CN111752295B - Unmanned aerial vehicle flight trajectory planning method and related device - Google Patents
Unmanned aerial vehicle flight trajectory planning method and related device Download PDFInfo
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- CN111752295B CN111752295B CN201910798538.4A CN201910798538A CN111752295B CN 111752295 B CN111752295 B CN 111752295B CN 201910798538 A CN201910798538 A CN 201910798538A CN 111752295 B CN111752295 B CN 111752295B
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Abstract
The embodiment of the invention provides a flight path planning method and a related device for an unmanned aerial vehicle, and relates to the field of unmanned aerial vehicle control. The flight state set is generated according to the flight state of the unmanned aerial vehicle track starting point and the preset flight variable, the smooth track set is determined according to the flight data of the unmanned aerial vehicle track starting point, the plurality of estimated flight states and the preset flight time, and then the smooth track with the minimum power consumption is taken as the flight track from the smooth track set so that the unmanned aerial vehicle flies along the flight track, so that the smooth flight track with the minimum power consumption is generated, and the unmanned aerial vehicle can efficiently complete the operation task.
Description
Technical Field
The invention relates to the field of unmanned aerial vehicle control, in particular to an unmanned aerial vehicle flight path planning method and a related device.
Background
With the progress of the control technology of Unmanned Aerial Vehicles (UAVs), the functions of the Unmanned Aerial vehicles are more and more perfect, the application fields are more and more extensive, and the operation scenes are more and more complicated. Under different operation scenes, the unmanned aerial vehicle usually operates according to different flight trajectories when executing operation tasks.
At present, the flight path planning method of the unmanned aerial vehicle is simple, the flight path actually generated by the unmanned aerial vehicle is not smooth, the unmanned aerial vehicle is easy to fly unsmoothly during operation, and a large amount of time is consumed in the process of controlling the flight. In addition, the trajectory generated by the existing unmanned aerial vehicle flight trajectory planning method is often not the optimal flight trajectory, so that the unmanned aerial vehicle cannot efficiently complete the operation task.
Disclosure of Invention
The invention aims to provide a flight path planning method and a related device for an unmanned aerial vehicle, which can generate a smooth flight path with minimum power consumption so that the unmanned aerial vehicle can efficiently complete an operation task.
Embodiments of the invention may be implemented as follows:
in a first aspect, an embodiment of the present invention provides a method for planning a flight trajectory of an unmanned aerial vehicle, including:
generating a flight state set according to the flight state of the unmanned aerial vehicle track starting point and a preset flight variable, wherein the flight state set comprises a plurality of estimated flight states;
determining a smooth track set according to the flight data of the unmanned aerial vehicle track starting point, the plurality of estimated flight states and preset flight time, wherein the smooth track set comprises a plurality of smooth tracks;
determining a smooth track with the minimum power consumption in the plurality of smooth tracks as a flight track so that the unmanned aerial vehicle flies along the flight track.
In a second aspect, an embodiment of the present invention provides an unmanned aerial vehicle flight trajectory planning apparatus, including:
the estimation module is used for generating a flight state set according to the flight state of the unmanned aerial vehicle track starting point and a preset flight variable, wherein the flight state set comprises a plurality of estimated flight states;
the track generation module is used for determining a smooth track set according to the flight data of the unmanned aerial vehicle track starting point, the plurality of estimated flight states and the preset flight time, wherein the smooth track set comprises a plurality of smooth tracks;
and the track determining module is used for determining a smooth track with the minimum power consumption in the plurality of smooth tracks as a flight track so that the unmanned aerial vehicle flies along the flight track.
In a third aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements a method for planning a flight trajectory of an unmanned aerial vehicle according to any one of the foregoing embodiments.
In a fourth aspect, an embodiment of the present invention provides an unmanned aerial vehicle control apparatus, including a processor and a memory, where the memory stores machine executable instructions executable by the processor, and the processor is configured to execute the machine executable instructions to implement the unmanned aerial vehicle flight trajectory planning method according to any one of the foregoing embodiments.
In a fifth aspect, an embodiment of the present invention provides an unmanned aerial vehicle, including:
a body;
the power equipment is arranged on the machine body and used for providing power for the unmanned aerial vehicle;
and a drone control device comprising a processor and a memory, the memory storing machine executable instructions executable by the processor, the processor for executing the machine executable instructions to implement the drone flight trajectory planning method of any one of the preceding embodiments.
The beneficial effects of the embodiment of the invention include, for example:
according to the unmanned aerial vehicle flight path planning method and the related device, the flight state set is generated according to the flight state of the unmanned aerial vehicle track starting point and the preset flight variable, the smooth track set is determined according to the flight data of the unmanned aerial vehicle track starting point, the plurality of estimated flight states and the preset flight time, and then the smooth track with the minimum power consumption is taken as the flight track from the smooth track set, so that the unmanned aerial vehicle flies along the flight track, the generation of the smooth flight track with the minimum power consumption is realized, and the unmanned aerial vehicle can efficiently complete the operation task.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 shows a schematic of the trajectory of a "bow course".
Fig. 2 shows a flowchart of a method for planning a flight trajectory of an unmanned aerial vehicle according to an embodiment of the present application.
FIG. 3 is a schematic diagram of the re-planned trajectory of the "arcade" shown in FIG. 1.
Fig. 4 shows a schematic diagram of a possible implementation scenario.
