CN111435255B - Unmanned aerial vehicle braking control method and device and unmanned aerial vehicle - Google Patents
Unmanned aerial vehicle braking control method and device and unmanned aerial vehicle Download PDFInfo
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- CN111435255B CN111435255B CN201911010316.8A CN201911010316A CN111435255B CN 111435255 B CN111435255 B CN 111435255B CN 201911010316 A CN201911010316 A CN 201911010316A CN 111435255 B CN111435255 B CN 111435255B
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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
- Y02T10/40—Engine management systems
Abstract
The invention discloses a method and a device for controlling unmanned aerial vehicle braking and an unmanned aerial vehicle. The method comprises the following steps: after receiving the 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 within a preset range, and ending the initial braking; the preset range is a speed range which can be detected by an optical flow sensor; and after the initial braking is finished, controlling the unmanned aerial vehicle to perform secondary braking through an optical flow sensor so as to reach a hovering stable state. The invention can realize the emergency braking of the unmanned aerial vehicle under high-speed flight, has lower requirement on hardware, and does not need to additionally install GPS.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicles, in particular to a method and a device for controlling the braking of an unmanned aerial vehicle and the unmanned aerial vehicle.
Background
At present, unmanned aerial vehicles are increasingly widely applied, and the importance of the unmanned aerial vehicles is increasingly highlighted in the fields of civil use, commercial use and even military use. With the increasing widespread application of unmanned aerial vehicles, the demand for unmanned aerial vehicles is increasing, but pursuing low cost and higher capability through the lowest hardware is still mainstream, especially in the situation that small unmanned aerial vehicles are popular in the general public at present. Currently, most small unmanned aerial vehicles can realize horizontal movement in a horizontal plane, for example, from flying to hovering in the horizontal plane, or from hovering to flying, speed measurement can be realized through an optical flow sensor, and the unmanned aerial vehicle is controlled to realize braking through a PID (proportion-integral-differential) algorithm. However, if the existing rotorcraft uses the optical flow speed measurement mode alone, the correct speed is measured at high speed, the frame rate of the optical flow speed measurement and the quality requirement of the algorithm are relatively high, so that a better camera is matched with an optical flow sensor with high frame rate, the system hardware requirement is increased by adopting the optical flow speed measurement with high frame rate and the better camera, and relatively large CPU resources are consumed to run the optical flow algorithm, if a general optical flow sensor with low frame rate is adopted, the optical flow speed measurement is easy to fail at high speed (the field of small unmanned aerial vehicle can be regarded as high-speed flight generally more than 6 m/s), and if GPS is adopted, the cost is increased and only outdoor condition is supported. Therefore, how to avoid failure of the low-frame-rate optical flow sensor during high-speed flight of the unmanned aerial vehicle without increasing hardware investment is a problem to be solved urgently.
Disclosure of Invention
Based on the above-mentioned situation, the main objective of the present invention is to provide a method and a device for controlling 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 above object, the present invention provides a method for controlling a robot to control a mechanism, comprising the steps of: s10, after receiving an acceleration instruction, calculating the estimated speed of the unmanned aerial vehicle in real time through a speed estimation model; 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 the 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 within a preset range, and ending the initial braking; the preset range is a speed range which can be detected by an optical flow sensor; and S40, controlling the unmanned aerial vehicle to perform secondary braking through an optical flow sensor after the initial braking is finished so as to achieve a hover stable state.
Preferably, step S10 includes: when an acceleration instruction is received, determining the initial speed of the unmanned aerial vehicle at the moment; acquiring attitude angle data of the unmanned aerial vehicle in real time; and calculating the estimated speed of the unmanned aerial vehicle in real time based on the acquired attitude angle data and the initial speed.
Preferably, step S30 comprises the steps of: s31, calculating a required braking parameter of the estimated speed of the unmanned aerial vehicle reaching a preset threshold according to the braking speed; wherein the braking parameter comprises braking time, and the preset threshold value is within the preset range; 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 comprises the steps of: s33, calculating and obtaining a braking parameter required by zero estimated speed of the unmanned aerial vehicle according to the braking speed and a braking estimation formula; 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 length is left from the end of the braking time, 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 any one or both of a pitch angle and a roll angle.
Preferably, step S32 or S34 includes: and controlling the unmanned aerial vehicle to perform initial braking at the braking attitude angle.
Preferably, step S32 or S34 includes: the braking attitude angle is taken as an initial attitude angle, and the unmanned aerial vehicle is controlled to start initial braking; wherein the attitude angle of the unmanned aerial vehicle gradually decreases from the initial attitude angle before the initial braking is finished.
