CN117726777B - Unmanned aerial vehicle route optimization method and device and computer storage medium - Google Patents
Unmanned aerial vehicle route optimization method and device and computer storage medium Download PDFInfo
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Abstract
The invention provides an unmanned aerial vehicle route optimization method, device and computer storage medium, which are characterized in that initial position information of each route is firstly obtained, then a first navigation point which is not intersected with each three-dimensional model is determined from all navigation points based on the initial position of each navigation point and the virtual position of each three-dimensional model in a virtual environment, then the first navigation point number and the total number of navigation points of each route are determined, and a target route is deleted from all routes based on the first navigation point number and the total number of navigation points of each route. The invention can solve the problems that the existing unmanned aerial vehicle simulation technology is difficult to reduce the workload of the route design and avoid the route passing through the mould.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle route optimization method, an unmanned aerial vehicle route optimization device and a computer storage medium.
Background
In order to improve the perception capability and obstacle detouring capability of the unmanned aerial vehicle, data in various scenes are required to be collected, and virtual models corresponding to the various scenes are established based on a digital twin technology so as to perform simulation tests of the unmanned aerial vehicle flying in the various scenes, wherein the simulation tests can face the problem of scene and route adaptation. The amount of manual effort required is significant if the route is designed for each scene separately, and the phenomenon of overlapping the route with the virtual model corresponding to one or more scenes (i.e., route threading) occurs if a common route is designed for a plurality of different scenes. Therefore, how to avoid the model crossing of the air route while reducing the workload of the air route design is an important problem to be solved in the existing unmanned aerial vehicle simulation technology.
Disclosure of Invention
In view of the above, the present invention aims to provide a method, a device and a computer storage medium for optimizing a route of an unmanned aerial vehicle, so as to alleviate the problem that the existing unmanned aerial vehicle simulation technology is difficult to reduce the workload of route design and avoid the problem of route pattern penetration.
In a first aspect, an embodiment of the present invention provides an unmanned aerial vehicle route optimization method, where the method is applied to a pre-established virtual environment including a plurality of three-dimensional models, each three-dimensional model being composed of a plurality of patches; the method comprises the following steps: acquiring initial position information of each route; each route comprises a plurality of waypoints, and the initial position information comprises the initial position of each waypoint contained in the corresponding route; determining a first waypoint which does not intersect each three-dimensional model from all the waypoints based on the initial position of each waypoint and the virtual position of each three-dimensional model in the virtual environment; the first number of waypoints and the total number of waypoints for each route are determined and the target route is deleted from all routes based on the first number of waypoints and the total number of waypoints for each route.
In a second aspect, the embodiment of the present invention further provides an unmanned aerial vehicle route optimization device, where the device is applied to a pre-established virtual environment including a plurality of three-dimensional models, each three-dimensional model is composed of a plurality of patches; the device comprises: the acquisition module is used for acquiring initial position information of each route; each route comprises a plurality of waypoints, and the initial position information comprises the initial position of each waypoint contained in the corresponding route; the determining module is used for determining a first waypoint which is not intersected with each three-dimensional model from all the waypoints based on the initial position of each waypoint and the virtual position of each three-dimensional model in the virtual environment; and the optimization module is used for determining the first navigation point number and the total number of navigation points of each route and deleting the target route from all routes based on the first navigation point number and the total number of navigation points of each route.
In a third aspect, an embodiment of the present invention further provides a computer storage medium, configured to store computer software instructions for use in the unmanned aerial vehicle route optimization method according to the first aspect.