Fig. 5 shows a functional block diagram of an unmanned aerial vehicle flight trajectory planning device provided in an embodiment of the present application.
Fig. 6 shows a block diagram of an unmanned aerial vehicle control device provided in an embodiment of the present application.
Fig. 7 shows a structural block diagram of the unmanned aerial vehicle provided in the embodiment of the present application.
Icon: 100-unmanned aerial vehicle; 110-body; 120-a power plant; 130-drone controlling devices; 131-a memory; 132-a communication interface; 133-a processor; 134-bus; 200-lane; 210-a first leg; 220-second leg; 230-third leg; 300-unmanned aerial vehicle flight path planning device; 310-a prediction module; 320-a trajectory generation module; 330-trajectory determination module.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
It should be noted that the features of the embodiments of the present invention may be combined with each other without conflict.
Along with the development of the unmanned aerial vehicle technology, the functions of the unmanned aerial vehicle are more and more perfect, the application field of the unmanned aerial vehicle is more and more extensive, and the operation scene is more and more complicated. Under different operation scenes, the unmanned aerial vehicle usually operates according to different flight trajectories when executing operation tasks.
The current unmanned aerial vehicle flight path planning method is simple, the flight path actually generated by the method is not smooth, the unmanned aerial vehicle is easy to fly unsmoothly during operation, and a large amount of time is consumed in the flight control process. In addition, the trajectory generated by the existing unmanned aerial vehicle flight trajectory planning method is often not the optimal flight trajectory, so that the unmanned aerial vehicle cannot efficiently complete the operation task. For example, the flight trajectory of the current plant protection unmanned aerial vehicle during operation is usually a "bow course" (as shown in fig. 1), and because the corners of the "bow course" are not smooth, when the plant protection unmanned aerial vehicle flies along the "bow course", a great amount of time is consumed to control the flight attitude to adapt to the course every time the plant protection unmanned aerial vehicle passes through one corner, which may cause the plant protection unmanned aerial vehicle to be unable to efficiently complete the operation task.
Based on the above problems, the present embodiment provides a method for planning a flight trajectory of an unmanned aerial vehicle, which can generate a smooth flight trajectory with the minimum power consumption, so that the unmanned aerial vehicle efficiently completes an operation task, and the following details are described.
Referring to fig. 2, fig. 2 shows a flowchart of a method for planning a flight trajectory of an unmanned aerial vehicle according to an embodiment of the present application. The unmanned aerial vehicle flight path planning method can be applied to an unmanned aerial vehicle, and comprises the following steps:
s100, generating a flight state set according to the flight state of the unmanned aerial vehicle track starting point and a preset flight variable, wherein the flight state set comprises a plurality of estimated flight states.
In this embodiment, the starting point of the trajectory of the drone may be the current position point of the drone or a starting point preset in the three-dimensional map space. Specifically, the drone may detect a surrounding environment, generate a three-dimensional map according to the detected surrounding environment, and convert the three-dimensional map into the three-dimensional map space with spatial distance information according to a preset conversion rule, for example, convert the three-dimensional map into an Euclidean three-dimensional map according to an Euclidean Distance Transform (EDT). Optionally, load on the unmanned aerial vehicle and carry the machine and carry the sensor, unmanned aerial vehicle can survey the surrounding environment through carrying the sensor.
The flight state of the trajectory starting point of the drone represents a physical quantity of the drone at the trajectory starting point, and may be, for example, acceleration or velocity information of the trajectory starting point of the drone. The preset flight variable characterizes a physical quantity acting on the drone, which may be, for example, a preset acceleration increment or a preset speed increment. It is understood that, since the flight state represents a physical quantity of the drone at the start of the trajectory and the preset flight variable represents a physical quantity acting on the drone, the set of flight states may represent a physical quantity (e.g., acceleration, velocity, force, etc.) acting on the drone.
Optionally, when the flight state set is generated according to the flight state of the unmanned aerial vehicle trajectory starting point and the preset flight variables, the preset flight variables and each constant in the set including the plurality of constants may be operated according to the preset calculation formula to obtain the preset flight variable set, and the flight variable set and the flight state are operated according to the preset calculation formula to obtain the flight state set. The preset calculation formula may be determined according to an actual application scenario, and the specific implementation manner of the preset calculation formula is not limited in the embodiment of the present application.
It should be noted that, when the starting point of the trajectory of the drone is a preset starting point in the three-dimensional map space, the flight state may be acceleration or speed information of the preset starting point in the three-dimensional map space of the drone. The acceleration or speed information of the preset starting point can be prestored for the unmanned aerial vehicle, for example, when the unmanned aerial vehicle plans a route in a three-dimensional map space, the acceleration or speed information of a point on the route can be recorded at the same time, and at this moment, the unmanned aerial vehicle can select any point from the route as the trajectory starting point of the unmanned aerial vehicle.
In a possible implementation, the flight state may include acceleration, the preset flight variable includes a preset acceleration increment, and S100 specifically includes: and generating a flight acceleration set as a flight state set according to the acceleration and the preset acceleration increment. The flight acceleration set comprises a plurality of flight accelerations, and the flight accelerations satisfy the following formula:
wherein, Delta a is a preset acceleration increment, ax、ay、azComponents of acceleration in different directions, kx、ky、kzAre any constant in a preset interval,
are the components of the flight acceleration in different directions.
