CN111435255A - Unmanned aerial vehicle brake control method and device and unmanned aerial vehicle - Google Patents
Unmanned aerial vehicle brake control method and device and unmanned aerial vehicle Download PDFInfo
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- CN111435255A CN111435255A CN201911010316.8A CN201911010316A CN111435255A CN 111435255 A CN111435255 A CN 111435255A CN 201911010316 A CN201911010316 A CN 201911010316A CN 111435255 A CN111435255 A CN 111435255A
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- 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
- G05D1/08—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
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- 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
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
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Abstract
The invention discloses an unmanned aerial vehicle brake control method and device and an unmanned aerial vehicle. The method comprises the following steps: after receiving an acceleration instruction, calculating the estimated speed of the unmanned aerial vehicle in real time through a speed estimation model; when a braking instruction is received, taking the estimated speed at the moment as a braking speed; controlling the unmanned aerial vehicle to start initial braking according to the braking speed until the speed of the unmanned aerial vehicle falls into a preset range, and ending the initial braking; wherein, the preset range is a speed range which can be detected by the optical flow sensor; after the initial braking is finished, the unmanned aerial vehicle is controlled by the optical flow sensor to perform secondary braking so as to reach a stable hovering state. The invention can realize the emergency braking of the unmanned aerial vehicle in high-speed flight, has lower requirement on hardware and does not need to additionally install a GPS.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle brake control method and device and an unmanned aerial vehicle.
Background
At present, unmanned aerial vehicles are more and more widely applied, and the importance of unmanned aerial vehicles is increasingly highlighted in civil, commercial and even military fields. With the increasingly wide application field of the unmanned aerial vehicle, the requirement on the unmanned aerial vehicle is more and more, but the pursuit of low cost and the capability of realizing higher performance through the lowest hardware is still the mainstream, and especially under the condition that the small unmanned aerial vehicle is popular among the general public at present. Currently, most small drones can achieve horizontal motion in the horizontal plane, for example, from flying to hovering in the horizontal plane, or from hovering to flying, speed measurement can be generally achieved through optical flow sensors, and braking is achieved by controlling the drones through a PID (proportional-integral-differential) algorithm. However, if the existing unmanned gyroplane uses the optical flow velocity measurement method alone, the correct velocity is measured at a high speed, and the frame rate of the optical flow velocity measurement and the quality requirement of the algorithm are high, so a high frame rate optical flow sensor needs to be adopted to match with a good camera, and the optical flow velocity measurement and the good camera adopting the high frame rate optical flow velocity measurement can increase the system hardware requirement, and consume a relatively large amount of CPU resources to operate the optical flow algorithm, if a general low frame rate optical flow sensor is adopted, the speed measurement is easy to fail at a high speed (in the field of small unmanned planes, generally, the speed measurement can be regarded as high-speed flight more than 6 m/s), and if a GPS is adopted, the cost is increased and only the outdoor situation is supported. Therefore, how to avoid the problem that the emergency braking cannot be realized due to the failure of the low-frame-rate optical flow sensor when the unmanned aerial vehicle flies at a high speed without increasing the hardware investment is a problem to be solved urgently.
Disclosure of Invention
Based on the above situation, the main objective of the present invention is to provide a method and an apparatus for controlling braking of an unmanned aerial vehicle, and an unmanned aerial vehicle, so as to solve the problem of emergency braking failure caused by failure of a low frame rate optical flow sensor when the unmanned aerial vehicle flies at a high speed.
In order to achieve the purpose, the invention provides an unmanned aerial vehicle brake control method, which comprises the following steps: s10, calculating the estimated speed of the unmanned aerial vehicle in real time through a speed estimation model after receiving the acceleration instruction; the speed estimation model is used for calculating the estimated speed of the unmanned aerial vehicle at the next moment according to the initial speed and attitude angle data of the unmanned aerial vehicle at any moment; s30, controlling the unmanned aerial vehicle to start initial braking according to the braking speed until the speed of the unmanned aerial vehicle falls into a preset range, and finishing the initial braking; wherein, the preset range is a speed range which can be detected by the optical flow sensor; and S40, after the initial braking is finished, controlling the unmanned aerial vehicle to perform secondary braking through the optical flow sensor so as to achieve a stable hovering state.
Preferably, step S10 includes: when an acceleration instruction is received, determining the initial speed of the unmanned aerial vehicle at the moment; acquiring unmanned aerial vehicle attitude angle data in real time; calculating an estimated speed of the drone in real time based on the acquired attitude angle data and the initial speed.
Preferably, step S30 includes the steps of: s31, calculating the required braking parameters for the estimated speed of the unmanned aerial vehicle to reach a preset threshold value according to the braking speed; the braking parameters comprise braking time, and the preset threshold is in the preset range; and S32, controlling the unmanned aerial vehicle to start initial braking according to the braking parameters, and ending the initial braking when the braking time is up.