Preferably, the determining the initial speed of the unmanned aerial vehicle includes: if the unmanned aerial vehicle is in a hovering stable state before receiving an acceleration instruction, 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 receiving the acceleration instruction, taking the current real-time speed of the user as an initial speed.
Preferably, step S40 includes: when the initial braking is finished, if the speed of the unmanned aerial vehicle is zero through the optical flow sensor, the gesture of the unmanned aerial vehicle is directly set to be the initial gesture when the unmanned aerial vehicle hovers in a stable 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, controlling
The unmanned aerial vehicle performs secondary braking to reach a hover stable state.
Preferably, in step S40, the controlling the unmanned aerial vehicle to perform secondary braking to reach a hover stable state includes: PID control is carried out on the unmanned aerial vehicle through an optical flow sensor, so that the real-time speed of the unmanned aerial vehicle reaches zero, and the unmanned aerial vehicle enters a hovering stable state.
Preferably, the attitude angle data includes an euler angle of the unmanned aerial vehicle, and calculating, in real time, the estimated speed of the unmanned aerial vehicle based on the acquired attitude angle data and the initial speed 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 system e 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:
wherein dt is the gyroscope measurement period, deltav e For the speed increment delta theta of the unmanned aerial vehicle in the next measurement period of the geographic coordinate system e For the effective angular increment of the drone in each measurement cycle that causes a speed change under the geographic coordinate system,for the estimated speed of the unmanned aerial vehicle at time t in the geographic coordinate system, < >>And r is the air resistance coefficient in the braking process for the initial speed of the unmanned aerial vehicle.
Preferably, calculating the effective angle increment Δθ of the attitude angle of the unmanned aerial vehicle according to the euler angle includes: determining an offset Euler angle when the unmanned aerial vehicle is in a hovering stable state; and calculating the effective angle increment delta theta according to the Euler angle and the offset Euler angle.
Preferably, the braking parameters further include a braking attitude angle, and the step S33 includes: converting the braking speed into braking quantity under a machine body coordinate systemCalculating a braking attitude angle and braking time according to a braking estimation formula, wherein the braking estimation formula is as follows:
wherein alpha is a braking attitude angle, T is braking time, and C is a time constant.
Preferably, the step of gradually decreasing the attitude angle of the unmanned aerial vehicle from the initial attitude angle includes: the attitude angle of the unmanned aerial vehicle is decreased from the initial attitude angle by taking a time constant C as a constant.
Preferably, the acceleration command is a lever operation, and the brake command is a lever end operation.
In order to achieve the above object, the present invention also provides an unmanned aerial vehicle braking control apparatus, 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 the 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 within a preset range, and the initial braking is finished; the preset range is a speed range which can be detected by an 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 after the initial braking is finished so as to achieve a hovering stable state.
In order to achieve the above object, the present invention further provides an unmanned aerial vehicle, including a processor and a computer-readable storage medium, the storage medium storing an unmanned aerial vehicle braking control program, which when executed by the processor, implements the unmanned aerial vehicle braking control method as described above.
The beneficial effects are that:
according to the unmanned aerial vehicle braking control method, under the high-speed flight condition that an optical flow sensor possibly fails, the braking speed of the unmanned aerial vehicle is directly estimated through the speed estimation model, braking parameters are calculated, the unmanned aerial vehicle is controlled to perform initial braking on the basis, conventional PID control is performed until the speed of the unmanned aerial vehicle is reduced to be within a range which can be accurately detected by the optical flow sensor, and secondary braking is performed by means of speed measurement of the optical flow sensor, so that under the condition that hardware investment is not required to be increased, even if the speed of the adopted low-frame-rate optical flow sensor fails during high-speed flight of the unmanned aerial vehicle, emergency braking during high-speed flight of the unmanned aerial vehicle can be smoothly, safely and reliably achieved.
Other advantages of the present invention will be described in the detailed description of the specific technical features and technical solutions, and those skilled in the art should understand the advantages of the technical features and technical solutions.
Drawings
Hereinafter, preferred embodiments according to the present invention will be described with reference to the accompanying drawings. In the figure:
FIG. 1 is a flow chart of a method of unmanned aerial vehicle braking control according to a preferred embodiment of the present invention;
FIG. 2 is a schematic diagram of the force applied to a unmanned aerial vehicle during movement according to a preferred embodiment of the present invention;
fig. 3 is a functional block diagram of an unmanned aerial vehicle brake control device according to a preferred embodiment of the present invention.