According to the unmanned aerial vehicle route optimization method, device and computer storage medium, initial position information of each route is acquired firstly, then first waypoints which are not intersected with each three-dimensional model are determined from all waypoints based on the initial positions of the waypoints and the virtual positions of the three-dimensional models in a virtual environment, then the first waypoints and the total number of the waypoints of each route are determined, and a target route is deleted from all routes based on the first waypoints and the total number of the waypoints of each route. By adopting the technology, the navigation points without penetrating the model can be screened out only by utilizing the navigation point information of the existing route and the three-dimensional model information in the virtual environment, so that the route is optimized, and the design workload of the route is reduced and the model penetration of the route is avoided.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of an unmanned aerial vehicle route optimization method in an embodiment of the invention;
FIG. 2 is an exemplary diagram of a method for route optimization for an unmanned aerial vehicle in accordance with an embodiment of the present invention;
FIG. 3 is a diagram illustrating an example virtual environment for visual waypoint detection in an embodiment of the invention;
FIG. 4 is a diagram of code examples of the results of the visible waypoint detection and the course score according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an unmanned aerial vehicle route optimizing device in an embodiment of the invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described in conjunction with the embodiments, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
At present, simulation tests of unmanned aerial vehicle flying in various scenes can face the problem of scene and route adaptation, if a route is designed for each scene independently, the required manual workload is large, and if a general route is designed for a plurality of different scenes, the phenomenon that the route overlaps with a virtual model corresponding to one or more scenes (namely, route passing mode) can occur.
Based on the method, the device and the computer storage medium for optimizing the unmanned aerial vehicle route, which are provided by the embodiment of the invention, can relieve the problem that the existing unmanned aerial vehicle simulation technology is difficult to reduce the workload of route design and avoid the problem that the route passes through a model.
For the convenience of understanding the present embodiment, first, a detailed description is given of an unmanned aerial vehicle route optimization method disclosed in the present embodiment, where the method may be applied to a virtual environment that is built in advance and includes a plurality of three-dimensional models, each of which is composed of a plurality of patches; referring to a schematic flow chart of a method for optimizing a unmanned aerial vehicle route shown in fig. 1, the method may include the following steps:
step S102, initial position information of each route is acquired.
Wherein each route may include a plurality of waypoints, and the initial position information may include an initial position of each waypoint included in the corresponding route.
Step S104, determining a first waypoint which is not intersected with each three-dimensional model from all the waypoints based on the initial position of each waypoint and the virtual position of each three-dimensional model in the virtual environment.
Step S106, determining the first number of points and the total number of points of each route, and deleting the target route from all routes based on the first number of points and the total number of points of each route.
According to the unmanned aerial vehicle route optimization method provided by the embodiment of the invention, initial position information of each route is acquired firstly, then, first waypoints which are not intersected with each three-dimensional model are determined from all the waypoints based on the initial positions of the waypoints and the virtual positions of the three-dimensional models in the virtual environment, then, the first waypoints and the total number of the waypoints of each route are determined, and the target route is deleted from all the routes based on the first waypoints and the total number of the waypoints of each route. By adopting the technology, the navigation points without penetrating the model can be screened out only by utilizing the navigation point information of the existing route and the three-dimensional model information in the virtual environment, so that the route is optimized, and the design workload of the route is reduced and the model penetration of the route is avoided.
As a possible implementation manner, the step S104 (i.e. determining, from all the waypoints, the first waypoint that does not intersect each three-dimensional model based on the initial position of each waypoint and the virtual position of each three-dimensional model in the virtual environment) may include:
step 1, determining the initial position of each waypoint to respectively correspond to a first position in the virtual environment.
The initial position may be an initial coordinate of a corresponding waypoint in a local coordinate system corresponding to the unmanned aerial vehicle flight area, and the virtual environment corresponds to a world coordinate system, and the initial coordinate of each waypoint may be converted into a corresponding coordinate in the world coordinate system as a corresponding first position, so that the first position and the virtual position of each three-dimensional model are unified in the same coordinate system.
And 2, detecting ray collision between each waypoint and each three-dimensional model based on the first position of each waypoint and the virtual position of each three-dimensional model so as to screen out the first waypoint from all the waypoints.
For example, based on the first position of each waypoint and the virtual position of each three-dimensional model, a ray-collision detection algorithm may determine whether each waypoint is located within the coverage area of the corresponding patch, and determine a waypoint that is not located within the coverage area of any patch as the first waypoint.