In this embodiment, since the drone may detect a surrounding environment, generate a three-dimensional map according to the detected surrounding environment, and convert the three-dimensional map into the three-dimensional map space with spatial distance information according to a preset conversion rule, the acceleration included in the flight state may have components in different directions, such as the above-mentioned ax、ay、az(i.e. a)x、ay、azConstituting acceleration), the flight acceleration may have components in different directions, e.g. as described above
(i.e. the
Constituting the flight acceleration). k is a radical ofx、ky、kzAre independent of each other, e.g. when the predetermined interval is [ -10, 10 [)]When k isxAfter taking [ -10, 10 ]]At any constant of (1), kyAnd kzAll can be taken over [ -10, 10 [)]And, k isx、ky、kzAre all any constant within a predetermined interval, and k isx、ky、kzThere may be multiple sets of different values.
Since each flight acceleration satisfies the formula:
and k isx、ky、kzTherefore, when the flight acceleration is generated according to the acceleration and the preset acceleration increment, a plurality of different flight accelerations can be generated to serve as the flight acceleration set. In other words, according to kx、ky、kzAn array set can be obtained, each element in the array set comprises three numbers in a preset interval, all elements in the array set comprise the combination of any three constants in the preset interval, and when the flight acceleration set is generated according to the acceleration and the preset acceleration increment to serve as the flight state set, the flight acceleration set can be firstly generated according to the preset acceleration increment and the array set (according to k)x、ky、kzObtained) generating a preset acceleration increment set, and then generating a flight acceleration set according to the preset acceleration increment set and the acceleration as the flight state set. It will be appreciated that in order to reduce the amount of computation, kx、ky、kzMay be any constant in an arithmetic series in a preset interval (i.e. according to k)x、ky、kzAll elements of the resulting array set include a combination of any three constants in an arithmetic series in a predetermined interval), for example, when the predetermined interval is [ -10, 10 [)]And when an arithmetic mean of the predetermined interval is an integer of-10 to 10, kx、ky、kzMay be any constant of the series of arithmetic differences.
In another possible embodiment, the flight state includes speed information of a starting point of the trajectory, the preset flight variable includes a preset speed increment, and S110 specifically includes: generating a flight speed set as a flight state set according to the speed information and a preset speed increment; the set of airspeeds includes a plurality of airspeeds, and the airspeeds satisfy the following formula:
where Δ v is a predetermined speed increment, vx、vy、vzFor the components of the velocity information in different directions, kx、ky、kzAre any constant in a preset interval,
are the components of the flight velocity in different directions.
In this embodiment, since the drone may detect a surrounding environment, generate a three-dimensional map according to the detected surrounding environment, and convert the three-dimensional map into the three-dimensional map space with spatial distance information according to a preset conversion rule, the speed information included in the flight status may have components in different directions, such as the above-mentioned vx、vy、vz(i.e., v)x、vy、vzConstituting velocity information), the flight velocity may have components in different directions, e.g. as described above
(i.e. the
Constituting the flying speed). k is a radical ofx、ky、kzAre independent of each other, e.g. when the predetermined interval is [ -10, 10 [)]When k isxAfter taking [ -10, 10 ]]At any constant of (1), kyAnd kzAll can be taken over [ -10, 10 [)]And, k isx、ky、kzAre all any constant within a predetermined interval, and k isx、ky、kzThere may be multiple sets of different values.
Since each flight speed satisfies the formula:
and k isx、ky、kzTherefore, when the flying speed is generated according to the speed information and the preset speed increment, a plurality of different flying speeds can be generated to serve as the flying acceleration set. In other words, according to kx、ky、kzAn array set can be obtained, each element in the array set comprises three numbers in a preset interval, all elements in the array set comprise the combination of any three constants in the preset interval, and when the flight speed set is generated as the flight state set according to the speed information and the preset speed increment, the flight speed set can be firstly generated according to the preset speed increment and the array set (according to k)x、ky、kzObtained) generating a preset speed increment set, and then generating a flying speed set according to the preset speed increment set and the speed information as the flying state set. It will be appreciated that in order to reduce the amount of computation, kx、ky、kzMay be any constant in an arithmetic series in a preset interval (i.e. according to k)x、ky、kzAll elements of the resulting array set include a combination of any three constants in an arithmetic series in a predetermined interval), for example, when the predetermined interval is [ -10, 10 [)]And when an arithmetic mean of the predetermined interval is an integer of-10 to 10, kx、ky、kzMay be any constant of the series of arithmetic differences.
And S110, determining a smooth track set according to the flight data of the unmanned aerial vehicle track starting point, a plurality of estimated flight states and preset flight time, wherein the smooth track set comprises a plurality of smooth tracks.
In this embodiment, the flight data of the trajectory start point of the drone may be position information or speed information of the trajectory start point. Since the set of flight states may characterize the physical quantities (e.g. acceleration, velocity, effort, etc.) acting on the drone, the set of trajectories obtained by computing the flight data with each of the plurality of estimated flight states based on the preset flight time is naturally smooth. For example, when the flight data is position information and speed information, the position information and the speed information may be calculated with each flight state of the plurality of estimated flight states based on the preset flight time, so as to obtain a smooth trajectory set.
