CN114840030A - Unmanned aerial vehicle ground-imitating flight route automatic planning method, unmanned aerial vehicle and storage medium - Google Patents
Unmanned aerial vehicle ground-imitating flight route automatic planning method, unmanned aerial vehicle and storage medium Download PDFInfo
- Publication number
- CN114840030A CN114840030A CN202210570286.1A CN202210570286A CN114840030A CN 114840030 A CN114840030 A CN 114840030A CN 202210570286 A CN202210570286 A CN 202210570286A CN 114840030 A CN114840030 A CN 114840030A
- Authority
- CN
- China
- Prior art keywords
- track
- node
- target
- dimensional
- flight
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/12—Target-seeking control
Abstract
The application discloses an unmanned aerial vehicle ground-imitating flight route automatic planning method, an unmanned aerial vehicle and a storage medium, wherein the unmanned aerial vehicle ground-imitating flight route automatic planning method comprises the following steps: the method comprises the steps of constructing a target track planning space of a target flight task, wherein the target flight task comprises an initial node and a target node, extracting a two-dimensional task flight profile based on the target track planning space, carrying out path search on the two-dimensional task flight profile to obtain a target two-dimensional track, adding a preset track height to each track point in the target two-dimensional track to obtain an initial three-dimensional track, adjusting the height of each track point in the initial three-dimensional track according to a preset track height adjustment constraint, and obtaining the ground-imitating flight track of the unmanned aerial vehicle. The method and the device solve the technical problems that the traditional track point path planning mode is low in efficiency and difficult to meet flight task requirements.
Description
Technical Field
The application relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle ground-imitating flight route automatic planning method, an unmanned aerial vehicle and a storage medium.
Background
The unmanned aerial vehicle path planning mostly adopts a semi-automatic ground-imitating flight path planning technology. The technology mainly comprises two steps of manually calibrating track points and adjusting the height of a track, wherein a plurality of track points are manually selected on a two-dimensional map to form a two-dimensional track meeting the task requirement, and then the height of each track point is calculated according to the task requirement so as to obtain the final ground-imitating flight track of the unmanned aerial vehicle. However, the unmanned aerial vehicle has a wide application range and a complex working region environment, and in addition, the semi-automatic manual calibration track point path planning mode has extremely low efficiency due to the requirement on obstacle avoidance, so that the requirement of a flight task is difficult to meet.
Disclosure of Invention
The main purpose of the application is to provide an unmanned aerial vehicle ground-imitating flight route automatic planning method, an unmanned aerial vehicle and a storage medium, and the method, the unmanned aerial vehicle and the storage medium aim at solving the technical problems that a route point path planning mode in the prior art is low in efficiency and difficult to meet flight task requirements.
In order to achieve the above object, the present application provides an automatic planning method for a ground-imitating flight route of an unmanned aerial vehicle, the automatic planning method for the ground-imitating flight route of the unmanned aerial vehicle includes:
constructing a target track planning space of a target flight task, wherein the target flight task comprises an initial node and a target node;
extracting a two-dimensional task flight profile based on the target track planning space;
performing path search on the two-dimensional task flight profile to obtain a target two-dimensional flight path, and adding a preset flight path height to each flight path point in the target two-dimensional flight path to obtain an initial three-dimensional trajectory;
and adjusting the height of each track point in the initial three-dimensional track according to a preset track height adjustment constraint to obtain the ground-imitating flight track of the unmanned aerial vehicle.
The application still provides an unmanned aerial vehicle imitative ground flight route automatic planning device, unmanned aerial vehicle imitative ground flight route automatic planning device is virtual device, unmanned aerial vehicle imitative ground flight route automatic planning device includes:
the system comprises a construction module, a data processing module and a data processing module, wherein the construction module is used for constructing a target track planning space of a target flight task, and the target flight task comprises an initial node and a target node;
the extraction module is used for extracting a two-dimensional task flight profile based on the target track planning space;
the path searching module is used for searching paths of the two-dimensional task flight profile to obtain a target two-dimensional track, and adding a preset track height to each track point in the target two-dimensional track to obtain an initial three-dimensional track;
and the height adjusting module is used for adjusting the height of each track point in the initial three-dimensional track according to a preset track height adjusting constraint to obtain the ground-imitating flight track of the unmanned aerial vehicle.
This application still provides an unmanned aerial vehicle, unmanned aerial vehicle is the entity equipment, unmanned aerial vehicle includes: the automatic planning method program of the ground-imitating flight route of the unmanned aerial vehicle is executed by the processor to realize the steps of the automatic planning method of the ground-imitating flight route of the unmanned aerial vehicle.
The application also provides a storage medium which is a computer readable storage medium, the computer readable storage medium stores a program of the automatic planning method for the ground-imitating flight route of the unmanned aerial vehicle, and the program of the automatic planning method for the ground-imitating flight route of the unmanned aerial vehicle is executed by a processor to realize the steps of the automatic planning method for the ground-imitating flight route of the unmanned aerial vehicle.
