CN115562335A - 3D map-based unmanned aerial vehicle flight control method, system and medium - Google Patents
3D map-based unmanned aerial vehicle flight control method, system and medium Download PDFInfo
- Publication number
- CN115562335A CN115562335A CN202211200326.XA CN202211200326A CN115562335A CN 115562335 A CN115562335 A CN 115562335A CN 202211200326 A CN202211200326 A CN 202211200326A CN 115562335 A CN115562335 A CN 115562335A
- Authority
- CN
- China
- Prior art keywords
- data
- aerial vehicle
- unmanned aerial
- map
- map data
- 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
- 238000000034 method Methods 0.000 title claims abstract description 47
- RZVHIXYEVGDQDX-UHFFFAOYSA-N 9,10-anthraquinone Chemical compound C1=CC=C2C(=O)C3=CC=CC=C3C(=O)C2=C1 RZVHIXYEVGDQDX-UHFFFAOYSA-N 0.000 title claims abstract description 31
- 238000004891 communication Methods 0.000 claims description 32
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000012544 monitoring process Methods 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 238000002372 labelling Methods 0.000 description 2
- 239000003550 marker Substances 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 208000035473 Communicable disease Diseases 0.000 description 1
- 241001465754 Metazoa Species 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 208000015181 infectious disease Diseases 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
- G05D1/106—Change initiated in response to external conditions, e.g. avoidance of elevated terrain or of no-fly zones
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/05—Geographic models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
- G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10028—Range image; Depth image; 3D point clouds
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30241—Trajectory
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Remote Sensing (AREA)
- Software Systems (AREA)
- Geometry (AREA)
- Theoretical Computer Science (AREA)
- Computer Graphics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Aviation & Aerospace Engineering (AREA)
- Radar, Positioning & Navigation (AREA)
- Automation & Control Theory (AREA)
- Navigation (AREA)
Abstract
The invention discloses a 3D map-based unmanned aircraft flight control method, a system and a medium, wherein the method comprises the following steps: acquiring 3D map data and positioning data of the unmanned aerial vehicle; based on a plurality of preset reference points in the 3D map data and the positioning data, identifying and obtaining position data of the unmanned aerial vehicle in the 3D map data; acquiring panoramic image data of the unmanned aerial vehicle, and correcting the flight path of the unmanned aerial vehicle based on the panoramic image data and the reference point; and acquiring spatial data of the unmanned aircraft during flight, and performing obstacle avoidance control of the unmanned aircraft in flight by combining the 3D map data. The method can position the unmanned aircraft and correct the flight path based on the 3D map data, and can perform obstacle avoidance control to reduce the damage of the unmanned aircraft in the automatic flight process of the unmanned aircraft.
Description
Technical Field
The invention relates to the technical field of unmanned control, in particular to a 3D map-based unmanned aircraft flight control method, system and medium.
Background
Along with the continuous development of science and technology, the application of the unmanned aircraft is unprecedentedly developed, and compared with the piloted aircraft, the piloted aircraft is usually more suitable for repeated mechanical tasks or tasks with high risk, and in the civil aspect, the piloted aircraft and the industrial application are really just needed; the unmanned aerial vehicle is applied to the fields of aerial photography, agriculture, plant protection, miniature self-timer, express transportation, disaster relief, wild animal observation, infectious disease monitoring, surveying and mapping, news reporting, power inspection, disaster relief, movie and television shooting, romantic manufacturing and the like, and the application of the unmanned aerial vehicle is greatly expanded.
Meanwhile, in the flying process of the unmanned aircraft, especially during automatic navigation, the surrounding environment of a flight line changes constantly, so that the flying surrounding environment of the unmanned aircraft needs to be monitored, and meanwhile, the traditional unmanned aircraft utilizes GPS (global positioning system) positioning or Beidou navigation positioning during navigation, so that the actual terrain where the unmanned aircraft is located cannot be well utilized, and therefore the problem needs to be solved urgently.