Detailed Description
For a more detailed description of the technical solutions of the present invention, to facilitate a further understanding of the present invention, specific embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that all of the illustrative embodiments and descriptions thereof are presented for purposes of illustration and are not intended to be a limitation on the invention.
In the invention, when the unmanned aerial vehicle is in a hovering stable state, the unmanned aerial vehicle is in a stop state on any horizontal plane, no speed exists in the horizontal direction at the moment, and the vertical direction and the horizontal direction are in a stress balance state. When the unmanned aerial vehicle is in the horizontal motion of hovering, the unmanned aerial vehicle moves leftwards and rightwards or forwards and backwards on any horizontal plane, the vertical direction height remains unchanged, the vertical direction is at a constant speed, and the unmanned aerial vehicle is in a stress balance state.
Referring to fig. 1, a flow chart of a method for controlling a robot braking control according to a first embodiment of the invention is shown. In this embodiment, the unmanned aerial vehicle brake control method includes the following steps S10 to S50:
s10, after receiving an acceleration instruction, calculating the estimated speed of the unmanned aerial vehicle in real time through a speed estimation model;
specifically, after receiving an acceleration instruction, the unmanned aerial vehicle enters an acceleration motion mode, and in the invention, the speed of the unmanned aerial vehicle generally reaches high speed after the unmanned aerial vehicle starts to accelerate in the horizontal direction, so that the possibility of failure of the low-frame-rate optical flow sensor in speed measurement is very high, or the unmanned aerial vehicle is already in braking before acceleration, and the speed of the unmanned aerial vehicle can reach high level, so that the braking control method starts to be executed as soon as the unmanned aerial vehicle enters the acceleration motion mode. At this time, the speed of the unmanned aerial vehicle is directly calculated through the speed estimation model instead of directly detecting the speed of the unmanned aerial vehicle through the optical flow sensor. In this embodiment, the speed estimation model is used to calculate 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.
In a specific scenario of other embodiments of the present invention, the acceleration instruction may be a user's operation of driving a rod, where in a conventional operation of an existing unmanned aerial vehicle, if the user performs the operation of driving a rod, it indicates that the unmanned aerial vehicle needs to enter an acceleration mode. When the user is detected to perform the rod 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 to S13:
s11, when an acceleration instruction is received, determining the initial speed of the unmanned aerial vehicle;
in the embodiment, determining the initial speed of the unmanned aerial vehicle comprises determining that the current speed of the unmanned aerial vehicle is 0 if the unmanned aerial vehicle is in a hovering stable state before receiving an acceleration instruction; and if the unmanned aerial vehicle is in a hovering horizontal motion state before receiving the acceleration instruction, taking the estimated speed at the moment as an initial speed.
Specifically, before the unmanned aerial vehicle performs acceleration movement after receiving an acceleration instruction, the unmanned aerial vehicle may be in a hovering stable state, and when the unmanned aerial vehicle receives the acceleration instruction, the unmanned aerial vehicle starts to move from a static state, and the initial speed is zero; and possibly also in a braking state, its initial speed should be an estimated speed estimated in real time, which is updated in real time.
S12, acquiring attitude angle data of the unmanned aerial vehicle in real time;
specifically, attitude angle data of the unmanned aerial vehicle can be obtained through a gyroscope, and Euler angles generated by rotation of the unmanned aerial vehicle are included. In this embodiment, the inclination angle of the unmanned aerial vehicle in flight can be determined through the euler angle acquired by the gyroscope, and is set to be 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, according to the inclination angle and the initial speed of the unmanned aerial vehicle, the estimated speed of the unmanned aerial vehicle can be estimated in real time by using the speed estimation model of the acceleration motion. The detailed estimation model is as follows:
when the unmanned aerial vehicle moves in the air, the unmanned aerial vehicle receives air resistance in the horizontal direction, which is opposite to the advancing direction, in the embodiment, the mathematical model of the unmanned aerial vehicle flight speed and the air resistance is assumed to be as shown in the formula (1):
F＝ksv t (1)
wherein k is generally 2.937, s is the surface area of the unmanned aerial vehicle opposite to the air resistance，v t The flight speed of the unmanned aerial vehicle at the current moment t.