As a possible implementation manner, the first position may be a first coordinate of the corresponding waypoint in a world coordinate system corresponding to the virtual environment, and the virtual position may be a first vertex coordinate of each patch included in the corresponding three-dimensional model in the world coordinate system; based on this, the determining, in step 2, whether each waypoint is located in the coverage area of the corresponding patch by using the ray collision detection algorithm based on the first position of each waypoint and the virtual position of each three-dimensional model may include:
and step A, taking each waypoint as a ray starting point to send rays to the next waypoint, and judging whether each ray intersects with the corresponding patch or not based on the ray parameters of each ray, the first coordinates of each waypoint and the first vertex coordinates of each patch.
Each ray needs to satisfy the ray equationP (t) is the coordinates of a point with a parameter t on the ray, O is the coordinates of the starting point of the ray (namely the coordinates of the corresponding waypoint), D is a unit vector representing the emitting direction of the ray, t is a random parameter of the ray,/>Is the direction vector of the ray. Based on this, each ray has a ray parameter including O, D in the ray equation.
For each ray, after unifying the ray and all the patches into the world coordinate system corresponding to the virtual environment, the following two ways can be used to determine whether the ray intersects the corresponding patch:
The first way is: the intersection point of the ray and the plane of the patch is obtained first, and then whether the intersection point is in the coverage area of the patch is judged.
The second way is: it is directly determined whether the ray intersects the corresponding patch.
For the first aspect, determining whether each ray intersects the corresponding patch in the step a based on the ray parameters of each ray, the first coordinates of each waypoint, and the first vertex coordinates of each patch may include:
And A1, determining the intersection point coordinates between each ray and the plane of each patch based on the ray parameters of each ray, the first coordinates of each navigation point and the first vertex coordinates of each patch.
And step A2, judging whether each ray intersects with the corresponding patch or not based on the coordinates of each intersection point and the coordinates of the first vertex of each patch.
Illustratively, the above step A2 (i.e., determining whether each ray intersects a corresponding patch based on the intersection coordinates and the first vertex coordinates of the patches) may employ the following operation modes: for each ray, determining the barycentric coordinates of each intersection point coordinate corresponding to the ray under a barycentric coordinate system based on each intersection point coordinate corresponding to the ray and the first vertex coordinates of each patch, and judging whether the ray intersects with the corresponding patch based on each barycentric coordinate corresponding to the ray.
Taking the above-mentioned patch as a triangular patch as an example, for any point p= (x, y, z) in the plane of a certain triangular patch, it can also be expressed as:
P = u V1+ v V2+ (1-u-v) V3
wherein V 1、V2 and V 3 are coordinates of three vertexes of the triangular patch, and u, V and 1-u-V are coordinates (i.e. barycentric coordinates) of the point P under a barycentric coordinate system corresponding to a plane of the triangular patch;
The settings V1= (x1, y1, z1),V2= (x2, y2, z2),V3= (x3, y3, z3), are:
x = u x1+ vx2+ (1-u-v) x3
y = u y1+ v y2+ (1-u-v) y3
z = u z1 + v z2+ (1-u-v) z3
solving the above equation set to obtain u and v:
u = ((x - x3)(y2- y3) - (x2- x3)(y - y3)) / ((x1- x3)(y2- y3) - (x2- x3)(y1- y3))
v = ((x1- x)(z3- z1) - (x3- x)(z1- z)) / ((x1- x3)(z2- z3) - (x2- x3)(z1- z3))
if u, v e [0,1], it means that the point P is within the triangular patch, i.e., the ray passing through the point P intersects the triangular patch.
According to the above principle, for a certain ray, the calculation mode for judging whether the ray intersects a certain triangular patch may be: when the intersection point coordinate between the ray and the plane of the triangular surface patch is obtained, the center of gravity coordinate corresponding to the intersection point coordinate can be calculated by utilizing the intersection point coordinate and the three vertex coordinates of the triangular surface patch, if the three coordinate values of the center of gravity coordinate are all in the interval [0,1], the ray is judged to intersect with the surface patch, and if the coordinate value of the center of gravity coordinate is not in the interval [0,1], the ray is judged to be not intersected with the surface patch.