Preferably, step S30 includes the steps of: s33, calculating according to the braking speed and a braking estimation formula to obtain braking parameters required when the estimated speed of the unmanned aerial vehicle is zero; the braking parameters comprise braking time and preset duration; s34, controlling the unmanned aerial vehicle to start initial braking according to the braking parameters; and S35, detecting the speed of the unmanned aerial vehicle through an optical flow sensor when a preset time is left after the braking time is over, and ending the initial braking if the detected speed is within the preset range.
Preferably, the braking parameters further include a braking attitude angle.
Preferably, the braking attitude angle includes either or both of a pitch angle and a roll angle.
Preferably, the step S32 or S34 includes: and controlling the unmanned aerial vehicle to perform initial braking at the braking attitude angle.
Preferably, the step S32 or S34 includes: controlling the unmanned aerial vehicle to start initial braking by taking the braking attitude angle as an initial attitude angle; wherein the attitude angle of the drone is progressively reduced from the initial attitude angle before the initial braking is over.
Preferably, the determining the initial velocity of the drone comprises: if the unmanned aerial vehicle is in a stable hovering state before the acceleration instruction is received, determining that the initial speed of the unmanned aerial vehicle is 0; and if the unmanned aerial vehicle is in a hovering horizontal motion state before the acceleration instruction is received, taking the current real-time speed of the user as the initial speed.
Preferably, step S40 includes: when the initial braking is finished, if the speed of the unmanned aerial vehicle is measured to be zero through the optical flow sensor, the attitude of the unmanned aerial vehicle is directly set to be the initial attitude of the unmanned aerial vehicle in the stable unmanned hovering state.
Preferably, step S40 includes: when the initial braking is finished, if the speed of the unmanned aerial vehicle measured by the optical flow sensor is not zero, the control station
And the unmanned aerial vehicle performs secondary braking to achieve a stable hovering state.
Preferably, in step S40, the controlling the drone to perform secondary braking to reach the hover stable state includes: and carrying out PID control on the unmanned aerial vehicle through an optical flow sensor so as to enable the real-time speed of the unmanned aerial vehicle to reach zero and enter a hovering stable state.
Preferably, the attitude angle data includes an euler angle of the drone, and the calculating an estimated velocity of the drone in real time based on the acquired attitude angle data and the initial velocity includes: calculating an effective angle increment delta theta of the attitude angle of the unmanned aerial vehicle according to the Euler angle of the unmanned aerial vehicle; converting the effective angle increment into an angle increment delta theta under a geographic coordinate systemeAnd calculating the estimated speed of the unmanned aerial vehicle in real time according to a speed estimation formula, wherein the speed estimation formula is as follows:
where dt is the gyroscope measurement period, Δ veFor the unmanned aerial vehicle, the speed increment in the next measurement period of the geographic coordinate system，ΔθeFor the effective angle increment of the unmanned aerial vehicle in the geographic coordinate system, which causes the speed change in each measurement period,
for the estimated speed of the drone at time t in the geographic coordinate system,
and r is an air resistance coefficient in the braking process.
Preferably, calculating the effective angle increment Δ θ of the attitude angle of the drone from the euler angle comprises: determining an offset Euler angle when the unmanned aerial vehicle is in a stable hovering state; and calculating to obtain the effective angle increment delta theta according to the Euler angle and the bias Euler angle.
Preferably, the braking parameters further include a braking attitude angle, and the step S33 includes: converting the braking speed into the braking amount under the coordinate system of the machine body
Calculating a braking attitude angle and braking time according to a braking estimation formula, wherein the braking estimation formula is as follows:
where α is the braking attitude angle, T is the braking time, and C is the time constant.
Preferably, the gradually decreasing of the attitude angle of the drone from the initial attitude angle comprises: and the attitude angle of the unmanned aerial vehicle is decreased progressively from the initial attitude angle by taking a time constant C as a constant.
Preferably, the acceleration command is a lever-hitting operation, and the braking command is a lever-hitting ending operation.
In order to achieve the above object, the present invention further provides a braking control device for an unmanned aerial vehicle, comprising: the speed estimation module is used for calculating the estimated speed of the unmanned aerial vehicle in real time through the speed estimation model after receiving the acceleration instruction; the speed estimation model is used for calculating the estimated speed of the unmanned aerial vehicle at the next moment according to the initial speed and attitude angle data of the unmanned aerial vehicle at any moment; the braking speed determining module is used for taking the estimated speed at the moment as the braking speed when a braking instruction is received; the initial braking module is used for controlling the unmanned aerial vehicle to start initial braking according to the braking speed until the speed of the unmanned aerial vehicle falls into a preset range, and the initial braking is finished; wherein, the preset range is a speed range which can be detected by the optical flow sensor; and the secondary braking module is used for controlling the unmanned aerial vehicle to perform secondary braking through the optical flow sensor so as to achieve a hovering stable state after the initial braking is finished.
In order to achieve the above object, the present invention further provides a drone, including a processor and a computer readable storage medium, where the storage medium stores a drone braking control program, and the drone braking control program, when executed by the processor, implements the drone braking control method as described above.
