtain the power required for the drone to return.
  • S603 Run a minimization fitting algorithm based on the actual unit time power consumption and the expected unit time power consumption to determine the one or more model coefficients to be determined, and update using the determined model coefficients The power consumption model per unit time.
  • a device that establishes a unit time power consumption model of a drone may obtain multiple movement status information, such as the movement status information of the drone at multiple different times during the flight.
  • a plurality of motion state information is substituted into a unit time power consumption model including a model coefficient to be determined to obtain a plurality of expected unit time power consumptions.
  • a device that establishes a unit time power consumption model of a drone may obtain the multiple A plurality of actual unit time power consumptions corresponding to the motion state information, and a minimization fitting algorithm is run based on the plurality of actual unit time power consumptions and a plurality of the expected unit time power consumptions to determine the one or more A model coefficient to be determined, and using the determined model coefficient to update the power consumption model per unit time.
  • the actual power consumption per unit time may be obtained according to a preset unit time.
  • the embodiment of the present invention does not specifically limit the type of the minimization fitting algorithm, and those skilled in the art It can be selected according to requirements, such as linear fitting algorithm, least square fitting algorithm, and so on.
  • the unit power consumption model may be updated by using the determined model coefficients, and the unit power consumption model of the UAV is successfully established.
  • the device for establishing a unit time power consumption model of the drone may obtain vertical flight speed, altitude, and horizontal flight speed, and obtain actual units corresponding to the vertical flight speed, altitude h, and horizontal flight speed.
  • the method runs a minimization fitting algorithm based on the expected unit time power consumption ⁇ bat resume and the actual unit time power consumption to determine the one or more model coefficients to be determined R1, R2, R3, R4, And using the determined model coefficients R1, R2, R3, and R4 to update the power consumption model per unit time.
  • the drone's return power estimation device estimates the return power according to the determined motion state information
  • it can substitute the determined motion state information at the preset cruise altitude into the above-mentioned drone.
  • the unit time power consumption model the unit time power consumption of the UAV at the preset cruise altitude is estimated, as shown in FIG. 7a, which is an estimate of the preset cruise altitude provided by an embodiment of the present invention.
  • the effect diagram of the power consumption per unit time, as shown in FIG. 7 a includes the original model power consumption 71 and the actual power consumption 72.
  • the determined droop return motion state information may be substituted into the above-mentioned unit time consumption of the drone.
  • the power consumption per unit time of the drone at the preset cruise altitude is estimated, as shown in FIG. 7b.
  • FIG. 7b is an estimated power consumption per unit time during the forced landing return process provided by an embodiment of the present invention.
  • the effect diagram of the quantity, as shown in FIG. 7b, includes the original model power consumption 73 and the actual power consumption 74. It can be seen from FIG. 7a and FIG. 7b that the unit power consumption model of the drone provided by the embodiment of the present invention is more accurate than the prior art model, so that the unit of the drone provided by the embodiment of the present invention is explained.
  • the time return power model estimates the accuracy of the return home power.
  • the device for establishing a unit time power consumption model of the drone may obtain the motion state information of the drone during flight and the actual unit time power consumption corresponding to the motion state information, and The motion state information is substituted into the unit time power consumption model to obtain an expected unit time power consumption of the drone, and a minimization fitting is performed based on the actual unit time power consumption and the expected unit time power consumption.
  • An algorithm determines the one or more model coefficients to be determined, and updates the power consumption model per unit time by using the determined model coefficients. In this way, the error in estimating the return home power is reduced, the accuracy of the model is improved, and the flight safety and user experience of the drone are improved.
  • FIG. 8 is a schematic structural diagram of a drone return control device according to an embodiment of the present invention.
  • the drone return control device includes: a memory 801, a processor 802, and a data interface 803.
  • the data interface 803 is used to transmit data information between the drone return control device and the drone.
  • the memory 801 may include a volatile memory; the memory 801 may also include a non-volatile memory; the memory 801 may further include a combination of the foregoing types of memories.
  • the processor 802 may be a central processing unit (CPU).
  • the processor 802 may further include a hardware chip.
  • the hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof.
  • the PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), or any combination thereof.
  • the memory 801 is configured to store program instructions, and the processor 802 may call the program instructions stored in the memory 801 to perform the following steps:
  • the drone When it is determined that the remaining power of the drone is less than or equal to a preset return power threshold, the drone is controlled to fly to a preset cruising altitude, and the drone is controlled at the preset cruising altitude according to a first preset horizontal speed control amount.
  • the first preset horizontal speed control amount and the preset falling speed control amount are determined. Control the drone to return home.
  • the target waypoint that satisfies a preset position relationship with the position of the drone is the target waypoint closest to the position of the drone.
  • processor 802 may call program instructions stored in the memory 801, and is further configured to perform the following steps:
  • the drone is controlled to return horizontally at the preset safe altitude according to a second preset horizontal speed control amount.
  • processor 802 may call program instructions stored in the memory 801, and is further configured to perform the following steps:
  • the drone In the process of returning horizontally at the preset safe altitude, when it is determined that the remaining power of the drone is less than or equal to a preset landing power threshold, the drone is controlled to land.
  • processor 802 may call a program instruction stored in the memory 801, and is further configured to execute the following steps:
  • the drone In the process of returning horizontally at the preset safe altitude, when it is determined that the drone reaches above the return point, the drone is controlled to land at the return point.
  • processor 802 may call program instructions stored in the memory 801, and is further configured to perform the following steps:
  • the drone is controlled to land to the return point.
  • processor 802 may call program instructions stored in the memory 801, and is further configured to perform the following steps:
  • the drone is controlled to land.
  • the drone return control device determines that the remaining power of the drone is less than or equal to a preset return power threshold
  • the drone is controlled to fly to a preset cruising altitude, and according to the first preset
  • the horizontal speed control amount controls the drone to return horizontally at the preset cruise altitude.
  • the preset reduced power threshold when it is determined that the remaining power of the drone is less than or equal to the preset reduced power threshold And controlling the drone to return to home according to the first preset horizontal speed control amount and the preset descent speed control amount. In this way, the probability of losing the drone is reduced, the descent time is saved, and the flight safety of the drone is improved.
  • FIG. 9 is a schematic structural diagram of an unmanned aerial vehicle return energy estimation device according to an embodiment of the present invention.
  • the drone return power estimation device includes: a memory 901, a processor 902, and a data interface 903.
  • the data interface 903 is used for transmitting data information between the drone return control device and the drone.
  • the memory 901 may include a volatile memory; the memory 901 may also include a non-volatile memory; the memory 801 may further include a combination of the foregoing types of memories.
  • the processor 902 may be a central processing unit (CPU).
  • the processor 902 may further include a hardware chip.
  • the hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof.
  • the PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), or any combination thereof.
  • the memory 901 is configured to store program instructions, and the processor 902 may call the program instructions stored in the memory 901 to perform the following steps:
  • the processor 902 may call the program instructions stored in the memory 901 to estimate the returning power amount based on the determined exercise state information, and is specifically configured to perform the following steps:
  • the return home power is estimated based on the power consumption per unit time.
  • the processor 902 may call a program instruction stored in the memory 901 to determine the power consumption per unit time according to the determined motion state information, and is specifically configured to perform the following steps:
  • the determined motion state information is substituted into a unit time power consumption model of the drone to determine the unit time power consumption.
  • the motion state information includes at least one of horizontal flying speed, vertical flying speed, and altitude information of the drone.
  • the return power estimation device of the drone may determine the motion state information of the drone during the return flight, and estimate the return flight power based on the determined motion state information. By estimating the return flight power in this way, Reduce estimation errors and improve drone flight safety and user experience.
  • FIG. 10 is a schematic structural diagram of a device for establishing a unit time power consumption model of a drone according to an embodiment of the present invention.
  • the device for establishing a unit time power consumption model of the UAV includes a memory 1001, a processor 1002, and a data interface 1003.
  • the data interface 1003 is used for transmitting data information between the drone return control device and the drone.
  • the memory 1001 may include a volatile memory; the memory 1001 may also include a non-volatile memory; the memory 1001 may further include a combination of the foregoing types of memories.
  • the processor 1002 may be a central processing unit (CPU).
  • the processor 1002 may further include a hardware chip.
  • the hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof.
  • the PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), or any combination thereof.
  • the memory 1001 is configured to store program instructions, and the processor 1002 may call the program instructions stored in the memory 1001 to perform the following steps:
  • the motion state information includes motion state information of the drone in a plurality of different flight states.
  • the motion state information includes motion state information of the drone in a plurality of different flight environments.
  • the dispersion degree of the motion state information is greater than or equal to a preset dispersion degree threshold.
  • the motion state information includes at least one of horizontal flying speed, vertical flying speed, and altitude information of the drone.
  • the device for establishing a unit time power consumption model of the drone may obtain the motion state information of the drone during flight and the actual unit time power consumption corresponding to the motion state information, and The motion state information is substituted into the unit time power consumption model to obtain an expected unit time power consumption of the drone, and a minimization fitting is performed based on the actual unit time power consumption and the expected unit time power consumption.
  • An algorithm determines the one or more model coefficients to be determined, and updates the power consumption model per unit time by using the determined model coefficients. In this way, the error in estimating the return home power is reduced, the accuracy of the model is improved, and the flight safety and user experience of the drone are improved.
  • An embodiment of the present invention further provides a drone, including: a fuselage; a power system configured on the fuselage for providing moving power for the drone; and a processor for performing the following steps:
  • the drone When it is determined that the remaining power of the drone is less than or equal to a preset return power threshold, the drone is controlled to fly to a preset cruising altitude, and the drone is controlled at the preset cruising altitude according to a first preset horizontal speed control amount.
  • the first preset horizontal speed control amount and the preset falling speed control amount are determined. Control the drone to return home.
  • processor is further configured to:
  • the drone is controlled to return horizontally at the preset safe altitude according to a second preset horizontal speed control amount.
  • processor is further configured to:
  • the drone In the process of returning horizontally at the preset safe altitude, when it is determined that the remaining power of the drone is less than or equal to a preset landing power threshold, the drone is controlled to land.
  • processor is further configured to:
  • the drone In the process of returning horizontally at the preset safe altitude, when it is determined that the drone reaches above the return point, the drone is controlled to land at the return point.
  • processor is further configured to:
  • the drone is controlled to land to the return point.
  • processor is further configured to:
  • the drone is controlled to land.
  • the drone return control device determines that the remaining power of the drone is less than or equal to a preset return power threshold
  • the drone is controlled to fly to a preset cruising altitude, and according to the first preset
  • the horizontal speed control amount controls the drone to return horizontally at the preset cruise altitude.
  • the preset reduced power threshold when it is determined that the remaining power of the drone is less than or equal to the preset reduced power threshold And controlling the drone to return to home according to the first preset horizontal speed control amount and the preset descent speed control amount. In this way, the probability of losing the drone is reduced, the descent time is saved, and the flight safety of the drone is improved.
  • An embodiment of the present invention also provides another drone, including: a fuselage; a power system configured on the fuselage to provide moving power for the drone; and a processor to perform the following steps:
  • the processor estimates the return home power according to the determined motion state information
  • the processor is specifically configured to:
  • the return home power is estimated based on the power consumption per unit time.
  • the processor determines the power consumption per unit time according to the determined exercise state information
  • the processor is specifically configured to:
  • the determined motion state information is substituted into a unit time power consumption model of the drone to determine the unit time power consumption.
  • the motion state information includes at least one of horizontal flying speed, vertical flying speed, and altitude information of the drone.
  • the return power estimation device of the drone may determine the motion state information of the drone during the return flight, and estimate the return flight power based on the determined motion state information. Reduce estimation errors and improve drone flight safety and user experience.
  • An embodiment of the present invention further provides another unmanned aerial vehicle, including: a fuselage; a power system configured on the fuselage for providing moving power for the unmanned aerial vehicle; and a processor for performing the following steps:
  • the motion state information includes motion state information of the drone in a plurality of different flight states.
  • the motion state information includes motion state information of the drone in a plurality of different flight environments.
  • the dispersion degree of the motion state information is greater than or equal to a preset dispersion degree threshold.
  • the motion state information includes at least one of horizontal flying speed, vertical flying speed, and altitude information of the drone.
  • the device for establishing a unit time power consumption model of the drone may obtain the motion state information of the drone during flight and the actual unit time power consumption corresponding to the motion state information, and The motion state information is substituted into the unit time power consumption model to obtain an expected unit time power consumption of the drone, and a minimization fitting is performed based on the actual unit time power consumption and the expected unit time power consumption.
  • An algorithm determines the one or more model coefficients to be determined, and updates the power consumption model per unit time by using the determined model coefficients. In this way, the error in estimating the return home power is reduced, the accuracy of the model is improved, and the flight safety and user experience of the drone are improved.
  • An embodiment of the present invention also provides a computer-readable storage medium.
  • the computer-readable storage medium stores a computer program, and the computer program implements the present invention when executed by a processor.
  • FIG. 1, FIG. 3, FIG. 5, or FIG. The method described in the corresponding embodiment of 6 can also implement the device of the corresponding embodiment of the present invention described in FIG. 8, FIG. 9, or FIG. 10, and details are not described herein again.
  • the computer-readable storage medium may be an internal storage unit of the device according to any one of the foregoing embodiments, such as a hard disk or a memory of the device.
  • the computer-readable storage medium may also be an external storage device of the device, such as a plug-in hard disk, a Smart Media Card (SMC), and a Secure Digital (SD) card provided on the device. , Flash card (Flash card) and so on.
  • the computer-readable storage medium may also include both an internal storage unit of the device and an external storage device.
  • the computer-readable storage medium is used to store the computer program and other programs and data required by the terminal.
  • the computer-readable storage medium may also be used to temporarily store data that has been or will be output.