For example, for the second aspect, determining whether each ray intersects the corresponding patch in the step a based on the ray parameters of each ray and the first coordinates of each waypoint and the first vertex coordinates of each patch may include:
for each ray, based on the ray parameters of the ray, the first coordinates of the navigation points corresponding to the ray and the first vertex coordinates of each patch, an M-T (or M-Trumbore) algorithm is adopted to judge whether the ray intersects with the corresponding patch.
Continuing the previous example, taking the above-mentioned patch as a triangular patch as an example, for any ray, the ray parameters O, D of the ray can be obtained according to the ray equation, and the ray equation is combined to obtain:
there are three unknowns t, b 1、b2 at this time, which can be solved according to the Cramer's Rule:
Wherein t is the intersecting distance between the ray and the triangle, and b 1、b2 is the coordinate value of the barycentric coordinate respectively;
according to the fact that rays cannot be counter-propagated, if the rays intersect with a triangular patch, the gravity center must be in the triangular patch, namely, the following needs to be satisfied simultaneously: ，/>，/>，/>。
According to the above principle, for a certain ray, the calculation mode for judging whether the ray intersects a certain triangular patch may be: the t of the ray equation corresponding to the ray and the b 1、b2 of the barycentric coordinate can be calculated by using the O and D of the ray equation corresponding to the ray and the three vertex coordinates V 1、V2 and V 3 of the triangular surface patch, if the two coordinates simultaneously satisfy 、/>、/>AndJudging that the ray intersects the patch, if the ray and the patch cannot meet/>, then、/>、/>AndIt is determined that the ray does not intersect the patch.
And B, for each waypoint, if the rays emitted by the waypoint and the last waypoint intersect with the corresponding patch, determining that the waypoint is positioned in the coverage area of the corresponding patch.
Because each waypoint can emit rays, and the rays emitted by each waypoint in the coverage area of the panel and the rays emitted by each waypoint on the waypoint intersect with the corresponding panel, but the rays emitted by one waypoint outside the coverage area of the panel and the rays emitted by the other waypoint outside the coverage area of the panel do not intersect with any panel, the position of the waypoint in the coverage area of the panel can be judged as long as the fact that the rays emitted by each waypoint and each ray emitted by each waypoint on the waypoint intersect with the corresponding panel is determined.
In practical application, in order to further reduce the amount of computation, the above step A2 (i.e. determining whether each ray intersects the corresponding patch based on the coordinates of each intersection point and the coordinates of the first vertex of each patch) may employ the following operation method:
(1) Based on the first vertex coordinates of each patch, dividing the three-dimensional space occupied by each three-dimensional model into a plurality of voxels by adopting a preset space acceleration structure.
Wherein each voxel has a respective second vertex coordinate.
The preset spatial acceleration structure may include a plurality of voxels uniformly divided in a three-dimensional space occupied by the three-dimensional model, or may include a plurality of voxels non-uniformly divided in a three-dimensional space occupied by the three-dimensional model. The voxel division mode of the three-dimensional space occupied by each three-dimensional model mainly comprises an Oct-Tree division mode, a KD-Tree division mode, a BSP-Tree division mode and the like, and the voxel division mode can be selected according to actual requirements and is not limited.
(2) For each ray, screening out first voxels intersected with the ray from all voxels based on the corresponding intersection point coordinates of the ray and the second vertex coordinates of the voxels, screening out first patches intersected with the corresponding first voxels from all the patches based on the first vertex coordinates of the patches and the second vertex coordinates of the first voxels, and judging whether the ray is intersected with the corresponding first patches based on the intersection point coordinates and the first vertex coordinates of each first patch corresponding to the ray.
By adopting the operation mode of dividing voxels to judge whether each ray intersects with the corresponding patch, the patch which does not intersect with each ray can be rapidly removed through the acceleration structure, so that the patch which intersects with the ray is only required to be searched in the rest patches for each ray, and compared with the method that the patch which intersects with the ray is directly searched in all patches for each ray, the calculation amount can be greatly reduced, and therefore, the efficiency of judging whether the ray emitted by each waypoint intersects with the corresponding patch is improved.