Has the advantages that:
according to the braking control method of the unmanned aerial vehicle, under the condition of high-speed flight with possible failure of the optical flow sensor, the braking speed of the unmanned aerial vehicle is directly estimated through the speed estimation model, the braking parameters are calculated, the unmanned aerial vehicle is controlled to perform initial braking on the basis until the speed of the unmanned aerial vehicle is reduced to a range which can be accurately detected by the optical flow sensor, then the conventional PID control is performed, and secondary braking is performed by means of speed measurement of the optical flow sensor.
Other advantages of the present invention will be described in the detailed description, through the description of specific technical features and technical solutions, which will be understood by those skilled in the art.
Drawings
Preferred embodiments according to the present invention will be described below with reference to the accompanying drawings. In the figure:
fig. 1 is a schematic flow chart of a braking control method for an unmanned aerial vehicle according to a preferred embodiment of the invention;
fig. 2 is a schematic diagram illustrating the force applied when the drone moves according to a preferred embodiment of the present invention;
fig. 3 is a functional block diagram of a brake control device of an unmanned aerial vehicle according to a preferred embodiment of the present invention.
Detailed Description
In order to describe the technical solutions of the present invention in more detail to facilitate further understanding of the present invention, the following describes specific embodiments of the present invention with reference to the accompanying drawings. It should be understood, however, that all of the illustrative embodiments and descriptions thereof are intended to illustrate the invention and are not to be construed as the only limitations of the invention.
According to the invention, when the unmanned aerial vehicle is in a stable hovering state, the unmanned aerial vehicle is in a stopping state on any horizontal plane, the unmanned aerial vehicle does not have speed in the horizontal direction, and the unmanned aerial vehicle is in a stress balance state in both the vertical direction and the horizontal direction. When the unmanned aerial vehicle is in hovering horizontal motion, the unmanned aerial vehicle moves leftwards and rightwards or forwards and backwards on any horizontal plane, the height of the unmanned aerial vehicle in the vertical direction is kept unchanged, at the moment, the unmanned aerial vehicle does not have speed in the vertical direction and is in a stress balance state, and the motion indicated in the invention is horizontal plane motion with the height of the unmanned aerial vehicle in the vertical direction kept unchanged.
Referring to fig. 1, a schematic flow chart of a braking control method for an unmanned aerial vehicle according to a first embodiment of the invention is shown. In the embodiment, the unmanned aerial vehicle brake control method includes the following steps S10-S50:
s10, calculating the estimated speed of the unmanned aerial vehicle in real time through the speed estimation model after receiving the acceleration instruction;
specifically, after receiving an acceleration instruction, the unmanned aerial vehicle enters an accelerated motion mode, in the invention, because the speed of the unmanned aerial vehicle generally reaches a high speed after the unmanned aerial vehicle starts to accelerate in the horizontal direction, the possibility of failure of the low-frame-rate optical flow sensor during speed measurement is very high, or the speed of the unmanned aerial vehicle can reach a higher level when the unmanned aerial vehicle is already in braking before accelerating, the braking control method provided by the invention is started to be executed once the unmanned aerial vehicle enters the accelerated motion mode. At the moment, the speed of the unmanned aerial vehicle is not directly detected through the optical flow sensor, but is directly calculated through the speed estimation model. In this embodiment, the speed estimation model is used to calculate the estimated speed of the drone at the next time according to the initial speed and attitude angle data of the drone at any time.
In a specific scenario of another embodiment of the present invention, the acceleration instruction may be a lever-hitting operation of a user, and in a conventional operation of the existing unmanned aerial vehicle, if the user performs the lever-hitting operation, it indicates that the unmanned aerial vehicle needs to enter an acceleration mode. When the user is detected to perform the lever-beating operation, the unmanned aerial vehicle enters an acceleration motion mode, and the speed of the unmanned aerial vehicle is the initial speed of the subsequent horizontal acceleration motion.
Further, in the present embodiment, S10 specifically includes the following steps S11-S13:
s11, when an acceleration instruction is received, determining the initial speed of the unmanned aerial vehicle;
in the embodiment, the determining the initial speed of the unmanned aerial vehicle comprises the steps of determining that the current speed of the unmanned aerial vehicle is 0 if the unmanned aerial vehicle is in a stable hovering state before an acceleration instruction is received; and if the unmanned aerial vehicle is in a hovering horizontal motion state before the acceleration instruction is received, taking the estimated speed at the moment as the initial speed.
Specifically, before the unmanned aerial vehicle performs the acceleration movement after receiving the acceleration instruction, the unmanned aerial vehicle may be in a hovering stable state, and then starts to move from a standstill after receiving the acceleration instruction, and the initial speed is zero; and possibly also in a braking state, the initial speed should be an estimated speed estimated in real time, which is updated in real time.
S12, acquiring the attitude angle data of the unmanned aerial vehicle in real time;
specifically, the attitude angle data of the drone may be obtained by a gyroscope, including the euler angle generated by the rotation of the drone. In this embodiment, the tilt angle of the unmanned aerial vehicle flight can be determined by the euler angle obtained by the gyroscope, and is set as θ.