Abstract

一种无人机的返航控制方法、设备及无人机，其中，该方法包括：当确定无人机的剩余电量小于或者等于预设返航电量阈值时，控制无人机飞行到预设巡航高度，并根据第一预设水平速度控制量控制无人机在所述预设巡航高度上水平返航（S301）；在所述预设巡航高度上水平返航的过程中，当确定无人机的剩余电量小于或等于预设下降电量阈值时，根据所述第一预设水平速度控制量和预设下降速度控制量控制无人机迫降返航（S302）。通过这种方式，降低无人机丢失的概率，节省了下降时间，提高了无人机返航的准确率和飞行安全。

Description

一种无人机的返航控制方法、设备、及无人机 技术领域
本发明涉及控制技术领域，尤其涉及一种无人机的返航控制方法、设备、及无人机。
背景技术
目前，使用智能电池的无人机具有智能电量返航的功能，然而，由于技术条件的限制和/或环境因素的影响，使得无人机计算得到的电量容易出现较大误差，以至于不能成功返航。针对上述问题，目前常用的解决方案是加大返航电量，然而这种加大返航电量的方式难以控制电量的多少，电量太多严重影响用户体验，电量太少无人机不能成功返航，容易造成无人机丢失。因此，如何更有效地控制无人机返航具有十分重要的意义。
发明内容
本发明实施例提供了一种无人机的返航控制方法、设备及无人机，可以提高无人机返航的准确率和飞行安全。
第一方面，本发明实施例提供了一种无人机的返航控制方法，包括：
当确定无人机的剩余电量小于或者等于预设返航电量阈值时，控制无人机飞行到预设巡航高度，并根据第一预设水平速度控制量控制无人机在所述预设巡航高度上水平返航；
在所述预设巡航高度上水平返航的过程中，当确定无人机的剩余电量小于或等于预设下降电量阈值时，根据所述第一预设水平速度控制量和预设下降速度控制量控制无人机迫降返航。
第二方面，本发明实施例提供了一种无人机的返航电量估算方法，包括：
确定无人机在返航过程中的运动状态信息，其中，所述返航过程为无人机从当前位置返航至返航点的过程；
根据所述确定的运动状态信息估算返航电量。
第三方面，本发明实施例提供了一种建立无人机的单位时间耗电模型的方法，包括：
获取无人机在飞行过程中的运动状态信息和与所述运动状态信息对应的实际单位时间耗电量；
将所述运动状态信息代入到所述单位时间耗电模型中以获取无人机的预期单位时间耗电量，其中，所述单位时间耗电模型包括一个或多个待确定的模型系数；
基于所述实际单位时间耗电量和所述预期单位时间耗电量运行最小化拟合算法以确定所述一个或多个待确定的模型系数，并利用所述确定后的模型系数更新所述单位时间耗电模型。
第四方面，本发明实施例提供了一种无人机的返航控制设备，包括存储器和处理器；
所述存储器，用于存储程序指令；
所述处理器，用于调用所述程序指令，当所述程序指令被执行时，用于执行以下操作：
当确定无人机的剩余电量小于或者等于预设返航电量阈值时，控制无人机飞行到预设巡航高度，并根据第一预设水平速度控制量控制无人机在所述预设巡航高度上水平返航；
在所述预设巡航高度上水平返航的过程中，当确定无人机的剩余电量小于或等于预设下降电量阈值时，根据所述第一预设水平速度控制量和预设下降速度控制量控制无人机迫降返航。
第五方面，本发明实施例提供了一种无人机的返航电量估算设备，包括存储器和处理器；
所述存储器，用于存储程序指令；
所述处理器，用于调用所述程序指令，当所述程序指令被执行时，用于执行以下操作：
确定无人机在返航过程中的运动状态信息，其中，所述返航过程为无人机从当前位置返航至返航点的过程；
根据所述确定的运动状态信息估算返航电量。
第六方面，本发明实施例提供了一种建立无人机的单位时间耗电模型的设备，包括存储器和处理器；
所述存储器，用于存储程序指令；
所述处理器，用于调用所述程序指令，当所述程序指令被执行时，用于执行以下操作：
获取无人机在飞行过程中的运动状态信息和与所述运动状态信息对应的实际单位时间耗电量；
将所述运动状态信息代入到所述单位时间耗电模型中以获取无人机的预期单位时间耗电量，其中，所述单位时间耗电模型包括一个或多个待确定的模型系数；
基于所述实际单位时间耗电量和所述预期单位时间耗电量运行最小化拟合算法以确定所述一个或多个待确定的模型系数，并利用所述确定后的模型系数更新所述单位时间耗电模型。
第七方面，本发明实施例提供了一种无人机，包括：
机身；
配置在机身上的动力系统，用于为无人机提供移动的动力；
处理器，用于执行以下步骤：
当确定无人机的剩余电量小于或者等于预设返航电量阈值时，控制无人机飞行到预设巡航高度，并根据第一预设水平速度控制量控制无人机在所述预设巡航高度上水平返航；
在所述预设巡航高度上水平返航的过程中，当确定无人机的剩余电量小于或等于预设下降电量阈值时，根据所述第一预设水平速度控制量和预设下降速度控制量控制无人机迫降返航。
第八方面，本发明实施例提供了另一种无人机，包括：
机身；
配置在机身上的动力系统，用于为无人机提供移动的动力；
处理器，用于执行以下步骤：
确定无人机在返航过程中的运动状态信息，其中，所述返航过程为无人机从当前位置返航至返航点的过程；
根据所述确定的运动状态信息估算返航电量。
第九方面，本发明实施例提供了又一种无人机，包括：
机身；
配置在机身上的动力系统，用于为无人机提供移动的动力；
处理器，用于执行以下步骤：
获取无人机在飞行过程中的运动状态信息和与所述运动状态信息对应的实际单位时间耗电量；
将所述运动状态信息代入到所述单位时间耗电模型中以获取无人机的预期单位时间耗电量，其中，所述单位时间耗电模型包括一个或多个待确定的模型系数；
基于所述实际单位时间耗电量和所述预期单位时间耗电量运行最小化拟合算法以确定所述一个或多个待确定的模型系数，并利用所述确定后的模型系数更新所述单位时间耗电模型。
第十方面，本发明实施例提供了一种计算机可读存储介质，该计算机可读存储介质存储有计算机程序，该计算机程序被处理器执行时实现如上述第一方面、第二方面或第三方面所述的方法。
本发明实施例中，无人机的返航控制设备可以在确定出无人机的剩余电量小于或者等于预设返航电量阈值时，控制无人机飞行到预设巡航高度，并根据第一预设水平速度控制量控制无人机在所述预设巡航高度上水平返航，在所述预设巡航高度上水平返航的过程中，当确定无人机的剩余电量小于或等于预设下降电量阈值时，根据所述第一预设水平速度控制量和预设下降速度控制量控制无人机迫降返航。通过这种方式，提高了无人机返航的准确率和飞行安全。
附图说明
为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是本发明实施例提供的一种无人机的返航控制系统的结构示意图；
图2a是现有技术提供的一种无人机常规返航方式的示意图；
图2b是现有技术提供的一种返航电量估算偏小时无人机返航方式的示意图；
图2c是本发明实施例提供的一种无人机迫降返航方式的示意图；
图3是本发明实施例提供的一种无人机的返航控制方法的流程示意图；
图4a是本发明实施例提供的另一种无人机迫降返航方式的示意图；
图4b是本发明实施例提供的又一种无人机迫降返航方式的示意图；
图4c是本发明实施例提供的又一种无人机迫降返航方式的示意图；
图4d是本发明实施例提供的又一种无人机迫降返航方式的示意图；
图5是本发明实施例提供的一种无人机的返航电量估算方法；
图6是本发明实施例提供的一种建立无人机的单位时间耗电模型的方法；
图7a是本发明实施例提供的一种在预设巡航高度上估计的单位时间耗电量的效果图；
图7b是本发明实施例提供的一种在迫降返航过程中估计的单位时间耗电量的效果图；
图8是本发明实施例提供的一种无人机的返航控制设备的结构示意图；
图9是本发明实施例提供的一种无人机的返航电量估算设备的结构示意图；
图10是本发明实施例提供的一种建立无人机的单位时间耗电模型的设备的结构示意图。
具体实施方式
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
下面结合附图，对本发明的一些实施方式作详细说明。在不冲突的情况下，下述的实施例及实施例中的特征可以相互组合。
本发明实施例中提供的无人机的返航控制方法可以由一种无人机的返航控制系统执行，所述无人机的返航控制设备和无人机之间可以进行双向通信。其中，所述无人机的返航控制系统包括无人机的返航控制设备和无人机，在某些实施例中，所述无人机的返航控制设备可以安装在无人机上，在某些实施例中，所述无人机的返航控制设备可以在空间上独立于无人机，在某些实施例中，所述无人机的返航控制设备可以是无人机的部件，即所述无人机包括无人机的返航控制设备。在其他实施例中，所述无人机的返航控制方法还可以应用于其 他可移动设备上，如能够自主移动的机器人、无人车、无人船等可移动设备。
该无人机的返航控制系统中无人机的返航控制设备可以在无人机的移动过程中，实时获取无人机的剩余电量，当确定出无人机的剩余电量小于或等于预设返航电量阈值时，所述无人机的返航控制设备可以控制无人机飞行到预设巡航高度，并根据第一预设水平速度控制量控制无人机在所述返航高度上水平返航。当所述无人机在所述预设巡航高度上水平返航时，如果无人机的返航控制设备确定出无人机的剩余电量小于或等于预设下降电量阈值，则可以根据所述第一预设水平速度控制量和预设下降速度控制量控制无人机迫降返航。通过这种方式，节约了无人机的下降时间，提高了无人机在电量不足的情况下返航的可能性，减少无人机丢失的概率，提高了无人机返航的准确率和飞行安全。下面对本发明实施例提供的无人机的返航控制系统进行示意性说明。