When the S100 is a set of flight accelerations generated according to the accelerations and the preset acceleration increments as a set of flight states, the flight data includes position information and velocity information of a track start point, and the S110 specifically includes: and determining a smooth track set according to the position information, the speed information, the preset flight time and the flight acceleration set.
In this embodiment, a smooth trajectory may be calculated according to any flight acceleration in the set of the position information, the speed information, the preset flight time, and the flight acceleration of the drone at the start of the trajectory. The maximum flying speed of the unmanned aerial vehicle is also set, and when the flying speed with track points in the smooth track reaches the maximum flying speed, the unmanned aerial vehicle can fly at a constant speed at the maximum flying speed on the track behind the track points in the smooth track.
When S100 is a set of flight speeds generated according to the speed information and the preset speed increment as a set of flight states, the flight data includes position information of a track start point, and S110 specifically includes: and determining a smooth track set according to the position information, the preset flight time and the flight speed set.
In this embodiment, a smooth trajectory may be calculated according to the position information of the drone at the start of the trajectory, the preset flight time, and any flight speed in the set of flight speeds. The maximum flying speed of the unmanned aerial vehicle is also set, and when the flying speed with track points in the smooth track reaches the maximum flying speed, the unmanned aerial vehicle can fly at a constant speed at the maximum flying speed on the track behind the track points in the smooth track.
And S120, determining the smooth track with the minimum power consumption in the plurality of smooth tracks as a flight track so that the unmanned aerial vehicle flies along the flight track.
In this embodiment, the calculation mode of the power consumption of the smooth trajectory may specifically be to directly estimate the work performed by the unmanned aerial vehicle flying along the smooth trajectory, or may be to calculate the work performed by the unmanned aerial vehicle flying along the smooth trajectory by using a dissipation function estimation mode.
Further, S120 specifically includes: and determining the smooth track with the minimum dissipation function value in the plurality of smooth tracks as the flight track.
In this embodiment, in order to make the planned flight trajectory smooth and minimize power consumption, the unmanned aerial vehicle can efficiently complete the operation task, and when planning the flight trajectory of the unmanned aerial vehicle, the generated flight trajectory satisfies the following conditions: avoid the barrier in the surrounding space, the orbit is smooth and the power consumption is minimum when unmanned aerial vehicle flies along this flight orbit. The dissipation function value of each of the plurality of smooth trajectories may be calculated, and the smooth trajectory having the smallest dissipation function value may be taken as the flight trajectory.
How to calculate the dissipation function values of a plurality of smooth tracks can be realized by the following method: firstly, carrying out multi-point sampling on each smooth track in a plurality of smooth tracks to obtain a plurality of sampling points corresponding to each smooth track, then obtaining related data comprising coordinates of the plurality of sampling points, coordinates of a track target point (namely an end point of a flight track), coordinates of a track starting point, coordinates of an obstacle and a reference track (the reference track can be a shortest line segment between the track starting point and the track target point), and finally substituting the obtained related data into a dissipation function value calculation formula to obtain a dissipation function value of each smooth track. The dissipation function value calculation formula comprises a reference track definition item, an obstacle distance definition item, a smoothing definition item and a direction definition item, wherein the reference track definition item represents the degree of the smooth track close to the reference track, the obstacle distance definition item represents the degree of the smooth track close to the obstacle, the smoothing definition item represents the smoothing degree of the smooth track, and the direction definition item represents the degree of the smooth track close to the track target point. When the dissipation function value of a smooth track is minimum, the comprehensive condition that the smooth track is close to the reference track, the obstacle, the smoothness and the track target point is optimal is represented, so that the planned flight track meets the conditions that the obstacle in the surrounding space is avoided, the track is smooth, and the power consumption of the unmanned aerial vehicle is minimum when the unmanned aerial vehicle flies along the flight track.
Further, in this embodiment, when the flight state set is the flight acceleration set, the dissipation function value of the smoothed trajectory satisfies the following formula:
wherein each smooth track comprises a plurality of sampling points, A, B, C, D and t are preset weight values, diIs the distance of the sampling point from the reference track, riIs the distance between the sampling point and the obstacle, n is the number of a plurality of sampling points, cost is a dissipation function value, xiIs the coordinate of the sampling point, xdAs coordinates of the trajectory target point, xsFor coordinates of the start of the smoothed trajectory, | xi-xd| characterize xiTo xdDistance, | | xs-xd| characterize xsTo xdThe distance of (d);
an item is defined for a reference trajectory,
defining terms for obstacle distance, C | kxΔa+kyΔa+kzΔ a | is a smooth constraint term,
for the direction defining term, the reference trajectory defining term characterizes a degree of the smooth trajectory approaching the reference trajectory, the obstacle distance defining term characterizes a degree of the smooth trajectory approaching the obstacle, the smooth defining term characterizes a degree of smoothness of the smooth trajectory, and the direction defining term characterizes a degree of the smooth trajectory approaching the trajectory target point.