S13, calculating the estimated speed of the unmanned aerial vehicle in real time based on the acquired attitude angle data and the initial speed;
specifically, the estimated speed of the unmanned aerial vehicle can be estimated in real time by a speed estimation model of accelerated motion according to the inclination angle and the initial speed of the unmanned aerial vehicle. The detailed estimation model is as follows:
when the unmanned aerial vehicle moves in the air, the unmanned aerial vehicle can receive air resistance opposite to the advancing direction in the horizontal direction, and in the embodiment, the mathematical model of the flight speed and the air resistance of the unmanned aerial vehicle is assumed as formula (1):
F＝ksvt(1)
wherein k is generally 2.937, s is the surface area of the unmanned aerial vehicle opposite to the air resistance, vtThe flight speed of the unmanned aerial vehicle at the current moment t.
Referring to fig. 2, a stress diagram of the drone is shown, assuming that at time T, the drone flies at an angle of tilt θ, assuming that the lift force provided by the motor of the drone is T, in order to keep the height constant, the upward component of T in the vertical direction must be mg, assuming that the component of T in the horizontal direction is mgtan θ, the resultant force in the horizontal direction is mg tan θ -F, and at this time, the velocity estimation model can be obtained as shown in equation (2):
where dt is the measurement period of the gyroscope, v0In the formula (2) in which the formula (1) is substituted for the velocity at time 0, the air resistance coefficient r is defined as ks/m, and the formula (3) can be obtained as follows:
wherein, the gtan theta is only related to the angle theta, and the inclination angle theta is smaller than that of the unmanned aerial vehicle in the flying process
So a linear process is performed, that is: g tan theta-g theta-theta, substituting formula (3), and obtaining a linear simplified model of the speed estimation model as shown in formula (4):
the velocity increment of the unmanned aerial vehicle in each measurement period can also be obtained by the formula (4) as shown in formula (5):
Δvt＝(θ-rvt-1)dt (5)
in actual flight, three euler angles representing the attitude of the unmanned aerial vehicle are a pitch angle (pitch), a roll angle (roll) and a yaw angle (yaw), and a bias angle theta is assumed to exist when the unmanned aerial vehicle is in stable hovering state in the air flight processpitch0And thetaroll0This offset angle can be recorded by the gyroscope when the unmanned aerial vehicle is suspended steadily. In the present embodiment, the body coordinate system X is represented by the subscript bbYbZbThe geographical coordinate system X is denoted by the subscript eeYeZeUnder the body coordinate, the nose direction is defined as an Xb axis, and the effective angle increment of the speed change generated by the airplane in the flying process is expressed by an equation (6):
based on the rotation matrix R will
And
converted into a geographic coordinate system to obtain
And
as shown in formula (7):
wherein, thetapitch，θrollAnd thetayawCan be calculated from gyroscope measurements.
Based on the equation (5), the speed increment in dt time under the geographic coordinate system can be obtained as the equation (8):
therefore, the estimation formula of the speed under the geographic coordinate system can be obtained as the formula (9):
Further, in the above analysis process, S13 specifically includes the following steps:
calculating an effective angle increment delta theta of the attitude angle of the unmanned aerial vehicle according to the Euler angle of the unmanned aerial vehicle;
converting the effective angle increment into an angle increment delta theta under a geographic coordinate systeme，
Calculating the estimated speed of the unmanned aerial vehicle in real time according to a speed estimation formula, wherein the speed estimation formula is as follows:
the formula (10) can be obtained from the formula (8) and the formula (9), and the derivation process is analyzed as above and is not described herein again. In the formula (10), dt is a gyro measurement period, Δ veIs the speed increment of the unmanned aerial vehicle in a measuring period under a geographic coordinate system, delta thetaeFor the effective angle increment of the unmanned aerial vehicle in the geographic coordinate system, which causes the speed change in each measurement period,
the estimated speed of the unmanned aerial vehicle at the time t under the geographic coordinate system is obtained, when t is 0,
namely the initial speed of the unmanned aerial vehicle, and r is the air resistance coefficient in the braking process.
Further, it can be determined from equation (6) that calculating the effective angle increment Δ θ of the attitude angle of the drone according to the euler angle of the drone includes the steps of:
determining an offset Euler angle when the unmanned aerial vehicle is in a stable hovering state;
and calculating to obtain the effective angle increment delta theta according to the Euler angle and the bias Euler angle.
The offset Euler angle refers to an Euler angle existing when the unmanned aerial vehicle is in stable hovering state in the air flight process, and the offset angle theta and the pitch angle can be recorded as an offset angle thetapitch0And thetaroll0This offset angle can be recorded by the gyroscope when the unmanned aerial vehicle is suspended steadily. In the invention, the change of the deflection angle and the pitch angle of the unmanned aerial vehicle can bring the change of the speed when flying, so the effective angle increment can be obtained by the increment of the deflection angle and the pitch angle.
S20, when a braking instruction is received, taking the estimated speed at the moment as a braking speed;
specifically, after receiving the braking instruction, the unmanned aerial vehicle enters a braking stage, and the speed when receiving the braking instruction is the initial speed at which the braking stage starts, namely the braking speed.