具体请参见图1，图1是本发明实施例提供的一种无人机的返航控制系统的结构示意图。所述无人机的返航控制系统包括：无人机的返航控制设备11、无人机12。其中，无人机12和无人机的返航控制设备11之间可以通过无线通信连接方式建立通信连接。其中，在某些特定的场景下，所述无人机12和无人机的返航控制设备11之间也可以通过有线通信连接方式建立通信连接。在某些实施例中，所述返航控制设备11可以为飞行控制器。所述无人机12可以为旋翼型飞行器，例如，四旋翼飞行器、六旋翼飞行器、八旋翼飞行器，也可以是固定翼飞行器等飞行器。所述无人机12包括动力系统121，所述动力系统121用于为无人机12提供飞行的动力。
本发明实施例中，所述无人机的返航控制设备11可以实时获取所述无人机12的剩余电量，并在确定出无人机12的剩余电量小于或者等于预设返航电量阈值时，控制无人机12飞行到预设巡航高度，从而根据第一预设水平速度控制量控制无人机12在所述预设巡航高度上水平返航。所述无人机12在所述预设巡航高度上水平返航的过程中，当无人机的返航控制设备11确定出无人机12的剩余电量小于或等于预设下降电量阈值时，无人机的返航控制设备11可以根据所述第一预设水平速度控制量和预设下降速度控制量控制无人机12迫降返航。
在一个实施例中，无人机12在飞行过程中可以实时获取无人机12的当前 位置，并计算无人机12从当前位置返航到返航点所需要的返航电量，即返航电量，并根据所述返航电量确定所述预设返航电量阈值。其中，所述返航电量可以通过本文后述部分提供的返航电量的估算方法来计算，无人机的返航控制设备11可以执行本文后述部分的返航电量的估算方法。可选地，无人机12可以实时地获取无人机12的当前高度，并计算无人机12从当前高度下降到地面所需的下降电量，即下降电量，并根据所述下降电量确定所述预设下降电量阈值。在某些实施例中，所述预设返航电量阈值和预设下降电量阈值均保留了安全裕量。
在一个实施例中，当确定出无人机12的剩余电量小于或等于预设返航电量阈值时，触发无人机12返航，控制无人机12飞行到预设巡航高度，并根据第一预设水平速度控制量控制无人机12在所述预设巡航高度上水平返航。
在一个实施例中，所述无人机12在所述预设巡航高度上水平返航的过程中，当无人机12的返航控制设备11确定出无人机12的剩余电量小于或等于预设下降电量阈值时，无人机的返航控制设备11可以根据所述第一预设水平速度控制量和预设下降速度控制量控制无人机12迫降返航。
在一个实施例中，所述无人机在迫降返航时，可以在第一预设水平速度控制量的基础上增加向下的速度分量即预设下降速度控制量，从而使无人机12边水平返航边下降，以节省下降时间。当无人机12下降到预设安全高度之后，可以不再下降，无人机12在所述预设安全高度上水平返航，以避免无人机撞击地面，提高无人机的安全性。当无人机12在预设安全高度上水平返航时，如果无人机12的剩余电量小于或等于预设降落电量阈值，则可以控制无人机降落，从而进一步提高无人机的安全性。在某些实施例中，无人机12可以实时地获取无人机12的当前高度，并计算无人机12从当前高度降落到地面所需的降落电量，即降落电量，并根据所述降落电量确定所述预设降落电量阈值。其中，所述预设降落电量阈值保留了较小的安全裕量。
可选地，本发明实施例可以基于图2a和图2b所示的现有技术中的常规返航方式，结合本发明实施例提供的如图2c所示的返航方式对本发明实施例提供的返航方式进行对比说明。
图2a是现有技术提供的一种无人机常规返航方式的示意图，如图2a所示，包括返航起点201、巡航高度点202、水平返航路线203、下降点204、返航点 205。无人机常规的返航方式一般采取直线返航，然后到达返航点上方再进行下降的方式。即如图2a所示，在返航起点201上升飞行至巡航高度点202，并沿着水平返航路线203水平返航至下降点204，其中，所述下降点204位于所述返航点205的正上方，无人机在下降点204开始下降并降落至返航点205，其中，所述返航点205可以设置在地面上。这种返航方式是通过将预设返航电量阈值设置为较大的电量阈值实现的，这种返航方式对无人机的剩余电量要求较高，即要求无人机进入返航模式时无人机具有较多的剩余电量，这样会减小无人机执行工作任务占用的电量，以及降低用户体验。
图2b是现有技术提供的一种返航电量估算偏小时无人机返航方式的示意图，如图2b所示，包括返航起点211、巡航高度点212、水平返航路线213、下降点214、返航点215。如图2b所示，无人机在返航起点211上升飞行至巡航高度点212，并沿着水平返航路线213水平返航。当无人机水平返航至下降点214时剩余电量小于预设下降电量阈值，则无人机在下降点214开始下降并降落至降落点215，其中，所述降落点215在所述返航点216前方。这种返航方式通过现有返航电量的估算方式估算返航电量，使得估算得到的返航电量偏小，以导致预设返航电量阈值设置较小的电量阈值，从而使无人机在进入返航模式时，剩余电量不足，以使无人机在飞行到返航点上方之前提前降落，从而容易导致无人机丢失。
图2c是本发明实施例提供的一种无人机迫降返航方式的示意图，如图2c所示，包括返航起点221、巡航高度点222、水平返航路线223、下降点224、安全高度点225、降落点226、返航点226。本发明实施例针对上述出现的情况，提供了图2c所示的无人机的返航控制方法，该方法在无人机迫降返航时，可以控制无人机在水平返航的基础上增加向下的速度分量即预设下降速度控制量，以使无人机边返航边下降，从而节省下降时间，提高无人机的飞行安全，以及用户体验。如图2c所示，无人机从返航起点221飞行至巡航高度点222，并控制无人机在水平返航路线223上返航，如果无人机在飞行至下降点224时剩余电量小于或等于预设下降电量阈值，则可以在水平方向和垂直于水平方向向下的方向上控制无人机迫降返航，当无人机下降至安全高度点225时，控制无人机水平返航，当水瓶返航到达降落点226降落至返航点227。
下面结合附图对无人机的返航控制方法进行示意性说明。
具体请参见图3，图3是本发明实施例提供的一种无人机的返航控制方法的流程示意图，所述方法可以由无人机的返航控制设备执行，其中，无人机的返航控制设备的具体解释如前所述。具体地，本发明实施例的所述方法包括如下步骤。
S301：当确定无人机的剩余电量小于或者等于预设返航电量阈值时，控制无人机飞行到预设巡航高度，并根据第一预设水平速度控制量控制无人机在所述预设巡航高度上水平返航。
本发明实施例中，无人机的返航控制设备可以实时地获取无人机的剩余电量，当确定出无人机的剩余电量小于或者等于预设返航电量阈值时，所述无人机的返航控制设备可以控制无人机飞行到预设巡航高度，并根据第一预设水平速度控制量控制无人机在所述预设巡航高度上水平返航。
S302：在所述巡航高度上水平返航的过程中，当确定无人机的剩余电量小于或等于预设下降电量阈值时，根据所述第一预设水平速度控制量和预设下降速度控制量控制无人机迫降返航。
本发明实施例中，当无人机在所述巡航高度上水平返航时，如果无人机的返航控制设备确定出无人机的剩余电量小于或等于预设下降电量阈值，则可以根据所述第一预设水平速度控制量和预设下降速度控制量控制无人机迫降返航。
具体可以图4a为例进行说明，图4a是本发明实施例提供的另一种无人机迫降返航方式的示意图，如图4a所示，包括：无人机40、巡航高度点401、下降点402、安全高度点403、降落点404、返航点405，其中，所述巡航高度点401对应预设巡航高度，所述安全高度点403对应所述预设安全高度。假设所述第一预设水平速度控制量为V1，当无人机从所述巡航高度点401以第一预设水平速度控制量V1沿所述预设巡航高度水平返航至下降点402时，如果无人机的返航控制设备确定出无人机40的剩余电量小于或等于预设下降电量阈值，则可以根据所述第一预设水平速度控制量V1和预设下降速度控制量Vx控制无人机迫降返航。
在一个实施例中，在无人机迫降返航的过程中，如果无人机的返航控制设备确定出无人机的高度下降至预设安全高度，则可以根据第二预设水平速度控 制量控制无人机在所述预设安全高度上水平返航。在某些实施例中，所述第一预设速度控制量可以与第二预设水平速度控制量相同，在其他实施例中，所述第一预设速度控制量也可以与第二预设水平速度控制量不相同，本发明实施例不做具体限定。
具体可以图4b为例进行说明，图4b是本发明实施例提供的又一种无人机迫降返航方式的示意图，如图4b所示，包括：无人机41、巡航高度点411、下降点412、安全高度点413、降落点414、返航点415，其中，所述巡航高度点411对应预设巡航高度，所述安全高度点413对应所述预设安全高度。假设第二预设水平速度控制量为V2，当无人机41从下降点412开始迫降返航时，如果无人机的返航控制设备确定出无人机41的高度下降至安全高度点413，则可以根据第二预设水平速度控制量V2控制无人机41在从安全高度点413开始在所述预设安全高度上水平返航。
在一个实施例中，当无人机在所述预设安全高度上水平返航时，如果无人机的返航控制设备确定出无人机的剩余电量小于或等于预设降落电量阈值，则可以控制无人机降落。在某些实施例中，所述无人机的剩余电量小于或等于预设降落电量阈值的位置点可以是所述预设安全高度上水平航线上的任意一位置点。