Further, in this embodiment, when the flight state set is the flight speed set, the dissipation function value of the smoothed trajectory satisfies the following formula:
wherein each smooth track comprises a plurality of sampling points, A, B, C, D and t are preset weight values, diIs the distance of the sampling point from the reference track, riIs the distance between the sampling point and the obstacle, n is the number of a plurality of sampling points, cost is a dissipation function value, xiIs the coordinate of the sampling point, xdAs coordinates of the trajectory target point, xsFor coordinates of the start of the smoothed trajectory, | xi-xd| characterize xiTo xdDistance, | | xs-xd| characterize xsTo xdThe distance of (d);
an item is defined for a reference trajectory,
defining terms for obstacle distance, C | kxΔv+kyΔv+kzAv | is a smooth constraint term that,
for the direction defining term, the reference trajectory defining term characterizes a degree of the smooth trajectory approaching the reference trajectory, the obstacle distance defining term characterizes a degree of the smooth trajectory approaching the obstacle, the smooth defining term characterizes a degree of smoothness of the smooth trajectory, and the direction defining term characterizes a degree of the smooth trajectory approaching the trajectory target point.
It should be noted that | | xi-xdI (penalty value) is used to penalize a smooth trajectory away from the trajectory target point, | | xs-xd| l is used to correct penalty values (| | x)i-xd| |) to avoid the problem that the farther the smooth track is from the track target point, the larger the value of the direction restriction item is, and the preset weight values A, B, C, D and τ can be set according to the actual application scenario.
Based on the unmanned aerial vehicle flight path planning method described in fig. 2, because the flight state set is generated according to the flight state of the unmanned aerial vehicle trajectory starting point and the preset flight variables, the smooth trajectory set is determined according to the flight data of the unmanned aerial vehicle trajectory starting point, a plurality of estimated flight states and the preset flight time, and then the smooth trajectory with the minimum power consumption is taken as the flight trajectory from the smooth trajectory set, so that the unmanned aerial vehicle flies along the flight trajectory, the generation of the smooth flight trajectory with the minimum power consumption is realized, and the unmanned aerial vehicle can efficiently complete the operation task.
In one possible application scenario, for example, based on the operation scenario of fig. 1, the unmanned aerial vehicle flight trajectory planning method provided in this embodiment of the present application may be applied to the corner of the "bow route" to re-plan the flight routes at the corner of the "bow route", as shown in fig. 3 (where the dotted line is the trajectory of the original "bow route" and the solid line is the trajectory of the "bow route" after re-planning), so that the flight trajectory at the corner of the newly planned "bow route" is smooth and the flight power consumption is minimal.
For how to re-plan the flight trajectory at the corner of the "bow course", taking the flight trajectory planning between A, B points in fig. 3 as an example, firstly taking point a as the trajectory starting point of the unmanned aerial vehicle, generating a flight state set including a plurality of estimated flight states according to the flight state of the unmanned aerial vehicle at point a and preset flight variables, then determining a smooth trajectory set including a plurality of smooth trajectories according to the flight data of the trajectory starting point of the unmanned aerial vehicle, the plurality of estimated flight states and preset flight time, finally taking point B as the trajectory target point, taking the dashed trajectory between points A, B (namely the corner flight trajectory of the original "bow course") as a reference trajectory, calculating the dissipation function value of each trajectory in the smooth trajectory set, and taking the smooth trajectory with the minimum dissipation function value as the flight trajectory obtained by re-planning. It can be understood that, for the complete process of replanning the flight trajectory at the corner of the "bow route", reference may be made to the unmanned aerial vehicle flight trajectory planning method provided in the foregoing embodiment, and details are not described here.
Referring to fig. 4, fig. 4 is a schematic diagram illustrating a possible implementation scenario. The drone 100 flies along a flight path 200, the flight path 200 including 4 segment endpoints T1, T2, T3, and T4. Wherein, T1 is the starting point of the route 200, T4 is the ending point of the route 200, the leg between T1 and T2 is the first leg 210, the leg between T2 and T3 is the second leg 220, and the leg between T3 and T4 is the third leg 230. It should be noted that the route 200 may be a route pre-stored in the drone 100, or a route in which the drone 100 receives transmissions from other terminals in real time. The number of flight segments and the specific trajectory of the flight path 200 may be set according to actual conditions, and the flight path 200 provided by the present application represents only one possible embodiment.
Since the danger zone of the obstacle intersects the first leg 210, the flight trajectory of the drone 100 needs to be re-planned in order to avoid the drone colliding with the obstacle during flight along the first leg 210. Based on the unmanned aerial vehicle flight trajectory planning method provided by the application, how to re-plan the flight trajectory of the unmanned aerial vehicle 100 can be realized by adopting the following method:
step 1, generating a flight state set according to a flight state of a current track starting point of an unmanned aerial vehicle 100 and a preset flight variable;
step 2, determining a smooth track set according to flight data of the track starting point of the unmanned aerial vehicle 100, a plurality of estimated flight states and preset flight time;
step 3, determining a smooth track with the minimum power consumption in the plurality of smooth tracks as a flight track;
and 4, judging whether the tail end point of the smooth track with the minimum power consumption is the track target point, if not, taking the tail end point of the smooth track with the minimum power consumption as the current track starting point, and returning to execute the step 1 until the tail end point of the smooth track with the minimum power consumption is the track target point.
For example, referring to fig. 4 again, when the unmanned aerial vehicle 100 determines to re-plan the flight trajectory to bypass the obstacle, first, the current position is taken as the current trajectory starting point, and a flight trajectory L1 with minimum power consumption is determined, where the end point of the flight trajectory L1 is not the trajectory target point, the end point of the flight trajectory L1 is taken as the current trajectory starting point, and a flight trajectory L2 with minimum power consumption is determined, where the end point of the flight trajectory L2 is still not the trajectory target point, and the end point of the flight trajectory L2 is taken as the current trajectory starting point, and a flight trajectory L3 with minimum power consumption is determined, where the end point of the flight trajectory L3 is the trajectory target point, and the planning of the flight trajectory is completed.