In a specific scenario of another embodiment of the present invention, the braking instruction may be triggered by the end of a lever-hitting operation by a user, and in a conventional operation of the existing unmanned aerial vehicle, if the lever-hitting operation by the user is ended, it indicates that the unmanned aerial vehicle needs to start braking. When the lever-hitting operation of the user is detected to be finished, the unmanned aerial vehicle enters a braking mode.
S30, controlling the unmanned aerial vehicle to start initial braking according to the braking speed until the speed of the unmanned aerial vehicle falls into a preset range, and finishing the initial braking;
and S40, after the initial braking is finished, controlling the unmanned aerial vehicle to perform secondary braking through the optical flow sensor so as to achieve a stable hovering state.
Specifically, braking stage, need provide a power opposite with speed direction for unmanned aerial vehicle, unmanned aerial vehicle just can step-by-step slow down to the steady state that hovers like this, consequently, need adjust unmanned aerial vehicle's attitude angle, make the lift can produce the component in the opposite direction in speed direction, make unmanned aerial vehicle can reach the stability of hovering within a certain time, we call the attitude angle that unmanned aerial vehicle need adjust in braking stage be braking attitude angle, required time is braking time, generally, braking parameters includes braking attitude angle and braking time. The braking attitude angle and the braking time can be calculated from the braking speed, and it can be understood that since the braking speed in the initial stage is an estimated speed, the braking attitude angle and the braking time obtained by estimating the speed are also only braking parameters under the estimated model.
In the embodiment of the invention, the braking speed and the braking parameters of the unmanned aerial vehicle in the initial braking stage are determined by the estimated speed, so that when the unmanned aerial vehicle actually flies, the state of the unmanned aerial vehicle does not necessarily reach a stable hovering state when the initial braking is finished, but because the initial braking control is carried out by the estimated speed, the speed of the unmanned aerial vehicle can be at least reduced to a range which can be accurately measured by the optical flow sensor, therefore, in the initial braking stage, as long as the speed of the unmanned aerial vehicle is reduced to a range which can be accurately measured by the optical flow sensor from a high-speed flying state (the preset range is determined by the optical flow sensor equipped with the unmanned aerial vehicle), the initial braking stage can be finished, and then the optical flow sensor carries out secondary braking on the unmanned aerial vehicle according to the real-time.
As described above, in the present embodiment, step S30 includes the following steps S31-S32:
s31, calculating a braking parameter required by the estimated speed of the unmanned aerial vehicle to reach a preset threshold value according to the braking speed; the braking parameters comprise braking time, and the preset threshold is in the preset range;
and S32, controlling the unmanned aerial vehicle to start initial braking according to the braking parameters, and ending the initial braking when the braking time is up.
In particular, the measurable range of the speed optical flow sensor of the unmanned aerial vehicle in the initial braking stage can comprise various conditions. For example, the braking parameter required for the estimated speed of the drone to reach a preset threshold is calculated using a speed estimation model, where the preset threshold is a smaller value within the measurable range of the optical flow sensor, for example, the measurable range is [0, a ], and any value of [0, a/2] can be selected. Like this, in braking time, unmanned aerial vehicle carries out initial braking, and braking time reaches then, can think that the speed of unmanned aerial vehicle this moment has certainly reached light stream sensor measurable range, and follow-up accessible light stream sensor carries out secondary braking.
In other embodiments, step S30 may also include the following steps S33-S35:
s33, calculating according to the braking speed and a braking estimation formula to obtain braking parameters required when the estimated speed of the unmanned aerial vehicle is zero;
s34, controlling the unmanned aerial vehicle to start initial braking according to the braking parameters;
s35, when a preset time is left after the braking time is over, detecting the speed of the unmanned aerial vehicle through an optical flow sensor, and if the detected speed is within the preset range, ending the initial braking
Specifically, make unmanned aerial vehicle speed light stream sensor measurable range at the initial braking stage, can directly calculate the braking parameter that unmanned aerial vehicle estimated speed reaches zero hour, predetermine the length of time before the braking time ends, directly listen unmanned aerial vehicle speed through light stream sensor, if listen successfully, explain this moment that unmanned aerial vehicle speed has fallen to light stream sensor measurable range, at this moment, can end initial braking. In this case, the braking parameter includes a preset time period in addition to the calculated braking time. It will be appreciated that if the drone speed is not detectable by the optical flow sensor for a predetermined period of time before the drone braking time ends, the initial braking may continue, followed by detection at a later time (e.g. every predetermined time), and ending the braking once the drone speed is detected.
Further, in this embodiment, S33 specifically includes the following steps:
converting braking speed into braking amount under machine body coordinate system
Calculating a braking attitude angle and braking time according to a braking estimation formula, wherein the braking estimation formula is as follows:
where α is the braking attitude angle, T is the braking time, and C is the time constant.