Referring to fig. 2, a force diagram of an unmanned aerial vehicle is shown, it is assumed that the unmanned aerial vehicle flies at an angle of inclination θ at time T, it is assumed that an upward force provided by a motor of the unmanned aerial vehicle is T at this time, in order to keep the height unchanged, an upward component in a vertical direction of T must be mg, it is assumed that a component in a horizontal direction of T is mgtan θ, and a resultant force in the horizontal direction is mg tan θ—f, and at this time, a speed estimation model may be obtained as shown in equation (2):
wherein dt is the measurement period of the gyroscope, v 0 For a velocity at time 0, equation (3) can be obtained by substituting equation (1) into equation (2) and defining the air resistance coefficient r=ks/m as follows:
wherein the term gtan theta is only related to the angle theta, and the inclination angle theta is smaller than the angle theta in the flying process of the unmanned planeSo the linear processing is performed, namely: and g tan theta to g theta to theta are substituted into the formula (3), and a linear simplified model of the speed estimation model can be obtained as shown in the formula (4):
the speed increment of the unmanned aerial vehicle in each measurement period can also be obtained by the formula (4) as formula (5):
Δv t ＝(θ-rv t-1 )dt (5)
in actual flight, three Euler angles representing the attitude of the unmanned aerial vehicle are pitch angle (pitch), roll angle (roll) and yaw angle (yaw), respectively, and the unmanned aerial vehicle is assumed to fly in the airHas a bias angle theta when in hover stabilization pitch0 And theta roll0 The offset angle may be recorded by the gyroscope when the drone is hovering stable. In the present embodiment, the body coordinate system X is denoted by the subscript b b Y b Z b The geographical coordinate system X is denoted by the subscript e e Y e Z e Under the machine body coordinates, defining the machine head direction as Xb axis, and the effective angle increment of the aircraft for generating speed change in the flight process is as shown in formula (6):
based on the rotation matrix RAnd->Conversion to the geographic coordinate System gives +.>And->As formula (7):
wherein θ pitch ，θ roll θ yaw Can be calculated from gyroscope measurements.
Based on equation (5), the speed increment in dt time in the geographic coordinate system can be obtained as equation (8):
from this, an estimation formula of the velocity in the geographic coordinate system can be obtained as formula (9):
and->The final speed at time t is X e Direction and Y e The component of the direction, in->Indicating the speed at time t +.>
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 system e ，
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:
formula (10) can be derived from formulas (8) and (9), the derivation of which is analyzed as above and is not described here. In the formula (10), dt is the gyroscope measurement period, deltav e Is the speed increment delta theta of the unmanned aerial vehicle in one measurement period under the geographic coordinate system e For the effective angular increment of the drone in each measurement cycle that causes a speed change under the geographic coordinate system,for the estimated speed of the unmanned aerial vehicle at the time t under the geographic coordinate system, when t=0, the unmanned aerial vehicle is +.>The initial speed of the unmanned aerial vehicle is the initial speed, and r is the air resistance coefficient in the braking process.
Further, as can be determined from equation (6), calculating the effective angle increment Δθ of the attitude angle of the unmanned aerial vehicle according to the euler angle of the unmanned aerial vehicle includes the steps of:
determining an offset Euler angle when the unmanned aerial vehicle is in a hovering stable state;
and calculating the effective angle increment delta theta according to the Euler angle and the offset Euler angle.
The offset Euler angle refers to Euler angle existing when the unmanned aerial vehicle is in hovering stability in the air flight process, and the offset angle and the pitch angle can be recorded as offset angle theta pitch0 And theta roll0 The offset angle may be recorded by the gyroscope when the drone is hovering stable. In the invention, the change of the deflection angle and the pitch angle can bring about the change of the speed when the unmanned aerial vehicle flies, so that 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, when a braking command is received, the unmanned aerial vehicle enters a braking stage, and the speed when the braking command is received is the initial speed at which the braking stage starts, namely the braking speed.
In a specific scenario of other embodiments of the present invention, the braking instruction may be triggered by the end of the user's rod-making operation, and in the conventional operation of the existing unmanned aerial vehicle, if the end of the user's rod-making operation, it indicates that the unmanned aerial vehicle needs to start braking. And when the end of the user lever operation is detected, 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 within a preset range, and ending the initial braking;
and S40, controlling the unmanned aerial vehicle to perform secondary braking through an optical flow sensor after the initial braking is finished so as to achieve a hover stable state.