Disclosure of Invention
The invention aims to provide a method, a system and a medium for controlling the flight of an unmanned aerial vehicle based on a 3D map, which can be used for positioning the unmanned aerial vehicle and correcting a flight path based on 3D map data, and can be used for carrying out obstacle avoidance control to reduce the damage of the unmanned aerial vehicle in the automatic flight process of the unmanned aerial vehicle.
The invention provides a flight control method of an unmanned aircraft based on a 3D map, which comprises the following steps:
acquiring 3D map data and positioning data of the unmanned aerial vehicle;
based on a plurality of preset reference points in the 3D map data and the positioning data, identifying and obtaining position data of the unmanned aerial vehicle in the 3D map data;
acquiring panoramic image data of the unmanned aircraft in the flying process of the unmanned aircraft, and correcting the flying path of the unmanned aircraft based on the panoramic image data and the reference point;
and acquiring spatial data of the unmanned aircraft during flight, and performing obstacle avoidance control of the unmanned aircraft in flight by combining the 3D map data.
In this scheme, the acquiring of the 3D map data and the positioning data of the unmanned aerial vehicle specifically includes:
establishing communication connection with a preset communication base station and/or a preset information transceiver device to acquire the 3D map data;
establishing a communication connection with the unmanned aerial vehicle to identify the positioning data, wherein the positioning data includes at least an unmanned aerial vehicle longitude value, an unmanned aerial vehicle latitude value, an unmanned aerial vehicle ground altitude value, and an unmanned aerial vehicle angle of flight value.
In this scheme, the identifying and obtaining the position data of the unmanned aerial vehicle in the 3D map data based on a plurality of preset reference points in the 3D map data in combination with the positioning data specifically includes:
matching a plurality of reference points corresponding to the current unmanned aerial vehicle based on preset key point cloud data in the 3D map data, wherein the number of the reference points at least comprises three;
and obtaining the position data based on the reference point and the positioning data, wherein the position data at least comprises a horizontal coordinate parameter value, a vertical coordinate parameter value and a deflection angle parameter value.
In this scheme, the obtaining the position data based on the reference point in combination with the positioning data specifically includes:
obtaining the horizontal and vertical coordinate parameter values of the unmanned aircraft in a space coordinate system in the 3D map data based on the reference point in combination with the longitude value and the latitude value of the unmanned aircraft;
obtaining the vertical coordinate parameter value of the unmanned aerial vehicle in a spatial coordinate system in the 3D map data based on the reference point in combination with the ground flying height value of the unmanned aerial vehicle;
and obtaining the deflection angle parameter value of the spatial coordinate system of the unmanned aerial vehicle in the 3D map data based on the reference point and the flight angle value of the unmanned aerial vehicle.
In this scheme, the acquiring panoramic image data of the unmanned aerial vehicle, and correcting the flight path of the unmanned aerial vehicle based on the panoramic image data in combination with the reference point specifically include:
matching the key point cloud data in the corresponding 3D map data based on the panoramic image data;
identifying the corresponding reference points based on the matching result and marking, wherein the number of the marked reference points at least comprises three;
calculating the linear distance between each reference point and the unmanned aerial vehicle, and obtaining point position data of the current unmanned aerial vehicle in the space coordinate system based on at least three linear distances;
and judging a deviation value between the unmanned aerial vehicle and a preset track based on the point location data, and correcting the flight path of the unmanned aerial vehicle based on the point location data when the deviation value exceeds a limit threshold value.
In this scheme, the obtaining of the spatial data of the unmanned aerial vehicle during flight and the performing of the obstacle avoidance control of the unmanned aerial vehicle flight in combination with the 3D map data specifically include:
acquiring the spatial data based on point location data of the unmanned aerial vehicle in the spatial coordinate system, wherein the spatial data comprises the point location data and trajectory data formed by the point location data;
and identifying relative relation data of the unmanned aerial vehicle and obstacles in the 3D map data based on the spatial data, and performing obstacle avoidance control based on the relative relation data.