As a possible implementation manner, deleting the target course from all courses based on the first number of courses and the total number of courses in the step S106 may include: determining the ratio of the first navigation point number to the total number of navigation points of each route, and deleting the route with the ratio of the first navigation point number to the total number of navigation points smaller than a preset threshold value from all routes as a target route.
After all the first waypoints are determined, the first waypoints and the total number of the waypoints of each route can be obtained, based on the first waypoints and the total number of the waypoints of each route can be counted, the ratio between the first waypoints and the total number of the waypoints of each route is calculated, and each calculated ratio is compared with a preset threshold value, if the ratio is smaller than the preset threshold value, the number of the first waypoints on the corresponding route is too low (the situation that the model-through phenomenon of the route can be considered to appear), if the ratio is not smaller than the preset threshold value, the number of the first waypoints on the corresponding route is too low (the situation that the model-through phenomenon of the route does not appear) can be considered, and only the route with the ratio smaller than the preset threshold value can be reserved through deleting the route with the ratio smaller than the preset threshold value, so that the reserved route can be suitable for unmanned aerial vehicle simulation test under various scenes because the model-through phenomenon of the route does not appear.
For ease of understanding, the manner in which the above-described unmanned aerial vehicle route optimization method operates is described herein by way of specific example as follows.
Referring to fig. 2, the above-mentioned unmanned aerial vehicle route optimization method may be performed in the following operation manner:
first, each waypoint in the local coordinate system is loaded, and the origin coordinate (home position) of the world coordinate system (wgs) corresponding to the virtual environment is read.
Each waypoint in the local coordinate system has an initial coordinate in the corresponding local coordinate system and an arrival time of the unmanned aerial vehicle.
And secondly, converting the initial coordinate of each navigation point in the local coordinate system into a first coordinate corresponding to the navigation point in the world coordinate system.
And thirdly, calculating connectivity among waypoints.
All waypoints can be ordered according to the positive sequence of the arrival time of the unmanned aerial vehicle so as to calculate the arrival time interval of the unmanned aerial vehicle among the waypoints, further, the waypoints with continuous arrival time of the unmanned aerial vehicle and the arrival time interval of the unmanned aerial vehicle being smaller than a certain interval are aggregated into a route, and therefore all the waypoints are divided into one or more routes, and connectivity calculation among the waypoints is completed.
And fourthly, judging whether the waypoints in each route are visible or not under the overlooking view angle, and calculating the route score.
The virtual environment is pre-established and comprises a plurality of three-dimensional models, each three-dimensional model consists of a plurality of triangular patches, whether each waypoint is visible relative to the three-dimensional model can be detected through a ray collision detection algorithm, whether the waypoint in each route is visible or not is judged specifically under the overlooking view, whether rays emitted by each waypoint to the next waypoint intersect with the corresponding triangular patch or not is judged specifically, rays which do not intersect with any triangular patch and rays which intersect with the corresponding triangular patch can be found out according to a related calculation mode, all visible waypoints are obtained, each waypoint except all visible waypoints is an invisible waypoint, and each invisible waypoint and the rays emitted by the last waypoint intersect with the corresponding patch.
When judging whether the waypoints in each route are visible or not in the overlooking view, the space acceleration structure can be adopted to divide voxels of the three-dimensional space occupied by each three-dimensional model, so that most of the three-dimensional models which are not intersected with each ray are rapidly eliminated by the space acceleration structure, and the overall calculated amount for judging whether the waypoints in each route are visible or not in the overlooking view is reduced.
After all the visible waypoints are obtained, the visible waypoints and the total number of the waypoints of each route can be counted, and for each route, the score of the route is obtained by adopting the following formula based on the visible waypoints and the total number of the waypoints of the route;
Wherein, For/>Score of strip course,/>For/>Visible number of navigation points of strip navigation line,/>For/>Total number of waypoints for a route.
Fifth, the invisible route is removed.
The scoring threshold T may be preset and after scoring each route, routes less than T may be removed as invisible routes (which may be considered to have run through the model).