以图4b为例，当无人机41从安全高度点413沿所述预设安全高度以第二预设水平速度控制量V2水平返航时，如果无人机的返航控制设备在降落点414确定出无人机41的剩余电量小于或等于预设降落电量阈值，则可以控制无人机从降落点414开始降落。
在一个实施例中，当无人机在所述预设安全高度上水平返航时，如果无人机的返航控制设备确定出无人机到达返航点上方，则可以控制无人机降落至返航点。
以图4b为例，当无人机41从安全高度点413沿所述预设安全高度以第二预设水平速度控制量V2水平返航时，如果无人机的返航控制设备确定出无人机41到达返航点415上方的降落点416，则可以控制无人机41从降落点416降落至返航点415。
在一个实施例中，无人机在所述迫降返航时，如果无人机的返航控制设备确定出无人机到达返航点上方，则可以控制无人机降落至返航点。在一些实施 例中，所述无人机在所述迫降返航时，如果无人机的返航控制设备确定出无人机下降到预设安全高度的时候到达返航点上方，则可以控制无人机降落至返航点。
具体可以图4c为例进行说明，图4c是本发明实施例提供的又一种无人机迫降返航方式的示意图，如图4c所示，包括：无人机42、巡航高度点421、下降点422、降落点423、返航点424，其中，所述巡航高度点421对应预设巡航高度，所述降落点423位于所述返航点上方的预设安全高度上。当无人机42从下降点422开始下降时，如果无人机的返航控制设备确定出无人机下降到预设安全高度的降落点423时，则可以控制无人机42降落至返航点424。
在一个实施例中，无人机在迫降返航时，如果无人机的返航控制设备确定出无人机的剩余电量小于或等于预设降落电量阈值，则可以控制无人机降落。
具体可以图4d为例，图4d是本发明实施例提供的又一种无人机迫降返航方式的示意图，如图4d所示，包括：无人机43、巡航高度点431、下降点432、降落点433、返航点434。当无人机43从下降点432开始下降返航时，如果无人机的返航控制设备确定出无人机的剩余电量小于或等于预设降落电量阈值，则可以控制无人机43从降落点433开始降落。
本发明实施例中，无人机的返航控制设备可以在确定出无人机的剩余电量小于或者等于预设返航电量阈值时，控制无人机飞行到预设巡航高度，并根据第一预设水平速度控制量控制无人机在所述预设巡航高度上水平返航，在所述预设巡航高度上水平返航的过程中，当确定无人机的剩余电量小于或等于预设下降电量阈值时，根据所述第一预设水平速度控制量和预设下降速度控制量控制无人机迫降返航。通过这种方式，降低无人机丢失的概率、节省了下降时间，提高了无人机返航的准确率和飞行安全。
请参见图5，图5是本发明实施例提供的一种无人机的返航电量估算方法，所述无人机的返航电量估算方法可以由无人机的返航电量估算设备执行，所述无人机的返航电量估算设备和无人机之间可以进行双向通信，所述无人机的返航电量估算设备可以安装在无人机上，在某些实施例中，所述无人机的返航电量估算设备可以在空间上独立于无人机，在某些实施例中，所述无人机的返航电量估算设备可以是无人机的部件，即所述无人机包括无人机的返航电量估算 设备，所述返航电量估算设备可以为无人机的飞行控制器。在其他实施例中，所述无人机的返航电量估算方法还可以应用于其他可移动设备上，如能够自主移动的机器人、无人车、无人船等可移动设备，本发明实施例不做具体限定。具体地，本发明实施例的所述方法包括如下步骤。
S501：确定无人机在返航过程中的运动状态信息。
本发明实施例中，无人机的返航电量估算设备在无人机的飞行过程中需要实时地估算无人机的返航电量，所述返航电量为无人机从当前位置返航到返航点所需的电量。无人机的返航电量估算设备可以确定无人机在返航过程中的运动状态信息，具体地，无人机在飞行的过程中，无人机的返航电量估算设备可以实时地确定从当前位置向返航点返航的过程中无人机的运动状态信息。在某些实施例中，所述运动状态信息可以包括无人机的水平飞行速度、垂直飞行速度、无人机的高度信息中的至少一种，其中，所述无人机的高度信息可以包括无人机所处的海拔高度或者无人机的对地高度。在某些实施例中，所述返航过程为无人机从当前位置返航至返航点的过程。以图2c为例，假设无人机的当前位置为返航起点221，则所述返航过程为无人机40从返航起点221返航至返航点227的过程。
S502：根据所述确定的运动状态信息估算返航电量。
本发明实施例中，无人机的返航电量估算设备可以根据所述确定的运动状态信息估算返航电量。
现有的返航电量估算，往往采用根据经验获得的单位时间耗电量乘以返航所需要的时间进行粗略估计，由于现有的返航电量估算时没有考虑返航过程无人机的运动状态信息，导致无法正确反映对于电量消耗的影响，无法覆盖各种飞行场景，造成某些场景下估计结果和实际情况偏差较大的问题，精度较差，尤其在飞行距离较远的情况下和真实返航电量差距更为明显。本发明实施例中，根据无人机确定的在返航过程中的运动状态信息来估算返航电量，能够真实地反映返航过程无人机的运动状态信息对于电量消耗的影响，可以准确地估算出返航电量。
在一个实施例中，无人机的返航电量估算设备在根据所述确定的运动状态信息估算返航电量时，可以根据确定的运动状态信息确定无人机在返航过程中的单位时间耗电量，根据所述单位时间耗电量估算所述返航电量。
具体地，由于无人机在返航过程中，在不同的时刻，无人机的运动状态信息可能不同，无人机可以根据所述运动状态信息确定无人机的单位时间耗电量。可以理解的是，由于在不同的时刻，无人机的运动状态信息可能不同，无人机在不同时刻的单位时间耗电量可能不同。在确定了无人机在返航过程中各个单位时间耗电量之后，可以根据单位时间耗电量确定返航电量。例如，可以在返航过程中对各个单位时间耗电量进行累加，根据累加运算可以估算整个返航过程中消耗的电量，即返航电量。
在一个实施例中，无人机的返航电量估算设备可以将确定的运动状态信息代入到无人机的单位时间耗电模型以确定所述单位时间耗电量。其中，所述无人机的单位时间耗电模型如下：
△bat resume＝R1+R2V vert+R3h+R4V horz
其中，V vert、h、V horz分别表示垂直飞行速度，高度和水平飞行速度。R1、R2、R3、R4为模型系数，其中，所述模型系数为无人机的单位时间耗电模型中除自变量之外的参数，△bat resume为单位时间耗电量。其中，所述无人机的单位时间耗电模型的建立方法请参见本文后述部分，无人机的返航电量估算设备可以执行本文后述部分的建立无人机的单位时间耗电模型的方法。
本发明实施例中，无人机的返航电量估算设备可以确定无人机在返航过程中的运动状态信息，并根据所述确定的运动状态信息估算返航电量，通过这种方式估算返航电量，可以降低电量估算误差，提高了无人机的飞行安全和用户体验。
请参见图6，图6是本发明实施例提供的一种建立无人机的单位时间耗电模型的方法，所述建立无人机的单位时间耗电模型的方法可以由建立无人机的单位时间耗电模型的设备执行，所述建立无人机的单位时间耗电模型的设备和无人机之间可以进行双向通信，所述建立无人机的单位时间耗电模型的设备可以安装在无人机上，在某些实施例中，所述建立无人机的单位时间耗电模型的设备可以在空间上独立于无人机，在某些实施例中，所述建立无人机的单位时间耗电模型的设备可以是无人机的部件，即所述无人机包括建立无人机的单位时间耗电模型的设备，所述建立无人机的单位时间耗电模型的设备可以为无人机的飞行控制器。在其他实施例中，所述建立无人机的单位时间耗电模型的方 法还可以应用于其他可移动设备上，如能够自主移动的机器人、无人车、无人船等可移动设备，本发明实施例不做具体限定。在某些实施例中，所述建立无人机的单位时间耗电模型的设备可以为终端设备，其中，所述终端设备包括智能手机、平板电脑、膝上型电脑、台式电脑中的至少一种。具体地，本发明实施例的所述方法包括如下步骤。
S601：获取无人机在飞行过程中的运动状态信息和与所述运动状态信息对应的实际单位时间耗电量。
本发明实施例中，建立无人机的单位时间耗电模型的设备可以获取无人机在飞行过程中的运动状态信息，并且获取与所述运动状态信息对应的实际单位时间耗电量，即运动状态信息样本和单位时间耗电量样本。
在一些实施例中，所述运动状态信息包括无人机在多个不同的飞行状态下的运动状态信息。在某些实施例中，所述多个不同的飞行状态包括悬停、匀速飞行、加速飞行、减速飞行中的至少两个。
在一些实施例中，所述运动状态信息包括无人机在多个不同的飞行环境下的运动状态信息。在某些实施例中，所述多个不同的飞行环境可以包括多个不同的地点、多个不同的飞行高度、多个不同的温度环境、多个不同的风速环境等中的任意一种或多种环境。
在一个实施例中，所述运动状态信息可以包括分散度，所述运动状态信息的分散程度大于或等于预设的分散程度阈值。在某些实施例中，所述运动状态信息包括无人机的水平飞行速度、垂直飞行速度、无人机的高度信息中的至少一种。
在某些实施例中，所述运动状态信息样本和单位时间耗电量样本根据大量的样本数据得到的，其中，无人机的返航电量估算设备在采集样本数据之前，可以对样本数据的有效性进行判断。在一个实施例中，所述无人机的返航电量估算设备可以检测获取样本数据的无人机的飞行状态是否正常，如果检测到无人机的飞行状态没有明显的故障，则可以确定所述无人机的飞行状态正常。在一个实施例中，所述无人机的返航电量估算设备可以检测无人机的飞行状态是否保持稳定的悬停、水平匀速飞行或垂直匀速飞行，如果检测结果为是，则可以确定所述无人机的飞行状态正常。在一个实施例中，所述无人机的返航电量估算设备在检测到无人机的飞行状态正常之后，开始采集样本数据。