Specifically, in the braking stage, a force opposite to the speed direction needs to be provided for the unmanned aerial vehicle, so that the unmanned aerial vehicle can gradually decelerate to a hovering stable state, and therefore, the attitude angle of the unmanned aerial vehicle needs to be adjusted, so that the lifting force can generate a component in the opposite direction in the speed direction, the unmanned aerial vehicle can reach hovering stability in a certain time, the attitude angle which the unmanned aerial vehicle needs to adjust in the braking stage is called as a braking attitude angle, and the required time is braking time, and generally, the braking parameters comprise the braking attitude angle and the braking time. The braking attitude angle and the braking time can be calculated from the braking speed, and it is understood that since the braking speed is the estimated speed in the initial stage, the braking attitude angle and the braking time obtained by the estimated speed are only braking parameters under the estimated model.
In the embodiment of the invention, the unmanned aerial vehicle braking speed and braking parameters 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 hover stable state, but the speed of the unmanned aerial vehicle can be reduced to at least a range which can be accurately measured by an optical flow sensor due to the initial braking control by the estimated speed, and therefore, in the initial braking stage, the unmanned aerial vehicle can finish the initial braking stage as long as the unmanned aerial vehicle reduces the speed from a high-speed flying state to the range which can be accurately measured by the optical flow sensor (the preset range is determined by the optical flow sensor equipped by the unmanned aerial vehicle), and then the optical flow sensor carries out secondary braking according to the real-time accurate speed of the unmanned aerial vehicle, so that the unmanned aerial vehicle reaches the hover stable state.
As described above, in the present embodiment, step S30 includes the following steps S31 to S32:
s31, calculating braking parameters required by the estimated speed of the unmanned aerial vehicle to reach a preset threshold according to the braking speed; wherein the braking parameter comprises braking time, and the preset threshold value is within the preset range;
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.
Specifically, in the initial braking stage, the range of the speed optical flow sensor of the unmanned aerial vehicle can be in a plurality of conditions. For example, a braking parameter required by the estimated speed of the unmanned aerial vehicle to reach a preset threshold is calculated by using a speed estimation model, wherein the preset threshold is selected from a smaller value within a measurable range of an optical flow sensor, for example, the measurable range is [0, a ], and any value of [0, a/2] can be selected. In this way, the unmanned aerial vehicle carries out initial braking in the braking time, and when the braking time reaches, the speed of the unmanned aerial vehicle at the moment can be considered to necessarily reach the measurable range of the optical flow sensor, and the follow-up secondary braking can be carried out through the optical flow sensor.
In other embodiments, step S30 may also include the following steps S33-S35:
s33, calculating and obtaining a braking parameter required by zero estimated speed of the unmanned aerial vehicle according to the braking speed and a braking estimation formula;
s34, controlling the unmanned aerial vehicle to start initial braking according to the braking parameters;
s35, detecting the speed of the unmanned aerial vehicle through an optical flow sensor when a preset time is left from the end of the braking time, and ending the initial braking if the detected speed is within the preset range
Specifically, in the initial braking stage, the braking parameter when the estimated speed of the unmanned aerial vehicle reaches zero can be directly calculated in the measurable range of the optical flow sensor of the speed of the unmanned aerial vehicle, the speed of the unmanned aerial vehicle is directly detected through the optical flow sensor in a preset duration before the end of the braking time, and if the detection is successful, the speed of the unmanned aerial vehicle is indicated to be reduced to the measurable range of the optical flow sensor at the moment, and then the initial braking can be ended. In this case, the braking parameters include a preset duration in addition to the calculated braking time. It will be appreciated that if the speed of the drone is still undetectable by the optical flow sensor, the initial braking may continue for a predetermined period of time before the end of the drone braking time, and then be detected at a re-timing (e.g., every predetermined time), and the braking is ended once the speed of the drone is detected.
Further, in the present embodiment, S33 specifically includes the following steps:
converting braking speed into braking quantity 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:
wherein alpha is a braking attitude angle, T is braking time, and C is a time constant.
The determination process of the braking formula is specifically as follows:
from the estimation model, the speed at the start of braking isThe speed is converted into the body coordinate to obtain +.>Assuming that the braking attitude angle at the time of braking is α (excluding the offset attitude angle θ) pitch0 And theta roll0 ) Assuming that braking is completed at the end, i.e. the speed of the unmanned aircraft has been reduced to zero, the actual speed of the aircraft is 0, at which time the attitude of the aircraft should also resume to the attitude angle at hover stability, i.e. θ pitch0 And theta roll0 Defining the time constant C, for the braking attitude angle, there is the following formula (11):
then it is obtained by the formula (5) under the body coordinate systemAlso existHere, the-> As described above, when the speed of the unmanned aerial vehicle is reduced to 0 during braking, the air resistance is ignored, and the following formula (12) can be obtained:
by combining the formula (11) and the formula (12), a braking attitude angle and a braking time can be obtained as follows
(13)：
It is understood that in the present invention, α refers to an attitude angle when the unmanned aerial vehicle is braked and deviates from a hovering stable state, and a component of a lift force of the unmanned aerial vehicle in a forward direction of the unmanned aerial vehicle is opposite to a speed, so that the unmanned aerial vehicle is gradually stopped.