The application provides an automatic planning method for an unmanned aerial vehicle ground-imitating flight route, an unmanned aerial vehicle and a storage medium, firstly, a target track planning space of a target flight task is constructed, wherein the target flight task comprises a starting node and a target node, then a two-dimensional task flight section is extracted based on the target track planning space, further, the two-dimensional task flight section is subjected to path search to obtain a target two-dimensional flight track, preset track heights are added to all track points in the target two-dimensional flight track to obtain an initial three-dimensional track, then the heights of all track points in the initial three-dimensional track are adjusted according to the preset track height adjustment constraint to obtain the ground-imitating flight track of the unmanned aerial vehicle, the two-dimensional task flight section is extracted from the target track planning space, and therefore the three-dimensional flight route planning problem is reduced to a two-dimensional plane, and then searching out a two-dimensional feasible flight path in the two-dimensional task flight profile, further adding a preset flight path height to each flight path point in the target two-dimensional flight path, and adjusting the height of each flight path point to obtain the unmanned aerial vehicle ground-imitating flight path which finally meets the preset flight path height adjustment constraint, and automatically planning the flight path according to the starting node and the target node without manually calibrating the flight path point, thereby effectively improving the efficiency of flight path planning.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious to those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
Fig. 1 is a schematic flow chart of a first embodiment of an automatic planning method for a ground-imitating flight path of an unmanned aerial vehicle according to the present application;
FIG. 2 is a schematic flow chart of a second embodiment of the method for automatically planning a ground-imitating flight path of an unmanned aerial vehicle according to the present application;
FIG. 3 is a three-dimensional topographic map after triangulation is performed in the embodiment of the present application;
FIG. 4 is a three-dimensional topographic map after cubic interpolation is performed in the embodiment of the present application;
FIG. 5 is a schematic flow chart of a third embodiment of a method for automatically planning a ground-imitating flight path of an unmanned aerial vehicle according to the present application;
FIG. 6 is a two-dimensional mission flight profile in an embodiment of the present application;
FIG. 7 is a schematic flow chart illustrating a fourth embodiment of a method for automatically planning a ground-imitating flight path of an unmanned aerial vehicle according to the present application;
FIG. 8 is a schematic diagram illustrating the determination of a two-dimensional trajectory topography in an embodiment of the present application;
FIG. 9 is a topographical map of an initial three-dimensional trajectory determined in an embodiment of the present application;
FIG. 10 is a schematic flow chart illustrating a fifth embodiment of a method for automatically planning a ground-imitating flight path of an unmanned aerial vehicle according to the present invention;
FIG. 11 is a three-dimensional terrain map of a trajectory after height adjustment in an embodiment of the present application;
FIG. 12 is a schematic diagram illustrating a comparison of terrain heights and heights before and after three-dimensional track adjustment according to an embodiment of the present application;
fig. 13 is a schematic structural diagram of an unmanned aerial vehicle in a hardware operating environment according to an embodiment of the present application;
fig. 14 is a functional module schematic diagram of the automatic planning device for the simulated ground flight route of the unmanned aerial vehicle.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The embodiment of the application provides an automatic planning method for an unmanned aerial vehicle ground-imitating flight route, and in a first embodiment of the automatic planning method for the unmanned aerial vehicle ground-imitating flight route, with reference to fig. 1, the automatic planning method for the unmanned aerial vehicle ground-imitating flight route comprises the following steps:
step S10, constructing a target track planning space of a target flight task, wherein the target flight task comprises an initial node and a target node;
in this embodiment, it should be noted that the target flight task includes a start node and a target node corresponding to the flight of the unmanned aerial vehicle, and further, in order to construct a three-dimensional search space suitable for a track planning algorithm, that is, to construct a target track planning space, a spatial coordinate represented by longitude and latitude height data needs to be converted into a rectangular coordinate system more favorable for calculating a spatial distance and a direction within a local range.
Specifically, the geospatial coordinates of a target area corresponding to the target flight mission are determined through a digital elevation model, wherein the geospatial coordinates include a terrain longitude, a terrain latitude and an altitude, and it should be noted that the digital elevation model generally describes a data set of earth surface elevation or altitude information and spatial distribution thereof by using a group of ordered numerical arrays, is a discrete digital expression of earth surface topography and landform, can reasonably and perfectly reflect various information (including information of terrain, threat, obstacle and the like) in a flight environment, and further, first converts the geospatial coordinates to a target coordinate position in a preset constructed target rectangular coordinate system, wherein the target rectangular coordinate system is a rectangular coordinate system constructed by taking an initial node as a coordinate origin, and a z-axis of the target rectangular coordinate system is coincident with an ellipsoid normal, it should be further noted that, after coordinate conversion, a plurality of discrete data are obtained, and according to these discrete data, it is often desirable to obtain a continuous function (i.e. a curve) or a denser discrete equation that matches known data, so in this embodiment, a spatial interpolation process is performed on discrete target coordinate positions to obtain the target track planning space.
Step S20, extracting a two-dimensional task flight profile based on the target track planning space;
in this embodiment, it should be noted that the two-dimensional task flight profile includes a task reachable node and an obstacle node, where the task reachable node is a node where the unmanned aerial vehicle can reach the target node in a crossing manner through an obstacle avoidance algorithm, and the obstacle node is a node where the unmanned aerial vehicle cannot reach the target node in a crossing manner through the obstacle avoidance algorithm.
Specifically, firstly, sequentially traversing all nodes in the target track planning space, determining the altitude corresponding to all nodes, and further determining whether the altitude of each node meets a preset altitude condition, wherein the preset altitude condition is a condition set according to a preset maximum flight altitude of the unmanned aerial vehicle and a specified relative ground height of a target flight task, and for each node, if the altitude corresponding to the node meets the preset altitude condition, the node is taken as a task reachable node, otherwise, if the altitude corresponding to the node does not meet the preset altitude condition, the node is taken as an obstacle node, further, based on each task reachable node and each obstacle node, forming the two-dimensional task flight profile, thereby realizing the reduction of the three-dimensional track planning problem to a two-dimensional plane, and based on the task reachable nodes and the obstacle nodes, a two-dimensional task flight profile is formed, and the obstacle avoidance requirement is met.
Step S30, performing path search on the two-dimensional task flight profile to obtain a target two-dimensional track, and adding a preset track height to each track point in the target two-dimensional track to obtain an initial three-dimensional track;
in this embodiment, it should be noted that the path Search includes a route searching algorithm such as an a star algorithm, a JPS algorithm (Jump Point Search algorithm), and in this embodiment, it is preferable to select an a star algorithm to perform route Search. Specifically, the A-x algorithm performs two-dimensional flight path planning of flight path re-planning. Further, as the drone needs to be kept flying at a certain relative ground level (ground-imitating flight). In the embodiment, according to the preset track target height of the target flight mission, the height information is added to each track point in each target two-dimensional track, so that the two-dimensional track is converted into a three-dimensional track, the feasibility of track planning can be ensured, and the efficiency of track planning can be improved.
Wherein, in the step S30: performing path search on the two-dimensional task flight profile to obtain a target two-dimensional flight path, which may include:
and step S31, based on the starting node and the target node, performing cost evaluation on each node in the two-dimensional task flight profile through an A-star algorithm, and selecting a track route with the minimum cost as the target two-dimensional track.
In this embodiment, specifically, node expansion is performed starting from an initial node as a current node, each node adjacent to the current node is queried, a new expansion node (barrier node) which does not satisfy a constraint is directly discarded, and for a new expansion feasible node (task reachable node) which satisfies the constraint, after calculating the cost values of all task reachable nodes, all task reachable nodes are placed in an open table, and then a task reachable node with the smallest value is selected in the open table as a next node, and the current node is used as a parent node of the task reachable node with the smallest cost value, and the current node is deleted from the open table and placed in a close table, and further, the next node is used as a new current node, because the feasibility of a flight path from the initial node to the current node is ensured in the expansion process through an a-star algorithm, therefore, the feasibility of the track section from the current node to the extended child node is detected, then based on the new current node, the step of executing query on each node adjacent to the current node is returned until the next node is the target node, and then according to the father node corresponding to each node, iteration backtracking is carried out from the target node to the starting node, so that the target two-dimensional track with the minimum cost is formed.
And step S40, adjusting the height of each track point in the initial three-dimensional track according to preset track height adjustment constraints to obtain the ground-imitating flight track of the unmanned aerial vehicle.