S602：将所述运动状态信息代入到所述单位时间耗电模型中以获取无人机的预期单位时间耗电量。
本发明实施例中，所述单位时间耗电模型包括一个或多个待确定的模型系数，当一个或多个待确定的模型系数确定之后，所述单位时间耗电模型就已经建立成功，所述单位时间耗电模型的自变量为运动状态信息自变量。建立无人机的单位时间耗电模型的设备可以将所述运动状态信息代入到所述单位时间耗电模型中以获取无人机的预期单位时间耗电量。
在一个实施例中，上述单位时间耗电量△bat resume，对于无人机的整个返航过程，建立无人机的单位时间耗电模型的设备可以根据当前的高度和设定的安全返航点的位置，综合预设巡航高度、巡航速度、下降速度等返航信息，计算返航时间，从而获取无人机返航所需的电量。
S603：基于所述实际单位时间耗电量和所述预期单位时间耗电量运行最小化拟合算法以确定所述一个或多个待确定的模型系数，并利用所述确定后的模型系数更新所述单位时间耗电模型。
本发明实施例中，建立无人机的单位时间耗电模型的设备可以获取多个运动状态信息，例如无人机在飞行过程中多个不同时刻的运动状态信息，根据如前所述方法将多个运动状态信息代入到包含待确定的模型系数的单位时间耗电模型中以获取多个预期单位时间耗电量，建立无人机的单位时间耗电模型的设备可以获取与所述多个运动状态信息对应的多个实际单位时间耗电量，基于多个所述实际单位时间耗电量和多个所述预期单位时间耗电量运行最小化拟合算法以确定所述一个或多个待确定的模型系数，并利用所述确定后的模型系数更新所述单位时间耗电模型。在某些实施例中，所述实际单位时间耗电量可以是根据预设的单位时间获取到的，本发明实施例对所述最小化拟合算法的类型不做具体限定，本领域技术人员可以根据需求选取，例如线性拟合算法、最小二乘拟合算法等等。在确定了所述一个或多个待确定的模型系数之后，可以利用所述确定后的模型系数更新所述单位时间耗电模型，则所述无人机的单位时间耗电模型建立成功。
在一个实施例中，所述建立无人机的单位时间耗电模型的设备可以获取垂直飞行速度、高度和水平飞行速度，并获取到与垂直飞行速度、高度h和水平 飞行速度对应的实际单位时间耗电量，将垂直飞行速度、高度和水平飞行速度代入到单位时间耗电模型△bat resume＝R1+R2V vert+R3h+R4V horz计算得到预期单位时间耗电量△bat resume，最后如前所述的方法根据所述预期单位时间耗电量△bat resume和实际单位时间耗电量运行最小化拟合算法以确定所述一个或多个待确定的模型系数R1、R2、R3、R4，并利用所述确定后的模型系数R1、R2、R3、R4更新所述单位时间耗电模型。
在一个实施例中，所述无人机的返航电量估算设备在根据所述确定的运动状态信息估算返航电量时，可以将确定的预设巡航高度上的运动状态信息代入到上述无人机的单位时间耗电模型中，以估算无人机在预设巡航高度上的单位时间耗电量，如图7a所示，图7a是本发明实施例提供的一种在预设巡航高度上估计的单位时间耗电量的效果图，如图7a所示，包括原模型耗电量71和实际耗电量72。
在一个实施例中，所述无人机的返航电量估算设备在根据所述确定的运动状态信息估算返航电量时，可以将确定的迫降返航的运动状态信息代入到上述无人机的单位时间耗电模型中，以估算无人机在预设巡航高度上的单位时间耗电量，如图7b所示，图7b是本发明实施例提供的一种在迫降返航过程中估计的单位时间耗电量的效果图，如图7b所示，包括原模型耗电量73和实际耗电量74。通过图7a和图7b可以看出，本发明实施例提供的无人机的单位时间耗电模型相比现有技术模型准确性更高，从而说明通过本发明实施例提供的无人机的单位时间耗电模型估算得到的返航电量的准确性更高。
本发明实施例中，建立无人机的单位时间耗电模型的设备可以获取无人机在飞行过程中的运动状态信息和与所述运动状态信息对应的实际单位时间耗电量，并将所述运动状态信息代入到所述单位时间耗电模型中以获取无人机的预期单位时间耗电量，基于所述实际单位时间耗电量和所述预期单位时间耗电量运行最小化拟合算法以确定所述一个或多个待确定的模型系数，并利用所述确定后的模型系数更新所述单位时间耗电模型。通过这种方式，降低了估算返航电量的误差，提高了模型准确度，从而提高了无人机的飞行安全和用户体验。
请参见图8为例进行说明，图8是本发明实施例提供的一种无人机的返航控制设备的结构示意图。具体的，所述无人机的返航控制设备包括：存储器 801、处理器802以及数据接口803。
所述数据接口803，用于传递无人机的返航控制设备和无人机之间的数据信息。
所述存储器801可以包括易失性存储器(volatile memory)；存储器801也可以包括非易失性存储器(non-volatile memory)；存储器801还可以包括上述种类的存储器的组合。所述处理器802可以是中央处理器(central processing unit，CPU)。所述处理器802还可以进一步包括硬件芯片。上述硬件芯片可以是专用集成电路(application-specific integrated circuit，ASIC)，可编程逻辑器件(programmable logic device，PLD)或其组合。上述PLD可以是复杂可编程逻辑器件(complex programmable logic device，CPLD)，现场可编程逻辑门阵列(field-programmable gate array，FPGA)或其任意组合。
所述存储器801用于存储程序指令，所述处理器802可以调用存储器801中存储的程序指令，用于执行如下步骤：
当确定无人机的剩余电量小于或者等于预设返航电量阈值时，控制无人机飞行到预设巡航高度，并根据第一预设水平速度控制量控制无人机在所述预设巡航高度上水平返航；
在所述预设巡航高度上水平返航的过程中，当确定无人机的剩余电量小于或等于预设下降电量阈值时，根据所述第一预设水平速度控制量和预设下降速度控制量控制无人机迫降返航。
进一步地，所述与所述无人机的位置满足预设位置关系的目标航点为与所述无人机的位置距离最近的目标航点。
进一步地，所述处理器802可以调用存储器801中存储的程序指令，还用于执行如下步骤：
在所述迫降返航的过程中，当确定无人机的高度下降至预设安全高度时，根据第二预设水平速度控制量控制无人机在所述预设安全高度上水平返航。
进一步地，所述处理器802可以调用存储器801中存储的程序指令，还用于执行如下步骤：
在所述预设安全高度上水平返航的过程中，当确定无人机的剩余电量小于或等于预设降落电量阈值时，控制无人机降落。
进一步地，所述处理器802可以调用存储器801中存储的程序指令，还用 于执行如下步骤：
在所述预设安全高度上水平返航的过程中，当确定无人机到达返航点上方时，控制无人机降落至返航点。
进一步地，所述处理器802可以调用存储器801中存储的程序指令，还用于执行如下步骤：
在所述迫降返航的过程中，当确定无人机到达返航点上方时，控制无人机降落至返航点。
进一步地，所述处理器802可以调用存储器801中存储的程序指令，还用于执行如下步骤：
在所述迫降返航的过程中，当确定无人机的剩余电量小于或等于预设降落电量阈值时，控制无人机降落。
本发明实施例中，无人机的返航控制设备可以在确定出无人机的剩余电量小于或者等于预设返航电量阈值时，控制无人机飞行到预设巡航高度，并根据第一预设水平速度控制量控制无人机在所述预设巡航高度上水平返航，在所述预设巡航高度上水平返航的过程中，当确定无人机的剩余电量小于或等于预设下降电量阈值时，根据所述第一预设水平速度控制量和预设下降速度控制量控制无人机迫降返航。通过这种方式，降低无人机丢失的概率、节省了下降时间，提高了无人机的飞行安全。
请参见图9，图9是本发明实施例提供的一种无人机的返航电量估算设备的结构示意图。具体的，所述无人机的返航电量估算设备包括：存储器901、处理器902以及数据接口903。
所述数据接口903，用于传递无人机的返航控制设备和无人机之间的数据信息。
所述存储器901可以包括易失性存储器(volatile memory)；存储器901也可以包括非易失性存储器(non-volatile memory)；存储器801还可以包括上述种类的存储器的组合。所述处理器902可以是中央处理器(central processing unit，CPU)。所述处理器902还可以进一步包括硬件芯片。上述硬件芯片可以是专用集成电路(application-specific integrated circuit，ASIC)，可编程逻辑器件(programmable logic device，PLD)或其组合。上述PLD可以是复杂可编 程逻辑器件(complex programmable logic device，CPLD)，现场可编程逻辑门阵列(field-programmable gate array，FPGA)或其任意组合。
所述存储器901用于存储程序指令，所述处理器902可以调用存储器901中存储的程序指令，用于执行如下步骤：