The brake formula is determined as follows:
from the estimation model, the speed at the start of braking is
Velocity conversion to body coordinates
Assume that the braking attitude angle at the time of braking is α (excluding the offset attitude angle θ)pitch0And thetaroll0) Assuming brakingThe operation is finished when the operation is finished, namely the speed of the unmanned aerial vehicle is reduced to zero, the actual speed of the aircraft is 0, and the attitude of the aircraft is recovered to the attitude angle under the stable hovering state, namely thetapitch0And thetaroll0Defining the time constant C, then for the braking attitude angle, there is the following equation (11):
then, the equation (5) can be used to obtain the coordinate system of the body
Here, the number of the first and second electrodes,
as mentioned above, during braking, when the speed of the drone decreases to 0, ignoring the air resistance, the following equation (12) can be obtained:
by combining the formula (11) and the formula (12), the following formula of the braking attitude angle and the braking time can be obtained
(13)：
It is understood that in the present invention, α refers to the attitude angle of the drone when braking away from the hover steady state, which brings the component of the lift force of the drone in the direction of advance of the drone opposite to the speed, thus gradually stopping the drone.
In various embodiments, the braking attitude angle may include one or both of a pitch angle and a roll angle.
For the flight speed of the unmanned aerial vehicle, as in equation (13)
At YbThe axial component being zero, i.e.
When the angle is determined, α is the pitch angle, and the angle is expressed by the formula (13)
At XbThe axial component being zero, i.e.
When the angle is equal to α, the flip angle is obtained
At XbAxis and YbIf there are components in the axes, α can be solved separately for each direction at YbAxis and YbThe component of the axis.
From equation (10) and equation (13), the accuracy that air resistance coefficient r and time constant C can influence braking attitude angle and braking time, to different unmanned aerial vehicles, can confirm corresponding r and C through debugging many times to obtain more accurate estimation model.
Further, in an embodiment, the step S32 or S34 specifically includes:
and controlling the unmanned aerial vehicle to perform initial braking at the braking attitude angle.
It can be understood that the braking parameters are calculated under the estimation model, so that the unmanned aerial vehicle can be braked by keeping the braking attitude angle in the initial braking stage when the initial braking is actually carried out. The attitude angle is kept unchanged in the braking process, the flight of the unmanned aerial vehicle can be more stable, and the speed of the unmanned aerial vehicle can be reduced to the measurable range of the optical flow sensor more quickly.
Specifically, if unmanned aerial vehicle keeps the attitude angle unchangeable in the initial braking process, when getting into the secondary braking, unmanned aerial vehicle's attitude angle also is the attitude angle when initial braking ended, like this, between twice braking, unmanned aerial vehicle's attitude angle can not take place the sudden change, but smooth transition, and speed up to unmanned aerial vehicle resumes to zero, and at this moment, unmanned aerial vehicle's attitude angle also resumes to offset attitude angle.
Further, in other embodiments, the step S32 or S34 may also include:
controlling the unmanned aerial vehicle to start initial braking by taking the braking attitude angle as an initial attitude angle; wherein the attitude angle of the drone is progressively reduced from the initial attitude angle before the initial braking is over.
It can be understood that, after the unmanned aerial vehicle braking began, unmanned aerial vehicle's speed also can progressively reduce, and at this moment, the reaction force that needs also can progressively reduce, consequently, the attitude angle also can begin from braking attitude angle in fact when unmanned aerial vehicle braking flight, progressively reduces the attitude angle, can reduce the burden of unmanned aerial vehicle motor in the braking time like this.
It is understood that, when the attitude angle is decreased step by step based on the time constant C, the attitude angle may be decreased step by step with the time constant C being a constant. That is, in other embodiments, the gradual decrease in the attitude angle of the drone from the initial attitude angle may be:
and the attitude angle of the unmanned aerial vehicle is decreased progressively from the initial attitude angle by taking a time constant C as a constant.
In this embodiment, step S40 may include the following steps:
when the initial braking is finished, if the speed of the unmanned aerial vehicle is measured to be zero through the optical flow sensor, the initial attitude of the unmanned aerial vehicle in the unmanned hovering state is directly set.
When the initial braking is finished, if the speed of the unmanned aerial vehicle is measured to be not zero through the optical flow sensor, controlling the unmanned aerial vehicle to perform secondary braking so as to achieve a hovering stable state.
Specifically, as described above, the braking speed and the braking parameters in the initial stage are obtained by estimation, and therefore, after the initial braking is finished, the actual speed of the unmanned aerial vehicle does not necessarily reach zero, and real-time detection is required through the optical flow sensor. If the initial braking is finished, the speed of the unmanned aerial vehicle is not zero, it is indicated that the braking performed under the estimation model is not enough to enable the unmanned aerial vehicle to reach the condition of entering the hovering state, at the moment, the unmanned aerial vehicle needs to be controlled to perform secondary braking again until the speed of the unmanned aerial vehicle is zero, and at the moment, the attitude angle of the unmanned aerial vehicle is the offset attitude angle.