In this embodiment, it should be noted that the preset track height adjustment constraint includes, but is not limited to, a climb rate constraint, a subsidence rate constraint, and a longitudinal curvature radius constraint. Specifically, all track points in the initial three-dimensional track are traversed in a circulating mode, the heights corresponding to the track points which do not meet the constraint are adjusted in an iterative mode until all the track points meet the preset track height adjustment constraint, all the track points which meet the constraint are obtained, and therefore the unmanned aerial vehicle ground-imitating flight track is formed.
The step S40 may include:
and S41, circularly traversing each track point in the initial three-dimensional track, and performing height adjustment on the track points with the heights not meeting the preset track height adjustment constraint until all the track points meet the preset track height adjustment constraint to obtain the ground-imitating flight track of the unmanned aerial vehicle.
Specifically, the initial node is used as a track point to be corrected, and then based on a coordinate position corresponding to the current track point to be corrected and a target coordinate position corresponding to a next track point in the initial three-dimensional track, a climbing rate (sinking rate) corresponding to the track point to be corrected is calculated, and if it is determined that the climbing rate does not satisfy the climbing rate constraint, the height of the track point to be corrected is updated, or if it is determined that the sinking rate does not satisfy the sinking rate constraint, the height of the track point to be corrected is updated, it needs to be noted that, because the current initial node is located and no longitudinal curvature radius exists, a longitudinal curvature radius corresponding to the initial node does not need to be calculated, and for the rest track points in the initial three-dimensional track, a corresponding longitudinal curvature radius needs to be calculated, and further, a next track point in the initial three-dimensional track is used as a track point to be corrected, and returning to the execution step: calculating the climbing rate or sinking rate of the track points to be corrected until all track points of the initial three-dimensional track are traversed to obtain each corrected track point, further performing a new iteration adjustment on the height of each corrected track point until no track point needing height adjustment exists, thereby finishing the iteration adjustment to obtain a three-dimensional track meeting each longitudinal constraint, taking the three-dimensional track as the ground-imitating flight track of the unmanned aerial vehicle, and performing height adjustment through presetting track height adjustment constraints to enable the ground-imitating flight track of the unmanned aerial vehicle to be more accurate.
Through the scheme, namely, a target track planning space of a target flight task is constructed, wherein the target flight task comprises an initial node and a target node, a two-dimensional task flight profile is extracted based on the target track planning space, further, the two-dimensional task flight profile is subjected to path search to obtain a target two-dimensional track, preset track heights are added to all track points in the target two-dimensional track to obtain an initial three-dimensional track, the heights of all track points in the initial three-dimensional track are adjusted according to preset track height adjustment constraints to obtain an unmanned aerial vehicle ground-imitating flight track, the two-dimensional task flight profile is extracted from the target track planning space, so that the three-dimensional track planning problem is reduced to a two-dimensional plane, and a two-dimensional feasible track is searched in the two-dimensional task flight profile, furthermore, a preset track height is added to each track point in the target two-dimensional track, the height of each track point is adjusted to obtain the unmanned aerial vehicle ground-imitating flight track which finally meets the preset track height adjustment constraint, the flight route is automatically planned according to the starting node and the target node, the track points do not need to be calibrated manually, and the efficiency of flight route planning is effectively improved.
Further, referring to fig. 2, based on the first embodiment in the present application, in another embodiment of the present application, the step S10: constructing a target track planning space for a target flight mission may include:
step S11, acquiring a geospatial coordinate of a target area corresponding to the target flight task, wherein the geospatial coordinate comprises a terrain longitude, a terrain latitude and an altitude;
step S12, converting the geographic space coordinate to a target coordinate position in a preset constructed target rectangular coordinate system, wherein the target rectangular coordinate system is a coordinate system constructed by taking the starting node as a coordinate origin;
in this embodiment, it should be noted that the geospatial coordinates cannot be directly converted into the coordinates corresponding to the target rectangular coordinate system, and the geospatial coordinates need to be converted into the coordinate position of the geocentric rectangular coordinate system first, and then the coordinate position of the geocentric rectangular coordinate system needs to be converted into the coordinates corresponding to the target rectangular coordinate system, the geocentric rectangular coordinate system is a geocentric rectangular coordinate system, namely, the origin O coincides with the earth centroid, the Z axis points to the north pole of the earth, the X axis points to the intersection point of the Greenwich mean plane and the equator of the earth, the Y axis is vertical to the XOZ plane to form a right-hand coordinate system, the target rectangular coordinate system is a rectangular coordinate system constructed by taking the starting node as the origin of coordinates, the z-axis of the target rectangular coordinate system is coincident with the normal line of the ellipsoid, and the upward direction is the positive direction (the zenith direction), the y-axis coincides with the minor semi-axis of the ellipsoid (north direction), and the x-axis coincides with the major semi-axis of the earth's ellipsoid (east direction).
Wherein, in the step S12: converting the geospatial coordinates to a target coordinate position in a preset constructed target rectangular coordinate system, which may include:
step S121, converting the geographic space coordinate to a coordinate position of a pre-constructed geocentric rectangular coordinate system;
step S122, selecting a coordinate position corresponding to the starting node as a reference point, and constructing the target rectangular coordinate system based on the reference point;
and step S123, converting the coordinate position of the geocentric rectangular coordinate system to a target coordinate position corresponding to the target rectangular coordinate system.
In this embodiment, specifically, first, the geospatial coordinate P ═ (L, λ, h) is converted into a coordinate position P corresponding to the geocentric rectangular coordinate system e ＝(x e ,y e ,z e )。
Wherein, the conversion formula is as follows:
wherein x is e X-axis coordinate, y, representing a rectangular coordinate system of the earth's center e Y-axis coordinate, z, representing a rectangular coordinate system of the earth's center e Z-axis representing a rectangular coordinate system of the earth's centerCoordinates, L represents the longitude of the terrain, λ represents the latitude of the terrain, h represents the altitude, R N Representing the radius of curvature of the earth's meridian.
The calculation formula of the radius of curvature of the meridian of the earth is as follows:
wherein R is e Is the radius of the earth, e is the first eccentricity of the ellipsoid of the earth, and further, the coordinate position corresponding to the starting node is selected as the reference point P in the rectangular coordinate system of the earth center 0 (x 0 ,y 0 ,z 0 ) And then, the reference point is used as the origin of coordinates of the target rectangular coordinate system, so that each coordinate position in the geocentric rectangular coordinate system is converted into a target coordinate position corresponding to the target rectangular coordinate system.