确定无人机在返航过程中的运动状态信息，其中，所述返航过程为无人机从当前位置返航至返航点的过程；
根据所述确定的运动状态信息估算返航电量。
进一步地，所述处理器902可以调用存储器901中存储的程序指令，根据确定的运动状态信息估算返航电量时，具体用于执行如下步骤：
根据确定的运动状态信息确定无人机在返航过程中的单位时间耗电量；
根据所述单位时间耗电量估算所述返航电量。
进一步地，所述处理器902可以调用存储器901中存储的程序指令，根据确定的运动状态信息确定所述单位时间耗电量时，具体用于执行如下步骤：
将确定的运动状态信息代入到无人机的单位时间耗电模型以确定所述单位时间耗电量。
进一步地，所述运动状态信息包括无人机的水平飞行速度、垂直飞行速度、无人机的高度信息中的至少一种。
本发明实施例中，无人机的返航电量估算设备可以确定无人机在返航过程中的运动状态信息，并根据所述确定的运动状态信息估算返航电量，通过这种方式估算返航电量，可以降低估算误差，提高了无人机的飞行安全和用户体验。
请参见图10，图10是本发明实施例提供的一种建立无人机的单位时间耗电模型的设备的结构示意图。具体的，所述建立无人机的单位时间耗电模型的设备包括：存储器1001、处理器1002以及数据接口1003。
所述数据接口1003，用于传递无人机的返航控制设备和无人机之间的数据信息。
所述存储器1001可以包括易失性存储器(volatile memory)；存储器1001也可以包括非易失性存储器(non-volatile memory)；存储器1001还可以包括上述种类的存储器的组合。所述处理器1002可以是中央处理器(central processing unit，CPU)。所述处理器1002还可以进一步包括硬件芯片。上述硬 件芯片可以是专用集成电路(application-specific integrated circuit，ASIC)，可编程逻辑器件(programmable logic device，PLD)或其组合。上述PLD可以是复杂可编程逻辑器件(complex programmable logic device，CPLD)，现场可编程逻辑门阵列(field-programmable gate array，FPGA)或其任意组合。
所述存储器1001用于存储程序指令，所述处理器1002可以调用存储器1001中存储的程序指令，用于执行如下步骤：
获取无人机在飞行过程中的运动状态信息和与所述运动状态信息对应的实际单位时间耗电量；
将所述运动状态信息代入到所述单位时间耗电模型中以获取无人机的预期单位时间耗电量，其中，所述单位时间耗电模型包括一个或多个待确定的模型系数；
基于所述实际单位时间耗电量和所述预期单位时间耗电量运行最小化拟合算法以确定所述一个或多个待确定的模型系数，并利用所述确定后的模型系数更新所述单位时间耗电模型。
进一步地，所述运动状态信息包括无人机在多个不同的飞行状态下的运动状态信息。
进一步地，所述运动状态信息包括无人机在多个不同的飞行环境下的运动状态信息。
进一步地，所述运动状态信息的分散程度大于或等于预设的分散程度阈值。
进一步地，所述运动状态信息包括无人机的水平飞行速度、垂直飞行速度、无人机的高度信息中的至少一种。
本发明实施例中，建立无人机的单位时间耗电模型的设备可以获取无人机在飞行过程中的运动状态信息和与所述运动状态信息对应的实际单位时间耗电量，并将所述运动状态信息代入到所述单位时间耗电模型中以获取无人机的预期单位时间耗电量，基于所述实际单位时间耗电量和所述预期单位时间耗电量运行最小化拟合算法以确定所述一个或多个待确定的模型系数，并利用所述确定后的模型系数更新所述单位时间耗电模型。通过这种方式，降低了估算返航电量的误差，提高了模型准确度，从而提高了无人机的飞行安全和用户体验。
本发明实施例还提供了一种无人机，包括：机身；配置在机身上的动力系统，用于为无人机提供移动的动力；处理器，用于执行以下步骤：
当确定无人机的剩余电量小于或者等于预设返航电量阈值时，控制无人机飞行到预设巡航高度，并根据第一预设水平速度控制量控制无人机在所述预设巡航高度上水平返航；
在所述预设巡航高度上水平返航的过程中，当确定无人机的剩余电量小于或等于预设下降电量阈值时，根据所述第一预设水平速度控制量和预设下降速度控制量控制无人机迫降返航。
进一步地，所述处理器还用于：
在所述迫降返航的过程中，当确定无人机的高度下降至预设安全高度时，根据第二预设水平速度控制量控制无人机在所述预设安全高度上水平返航。
进一步地，所述处理器还用于：
在所述预设安全高度上水平返航的过程中，当确定无人机的剩余电量小于或等于预设降落电量阈值时，控制无人机降落。
进一步地，所述处理器还用于：
在所述预设安全高度上水平返航的过程中，当确定无人机到达返航点上方时，控制无人机降落至返航点。
进一步地，所述处理器还用于：
在所述迫降返航的过程中，当确定无人机到达返航点上方时，控制无人机降落至返航点。
进一步地，所述处理器还用于：
在所述迫降返航的过程中，当确定无人机的剩余电量小于或等于预设降落电量阈值时，控制无人机降落。
本发明实施例中，无人机的返航控制设备可以在确定出无人机的剩余电量小于或者等于预设返航电量阈值时，控制无人机飞行到预设巡航高度，并根据第一预设水平速度控制量控制无人机在所述预设巡航高度上水平返航，在所述预设巡航高度上水平返航的过程中，当确定无人机的剩余电量小于或等于预设下降电量阈值时，根据所述第一预设水平速度控制量和预设下降速度控制量控制无人机迫降返航。通过这种方式，降低无人机丢失的概率、节省了下降时间，提高了无人机的飞行安全。
本发明实施例还提供了另一种无人机，包括：机身；配置在机身上的动力系统，用于为无人机提供移动的动力；处理器，用于执行以下步骤：
确定无人机在返航过程中的运动状态信息，其中，所述返航过程为无人机从当前位置返航至返航点的过程；
根据所述确定的运动状态信息估算返航电量。
进一步地，所述处理器根据确定的运动状态信息估算返航电量时，具体用于：
根据确定的运动状态信息确定无人机在返航过程中的单位时间耗电量；
根据所述单位时间耗电量估算所述返航电量。
进一步地，所述处理器根据确定的运动状态信息确定所述单位时间耗电量时，具体用于：
将确定的运动状态信息代入到无人机的单位时间耗电模型以确定所述单位时间耗电量。
进一步地，所述运动状态信息包括无人机的水平飞行速度、垂直飞行速度、无人机的高度信息中的至少一种。
本发明实施例中，无人机的返航电量估算设备可以确定无人机在返航过程中的运动状态信息，并根据所述确定的运动状态信息估算返航电量，通过这种方式估算返航电量，可以降低估算误差，提高了无人机的飞行安全和用户体验。
本发明实施例还提供了又一种无人机，包括：机身；配置在机身上的动力系统，用于为无人机提供移动的动力；处理器，用于执行以下步骤：
获取无人机在飞行过程中的运动状态信息和与所述运动状态信息对应的实际单位时间耗电量；
将所述运动状态信息代入到所述单位时间耗电模型中以获取无人机的预期单位时间耗电量，其中，所述单位时间耗电模型包括一个或多个待确定的模型系数；
基于所述实际单位时间耗电量和所述预期单位时间耗电量运行最小化拟合算法以确定所述一个或多个待确定的模型系数，并利用所述确定后的模型系数更新所述单位时间耗电模型。
进一步地，所述运动状态信息包括无人机在多个不同的飞行状态下的运动 状态信息。
进一步地，所述运动状态信息包括无人机在多个不同的飞行环境下的运动状态信息。
进一步地，所述运动状态信息的分散程度大于或等于预设的分散程度阈值。
进一步地，所述运动状态信息包括无人机的水平飞行速度、垂直飞行速度、无人机的高度信息中的至少一种。
本发明实施例中，建立无人机的单位时间耗电模型的设备可以获取无人机在飞行过程中的运动状态信息和与所述运动状态信息对应的实际单位时间耗电量，并将所述运动状态信息代入到所述单位时间耗电模型中以获取无人机的预期单位时间耗电量，基于所述实际单位时间耗电量和所述预期单位时间耗电量运行最小化拟合算法以确定所述一个或多个待确定的模型系数，并利用所述确定后的模型系数更新所述单位时间耗电模型。通过这种方式，降低了估算返航电量的误差，提高了模型准确度，从而提高了无人机的飞行安全和用户体验。
本发明的实施例还提供了一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序被处理器执行时实现本发明图1、图3、图5或图6所对应实施例中描述的方法，也可实现图8、图9或图10所述本发明所对应实施例的设备，在此不再赘述。
所述计算机可读存储介质可以是前述任一实施例所述的设备的内部存储单元，例如设备的硬盘或内存。所述计算机可读存储介质也可以是所述设备的外部存储设备，例如所述设备上配备的插接式硬盘，智能存储卡(Smart Media Card,SMC)，安全数字(Secure Digital,SD)卡，闪存卡(Flash Card)等。进一步地，所述计算机可读存储介质还可以既包括所述设备的内部存储单元也包括外部存储设备。所述计算机可读存储介质用于存储所述计算机程序以及所述终端所需的其他程序和数据。所述计算机可读存储介质还可以用于暂时地存储已经输出或者将要输出的数据。
以上所揭露的仅为本发明部分实施例而已，当然不能以此来限定本发明之权利范围，因此依本发明权利要求所作的等同变化，仍属本发明所涵盖的范围。