Taking a specific virtual environment as an example, referring to fig. 3, after converting 13 waypoints (i.e. the waypoint numbers are integers from 1 to 13 respectively) into a world coordinate system corresponding to the virtual environment, a total of 5 routes are obtained after calculation through connectivity between the waypoints, and then visible waypoint detection is performed (i.e. whether the waypoints in each route are visible relative to the virtual environment is determined) to find visible waypoints. In fig. 3, the waypoints 4,5, and 9 are invisible waypoints (only the digitally represented waypoint number can be seen but the waypoints represented by the solid origin cannot be seen), while the other waypoints are visible waypoints (both the digitally represented waypoint number and the waypoints represented by the solid origin can be seen).
Referring to fig. 4, fig. 4 shows a code of a visible waypoint detection result and an airline score, the code showing contents including: the total number of the waypoints is 13, 5 routes are copolymerized, the scores of the 5 routes are 1, 0.5, 1, 0 and 1 respectively, the route score threshold is set to be 0.6, two route passing through the mould (namely, the route with the score less than 0.6, namely, the route with the visible waypoint accounting for less than 60 percent) need to be removed at the moment, the total number of the two route passing through the mould is 5, and the number of the route passing through the mould is 4, 5, 6, 7 and 9 respectively.
By adopting the unmanned aerial vehicle route optimization method, all the waypoints are communicated into routes, whether the waypoints on each route are overlooked and visible or not is judged to find out the visible waypoints, and then the score of each route is calculated to find out and remove the model-penetrating route, so that route optimization is realized, and the model penetration of the route can be avoided while the design workload of the route is reduced.
Based on the above unmanned aerial vehicle route optimization method, the embodiment of the invention also provides an unmanned aerial vehicle route optimization device, as shown in fig. 5, which may include the following modules:
An obtaining module 502, configured to obtain initial position information of each route; each route comprises a plurality of waypoints, and the initial position information comprises the initial position of each waypoint contained in the corresponding route.
A determining module 504 is configured to determine a first waypoint that does not intersect each three-dimensional model from all waypoints based on the initial position of each waypoint and the virtual position of each three-dimensional model in the virtual environment.
An optimization module 506 for determining the first number of points and the total number of points for each route and deleting the target route from all routes based on the first number of points and the total number of points for each route.
According to the unmanned aerial vehicle route optimizing device provided by the embodiment of the invention, the waypoints which do not penetrate through the model can be screened out only by utilizing the waypoint information of the existing route and the three-dimensional model information in the virtual environment, so that the route is optimized, and the design workload of the route is reduced and the route penetrating through the model is avoided.
The determination module 504 described above may also be used to: determining the initial position of each waypoint to correspond to a first position in the virtual environment; and detecting ray collision between each waypoint and each three-dimensional model based on the first position of each waypoint and the virtual position of each three-dimensional model so as to screen out the first waypoint from all the waypoints.
The determination module 504 described above may also be used to: and judging whether each waypoint is positioned in the coverage area of the corresponding patch by a ray collision detection algorithm based on the first position of each waypoint and the virtual position of each three-dimensional model, and determining the waypoint which is not positioned in the coverage area of any patch as the first waypoint.
The first position may be a first coordinate of the corresponding waypoint in a world coordinate system corresponding to the virtual environment, and the virtual position may be a first vertex coordinate of each patch in the world coordinate system included in the corresponding three-dimensional model; based on this, the determination module 504 described above may also be used to: taking each waypoint as a ray starting point to emit rays to the next waypoint, and judging whether each ray intersects with the corresponding patch or not based on the ray parameters of each ray, the first coordinates of each waypoint and the first vertex coordinates of each patch; for each waypoint, if the rays emitted by the waypoint and the waypoint above each intersect with the corresponding patch, determining that the waypoint is located within the coverage area of the corresponding patch.
The determination module 504 described above may also be used to: determining the intersection point coordinates between each ray and the plane of each patch based on the ray parameters of each ray, the first coordinates of each waypoint and the first vertex coordinates of each patch; based on the intersection point coordinates and the first vertex coordinates of the patches, whether each ray intersects the corresponding patch is determined.