Wherein, the conversion formula is as follows:
wherein x0, y0 and z0 are coordinates on x, y and z axes of the coordinate origin respectively, and x is e 、y e 、z e Respectively is the coordinate position of any point x, y and z axis in the earth center rectangular coordinate system, x L 、y L 、z L Representing P in a rectangular coordinate system of the earth's center e ＝(x e ,y e ,z e ) And converting the coordinate position into the coordinate position of the target rectangular coordinate system.
Step S13, performing triangulation processing on the target coordinate position to obtain a target subdivision result;
in this embodiment, it should be noted that all the circumscribed circles of the triangle satisfy the triangulation of the empty circle property, which is called a Delaunay triangulation, where the empty circle property indicates that any vertex in the set of points is not included in the circumscribed circle range (except for the boundary) of a triangle (or a side). Referring to fig. 3, fig. 3 is a three-dimensional topographic map after triangulation is performed in the embodiment of the present application.
And step S14, performing spatial interpolation processing on the target subdivision result to obtain the target track planning space.
In this embodiment, specifically, referring to fig. 4, fig. 4 is a three-dimensional topographic map after cubic interpolation performed in the embodiment of the present application, and based on the target subdivision result, the approximate coordinates of any point on the section are obtained by using a cubic spatial interpolation method with the vertex of each triangular section as a reference coordinate point.
Through the scheme, the embodiment of the application obtains the geographic space coordinates of the target area corresponding to the target flight task, wherein the geographic space coordinate comprises a terrain longitude, a terrain latitude and an altitude, and is further converted to a target coordinate position in a preset constructed target rectangular coordinate system, wherein the target rectangular coordinate system is a coordinate system constructed by taking the starting node as a coordinate origin, further triangulation processing is carried out on the target coordinate position to obtain a target subdivision result, finally spatial interpolation processing is carried out on the target subdivision result to obtain the target track planning space, so that the spatial coordinates are converted into coordinate positions in the target rectangular coordinate system, therefore, the ground-imitating flight route is automatically planned based on the information such as the coordinate position, the altitude and the like in the target rectangular coordinate system.
Further, referring to fig. 5, based on the first embodiment in the present application, in another embodiment of the present application, the step S20: extracting a two-dimensional task flight profile based on the target track planning space, comprising:
step S21, traversing all nodes in the target track planning space through a preset step length;
step S22, aiming at each node, if the altitude corresponding to the node meets a preset altitude condition, the node is used as a task reachable node; if the altitude corresponding to the node does not meet the preset altitude condition, taking the node as a barrier node;
step S23, forming the two-dimensional task flight profile based on each of the task reachable nodes and each of the obstacle nodes.
In this embodiment, it should be noted that the preset step length is a preset distance step length of traversing nodes, the two-dimensional task flight profile is a two-dimensional top view formed by each node in a target track planning space, specifically, all nodes in the target track planning space are traversed by the preset step length, where the preset step length may be an inquiry step length manually set according to an actual situation, where no specific limitation is made, and for each node, whether the node meets a preset height condition is determined, where the preset height condition is expressed as: h is g ≤h max -h m Wherein h is max Represents the preset maximum flight altitude, h, of the drone m The relative ground height specified by the target flight mission is represented, further, if the relative ground height specified by the target flight mission is met, it is proved that the unmanned aerial vehicle can fly over the altitude of the node, the node is used as a mission reachable node, the node is set to be 0, if the relative ground height specified by the target flight mission is not met, it is proved that the unmanned aerial vehicle cannot cross the altitude of the node, the node is used as a barrier node, the node is set to be 1, finally, the two-dimensional mission flight profile is formed based on all mission reachable nodes and barrier nodes, and referring to fig. 6, fig. 6 is a two-dimensional mission flight profile diagram in the embodiment of the application, wherein a black area in the diagram is a barrier area formed by each barrier node.
According to the scheme, all nodes in the target track planning space are traversed through the preset step length, and then for each node, if the altitude corresponding to the node meets the preset height condition, the node is used as a task reachable node; if the altitude corresponding to the node does not meet the preset altitude condition, the node is used as an obstacle node, and further, the two-dimensional task flight profile is formed based on each task reachable node and each obstacle node, so that the three-dimensional track planning problem is reduced to a two-dimensional plane by dividing all nodes in the target track planning space into the task reachable nodes and the obstacle nodes, and feasible two-dimensional tracks can be quickly searched in the two-dimensional task flight profile.
Further, referring to fig. 7, based on the first embodiment in the present application, in another embodiment of the present application, the step S31: based on the starting node and the target node, performing cost evaluation on each node in the two-dimensional task flight profile through an A-x algorithm, and selecting a track route with the minimum cost as the target two-dimensional track, wherein the method comprises the following steps of:
step S311, the starting node is taken as a current node, and the current node is placed in an open table;
step S312, inquiring each task reachable node adjacent to the current node, and putting each task reachable node into an open table;
step S313, deleting the current node in the open table and putting the current node into a close table;
step S314, selecting a task reachable node with the minimum cost from the starting node to the target node from an open table as a next node, setting the current node as a father node of the next node, and putting the rest task reachable nodes into a close table;
step S315, taking the next node as the current node, and returning to execute the steps: inquiring each task reachable node adjacent to the current node, and putting each task reachable node into an open table until the next node is the target node;
and step S316, performing iterative backtracking from the target node to the starting node to form the target two-dimensional flight path.
In this embodiment, it should be noted that, in order to distinguish the states of each node, the a-x algorithm creates an open table and a close table, where the open table is used to store the nodes to be retrieved, and the close table is used to store the nodes that have been retrieved.
Firstly, the starting node is used as a current node, the current node is placed in an open table, a close table is set to be empty, then each node adjacent to the current node is inquired, each task reachable node is stored in the open table based on each adjacent node, furthermore, the current node is deleted from the open table, the current node is placed in the close table, and then the corresponding cost from the starting node to the target node is calculated based on each task reachable node in the open table, wherein the cost calculation method comprises the following steps: f (n) (+ h (n), where f (n) is the estimated cost from the start node to the target node via node n, g (n) is the actual cost from the start node to node n in the state space, h (n) is the estimated cost of the best track from node n to the target node, in one possible implementation, the cost may be determined based on the distance between the task-reachable node and the current node, in some embodiments, the distance cost is positively correlated with the distance length, and then the task reachable node with the minimum cost from the starting node to the target node is selected as the next node, setting the current node as the father node of the next node, and putting the rest nodes with the minimum non-cost into a close table, wherein, the next node is further taken as the current node, so as to return to execute step S312: querying each task reachable node adjacent to the current node, and placing each task reachable node in an open table until a next node is the target node, when the next node is determined to be the target node, ending the loop traversal of the a-x algorithm, and then performing iteration backtracking from the target node to the start node according to a father node associated with each node to form the target two-dimensional track, referring to fig. 8, where fig. 8 is a two-dimensional track topographic map determined in the embodiment of the present application, so that a three-dimensional track can be obtained by adding a corresponding altitude to the target two-dimensional track, referring to fig. 9, where fig. 9 is an initial three-dimensional track topographic map determined in the embodiment of the present application.