It should be noted that, the dimension of the unmanned aerial vehicle flight trajectory planning method is not limited to two dimensions in the embodiment of the present application, and the dimension of the unmanned aerial vehicle flight trajectory planning method provided in the embodiment of the present application may actually be three dimensions. Therefore, only the two-dimensional schematic diagram is illustrated herein, and on the basis of the solution shown in the embodiment of the present application, a person skilled in the art can implement the technical solution of the present application in a three-dimensional environment without creative efforts, and details are not described here.
In order to execute corresponding steps in the foregoing embodiment and various possible manners, an implementation manner of the unmanned aerial vehicle flight path planning apparatus is provided below, please refer to fig. 5, and fig. 5 shows a functional block diagram of the unmanned aerial vehicle flight path planning apparatus provided in the embodiment of the present application. It should be noted that the basic principle and the generated technical effects of the unmanned aerial vehicle flight path planning apparatus 300 provided in the present embodiment are the same as those of the above embodiments, and for brief description, no part of the present embodiment is mentioned, and reference may be made to the corresponding contents in the above embodiments. This unmanned aerial vehicle flight trajectory planning device 300 includes: a prediction module 310, a trajectory generation module 320, and a trajectory determination module 330.
The estimation module 310 is configured to generate a flight state set according to a flight state of the unmanned aerial vehicle trajectory starting point and a preset flight variable, where the flight state set includes a plurality of estimated flight states.
In a possible embodiment, the flight state includes an acceleration, the preset flight variable includes a preset acceleration increment, and the estimation module 310 may be configured to generate a flight acceleration set as the flight state set according to the acceleration and the preset acceleration increment; the flight acceleration set comprises a plurality of flight accelerations, and the flight accelerations satisfy the following formula:
wherein, Delta a is a preset acceleration increment, ax、ay、azComponents of acceleration in different directions, kx、ky、kzAre any constant in a preset interval,
are the components of the flight acceleration in different directions.
In another possible embodiment, the flight state includes speed information of a track starting point, the preset flight variable includes a preset speed increment, and the estimation module 310 may be configured to generate a flight speed set as the flight state set according to the speed information and the preset speed increment; the set of airspeeds includes a plurality of airspeeds, and the airspeeds satisfy the following formula:
where Δ v is a predetermined speed increment, vx、vy、vzFor the components of the velocity information in different directions, kx、ky、kzAre any constant in a preset interval,
are the components of the flight velocity in different directions.
It is understood that the estimation module 310 may perform the above S100.
The trajectory generation module 320 is configured to determine a smooth trajectory set according to flight data of the unmanned aerial vehicle trajectory starting point, a plurality of estimated flight states, and a preset flight time, where the smooth trajectory set includes a plurality of smooth trajectories.
In one possible embodiment, the flight data includes position information and velocity information of the start point of the trajectory, and the trajectory generation module 320 may be configured to determine a set of smooth trajectories according to the position information, the velocity information, a preset flight time, and a set of flight accelerations.
In another possible embodiment, the flight data includes position information of a starting point of the trajectory, and the trajectory generation module 320 may be configured to determine a set of smooth trajectories according to the position information, a preset flight time, and a set of flight speeds.
It is understood that the trajectory generation module 320 may perform S110 described above.
The trajectory determination module 330 is configured to determine a smooth trajectory with the smallest power consumption from the plurality of smooth trajectories as a flight trajectory, so that the drone flies along the flight trajectory.
In this embodiment, the trajectory determination module 330 may be configured to determine a smooth trajectory with the smallest dissipation function value from among the plurality of smooth trajectories as the flight trajectory.
Further, when the flight state set is the flight acceleration set, the dissipation function value of the smooth trajectory satisfies the following formula:
wherein each smooth track comprises a plurality of sampling points, A, B, C, D and t are preset weight values, diIs the distance of the sampling point from the reference track, riIs the distance between the sampling point and the obstacle, n is the number of a plurality of sampling points, cost is a dissipation function value, xiIs the coordinate of the sampling point, xdAs coordinates of the trajectory target point, xsFor coordinates of the start of the smoothed trajectory, | xi-xd| characterize xiTo xdDistance, | | xs-xd| characterize xsTo xdThe distance of (d);
Further, when the flight state set is the flight speed set, the dissipation function value of the smooth trajectory satisfies the following formula:
wherein each smooth track comprises a plurality of sampling points, A, B, C, D and t are preset weight values, diIs the distance of the sampling point from the reference track, riIs the distance between the sampling point and the obstacle, n is the number of multiple sampling points, cos t is the dissipation function value, xiIs the coordinate of the sampling point, xdAs coordinates of the trajectory target point, xsFor coordinates of the start of the smoothed trajectory, | xi-xd| characterize xiTo xdDistance, | | xs-xd| characterize xsTo xdThe distance of (d);
It is understood that the trajectory determination module 330 may perform S120 described above.
Referring to fig. 6, fig. 6 is a block diagram illustrating a structure of an unmanned aerial vehicle control device according to an embodiment of the present application. The drone controlling device 130 comprises a memory 131, a communication interface 132, a processor 133 and a bus 134, the memory 131, the communication interface 132 and the processor 133 being connected by the bus 134, the processor 133 being adapted to execute executable modules, such as computer programs, stored in the memory 131.