The determination module 504 described above may also be used to: dividing the three-dimensional space occupied by each three-dimensional model into a plurality of voxels by adopting a preset space acceleration structure based on the first vertex coordinates of each patch; wherein each voxel has a respective second vertex coordinate; for each ray, screening out first voxels intersected with the ray from all voxels based on the corresponding intersection point coordinates of the ray and the second vertex coordinates of the voxels, screening out first patches intersected with the corresponding first voxels from all the patches based on the first vertex coordinates of the patches and the second vertex coordinates of the first voxels, and judging whether the ray is intersected with the corresponding first patches based on the intersection point coordinates and the first vertex coordinates of each first patch corresponding to the ray.
The optimization module 506 described above may also be used to: determining the ratio of the first navigation point number to the total number of navigation points of each route, and deleting the route with the ratio of the first navigation point number to the total number of navigation points smaller than a preset threshold value from all routes as a target route.
The determination module 504 described above may also be used to: for each ray, determining the barycentric coordinates of each intersection point coordinate corresponding to the ray under a barycentric coordinate system based on each intersection point coordinate corresponding to the ray and the first vertex coordinates of each patch, and judging whether the ray intersects with the corresponding patch based on each barycentric coordinate corresponding to the ray.
The implementation principle and the generated technical effects of the unmanned aerial vehicle route optimization device provided by the embodiment of the invention are the same as those of the unmanned aerial vehicle route optimization method embodiment, and for the sake of brief description, the corresponding contents in the method embodiment can be referred to where the device embodiment part is not mentioned.
The embodiment of the invention also provides a computer storage medium for storing computer software instructions used for the unmanned aerial vehicle route optimization method, and the specific implementation can be found in the foregoing method embodiment, and the details are not repeated here.
The computer program product of the unmanned aerial vehicle route optimization method and device provided by the embodiment of the invention comprises a computer readable storage medium storing program codes, wherein the instructions included in the program codes can be used for executing the method described in the method embodiment, and specific implementation can be seen in the method embodiment and is not repeated herein.
The relative steps, numerical expressions and numerical values of the components and steps set forth in these embodiments do not limit the scope of the present invention unless it is specifically stated otherwise.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer readable storage medium executable by a processor. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings, are merely for convenience of describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the above examples are only specific embodiments of the present invention, and are not intended to limit the scope of the present invention, but it should be understood by those skilled in the art that the present invention is not limited thereto, and that the present invention is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be 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 claims.
Claims (9)
1. An unmanned aerial vehicle route optimization method is characterized in that the method is applied to a pre-established virtual environment comprising a plurality of three-dimensional models, and each three-dimensional model consists of a plurality of patches; the method comprises the following steps:
acquiring initial position information of each route; each route comprises a plurality of waypoints, the initial position information comprises initial positions of the waypoints contained in the corresponding route, and the initial positions are initial coordinates of the corresponding waypoints under a local coordinate system corresponding to the unmanned aerial vehicle flight area;
Determining the initial position of each waypoint to correspond to a first position in the virtual environment; the first position is a first coordinate of the corresponding waypoint under a world coordinate system corresponding to the virtual environment;
Based on the first position of each waypoint and the virtual position of each three-dimensional model in the virtual environment, performing ray collision detection between each waypoint and each three-dimensional model to screen out first waypoints which are not intersected with each three-dimensional model from all the waypoints; the virtual position is a first vertex coordinate of each patch contained in the corresponding three-dimensional model under the world coordinate system;
The first number of waypoints and the total number of waypoints for each route are determined and the target route is deleted from all routes based on the first number of waypoints and the total number of waypoints for each route.
2. The method of claim 1, wherein performing ray-collision detection between each waypoint and each three-dimensional model based on the first location of each waypoint and the virtual location of each three-dimensional model in the virtual environment to screen out the first waypoint from all waypoints comprises:
And judging whether each waypoint is positioned in the coverage area of the corresponding patch by a ray collision detection algorithm based on the first position of each waypoint and the virtual position of each three-dimensional model, and determining the waypoint which is not positioned in the coverage area of any patch as the first waypoint.