According to the scheme, cost evaluation is carried out through the A-algorithm based on the initial node and the target node, the path with the minimum cost is obtained through planning, the feasibility of path planning is guaranteed, the energy consumption of the unmanned aerial vehicle can be reduced, the characteristics of high speed and high efficiency of the algorithm are utilized, the path planning from the initial node to the target node is automatically completed through the cyclic operation of the nodes one by one, and the efficiency of the path planning is improved.
Further, referring to fig. 10, based on the first embodiment in the present application, in another embodiment of the present application, the step S41 described above: and circularly traversing each track point in the initial three-dimensional track, and performing height adjustment on the track points with the heights not meeting the preset track height adjustment constraint until all the track points meet the preset track height adjustment constraint, wherein the step of obtaining the ground-imitating flight track of the unmanned aerial vehicle comprises the following steps:
step S411, taking the initial node in the initial three-dimensional track as a track point to be corrected;
step S412, calculating the climbing rate or sinking rate of the waypoint to be corrected;
step S413, if the climbing rate does not meet the climbing rate constraint, updating the height of the waypoint to be corrected; or if the sinking rate does not meet the sinking rate constraint, updating the height of the waypoint to be corrected;
step S414, if the waypoint to be corrected is not the initial node, calculating a longitudinal curvature radius corresponding to the waypoint to be corrected, and if the longitudinal curvature radius does not meet the longitudinal curvature radius constraint, updating the height of the waypoint to be corrected;
step S415, taking the next track point in the initial three-dimensional track as a track point to be corrected, and returning to the execution step: calculating the climbing rate or the sinking rate of the track point to be corrected until all track points of the initial three-dimensional track are traversed to obtain each corrected track point;
step S416, determining the corrected initial three-dimensional track based on each corrected track point, and returning to the execution step: and taking the initial node in the initial three-dimensional track as a track point to be corrected until no track point needing to be updated exists in the corrected initial three-dimensional track, so as to obtain the ground-imitating flight track of the unmanned aerial vehicle.
In this embodiment, specifically, the real node is first used as a waypoint to be corrected, and then based on the waypoint to be corrected and a next waypoint in the initial three-dimensional trajectory, a climbing rate or a sinking rate of the waypoint to be corrected is calculated, where the climbing rate or the sinking rate is calculated according to the following formula:
wherein k is i Representing the climbing rate or sinking rate, x, corresponding to the waypoint to be corrected i 、y i 、z i Is the target coordinate position, x, of the waypoint to be corrected i+1 、y i+1 、z i+1 Representing the target coordinate position of the next track point, and updating the height of the track point to be corrected if the climbing rate is greater than a preset maximum climbing rate, for example, if k i >(k climb ) max Then z is i ＝z i+1 -s i (k climb ) max Wherein (k) climb ) max Representing the preset maximum climb rate. Or if the sinking rate is less than the negative value of the preset maximum sinking rate, updating the height of the waypoint to be corrected, for example, if k is less than the negative value of the preset maximum sinking rate i <-(k descend ) max Then the altitude update operation is performed: z is a radical of i+1 ＝z i -s i (k descend ) max Wherein (k) descend ) max Representing the preset maximum sinking rate.
It should be further noted that, because the calculation of the longitudinal curvature radius needs to be obtained by approximate calculation from the coordinates of three consecutive track points, the longitudinal curvature radius of the start node does not need to be calculated, and further, if the current track point to be corrected is not the start node, the longitudinal curvature radius of the track point to be corrected is calculated according to the target coordinate positions corresponding to two adjacent track points before and after the track point to be corrected, where the longitudinal curvature radius calculation formula is as follows:
ri denotes the longitudinal radius of curvature, z' and z "are the first and second derivatives, respectively, of the waypoint to be corrected, wherein,
wherein z is i+1 Representing the z-axis coordinate, z, corresponding to a track point subsequent to the track point to be corrected i Representing the z-axis coordinate, z, corresponding to the waypoint to be corrected i-1 Representing the z-axis coordinate, s, corresponding to a track point preceding the track point to be corrected i ＝||(x i ，y i )-(x i+1 ，y i+1 )||,s i-1 ＝||(x i-1 ，y i-1 )-(x i ，y i )||,(x i ，y i ) Representing the coordinates of the locus point to be corrected on the x and y axes, (x) i+1 ，y i+1 ) Representing the coordinates of a track point to be corrected on the x and y axes (x) i-1 ，y i-1 ) And representing the coordinates of a track point before the track point to be corrected on the x and y axes. And further if the longitudinal curvature radius of the waypoint to be corrected is smaller than the preset minimum longitudinal curvature radius, namely R i <R min Wherein R is min And if the preset minimum longitudinal curvature radius is represented, updating the height of the waypoint to be corrected, wherein the height updating formula is as follows:
and then taking the next track point in the initial three-dimensional track as a track point to be corrected, and returning to execute the step S412: calculating the climbing rate or sinking rate of the course point to be corrected until all course points of the initial three-dimensional trajectory are traversed to obtain each corrected course point corrected in the current round, determining the corrected initial three-dimensional trajectory based on each corrected course point, and returning to execute the step S411: will initial node in the initial three-dimensional orbit is as waiting to revise the track point to carry out the altitude mixture control operation of new round, until initial three-dimensional orbit after the revision does not have the track point that needs the renewal, obtains unmanned aerial vehicle imitative ground flight track, further, refer to fig. 11, fig. 11 is the three-dimensional orbit topographic map after the altitude mixture control in this application embodiment, refer to fig. 12, fig. 12 is the comparison sketch of topographic height and three-dimensional track adjustment front and back height in this application embodiment, wherein, former track height is the height of each track point in initial three-dimensional orbit, and the track height does after the adjustment in unmanned aerial vehicle imitative ground flight track each track point's in height, the topographic height is the altitude that each track point corresponds.
This application has realized through the height of adjusting each track point in the initial three-dimensional orbit through above-mentioned scheme, obtains satisfying the unmanned aerial vehicle imitative ground flight path of presetting track altitude mixture control restraint to make based on unmanned aerial vehicle imitative ground flight path improves unmanned aerial vehicle at the security of flight process.
Referring to fig. 13, fig. 13 is a schematic structural diagram of a drone of a hardware operating environment according to an embodiment of the present application.
As shown in fig. 13, the drone may include: a processor 1001, such as a CPU, a memory 1005, and a communication bus 1002. The communication bus 1002 is used to realize connection and communication between the processor 1001 and the memory 1005. The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a memory device separate from the processor 1001 described above.