Further, in this embodiment, in step 40, controlling the drone to perform secondary braking to reach the hover stable state includes:
and carrying out PID control on the unmanned aerial vehicle through an optical flow speed measuring sensor so as to enable the real-time speed of the unmanned aerial vehicle to reach zero and enter a hovering stable state.
In actual braking process as above, when initial braking ended, because braking speed and braking parameter are the estimation, unmanned aerial vehicle speed can not reduce to zero completely this moment, and at this moment, secondary braking can carry out PID control to unmanned aerial vehicle through the light stream sensor speed measurement, and the attitude angle change is controlled step by step, makes unmanned aerial vehicle reach the steady state of hovering.
In the invention, when the unmanned aerial vehicle performs acceleration motion and braking, the flight speed of the unmanned aerial vehicle is estimated, the unmanned aerial vehicle is controlled to perform initial braking through the estimated speed, after primary braking, if the unmanned aerial vehicle does not recover a hovering stable state, the speed of the unmanned aerial vehicle is reduced from a high speed to a measurable range of a low frame rate optical flow sensor, and then secondary braking control can be performed by the low frame rate optical flow sensor, so that the failure of the low frame rate optical flow sensor can be avoided, and a high frame rate camera or a GPS (global positioning system) is not required to be additionally added, thereby realizing the emergency braking of the unmanned aerial vehicle under lower hardware.
The second embodiment of the invention further provides an unmanned aerial vehicle brake control device. In this embodiment, the braking control device of the unmanned aerial vehicle includes a speed estimation module 31, a braking initiation module 32, an initiation braking module 33 and a secondary braking module 35.
The speed estimation module 31 is used for starting to calculate the estimated speed of the unmanned aerial vehicle in real time through the speed estimation model when receiving the acceleration instruction;
a braking initiation module 32, configured to, when a braking instruction is received, use the estimated speed at this time as a braking speed;
the initial braking module 33 is used for controlling the unmanned aerial vehicle to start initial braking according to the braking speed; when the speed of the unmanned aerial vehicle falls into a preset range, the initial braking is finished; and
and the secondary braking module 34 is used for controlling the unmanned aerial vehicle to perform secondary braking through the optical flow sensor so as to recover to a hovering stable state after the initial braking is finished.
The process of implementing the braking control method of the unmanned aerial vehicle by the braking control device of the unmanned aerial vehicle is described in detail in the foregoing, and is not described herein again.
A third embodiment of the present invention further provides a drone comprising a processor and a computer readable storage medium having a drone braking control program stored thereon, the drone braking control program being executed by the processor by the drone braking control method as described above.
It will be appreciated by those skilled in the art that the above-described preferred embodiments may be freely combined, superimposed, without conflict.
It will be understood that the embodiments described above are illustrative only and not restrictive, and that various obvious and equivalent modifications and substitutions for details described herein may be made by those skilled in the art without departing from the basic principles of the invention.
Claims (19)
1. An unmanned aerial vehicle brake control method, characterized in that the method comprises the following steps:
s10, calculating the estimated speed of the unmanned aerial vehicle in real time through a speed estimation model after receiving the acceleration instruction; the speed estimation model is used for calculating the estimated speed of the unmanned aerial vehicle at the next moment according to the initial speed and attitude angle data of the unmanned aerial vehicle at any moment;
s20, when a braking instruction is received, taking the estimated speed at the moment as a braking speed;
s30, controlling the unmanned aerial vehicle to start initial braking according to the braking speed until the speed of the unmanned aerial vehicle falls into a preset range, and finishing the initial braking; wherein, the preset range is a speed range which can be detected by the optical flow sensor;
and S40, after the initial braking is finished, controlling the unmanned aerial vehicle to perform secondary braking through the optical flow sensor so as to achieve a stable hovering state.
2. The unmanned aerial vehicle brake control method of claim 1, wherein step S10 includes:
when an acceleration instruction is received, determining the initial speed of the unmanned aerial vehicle at the moment;
acquiring unmanned aerial vehicle attitude angle data in real time;
calculating an estimated speed of the drone in real time based on the acquired attitude angle data and the initial speed.
3. The drone controlling method according to claim 1, wherein the step S30 includes the steps of:
s31, calculating a braking parameter required by the estimated speed of the unmanned aerial vehicle to reach a preset threshold value according to the braking speed; the braking parameters comprise braking time, and the preset threshold is in the preset range;
and S32, controlling the unmanned aerial vehicle to start initial braking according to the braking parameters, and ending the initial braking when the braking time is up.
4. The drone controlling method according to claim 1, wherein the step S30 includes the steps of:
s33, calculating according to the braking speed and a braking estimation formula to obtain braking parameters required when the estimated speed of the unmanned aerial vehicle is zero; the braking parameters comprise braking time and preset duration;
s34, controlling the unmanned aerial vehicle to start initial braking according to the braking parameters;
and S35, detecting the speed of the unmanned aerial vehicle through an optical flow sensor when a preset time is left after the braking time is over, and ending the initial braking if the detected speed is within the preset range.
5. The drone braking control method of any one of claims 3 or 4, wherein the braking parameters further include a braking attitude angle.