3. The method of claim 2, wherein determining whether each waypoint is located within the coverage area of the corresponding patch by a ray-collision detection algorithm based on the first location of each waypoint and the virtual location of each three-dimensional model comprises:
Taking each waypoint as a ray starting point to emit rays to the next waypoint, and judging whether each ray intersects with the corresponding patch or not based on the ray parameters of each ray, the first coordinates of each waypoint and the first vertex coordinates of each patch;
For each waypoint, if the rays emitted by the waypoint and the waypoint above each intersect with the corresponding patch, determining that the waypoint is located within the coverage area of the corresponding patch.
4. A method according to claim 3, wherein determining whether each ray intersects a respective patch based on the ray parameters of each ray and the first coordinates of each waypoint and the first vertex coordinates of each patch comprises:
Determining the intersection point coordinates between each ray and the plane of each patch based on the ray parameters of each ray, the first coordinates of each waypoint and the first vertex coordinates of each patch;
Based on the intersection point coordinates and the first vertex coordinates of the patches, whether each ray intersects the corresponding patch is determined.
5. The method of claim 4, wherein determining whether each ray intersects a respective patch based on each intersection point coordinate and a first vertex coordinate of each patch comprises:
dividing the three-dimensional space occupied by each three-dimensional model into a plurality of voxels by adopting a preset space acceleration structure based on the first vertex coordinates of each patch; wherein each voxel has a respective second vertex coordinate;
For each ray, screening out first voxels intersected with the ray from all voxels based on the corresponding intersection point coordinates of the ray and the second vertex coordinates of the voxels, screening out first patches intersected with the corresponding first voxels from all the patches based on the first vertex coordinates of the patches and the second vertex coordinates of the first voxels, and judging whether the ray is intersected with the corresponding first patches based on the intersection point coordinates and the first vertex coordinates of each first patch corresponding to the ray.
6. The method of claim 1, wherein deleting the target course from all courses based on the first number of courses and the total number of courses for each course comprises:
Determining the ratio of the first navigation point number to the total number of navigation points of each route, and deleting the route with the ratio of the first navigation point number to the total number of navigation points smaller than a preset threshold value from all routes as a target route.
7. The method of claim 4, wherein determining whether each ray intersects a respective patch based on each intersection point coordinate and a first vertex coordinate of each patch comprises:
For each ray, determining the barycentric coordinates of each intersection point coordinate corresponding to the ray under a barycentric coordinate system based on each intersection point coordinate corresponding to the ray and the first vertex coordinates of each patch, and judging whether the ray intersects with the corresponding patch based on each barycentric coordinate corresponding to the ray.
8. An unmanned aerial vehicle route optimization device, which is characterized in that the device is applied to a pre-established virtual environment comprising a plurality of three-dimensional models, wherein each three-dimensional model consists of a plurality of patches; the device comprises:
the acquisition module is used for acquiring initial position information of each route; each route comprises a plurality of waypoints, the initial position information comprises initial positions of the waypoints contained in the corresponding route, and the initial positions are initial coordinates of the corresponding waypoints under a local coordinate system corresponding to the unmanned aerial vehicle flight area;
A determining module for: determining the initial position of each waypoint to correspond to a first position in the virtual environment; the first position is a first coordinate of the corresponding waypoint under a world coordinate system corresponding to the virtual environment; based on the first position of each waypoint and the virtual position of each three-dimensional model in the virtual environment, performing ray collision detection between each waypoint and each three-dimensional model to screen out first waypoints which are not intersected with each three-dimensional model from all the waypoints; the virtual position is a first vertex coordinate of each patch contained in the corresponding three-dimensional model under the world coordinate system;
and the optimization module is used for determining the first navigation point number and the total number of navigation points of each route and deleting the target route from all routes based on the first navigation point number and the total number of navigation points of each route.
9. A computer storage medium storing computer software instructions for use in the unmanned aerial vehicle route optimisation method according to any one of claims 1 to 7.
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