Optionally, the drone may also include a rectangular user interface, a network interface, cameras, RF (Radio Frequency) circuitry, sensors, audio circuitry, WiFi modules, and so forth. The rectangular user interface may comprise a Display screen (Display), an input sub-module such as a Keyboard (Keyboard), and the optional rectangular user interface may also comprise a standard wired interface, a wireless interface. The network interface may optionally include a standard wired interface, a wireless interface (e.g., WIFI interface).
Those skilled in the art will appreciate that the drone structure shown in fig. 13 does not constitute a limitation on drones, and may include more or fewer components than shown, or some components in combination, or a different arrangement of components.
As shown in fig. 13, a memory 1005, which is a kind of computer storage medium, may include therein an operating network communication module and a program of the unmanned aerial vehicle ground imitating flight route automatic planning method. The operating device is a program for managing and controlling hardware and software resources of the unmanned aerial vehicle, and supports the automatic planning method program of the ground-imitating flight path of the unmanned aerial vehicle and the operation of other software and/or programs. The network communication module is used for realizing communication among components in the storage 1005 and communication with other hardware and software in the unmanned aerial vehicle ground-imitating flight path automatic planning device.
In the unmanned aerial vehicle shown in fig. 13, the processor 1001 is configured to execute the program of the automatic planning method for the ground imitating flight route of the unmanned aerial vehicle stored in the memory 1005, so as to implement any one of the steps of the automatic planning method for the ground imitating flight route of the unmanned aerial vehicle described above.
The specific implementation mode of the unmanned aerial vehicle is basically the same as that of each embodiment of the automatic planning method for the ground-imitating flight route of the unmanned aerial vehicle, and is not repeated here.
In addition, please refer to fig. 14, fig. 14 is a functional module schematic diagram of the automatic planning device for the ground-imitating flight route of the unmanned aerial vehicle according to the present application, the present application further provides an automatic planning device for the ground-imitating flight route of the unmanned aerial vehicle, the automatic planning device for the ground-imitating flight route of the unmanned aerial vehicle comprises:
the system comprises a construction module, a data processing module and a data processing module, wherein the construction module is used for constructing a target track planning space of a target flight task, and the target flight task comprises an initial node and a target node;
the extraction module is used for extracting a two-dimensional task flight profile based on the target track planning space;
the path searching module is used for searching paths of the two-dimensional task flight profile to obtain a target two-dimensional track, and adding a preset track height to each track point in the target two-dimensional track to obtain an initial three-dimensional track;
and the height adjusting module is used for adjusting the height of each track point in the initial three-dimensional track according to a preset track height adjusting constraint to obtain the ground-imitating flight track of the unmanned aerial vehicle.
Optionally, the building module is further configured to:
acquiring a geographic space coordinate of a target area corresponding to the target flight task, wherein the geographic space coordinate comprises a terrain longitude, a terrain latitude and an altitude;
converting the geographic space coordinate to a target coordinate position in a preset constructed target rectangular coordinate system, wherein the target rectangular coordinate system is a coordinate system constructed by taking the starting node as a coordinate origin;
carrying out triangulation processing on the target coordinate position to obtain a target subdivision result;
and carrying out spatial interpolation processing on the target subdivision result to obtain the target track planning space.
Optionally, the building module is further configured to:
converting the geographic space coordinate to a coordinate position of a pre-constructed geocentric rectangular coordinate system;
selecting a coordinate position corresponding to the starting node as a reference point, and constructing the target rectangular coordinate system based on the reference point;
and converting the coordinate position of the earth center rectangular coordinate system to a target coordinate position corresponding to the target rectangular coordinate system.
Optionally, the extracting module is further configured to:
traversing all nodes in the target track planning space through a preset step length;
for each node, if the altitude corresponding to the node meets a preset altitude condition, taking the node as a task reachable node; if the altitude corresponding to the node does not meet the preset altitude condition, taking the node as a barrier node;
and forming the two-dimensional task flight profile based on each task reachable node and each obstacle node.
Optionally, the path searching module is further configured to:
based on the starting node and the target node, performing cost evaluation on each node in the two-dimensional task flight profile through an A-x algorithm, and selecting a track route with the minimum cost as the target two-dimensional track.
Optionally, the path searching module is further configured to:
taking the starting node as a current node, and putting the current node into an open table;
inquiring each task reachable node adjacent to the current node, and putting each task reachable node into an open table;
deleting the current node in the open table, and putting the current node into a close table;
selecting a task reachable node with the minimum cost from the starting node to the target node from an open table as a next node, setting the current node as a parent node of the next node, and putting the other task reachable nodes into a close table;
taking the next node as the current node, and returning to execute the steps: inquiring each task reachable node adjacent to the current node, and putting each task reachable node into an open table until the next node is the target node;
and performing iterative backtracking from the target node to the starting node to form the target two-dimensional flight path.
Optionally, the height adjustment module is further configured to:
and circularly traversing each track point in the initial three-dimensional track, and performing height adjustment on the track points with the heights not meeting the preset track height adjustment constraint until all the track points meet the preset track height adjustment constraint to obtain the ground-imitating flight track of the unmanned aerial vehicle.
Optionally, the height adjustment module is further configured to:
taking the initial node in the initial three-dimensional track as a track point to be corrected;
calculating the climbing rate or sinking rate of the waypoint to be corrected;
if the climbing rate does not meet the climbing rate constraint, updating the height of the waypoint to be corrected; or if the sinking rate does not meet the sinking rate constraint, updating the height of the waypoint to be corrected;
if the waypoint to be corrected is not the initial node, calculating a longitudinal curvature radius corresponding to the waypoint to be corrected, and if the longitudinal curvature radius does not meet the longitudinal curvature radius constraint, updating the height of the waypoint to be corrected;
taking the next track point in the initial three-dimensional track as a track point to be corrected, and returning to the executing step: calculating the climbing rate or sinking rate of the course point to be corrected until all course points of the initial three-dimensional trajectory are traversed to obtain each corrected course point;
determining a corrected initial three-dimensional track based on each corrected track point, and returning to the execution step: and taking the initial node in the initial three-dimensional track as a track point to be corrected until no track point needing to be updated exists in the corrected initial three-dimensional track, so as to obtain the ground-imitating flight track of the unmanned aerial vehicle.
The specific implementation mode of the automatic planning device for the ground-imitating flight route of the unmanned aerial vehicle is basically the same as that of each embodiment of the automatic planning method for the ground-imitating flight route of the unmanned aerial vehicle, and is not repeated here.