In various embodiments, the braking attitude angle may include one or both of a pitch angle and a roll angle.For unmanned plane flying speed, if +.>In Y b The axis component being zero, i.e->In the case where the obtained α is the pitch angle, in the case of formula (13)>At X b The axis component being zero, i.e->When the calculated α is the flip angle. If->At X b Axes and Y b The axes have components, and then each direction can be respectively solved to obtain alpha in Y b Axes and Y b Component of the axis.
From the formulas (10) and (13), the air resistance coefficient r and the time constant C can influence the accuracy of the braking attitude angle and the braking time, and for different unmanned aerial vehicles, the corresponding r and C can be determined through multiple times of debugging, so that a more accurate estimation model is obtained.
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 keep the braking attitude angle to brake in the initial braking stage when the initial braking is actually performed. The attitude angle is kept unchanged in the braking process, so that the unmanned aerial vehicle can fly more stably, and the speed of the unmanned aerial vehicle can be reduced to be within the measurable range of the optical flow sensor more quickly.
Specifically, if the attitude angle of the unmanned aerial vehicle is kept unchanged in the initial braking process, when the unmanned aerial vehicle enters the secondary braking, the attitude angle of the unmanned aerial vehicle, namely the attitude angle at the end of the initial braking, is not suddenly changed, but stably transits between the two braking processes until the speed of the unmanned aerial vehicle is restored to zero, and at the moment, the attitude angle of the unmanned aerial vehicle is also restored to the offset attitude angle.
Further, in other embodiments, step S32 or S34 may also include:
the braking attitude angle is taken as an initial attitude angle, and the unmanned aerial vehicle is controlled to start initial braking; wherein the attitude angle of the unmanned aerial vehicle gradually decreases from the initial attitude angle before the initial braking is finished.
It will be appreciated that as the unmanned aerial vehicle is braked, the speed of the unmanned aerial vehicle will also gradually decrease, and the reaction force required will also gradually decrease, so that the attitude angle of the unmanned aerial vehicle in braking flight may actually start from the braking attitude angle and gradually decrease, so that the load on the unmanned aerial vehicle motor can be reduced in the braking time.
It will be appreciated that, based on the time constant C, the attitude angle may be gradually reduced with the time constant C as a constant. That is, in other embodiments, the gradual decrease of the attitude angle of the unmanned aerial vehicle from the initial attitude angle may be:
the attitude angle of the unmanned aerial vehicle is decreased from the initial attitude angle by taking a time constant C as a constant.
In this embodiment, step S40 may include the steps of:
when the initial braking is finished, if the speed of the unmanned aerial vehicle is zero through the optical flow sensor, the initial gesture when the unmanned aerial vehicle gesture is in an unmanned hovering state is directly set.
And when the initial braking is finished, if the speed of the unmanned aerial vehicle is measured by the optical flow sensor to be not zero, 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 both obtained through estimation, so that the actual speed of the unmanned aerial vehicle is not necessarily zero after the initial braking is finished, real-time detection is required through the optical flow sensor, if the speed of the unmanned aerial vehicle just reaches zero at this time, this indicates that the unmanned aerial vehicle has reached the condition of entering the hovering state at this time, the initial posture when the posture of the unmanned aerial vehicle is the hovering state is set, that is, the posture angle of the unmanned aerial vehicle is set as the offset posture angle, and braking is not required. If the speed of the unmanned aerial vehicle is not zero after the initial braking is finished, the fact that the braking performed under the estimation model is insufficient to enable the unmanned aerial vehicle to reach the condition of entering a hovering state is indicated, at this time, 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 this time, the attitude angle of the unmanned aerial vehicle is an offset attitude angle.
Further, in the present embodiment, in step 40, controlling the unmanned aerial vehicle to perform the secondary braking to reach the hover stable state includes:
PID control is carried out on the unmanned aerial vehicle through the optical flow speed measuring sensor, so that the real-time speed of the unmanned aerial vehicle reaches zero, and the unmanned aerial vehicle enters a hovering stable state.