The second aspect of the present invention further provides a 3D map-based unmanned aircraft flight control system, which includes a memory and a processor, where the memory includes a 3D map-based unmanned aircraft flight control method program, and when executed by the processor, the 3D map-based unmanned aircraft flight control method program implements the following steps:
acquiring 3D map data and positioning data of the unmanned aerial vehicle;
based on a plurality of preset reference points in the 3D map data and the positioning data, identifying and obtaining position data of the unmanned aerial vehicle in the 3D map data;
acquiring panoramic image data of the unmanned aircraft in the flying process of the unmanned aircraft, and correcting the flying path of the unmanned aircraft based on the panoramic image data and the reference point;
and acquiring spatial data of the unmanned aircraft during flight, and performing obstacle avoidance control of the unmanned aircraft in flight by combining the 3D map data.
In this scheme, the acquiring of the 3D map data and the positioning data of the unmanned aerial vehicle specifically includes:
establishing communication connection with a preset communication base station and/or a preset information transceiver device to acquire the 3D map data;
establishing a communication connection with the unmanned aerial vehicle to identify the positioning data, wherein the positioning data includes at least an unmanned aerial vehicle longitude value, an unmanned aerial vehicle latitude value, an unmanned aerial vehicle ground altitude value, and an unmanned aerial vehicle angle of flight value.
In this scheme, the identifying and obtaining the position data of the unmanned aerial vehicle in the 3D map data based on a plurality of preset reference points in the 3D map data in combination with the positioning data specifically includes:
matching a plurality of reference points corresponding to the current unmanned aerial vehicle based on preset key point cloud data in the 3D map data, wherein the number of the reference points at least comprises three;
and obtaining the position data based on the reference point and the positioning data, wherein the position data at least comprises a horizontal coordinate parameter value, a vertical coordinate parameter value and a deflection angle parameter value.
In this scheme, the obtaining the position data based on the reference point in combination with the positioning data specifically includes:
obtaining the abscissa and ordinate parameter values of the unmanned aircraft in a spatial coordinate system in the 3D map data based on the reference point in combination with the longitude value and the latitude value of the unmanned aircraft;
obtaining the vertical coordinate parameter value of the unmanned aerial vehicle in a spatial coordinate system in the 3D map data based on the reference point and the ground flying height value of the unmanned aerial vehicle;
and obtaining the deflection angle parameter value of the space coordinate system of the unmanned aircraft in the 3D map data based on the reference point and the flight angle value of the unmanned aircraft.
In this scheme, the acquiring panoramic image data of the unmanned aerial vehicle, and correcting the flight path of the unmanned aerial vehicle based on the panoramic image data in combination with the reference point specifically include:
matching the key point cloud data in the corresponding 3D map data based on the panoramic image data;
identifying the corresponding reference points based on the matching result and marking, wherein the number of the marked reference points at least comprises three;
calculating the linear distance between each reference point and the unmanned aerial vehicle, and obtaining point position data of the current unmanned aerial vehicle in the space coordinate system based on at least three linear distances;
and judging a deviation value between the unmanned aerial vehicle and a preset track based on the point location data, and correcting the flight path of the unmanned aerial vehicle based on the point location data when the deviation value exceeds a limit threshold value.
In this scheme, the obtaining spatial data of the unmanned aerial vehicle during flight and performing obstacle avoidance control of the unmanned aerial vehicle during flight by combining with the 3D map data specifically include:
acquiring the spatial data based on point location data of the unmanned aerial vehicle in the spatial coordinate system, wherein the spatial data comprises the point location data and trajectory data formed by the point location data;
and identifying relative relation data of the unmanned aircraft and the obstacles in the 3D map data based on the spatial data, and performing obstacle avoidance control based on the relative relation data.
A third aspect of the invention provides a computer-readable storage medium, which contains a 3D map-based unmanned aircraft flight control method program for a machine, which, when executed by a processor, implements the steps of a 3D map-based unmanned aircraft flight control method as defined in any one of the above.
The invention discloses a 3D map-based pilotless aircraft flight control method, a system and a medium, which can be used for positioning the pilotless aircraft and correcting a flight path based on 3D map data, and can be used for carrying out obstacle avoidance control to reduce the damage of the pilotless aircraft in the automatic flight process of the pilotless aircraft.