The embodiment of the application provides a storage medium, the storage medium is a computer-readable storage medium, and the computer-readable storage medium stores one or more programs, which can be further executed by one or more processors for implementing the steps of the unmanned aerial vehicle ground-imitating flight path automatic planning method.
The specific implementation manner of the computer-readable storage medium of the present application is substantially the same as that of each embodiment of the above unmanned aerial vehicle ground-imitating flight path automatic planning method, and is not described herein again.
The above description is only a preferred embodiment of the present application, and not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings, or which are directly or indirectly applied to other related technical fields, are included in the scope of the present application.
Claims (10)
1. An unmanned aerial vehicle ground-imitating flight route automatic planning method is characterized in that the unmanned aerial vehicle ground-imitating flight route automatic planning method comprises the following steps:
constructing a target track planning space of a target flight task, wherein the target flight task comprises an initial node and a target node;
extracting a two-dimensional task flight profile based on the target track planning space;
performing path search on the two-dimensional task flight profile to obtain a target two-dimensional flight path, and adding a preset flight path height to each flight path point in the target two-dimensional flight path to obtain an initial three-dimensional trajectory;
and adjusting the height of each track point in the initial three-dimensional track according to a preset track height adjustment constraint to obtain the ground-imitating flight track of the unmanned aerial vehicle.
2. The method for automatically planning the simulated ground flight route of the unmanned aerial vehicle according to claim 1, wherein the step of constructing a target track planning space for the target flight mission comprises:
acquiring a geographic space coordinate of a target area corresponding to the target flight task, wherein the geographic space coordinate comprises a terrain longitude, a terrain latitude and an altitude;
converting the geographic space coordinate to a target coordinate position in a preset constructed target rectangular coordinate system, wherein the target rectangular coordinate system is a coordinate system constructed by taking the starting node as a coordinate origin;
carrying out triangulation processing on the target coordinate position to obtain a target subdivision result;
and carrying out spatial interpolation processing on the target subdivision result to obtain the target track planning space.
3. The method of claim 2, wherein the step of transforming the geospatial coordinates to a target coordinate position in a pre-established, constructed target rectangular coordinate system comprises:
converting the geographic space coordinate to a coordinate position of a pre-constructed geocentric rectangular coordinate system;
selecting a coordinate position corresponding to the starting node as a reference point, and constructing the target rectangular coordinate system based on the reference point;
and converting the coordinate position of the earth center rectangular coordinate system to a target coordinate position corresponding to the target rectangular coordinate system.
4. The method for automatically planning the simulated ground flight route of the unmanned aerial vehicle according to claim 1, wherein the step of extracting a two-dimensional mission flight profile based on the target track planning space comprises:
traversing all nodes in the target track planning space through a preset step length;
for each node, if the altitude corresponding to the node meets a preset altitude condition, taking the node as a task reachable node; if the altitude corresponding to the node does not meet the preset altitude condition, taking the node as a barrier node;
and forming the two-dimensional task flight profile based on each task reachable node and each obstacle node.
5. The automatic planning method for the ground-imitating flight route of the unmanned aerial vehicle as claimed in claim 4, wherein the step of searching the path of the two-dimensional mission flight profile to obtain the target two-dimensional flight path comprises:
based on the starting node and the target node, performing cost evaluation on each node in the two-dimensional task flight profile through an A-x algorithm, and selecting a track route with the minimum cost as the target two-dimensional track.
6. The method for automatically planning the simulated ground flight route of the unmanned aerial vehicle according to claim 5, wherein the step of performing cost evaluation on each node in the two-dimensional mission flight profile through an A-x algorithm based on the starting node and the target node, and selecting the route with the minimum cost as the target two-dimensional route comprises the following steps:
taking the starting node as a current node, and putting the current node into an open table;
inquiring each task reachable node adjacent to the current node, and putting each task reachable node into an open table;
deleting the current node in the open table, and putting the current node into a close table;
selecting a task reachable node with the minimum cost from the starting node to the target node from an open table as a next node, setting the current node as a father node of the next node, and putting the rest task reachable nodes into a close table;
taking the next node as the current node, and returning to execute the steps: inquiring each task reachable node adjacent to the current node, and putting each task reachable node into an open table until the next node is the target node;
and performing iterative backtracking from the target node to the starting node to form the target two-dimensional flight path.
7. The unmanned aerial vehicle ground-imitating flight path automatic planning method of claim 1, wherein the preset path height adjustment constraints include a climb rate constraint, a sink rate constraint and a longitudinal curvature radius constraint,
the step of adjusting the height of each track point in the initial three-dimensional track according to the preset track height adjustment constraint to obtain the ground-imitating flight track of the unmanned aerial vehicle comprises the following steps of:
and circularly traversing each track point in the initial three-dimensional track, and performing height adjustment on the track points with the heights not meeting the preset track height adjustment constraint until all the track points meet the preset track height adjustment constraint to obtain the ground-imitating flight track of the unmanned aerial vehicle.
8. The automatic planning method for the ground-imitating flight route of the unmanned aerial vehicle according to claim 7, wherein the step of circularly traversing each track point in the initial three-dimensional track, and adjusting the height of the track point which does not satisfy the preset track height adjustment constraint until all the track points satisfy the preset track height adjustment constraint, and obtaining the ground-imitating flight route of the unmanned aerial vehicle comprises the following steps:
taking the initial node in the initial three-dimensional track as a track point to be corrected;
calculating the climbing rate or sinking rate of the waypoint to be corrected;
if the climbing rate does not meet the climbing rate constraint, updating the height of the waypoint to be corrected; or if the sinking rate does not meet the sinking rate constraint, updating the height of the waypoint to be corrected;
if the waypoint to be corrected is not the initial node, calculating a longitudinal curvature radius corresponding to the waypoint to be corrected, and if the longitudinal curvature radius does not meet the longitudinal curvature radius constraint, updating the height of the waypoint to be corrected;
taking the next track point in the initial three-dimensional track as a track point to be corrected, and returning to the executing step: calculating the climbing rate or sinking rate of the course point to be corrected until all course points of the initial three-dimensional trajectory are traversed to obtain each corrected course point;
determining a corrected initial three-dimensional track based on each corrected track point, and returning to the execution step: and taking the initial node in the initial three-dimensional track as a track point to be corrected until no track point needing to be updated exists in the corrected initial three-dimensional track, so as to obtain the ground-imitating flight track of the unmanned aerial vehicle.
9. A drone, characterized in that it comprises: a memory, a processor and a program of the automatic planning method of the ground-imitating flight route of the unmanned aerial vehicle stored on the memory,
the automatic planning method program for the ground-imitating flight route of the unmanned aerial vehicle is executed by the processor to realize the automatic planning method for the ground-imitating flight route of the unmanned aerial vehicle according to any one of claims 1 to 8.