In the actual braking process, when the initial braking is finished, as the braking speed and the braking parameters are estimated, the speed of the unmanned aerial vehicle can not be completely reduced to zero at the moment, the secondary braking can carry out PID control on the unmanned aerial vehicle through the speed measurement of the optical flow sensor, and the attitude angle change is controlled gradually, so that the unmanned aerial vehicle reaches a hovering stable state.
In the invention, when the unmanned aerial vehicle accelerates and brakes, the flying speed of the unmanned aerial vehicle is estimated, the unmanned aerial vehicle is controlled to initially brake through the estimated speed, after primary braking, if the unmanned aerial vehicle does not recover the hovering stable state, the speed of the unmanned aerial vehicle is reduced from high speed to the range which can be measured by the low-frame-rate optical flow sensor, and at the moment, the low-frame-rate optical flow sensor can perform secondary braking control, thereby avoiding the failure of the low-frame-rate optical flow sensor, and realizing the emergency braking of the unmanned aerial vehicle under lower hardware without additionally adding a high-frame-rate camera or GPS.
The second embodiment of the present invention further provides an unmanned aerial vehicle braking control device. In the present embodiment, the unmanned aerial vehicle brake control apparatus includes a speed estimation module 31, a brake initiation module 32, an initiation brake module 33, and a secondary brake module 35.
The speed estimation module 31 is configured to start calculating an estimated speed of the unmanned aerial vehicle in real time through a speed estimation model when an acceleration instruction is received;
a braking initiation module 32, configured to take the estimated speed at the time as a braking speed when a braking instruction is received;
an initial braking module 33, configured to control the unmanned aerial vehicle to start initial braking according to the braking speed; when the speed of the unmanned aerial vehicle falls within 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 after the initial braking is finished so as to recover to a hovering stable state.
The process of implementing the unmanned aerial vehicle brake control method by the unmanned aerial vehicle brake control device is described in detail above and will not be repeated here.
The third embodiment of the present invention further provides an unmanned aerial vehicle including a processor and a computer-readable storage medium storing an unmanned aerial vehicle braking control program that is executed by the processor to perform the unmanned aerial vehicle braking control method as described above.
Those skilled in the art will appreciate that the above-described preferred embodiments can be freely combined and stacked without conflict.
It will be understood that the above-described embodiments are merely illustrative and not restrictive, and that all obvious or equivalent modifications and substitutions to the details given above may be made by those skilled in the art without departing from the underlying principles of the invention, are intended to be included within the scope of the appended claims.
Claims (17)
1. A method of unmanned aerial vehicle control, the method comprising the steps of:
s10, after an acceleration instruction is received, determining the initial speed of the unmanned aerial vehicle at the moment, acquiring attitude angle data of the unmanned aerial vehicle in real time, and calculating the estimated speed of the unmanned aerial vehicle in real time based on the acquired attitude angle data and the initial speed, wherein the attitude angle data comprises Euler angles of the unmanned aerial vehicle, and calculating the estimated speed of the unmanned aerial vehicle in real time based on the acquired attitude angle data and the initial speed comprises 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 system e ，
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:
wherein dt is the gyroscope measurement period, deltav e For the speed increment delta theta of the unmanned aerial vehicle in the next measurement period of the geographic coordinate system e For the effective angular increment of the drone in each measurement cycle that causes a speed change under the geographic coordinate system,for the estimated speed of the unmanned aerial vehicle at time t in the geographic coordinate system, < >>R is the air resistance coefficient in the braking process for the initial speed of the unmanned aerial vehicle;
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 within a preset range, and ending the initial braking; the preset range is a speed range which can be detected by an optical flow sensor;
and S40, controlling the unmanned aerial vehicle to perform secondary braking through an optical flow sensor after the initial braking is finished so as to achieve a hover stable state.
2. The unmanned aerial vehicle brake control method according to claim 1, wherein step S30 comprises the steps of:
s31, calculating braking parameters required by the estimated speed of the unmanned aerial vehicle to reach a preset threshold according to the braking speed; wherein the braking parameter comprises braking time, and the preset threshold value is within the preset range;
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.
3. The unmanned aerial vehicle brake control method according to claim 1, wherein step S30 comprises the steps of:
s33, calculating and obtaining a braking parameter required by zero estimated speed of the unmanned aerial vehicle according to the braking speed and a braking estimation formula; 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 length is left from the end of the braking time, and ending the initial braking if the detected speed is within the preset range.