The Memory 131 may include a high-speed Random Access Memory (RAM) and may further include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The communication connection between the drone control device 130 and other terminal devices is achieved through at least one communication interface 132 (which may be wired or wireless).
The bus 134 may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (E4 extended Industry Standard Architecture) bus, or the like. Only one bi-directional arrow is shown in fig. 6, but this does not indicate only one bus or one type of bus.
The memory 131 is used for storing a program, and the processor 133 executes the program after receiving the execution instruction, so as to implement the unmanned aerial vehicle flight trajectory planning method disclosed in the above embodiment.
The embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by the processor 133, the method for planning the flight trajectory of the unmanned aerial vehicle disclosed in the above embodiment is implemented.
It should be understood that the configuration shown in fig. 6 is merely a schematic diagram of the configuration of the drone control device 130, and that the drone control device 130 may include more or fewer components than shown in fig. 6, or have a different configuration than shown in fig. 6. The components shown in fig. 6 may be implemented in hardware, software, or a combination thereof.
Referring to fig. 7, fig. 7 shows a block diagram of a structure of an unmanned aerial vehicle according to an embodiment of the present application. The drone 100 comprises: the airframe 110, the power equipment 120, and the drone controlling device 130. The power equipment 120 is mounted on the airframe for providing power for the drone 100 to fly, wherein the power equipment 120 may include at least one of a motor, a power source, and a propeller. The drone controlling device 130 is communicatively connected to the power device 120 for controlling the flight of the drone 100 along the flight path, and in some possible embodiments, the drone controlling device 130 may be a drone flight controller. When the unmanned aerial vehicle control device 130 is used for controlling the unmanned aerial vehicle 100 to fly, the unmanned aerial vehicle flight trajectory planning method disclosed in the above embodiment may be implemented, and the specific implementation manner and principle are consistent with those of the above embodiment and are not described herein again. It should be noted that the drone 100 provided by the embodiment of the present application includes, but is not limited to, a patrol drone, an agricultural drone, a meteorological drone, an exploration drone, a surveying drone, and the like.
In summary, the embodiments of the present invention provide an unmanned aerial vehicle flight trajectory planning method and a related apparatus. The flight state set is generated according to the flight state of the unmanned aerial vehicle track starting point and the preset flight variable, the smooth track set is determined according to the flight data of the unmanned aerial vehicle track starting point, the plurality of estimated flight states and the preset flight time, and then the smooth track with the minimum power consumption is taken as the flight track from the smooth track set so that the unmanned aerial vehicle flies along the flight track, so that the smooth flight track with the minimum power consumption is generated, and the unmanned aerial vehicle can efficiently complete the operation task.
It should be noted that, the method embodiments provided in the embodiments of the present application are not limited to the specific order in the flowcharts, and it should be understood that, in other embodiments, the order of some steps in the method embodiments provided in the embodiments of the present application may be interchanged according to actual needs, or some steps in the method embodiments may also be omitted or deleted.
The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (15)
1. An unmanned aerial vehicle flight trajectory planning method is characterized by comprising the following steps:
generating a flight state set according to the flight state of the unmanned aerial vehicle track starting point and a preset flight variable, wherein the flight state set comprises a plurality of estimated flight states;
determining a smooth track set according to the flight data of the unmanned aerial vehicle track starting point, the plurality of estimated flight states and preset flight time, wherein the smooth track set comprises a plurality of smooth tracks;
determining a smooth track with the minimum dissipation function value in the plurality of smooth tracks as a flight track so as to enable the unmanned aerial vehicle to fly along the flight track, wherein the dissipation function value of the smooth track is calculated according to a dissipation function value calculation formula, the dissipation function value calculation formula comprises a reference track definition item, an obstacle distance definition item, a smoothing definition item and a direction definition item, the reference track definition item represents the degree of the smooth track approaching the reference track, the obstacle distance definition item represents the degree of the smooth track approaching the obstacle, the smoothing definition item represents the smoothing degree of the smooth track, and the direction definition item represents the degree of the smooth track approaching the track target point.
2. The method of claim 1, wherein the flight status comprises acceleration, the preset flight variables comprise preset acceleration increments, and the step of generating the set of flight statuses from the flight status of the unmanned aerial vehicle trajectory starting point and the preset flight variables comprises:
generating a flight acceleration set as the flight state set according to the acceleration and the preset acceleration increment; the set of flight accelerations comprises a plurality of flight accelerations, which satisfy the following formula:
wherein Δ a is the preset acceleration increment, ax、ay、azAs components of said acceleration in different directions, kx、ky、kzAre any constant in a preset interval,
are the components of the flight acceleration in different directions.
3. The method of claim 2, wherein the flight data includes position information and velocity information of the trajectory starting point, and the step of determining a set of smooth trajectories according to the flight data of the drone trajectory starting point, the plurality of predicted flight states, and a preset flight time includes:
and determining a smooth track set according to the position information, the speed information, the preset flight time and the flight acceleration set.