Claims (46)

  1. 一种无人机的返航控制方法，其特征在于，包括：
    当确定无人机的剩余电量小于或者等于预设返航电量阈值时，控制无人机飞行到预设巡航高度，并根据第一预设水平速度控制量控制无人机在所述预设巡航高度上水平返航；
    在所述预设巡航高度上水平返航的过程中，当确定无人机的剩余电量小于或等于预设下降电量阈值时，根据所述第一预设水平速度控制量和预设下降速度控制量控制无人机迫降返航。
  2. 根据权利要求1所述的方法，其特征在于，所述方法还包括：
    在所述迫降返航的过程中，当确定无人机的高度下降至预设安全高度时，根据第二预设水平速度控制量控制无人机在所述预设安全高度上水平返航。
  3. 根据权利要求2所述的方法，其特征在于，所述方法还包括：
    在所述预设安全高度上水平返航的过程中，当确定无人机的剩余电量小于或等于预设降落电量阈值时，控制无人机降落。
  4. 根据权利要求2或3所述的方法，其特征在于，所述方法还包括：
    在所述预设安全高度上水平返航的过程中，当确定无人机到达返航点上方时，控制无人机降落至返航点。
  5. 根据权利要求1-4任一项所述的方法，其特征在于，所述方法还包括：
    在所述迫降返航的过程中，当确定无人机到达返航点上方时，控制无人机降落至返航点。
  6. 根据权利要求1-5任一项所述的方法，其特征在于，所述方法还包括：
    在所述迫降返航的过程中，当确定无人机的剩余电量小于或等于预设降落电量阈值时，控制无人机降落。
  7. 一种无人机的返航电量估算方法，其特征在于，包括：
    确定无人机在返航过程中的运动状态信息，其中，所述返航过程为无人机从当前位置返航至返航点的过程；
    根据所述确定的运动状态信息估算返航电量。
  8. 根据权利要求7所述的方法，其特征在于，
    所述根据确定的运动状态信息估算返航电量包括：
    根据确定的运动状态信息确定无人机在返航过程中的单位时间耗电量；
    根据所述单位时间耗电量估算所述返航电量。
  9. 根据权利要求8所述的方法，其特征在于，所述根据确定的运动状态信息确定所述单位时间耗电量包括：
    将确定的运动状态信息代入到无人机的单位时间耗电模型以确定所述单位时间耗电量。
  10. 根据权利要求7-9任一项所述的方法，其特征在于，所述运动状态信息包括无人机的水平飞行速度、垂直飞行速度、无人机的高度信息中的至少一种。
  11. 一种建立无人机的单位时间耗电模型的方法，其特征在于，包括：
    获取无人机在飞行过程中的运动状态信息和与所述运动状态信息对应的实际单位时间耗电量；
    将所述运动状态信息代入到所述单位时间耗电模型中以获取无人机的预期单位时间耗电量，其中，所述单位时间耗电模型包括一个或多个待确定的模型系数；
    基于所述实际单位时间耗电量和所述预期单位时间耗电量运行最小化拟合算法以确定所述一个或多个待确定的模型系数，并利用所述确定后的模型系数更新所述单位时间耗电模型。
  12. 根据权利要求11所述的方法，其特征在于，所述运动状态信息包括 无人机在多个不同的飞行状态下的运动状态信息。
  13. 根据权利要求11或12所述的方法，其特征在于，所述运动状态信息包括无人机在多个不同的飞行环境下的运动状态信息。
  14. 根据权利要求11-13任一项所述的方法，其特征在于，所述运动状态信息的分散程度大于或等于预设的分散程度阈值。
  15. 根据权利要求11-14任一项所述的方法，其特征在于，所述运动状态信息包括无人机的水平飞行速度、垂直飞行速度、无人机的高度信息中的至少一种。
  16. 一种无人机的返航控制设备，其特征在于，包括存储器和处理器；
    所述存储器，用于存储程序指令；
    所述处理器，用于调用所述程序指令，当所述程序指令被执行时，用于执行以下操作:
    当确定无人机的剩余电量小于或者等于预设返航电量阈值时，控制无人机飞行到预设巡航高度，并根据第一预设水平速度控制量控制无人机在所述预设巡航高度上水平返航；
    在所述预设巡航高度上水平返航的过程中，当确定无人机的剩余电量小于或等于预设下降电量阈值时，根据所述第一预设水平速度控制量和预设下降速度控制量控制无人机迫降返航。
  17. 根据权利要16所述的设备，其特征在于，所述处理器还用于：
    在所述迫降返航的过程中，当确定无人机的高度下降至预设安全高度时，根据第二预设水平速度控制量控制无人机在所述预设安全高度上水平返航。
  18. 根据权利要17所述的设备，其特征在于，所述处理器还用于：
    在所述预设安全高度上水平返航的过程中，当确定无人机的剩余电量小于或等于预设降落电量阈值时，控制无人机降落。
  19. 根据权利要17或18所述的设备，其特征在于，所述处理器还用于：
    在所述预设安全高度上水平返航的过程中，当确定无人机到达返航点上方时，控制无人机降落至返航点。
  20. 根据权利要求16-19任一项所述的设备，其特征在于，所述处理器还用于：
    在所述迫降返航的过程中，当确定无人机到达返航点上方时，控制无人机降落至返航点。
  21. 根据权利要求16-20任一项所述的设备，其特征在于，所述处理器还用于：
    在所述迫降返航的过程中，当确定无人机的剩余电量小于或等于预设降落电量阈值时，控制无人机降落。
  22. 一种无人机的返航电量估算设备，其特征在于，包括存储器和处理器；
    所述存储器，用于存储程序指令；
    所述处理器，用于调用所述程序指令，当所述程序指令被执行时，用于执行以下操作：
    确定无人机在返航过程中的运动状态信息，其中，所述返航过程为无人机从当前位置返航至返航点的过程；
    根据所述确定的运动状态信息估算返航电量。
  23. 根据权利要求22所述的设备，其特征在于，
    所述处理器根据确定的运动状态信息估算返航电量时，具体用于：
    根据确定的运动状态信息确定无人机在返航过程中的单位时间耗电量；
    根据所述单位时间耗电量估算所述返航电量。
  24. 根据权利要求23所述的设备，其特征在于，
    所述处理器根据确定的运动状态信息确定所述单位时间耗电量时，具体用 于：
    将确定的运动状态信息代入到无人机的单位时间耗电模型以确定所述单位时间耗电量。
  25. 根据权利要求22-24任一项所述的设备，其特征在于，
    所述运动状态信息包括无人机的水平飞行速度、垂直飞行速度、无人机的高度信息中的至少一种。
  26. 一种建立无人机的单位时间耗电模型的设备，其特征在于，包括存储器和处理器；
    所述存储器，用于存储程序指令；
    所述处理器，用于调用所述程序指令，当所述程序指令被执行时，用于执行以下操作:
    获取无人机在飞行过程中的运动状态信息和与所述运动状态信息对应的实际单位时间耗电量；
    将所述运动状态信息代入到所述单位时间耗电模型中以获取无人机的预期单位时间耗电量，其中，所述单位时间耗电模型包括一个或多个待确定的模型系数；
    基于所述实际单位时间耗电量和所述预期单位时间耗电量运行最小化拟合算法以确定所述一个或多个待确定的模型系数，并利用所述确定后的模型系数更新所述单位时间耗电模型。
  27. 根据权利要求26所述的设备，其特征在于，
    所述运动状态信息包括无人机在多个不同的飞行状态下的运动状态信息。
  28. 根据权利要求26或27所述的设备，其特征在于，
    所述运动状态信息包括无人机在多个不同的飞行环境下的运动状态信息。
  29. 根据权利要求26-28任一项所述的设备，其特征在于，
    所述运动状态信息的分散程度大于或等于预设的分散程度阈值。
  30. 根据权利要求26-29任一项所述的设备，其特征在于，
    所述运动状态信息包括无人机的水平飞行速度、垂直飞行速度、无人机的高度信息中的至少一种。
  31. 一种无人机，其特征在于，包括：
    机身；
    配置在机身上的动力系统，用于为移动机器人提供移动的动力；
    处理器，用于执行以下步骤：
    当确定无人机的剩余电量小于或者等于预设返航电量阈值时，控制无人机飞行到预设巡航高度，并根据第一预设水平速度控制量控制无人机在所述预设巡航高度上水平返航；
    在所述预设巡航高度上水平返航的过程中，当确定无人机的剩余电量小于或等于预设下降电量阈值时，根据所述第一预设水平速度控制量和预设下降速度控制量控制无人机迫降返航。
  32. 根据权利要求31所述的无人机，其特征在于，所述处理器还用于：
    在所述迫降返航的过程中，当确定无人机的高度下降至预设安全高度时，根据第二预设水平速度控制量控制无人机在所述预设安全高度上水平返航。
  33. 根据权利要求32所述的无人机，其特征在于，所述处理器还用于：
    在所述预设安全高度上水平返航的过程中，当确定无人机的剩余电量小于或等于预设降落电量阈值时，控制无人机降落。
  34. 根据权利要求32或33所述的无人机，其特征在于，所述处理器还用于：
    在所述预设安全高度上水平返航的过程中，当确定无人机到达返航点上方时，控制无人机降落至返航点。
  35. 根据权利要求21-34任一项所述的无人机，其特征在于，所述处理器 还用于：
    在所述迫降返航的过程中，当确定无人机到达返航点上方时，控制无人机降落至返航点。
  36. 根据权利要求31-35任一项所述的无人机，其特征在于，所述处理器还用于：
    在所述迫降返航的过程中，当确定无人机的剩余电量小于或等于预设降落电量阈值时，控制无人机降落。
  37. 一种无人机，其特征在于，包括：
    机身；
    配置在机身上的动力系统，用于为移动机器人提供移动的动力；
    处理器，用于执行以下步骤：
    确定无人机在返航过程中的运动状态信息，其中，所述返航过程为无人机从当前位置返航至返航点的过程；
    根据所述确定的运动状态信息估算返航电量。
  38. 根据权利要求37所述的无人机，其特征在于，所述处理器根据确定的运动状态信息估算返航电量时，具体用于：
    根据确定的运动状态信息确定无人机在返航过程中的单位时间耗电量；
    根据所述单位时间耗电量估算所述返航电量。
  39. 根据权利要求38所述的无人机，其特征在于，所述处理器根据确定的运动状态信息确定所述单位时间耗电量时，具体用于：
    将确定的运动状态信息代入到无人机的单位时间耗电模型以确定所述单位时间耗电量。
  40. 根据权利要求37-39任一项所述的无人机，其特征在于，
    所述运动状态信息包括无人机的水平飞行速度、垂直飞行速度、无人机的高度信息中的至少一种。
  41. 一种无人机，其特征在于，包括：
    机身；
    配置在机身上的动力系统，用于为移动机器人提供移动的动力；
    处理器，用于执行以下步骤：
    获取无人机在飞行过程中的运动状态信息和与所述运动状态信息对应的实际单位时间耗电量；
    将所述运动状态信息代入到所述单位时间耗电模型中以获取无人机的预期单位时间耗电量，其中，所述单位时间耗电模型包括一个或多个待确定的模型系数；
    基于所述实际单位时间耗电量和所述预期单位时间耗电量运行最小化拟合算法以确定所述一个或多个待确定的模型系数，并利用所述确定后的模型系数更新所述单位时间耗电模型。
  42. 根据权利要求41所述的无人机，其特征在于，
    所述运动状态信息包括无人机在多个不同的飞行状态下的运动状态信息。
  43. 根据权利要求41或42所述的无人机，其特征在于，
    所述运动状态信息包括无人机在多个不同的飞行环境下的运动状态信息。
  44. 根据权利要求41-43任一项所述的无人机，其特征在于，
    所述运动状态信息的分散程度大于或等于预设的分散程度阈值。
  45. 根据权利要求41-44任一项所述的无人机，其特征在于，
    所述运动状态信息包括无人机的水平飞行速度、垂直飞行速度、无人机的高度信息中的至少一种。
  46. 一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，其特征在于，所述计算机程序被处理器执行时实现如权利要求1至15任一项所述方法。
PCT/CN2018/101958 2018-08-23 2018-08-23 一种无人机的返航控制方法、设备、及无人机 WO2020037602A1 (zh)