4. A method of unmanned aerial vehicle braking control as claimed in claim 2 or claim 3, wherein the braking parameters further comprise a braking attitude angle.
5. The unmanned aerial vehicle braking control method of claim 4, wherein the braking attitude angle comprises either or both of a pitch angle and a roll angle.
6. The unmanned aerial vehicle brake control method of claim 4, wherein step S32 or S34 comprises:
and controlling the unmanned aerial vehicle to perform initial braking at the braking attitude angle.
7. The unmanned aerial vehicle brake control method according to claim 4, wherein step S32 or S34 comprises:
the braking attitude angle is taken as an initial attitude angle, and the unmanned aerial vehicle is controlled to start initial braking; wherein the attitude angle of the unmanned aerial vehicle gradually decreases from the initial attitude angle before the initial braking is finished.
8. The unmanned aerial vehicle braking control method of claim 1, wherein the determining the initial speed of the unmanned aerial vehicle comprises:
if the unmanned aerial vehicle is in a hovering stable state before receiving an acceleration instruction, 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 receiving the acceleration instruction, taking the current real-time speed of the user as an initial speed.
9. The unmanned aerial vehicle brake control method according to claim 1, wherein step S40 comprises:
when the initial braking is finished, if the speed of the unmanned aerial vehicle is zero through the optical flow sensor, the gesture of the unmanned aerial vehicle is directly set to be the initial gesture when the unmanned aerial vehicle hovers in a stable state.
10. The unmanned aerial vehicle brake control method according to claim 1, wherein step S40 comprises:
and when the initial braking is finished, if the speed of the unmanned aerial vehicle is measured by the optical flow sensor to be not zero, controlling the unmanned aerial vehicle to perform secondary braking so as to achieve a hovering stable state.
11. The unmanned aerial vehicle braking control method of claim 1, wherein in step S40, the controlling the unmanned aerial vehicle to perform a secondary braking to reach a hover steady state comprises:
PID control is carried out on the unmanned aerial vehicle through an optical flow sensor, so that the real-time speed of the unmanned aerial vehicle reaches zero, and the unmanned aerial vehicle enters a hovering stable state.
12. The unmanned aerial vehicle braking control method of claim 1, wherein calculating an effective angle delta Δθ for the unmanned aerial vehicle attitude angle as a function of the euler angle comprises:
determining an offset Euler angle when the unmanned aerial vehicle is in a hovering stable state;
and calculating the effective angle increment delta theta according to the Euler angle and the offset Euler angle.
13. A method of controlling a robot brake according to claim 3, wherein the braking parameters further include a braking attitude angle, and the step S33 includes:
converting the braking speed into braking quantity under a 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:
wherein alpha is a braking attitude angle, T is braking time, and C is a time constant.
14. The unmanned aerial vehicle braking control method of claim 7, wherein the gradual decrease in attitude angle of the unmanned aerial vehicle from the initial attitude angle comprises:
the attitude angle of the unmanned aerial vehicle is decreased from the initial attitude angle by taking a time constant C as a constant.
15. The unmanned aerial vehicle brake control method according to claim 1, wherein the acceleration instruction is a lever operation, and the brake instruction is a lever end operation.
16. An unmanned aerial vehicle brake control apparatus, the apparatus comprising:
the speed estimation module is configured to determine an initial speed of the unmanned aerial vehicle at this time after receiving an acceleration instruction, acquire attitude angle data of the unmanned aerial vehicle in real time, calculate an estimated speed of the unmanned aerial vehicle in real time based on the acquired attitude angle data and the initial speed, the attitude angle data include euler angles of the unmanned aerial vehicle, and calculate the estimated speed of the unmanned aerial vehicle in real time based on the acquired attitude angle data and the initial speed 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 system e ，
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:
wherein dt is the gyroscope measurement period, deltav e For the speed increment delta theta of the unmanned aerial vehicle in the next measurement period of the geographic coordinate system e For the effective angular increment of the drone in each measurement cycle that causes a speed change under the geographic coordinate system,for the estimated speed of the unmanned aerial vehicle at time t in the geographic coordinate system, < >>R is the air resistance coefficient in the braking process for the initial speed of the unmanned aerial vehicle;
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 within a preset range, and the initial braking is finished; the preset range is a speed range which can be detected by an 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 after the initial braking is finished so as to achieve a hovering stable state.
17. A drone comprising a processor and a computer readable storage medium, wherein the storage medium stores a drone braking control program that when executed implements the drone braking control method of any one of claims 1-15.
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