4. The method of claim 1, wherein the flight status comprises speed information of the trajectory starting point, the preset flight variables comprise preset speed increments, and the step of generating the set of flight statuses from the flight status of the trajectory starting point of the drone and the preset flight variables comprises:
generating a flying speed set as the flying state set according to the speed information and the preset speed increment; the set of airspeeds includes a plurality of airspeeds that satisfy the following equation:
where Δ v is the preset speed increment, vx、vy、vzFor the components of the velocity information in different directions, kx、ky、kzAre any constant in a preset interval,
are the components of the flight speed in different directions.
5. The method of claim 4, wherein the flight data includes position information of the trajectory starting point, and the step of determining a set of smooth trajectories according to the flight data of the drone trajectory starting point, the plurality of predicted flight states, and a preset flight time includes:
and determining a smooth track set according to the position information, the preset flight time and the flight speed set.
6. The method of claim 2, wherein when the set of flight states is the set of flight accelerations, the dissipation function value for the smoothed trajectory satisfies the following formula:
wherein each smooth track comprises a plurality of sampling points, A, B, C, D and t are preset weight values, diIs the distance of the sampling point from the reference track, riIs the distance between the sampling point and the obstacle, n is the number of the plurality of sampling points, cost is the dissipation function value, xiIs the coordinate, x, of the sampling pointdAs coordinates of the trajectory target point, xsIs the coordinate of the starting point of the smooth track, | xi-xd| characterize xiTo xdDistance, | | xs-xd| characterize xsTo xdThe distance of (d);
7. The method of claim 4, wherein when the set of flight states is the set of flight velocities, the dissipation function value for the smoothed trajectory satisfies the following equation:
wherein each smooth track comprises a plurality of sampling points, A, B, C, D and t are preset weight values, diIs the distance of the sampling point from the reference track, riIs the distance between the sampling point and the obstacle, n is the number of the plurality of sampling points, cost is the dissipation function value, xiIs the coordinate, x, of the sampling pointdAs coordinates of the trajectory target point, xsIs the coordinate of the starting point of the smooth track, | xi-xd| characterize xiTo xdDistance, | | xs-xd| characterize xsTo xdThe distance of (d);
8. The utility model provides an unmanned aerial vehicle flight path planning device which characterized in that includes:
the prediction module is used for generating a flight state set according to the flight state of the unmanned aerial vehicle track starting point and a preset flight variable, wherein the flight state set comprises a plurality of predicted flight states;
the track generation module is used for determining a smooth track set according to the flight data of the unmanned aerial vehicle track starting point, the plurality of estimated flight states and the preset flight time, wherein the smooth track set comprises a plurality of smooth tracks;
and the trajectory determination module is used for determining a smooth trajectory with the minimum dissipation function value in the plurality of smooth trajectories as a flight trajectory so as to enable the unmanned aerial vehicle to fly along the flight trajectory, wherein the dissipation function value of the smooth trajectory is calculated according to a dissipation function value calculation formula, the dissipation function value calculation formula comprises a reference trajectory definition item, an obstacle distance definition item, a smoothness definition item and a direction definition item, the reference trajectory definition item represents the degree of the smooth trajectory approaching the reference trajectory, the obstacle distance definition item represents the degree of the smooth trajectory approaching the obstacle, the smoothness definition item represents the smoothness degree of the smooth trajectory, and the direction definition item represents the degree of the smooth trajectory approaching the trajectory target point.
9. The apparatus of claim 8, wherein the flight status comprises an acceleration, the preset flight variable comprises a preset acceleration increment, and the estimation module is configured to generate a set of flight accelerations as the set of flight statuses according to the acceleration and the preset acceleration increment; the set of flight accelerations comprises a plurality of flight accelerations, which satisfy the following formula:
wherein Δ a is the preset acceleration increment, ax、ay、azAs components of said acceleration in different directions, kx、ky、kzAre any constant in a preset interval,
are the components of the flight acceleration in different directions.
10. The apparatus of claim 9, wherein the flight data comprises position information and velocity information of the start of the trajectory, and the trajectory generation module is configured to determine a set of smooth trajectories according to the position information, the velocity information, the preset time of flight, and the set of flight accelerations.
11. The apparatus of claim 8, wherein the flight status comprises speed information of the starting point of the trajectory, the preset flight variable comprises a preset speed increment, and the estimation module is configured to generate a set of flight speeds as the set of flight statuses according to the speed information and the preset speed increment; the set of airspeeds includes a plurality of airspeeds that satisfy the following equation:
where Δ v is the preset speed increment, vx、vy、vzFor the components of the velocity information in different directions, kx、ky、kzAre any constant in a preset interval,
are the components of the flight speed in different directions.
12. The apparatus of claim 11, wherein the flight data comprises position information of a start of the trajectory, and wherein the trajectory generation module is configured to determine a set of smooth trajectories according to the position information, the preset time of flight, and the set of speeds of flight.
13. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements a method for unmanned aerial vehicle flight trajectory planning according to any one of claims 1-7.
14. An drone controlling device comprising a processor and a memory, the memory storing machine executable instructions executable by the processor for executing the machine executable instructions to implement the drone flight trajectory planning method of any one of claims 1-7.
15. An unmanned aerial vehicle, comprising:
a body;
the power equipment is arranged on the machine body and used for providing power for the unmanned aerial vehicle;
and a drone control device comprising a processor and a memory, the memory storing machine executable instructions executable by the processor, the processor for executing the machine executable instructions to implement the drone flight trajectory planning method of any one of claims 1-7.
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