Priority Applications (3)

Application Number Priority Date Filing Date Title
CN201880037310.7A CN110730933A (zh) 2018-08-23 2018-08-23 一种无人机的返航控制方法、设备、及无人机
PCT/CN2018/101958 WO2020037602A1 (zh) 2018-08-23 2018-08-23 一种无人机的返航控制方法、设备、及无人机
US17/180,534 US20210181766A1 (en) 2018-08-23 2021-02-19 Return flight control method and device, and unmanned aerial vehicle

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2018/101958 WO2020037602A1 (zh) 2018-08-23 2018-08-23 一种无人机的返航控制方法、设备、及无人机

Related Child Applications (1)

Application Number Title Priority Date Filing Date
US17/180,534 Continuation US20210181766A1 (en) 2018-08-23 2021-02-19 Return flight control method and device, and unmanned aerial vehicle

Publications (1)

Publication Number Publication Date
WO2020037602A1 true WO2020037602A1 (zh) 2020-02-27

Family

ID=69217758

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2018/101958 WO2020037602A1 (zh) 2018-08-23 2018-08-23 一种无人机的返航控制方法、设备、及无人机

Country Status (3)

Country Link
US (1) US20210181766A1 (zh)
CN (1) CN110730933A (zh)
WO (1) WO2020037602A1 (zh)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114137426A (zh) * 2021-11-30 2022-03-04 广州极飞科技股份有限公司 一种剩余电量估算方法、装置、设备及存储介质
CN114877876A (zh) * 2022-07-12 2022-08-09 南京市计量监督检测院 一种无人机悬停精度评估方法

Families Citing this family (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021195828A1 (zh) * 2020-03-30 2021-10-07 深圳市大疆创新科技有限公司 无人机下降的控制方法和装置、无人机
CN112180723B (zh) * 2020-09-15 2022-02-01 东北大学 一种基于能量分析的无人机任务规划方法及装置
CN112987772A (zh) * 2021-05-11 2021-06-18 北京三快在线科技有限公司 无人机近地面飞行控制方法、装置、介质、设备和无人机
CN113741541A (zh) * 2021-09-28 2021-12-03 广州极飞科技股份有限公司 无人设备飞行控制方法、装置、系统、设备及存储介质
CN114779824B (zh) * 2022-06-20 2022-09-23 成都翼比特自动化设备有限公司 一种无人机智能返航的方法及系统

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105334865A (zh) * 2015-11-24 2016-02-17 余江 基于电量监控的飞行控制方法及飞行控制装置
CN205120933U (zh) * 2015-09-17 2016-03-30 杨珊珊 一种续航能力监测系统及其无人飞行器和飞控台
CN107783552A (zh) * 2016-08-26 2018-03-09 北京臻迪机器人有限公司 控制无人机返航的方法及装置
JP2018052341A (ja) * 2016-09-29 2018-04-05 セコム株式会社 飛行ロボット制御システムおよび飛行ロボット
CN107885225A (zh) * 2014-07-16 2018-04-06 深圳市大疆创新科技有限公司 电动无人机及其智能电量保护方法

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107531326B (zh) * 2015-03-12 2019-04-16 奈庭吉尔智慧系统公司 自动化无人机系统
CN106647801A (zh) * 2016-10-21 2017-05-10 广东容祺智能科技有限公司 一种无人机返航航线规划系统
CN106899054A (zh) * 2016-12-15 2017-06-27 深圳市元征科技股份有限公司 无人机、无人机充电的控制方法及系统
CN106951650B (zh) * 2017-03-28 2020-07-31 南京信息工程大学 无人机续航能力评估系统
CN108256553B (zh) * 2017-12-20 2020-03-27 中国人民解放军国防科技大学 车辆搭载无人机双层路径的构造方法及装置
CN108226796A (zh) * 2017-12-28 2018-06-29 广州亿航智能技术有限公司 遥控无人机及电池电量监控方法

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107885225A (zh) * 2014-07-16 2018-04-06 深圳市大疆创新科技有限公司 电动无人机及其智能电量保护方法
CN205120933U (zh) * 2015-09-17 2016-03-30 杨珊珊 一种续航能力监测系统及其无人飞行器和飞控台
CN105334865A (zh) * 2015-11-24 2016-02-17 余江 基于电量监控的飞行控制方法及飞行控制装置
CN107783552A (zh) * 2016-08-26 2018-03-09 北京臻迪机器人有限公司 控制无人机返航的方法及装置
JP2018052341A (ja) * 2016-09-29 2018-04-05 セコム株式会社 飛行ロボット制御システムおよび飛行ロボット

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114137426A (zh) * 2021-11-30 2022-03-04 广州极飞科技股份有限公司 一种剩余电量估算方法、装置、设备及存储介质
CN114137426B (zh) * 2021-11-30 2024-04-09 广州极飞科技股份有限公司 一种剩余电量估算方法、装置、设备及存储介质
CN114877876A (zh) * 2022-07-12 2022-08-09 南京市计量监督检测院 一种无人机悬停精度评估方法

Also Published As

Publication number Publication date
US20210181766A1 (en) 2021-06-17
CN110730933A (zh) 2020-01-24

Similar Documents

Publication Publication Date Title
WO2020037602A1 (zh) 一种无人机的返航控制方法、设备、及无人机
CN109634295B (zh) 一种自动返航方法、装置和无人机
WO2020191647A1 (zh) 一种无人机的降落控制方法、飞行控制设备及无人机
US11592824B2 (en) Using machine learning techniques to estimate available energy for vehicles
US9938008B2 (en) Systems and methods for execution of recovery actions on an unmanned aerial vehicle
CA2828444C (en) Aircraft control system, aircraft, aircraft control program, and method for controlling aircraft
US20140358415A1 (en) Flight prediction system
CN111699451A (zh) 垂直起降无人机的飞行控制方法、设备及垂直起降无人机
WO2016172251A1 (en) Systems and methods for execution of recovery actions on an unmanned aerial vehicle
US20210141373A1 (en) System and method for aerial traffic management of unmanned aerial vehicles
US20230280763A1 (en) Method for protection unmanned aerial vehicle and unmanned aerial vehicle
WO2020191666A1 (zh) 返航控制方法、飞行控制装置及无人机
CN110297501A (zh) 无人机控制方法、装置和设备
CN112673330A (zh) 无人机下降的控制方法和装置、无人机
CN113985914A (zh) 一种无人设备降落控制方法、装置、设备及存储介质
WO2020237529A1 (zh) 一种无人机的飞行控制方法、设备及无人机
WO2020237531A1 (zh) 无人机返航方法、设备、无人机和存储介质
Liang et al. Tailsitter VTOL flying wing aircraft attitude control
US20220227479A1 (en) Flying body, control method, and program
CN111752295B (zh) 无人机飞行轨迹规划方法及相关装置
WO2021016871A1 (zh) 无人飞行器控制方法、控制装置及计算机可读存储介质
WO2022201245A1 (ja) 制御装置、飛行体制御方法およびプログラム
CN113109852B (zh) 一种无人机进狭窄空间的路径规划方法及装置
CN112136092A (zh) 一种飞行控制方法、设备及飞行器
WO2023178476A1 (zh) 无人机降落的控制方法和装置、无人机

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 18931237

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 18931237

Country of ref document: EP

Kind code of ref document: A1