6. The drone braking control method of claim 5, wherein the braking attitude angle includes either or both of a pitch angle and a roll angle.
7. The drone braking control method of claim 5, wherein the step S32 or S34 includes:
and controlling the unmanned aerial vehicle to perform initial braking at the braking attitude angle.
8. The drone braking control method of claim 5, wherein step S32 or S34 includes:
controlling the unmanned aerial vehicle to start initial braking by taking the braking attitude angle as an initial attitude angle; wherein the attitude angle of the drone is progressively reduced from the initial attitude angle before the initial braking is over.
9. The drone braking control method of claim 2, wherein the determining the drone initial speed includes:
if the unmanned aerial vehicle is in a stable hovering state before the acceleration instruction is received, determining that the initial speed of the unmanned aerial vehicle is 0;
and if the unmanned aerial vehicle is in a hovering horizontal motion state before the acceleration instruction is received, taking the current real-time speed of the user as the initial speed.
10. The unmanned aerial vehicle brake control method of any one of claims 1-9, wherein step S40 includes:
when the initial braking is finished, if the speed of the unmanned aerial vehicle is measured to be zero through the optical flow sensor, the attitude of the unmanned aerial vehicle is directly set to be the initial attitude of the unmanned aerial vehicle in the stable unmanned hovering state.
11. The unmanned aerial vehicle brake control method of any one of claims 1-9, wherein step S40 includes:
when the initial braking is finished, if the speed of the unmanned aerial vehicle is measured to be not zero through the optical flow sensor, controlling the unmanned aerial vehicle to perform secondary braking so as to achieve a hovering stable state.
12. The drone braking control method of claim 1, wherein in step S40, the controlling the drone to perform secondary braking to reach a hover steady state includes:
and carrying out PID control on the unmanned aerial vehicle through an optical flow sensor so as to enable the real-time speed of the unmanned aerial vehicle to reach zero and enter a hovering stable state.
13. The drone braking control method of claim 2, wherein the attitude angle data includes an euler angle of the drone, and the calculating the estimated velocity of the drone in real-time based on the acquired attitude angle data and the initial velocity includes:
calculating an effective angle increment delta theta of the attitude angle of the unmanned aerial vehicle according to the Euler angle of the unmanned aerial vehicle;
converting the effective angle increment into an angle increment delta theta under a geographic coordinate systeme，
Calculating the estimated speed of the unmanned aerial vehicle in real time according to a speed estimation formula, wherein the speed estimation formula is as follows:
where dt is the gyroscope measurement period, Δ veThe speed increment, delta theta, of the unmanned aerial vehicle in the next measurement period of the geographic coordinate systemeFor the effective angle increment of the unmanned aerial vehicle in the geographic coordinate system, which causes the speed change in each measurement period,
for the estimated speed of the drone at time t in the geographic coordinate system,
and r is an air resistance coefficient in the braking process.
14. The drone braking control method of claim 13, wherein calculating the effective angle increment, Δ Θ, of the drone attitude angle as a function of the euler angle comprises:
determining an offset Euler angle when the unmanned aerial vehicle is in a stable hovering state;
and calculating to obtain the effective angle increment delta theta according to the Euler angle and the bias Euler angle.
15. The drone braking control method of claim 5, wherein the braking parameters further include a braking attitude angle, the step S33 includes:
converting the braking speed into the braking amount under the coordinate system of the machine body
Calculating a braking attitude angle and braking time according to a braking estimation formula, wherein the braking estimation formula is as follows:
where α is the braking attitude angle, T is the braking time, and C is the time constant.
16. The drone braking control method of claim 8, wherein the gradual decrease in the attitude angle of the drone from the initial attitude angle includes:
and the attitude angle of the unmanned aerial vehicle is decreased progressively from the initial attitude angle by taking a time constant C as a constant.
17. The unmanned aerial vehicle brake control method of any one of claims 1-16, wherein the acceleration command is a lever actuation and the brake command is a lever actuation termination.
18. An unmanned aerial vehicle brake control device, its characterized in that, the device includes:
the speed estimation module is used for calculating the estimated speed of the unmanned aerial vehicle in real time through the speed estimation model after receiving the acceleration instruction; the speed estimation model is used for calculating the estimated speed of the unmanned aerial vehicle at the next moment according to the initial speed and attitude angle data of the unmanned aerial vehicle at any moment;
the braking speed determining module is used for taking the estimated speed at the moment as the braking speed when a braking instruction is received;
the initial braking module is used for controlling the unmanned aerial vehicle to start initial braking according to the braking speed until the speed of the unmanned aerial vehicle falls into a preset range, and the initial braking is finished; wherein, the preset range is a speed range which can be detected by the optical flow sensor; and
and the secondary braking module is used for controlling the unmanned aerial vehicle to perform secondary braking through the optical flow sensor so as to achieve a hovering stable state after the initial braking is finished.
19. A drone, comprising a processor and a computer-readable storage medium, wherein the storage medium stores a drone brake control program that, when executed, implements a drone brake control method according to any one of claims 1-17.
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