10. A storage medium which is a computer-readable storage medium, wherein the computer-readable storage medium stores thereon a program of a method for automatically planning a ground-imitating flight route of an unmanned aerial vehicle, and the program of the method is executed by a processor to implement the method for automatically planning the ground-imitating flight route of the unmanned aerial vehicle according to any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210570286.1A CN114840030A (en) | 2022-05-24 | 2022-05-24 | Unmanned aerial vehicle ground-imitating flight route automatic planning method, unmanned aerial vehicle and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210570286.1A CN114840030A (en) | 2022-05-24 | 2022-05-24 | Unmanned aerial vehicle ground-imitating flight route automatic planning method, unmanned aerial vehicle and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114840030A true CN114840030A (en) | 2022-08-02 |
Family
ID=82573182
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210570286.1A Pending CN114840030A (en) | 2022-05-24 | 2022-05-24 | Unmanned aerial vehicle ground-imitating flight route automatic planning method, unmanned aerial vehicle and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114840030A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115145313A (en) * | 2022-08-31 | 2022-10-04 | 中国电子科技集团公司第二十八研究所 | Method for predicting and correcting moving target track in real time |
| CN115268504A (en) * | 2022-09-29 | 2022-11-01 | 四川腾盾科技有限公司 | Ground-imitating flight path planning method for large unmanned aerial vehicle |
| CN115435776A (en) * | 2022-11-03 | 2022-12-06 | 成都沃飞天驭科技有限公司 | Method and device for displaying three-dimensional airway route, aircraft and storage medium |
| CN115585814A (en) * | 2022-12-12 | 2023-01-10 | 北京理工大学 | Aircraft variable-scale terrain following method based on settlement mechanism |
| CN117274845A (en) * | 2023-11-22 | 2023-12-22 | 山东中宇航空科技发展有限公司 | Method, system, equipment and storage medium for capturing images of flying unmanned aerial vehicle |
-
2022
- 2022-05-24 CN CN202210570286.1A patent/CN114840030A/en active Pending
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115145313A (en) * | 2022-08-31 | 2022-10-04 | 中国电子科技集团公司第二十八研究所 | Method for predicting and correcting moving target track in real time |
| CN115145313B (en) * | 2022-08-31 | 2023-01-31 | 中国电子科技集团公司第二十八研究所 | Method for predicting and correcting moving target track in real time |
| CN115268504A (en) * | 2022-09-29 | 2022-11-01 | 四川腾盾科技有限公司 | Ground-imitating flight path planning method for large unmanned aerial vehicle |
| CN115268504B (en) * | 2022-09-29 | 2022-12-27 | 四川腾盾科技有限公司 | Ground-imitating flight path planning method for large unmanned aerial vehicle |
| CN115435776A (en) * | 2022-11-03 | 2022-12-06 | 成都沃飞天驭科技有限公司 | Method and device for displaying three-dimensional airway route, aircraft and storage medium |
| CN115435776B (en) * | 2022-11-03 | 2023-03-14 | 成都沃飞天驭科技有限公司 | Method and device for displaying three-dimensional airway route, aircraft and storage medium |
| CN115585814A (en) * | 2022-12-12 | 2023-01-10 | 北京理工大学 | Aircraft variable-scale terrain following method based on settlement mechanism |
| CN117274845A (en) * | 2023-11-22 | 2023-12-22 | 山东中宇航空科技发展有限公司 | Method, system, equipment and storage medium for capturing images of flying unmanned aerial vehicle |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114840030A (en) | Unmanned aerial vehicle ground-imitating flight route automatic planning method, unmanned aerial vehicle and storage medium | |
| CN107169608B (en) | Distribution method and device for multiple unmanned aerial vehicles to execute multiple tasks | |
| US20180180428A1 (en) | Navigation for vehicles | |
| CN106599108A (en) | Method for constructing multi-mode environmental map in three-dimensional environment | |
| CN106054920A (en) | Unmanned aerial vehicle flight path planning method and device | |
| CN112097770B (en) | Multi-unmanned aerial vehicle collaborative full coverage path planning method and device, storage medium and terminal | |
| CN109916416A (en) | Lane line data processing and update method, device and equipment | |
| CN102901500A (en) | Aircraft optimal path determination method based on mixed probability A star and agent | |
| CN109737965B (en) | Method for optimally selecting navigation path in three-dimensional virtual scene | |
| CN113776534B (en) | Unmanned aerial vehicle three-dimensional time-varying airspace navigation method based on three-dimensional subdivision grid | |
| CN112985408B (en) | Path planning optimization method and system | |
| CN107632616B (en) | A kind of unmanned plane collaboration paths planning method based on three-dimensional space curve | |
| CN106772366B (en) | Real-time autonomous control method on the star of satellite microwave imaging | |
| CN112084853A (en) | Footprint prediction method, footprint prediction device and humanoid robot | |
| US11199411B2 (en) | Systems and methods for utilizing graph based map information as priors for localization using particle filter | |
| CN115903888A (en) | Rotor unmanned aerial vehicle autonomous path planning method based on longicorn swarm algorithm | |
| CN115200585A (en) | Unmanned aerial vehicle track planning method and device based on airspace grid and electronic equipment | |
| CN110366188B (en) | Interference measurement point deployment method, interference measurement path planning method and system | |
| CN108268514A (en) | High in the clouds map map rejuvenation equipment based on Octree | |
| CN116182859A (en) | Path planning method and device, equipment and storage medium | |
| CN113761647A (en) | Simulation method and system of unmanned cluster system | |
| Gao et al. | SLARM: Simultaneous localization and radio mapping for communication-aware connected robot | |
| CN116954239B (en) | Unmanned aerial vehicle track planning method and system based on improved particle swarm optimization | |
| CN113810846B (en) | Indoor positioning method based on WiFi and IMU fusion | |
| CN114173281B (en) | TOA-based positioning system beacon node optimization layout method in indoor NLOS environment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20230629 Address after: 610000 No. 601 and 602, block a, building 5, No. 200, Tianfu Fifth Street, Chengdu hi tech Zone, Chengdu (Sichuan) pilot Free Trade Zone, Sichuan Province Applicant after: SICHUAN AOSSCI TECHNOLOGY Co.,Ltd. Applicant after: BEIHANG University Address before: 610000 No. 601 and 602, block a, building 5, No. 200, Tianfu Fifth Street, Chengdu hi tech Zone, Chengdu (Sichuan) pilot Free Trade Zone, Sichuan Province Applicant before: SICHUAN AOSSCI TECHNOLOGY Co.,Ltd. Applicant before: BEIHANG University Applicant before: ZHEJIANG GEELY HOLDING GROUP Co.,Ltd. |