Drawings
FIG. 1 shows a flow chart of a 3D map based unmanned aircraft flight control method of the present invention;
FIG. 2 is a schematic diagram of a spatial coordinate system of a 3D map-based unmanned aerial vehicle flight control method of the present invention;
FIG. 3 illustrates a schematic view of the unmanned aircraft positioning for a 3D map based unmanned aircraft flight control method of the present invention;
fig. 4 shows a block diagram of a 3D map based unmanned aircraft flight control system of the present invention.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention, taken in conjunction with the accompanying drawings and detailed description, is set forth below. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
Fig. 1 shows a flow chart of a 3D map-based unmanned aircraft flight control method of the present application.
As shown in fig. 1, the application discloses a flight control method of an unmanned aerial vehicle based on a 3D map, comprising the following steps:
s102, acquiring 3D map data and positioning data of the unmanned aerial vehicle;
s104, based on a plurality of preset reference points in the 3D map data and the positioning data, identifying and obtaining position data of the unmanned aerial vehicle in the 3D map data;
s106, acquiring panoramic image data of the unmanned aircraft in the flying process of the unmanned aircraft, and correcting the flying path of the unmanned aircraft based on the panoramic image data and the reference point;
and S108, acquiring spatial data of the unmanned aircraft during flying, and combining the 3D map data to perform obstacle avoidance control of the unmanned aircraft during flying.
It should be noted that, in this embodiment, first, the 3D map data and the positioning data are obtained, where the 3D map data is data input in advance or by human, and the positioning data is obtained based on GPS and/or beidou navigation, specifically, the positioning data at least includes a longitude value, a latitude value, a ground altitude value, and a flight angle value of an unmanned aerial vehicle, after the 3D map data and the positioning data are obtained, the position data of the unmanned aerial vehicle in the 3D map data may be obtained based on a plurality of reference points preset on the 3D map data and the positioning data, so that the position of the unmanned aerial vehicle may be identified based on the 3D map data, and then, during the flight of the unmanned aerial vehicle, the image data corresponding to the unmanned aerial vehicle is obtained, so that the flight path of the unmanned aerial vehicle is modified based on the panoramic image data and the reference point, so as to reduce the problem of collision avoidance of the unmanned aerial vehicle, and the problem of the flight of the unmanned aerial vehicle caused by combining the collision avoidance of the unmanned aerial vehicle with the positioning data and the unmanned aerial vehicle is reduced.
According to an embodiment of the present invention, the acquiring of the 3D map data and the positioning data of the unmanned aerial vehicle specifically includes:
establishing communication connection with a preset communication base station and/or a preset information transceiver to acquire the 3D map data;
establishing a communication connection with the unmanned aerial vehicle to identify the positioning data, wherein the positioning data includes at least an unmanned aerial vehicle longitude value, an unmanned aerial vehicle latitude value, an unmanned aerial vehicle ground altitude value, and an unmanned aerial vehicle angle of flight value.
In this embodiment, the 3D map data is obtained by establishing a communication connection with the communication base station and/or the information transceiver device, such as a router, and the 3D map data may be stored in advance by the communication base station or the information transceiver device, or may be obtained by forwarding the 3D map data through the communication base station or the information transceiver device; the positioning data corresponding to the unmanned aerial vehicle is identified by establishing a communication connection with the unmanned aerial vehicle, the communication connection is established by means of wireless Bluetooth and/or WiFi connection or wired connection, and the identified positioning data at least comprises an unmanned aerial vehicle longitude value, an unmanned aerial vehicle latitude value, an unmanned aerial vehicle ground flying height value and an unmanned aerial vehicle flying angle value, preferably, the heading value of the unmanned aerial vehicle and the like.
According to the embodiment of the present invention, the identifying and obtaining the position data of the unmanned aerial vehicle in the 3D map data based on a plurality of preset reference points in the 3D map data in combination with the positioning data specifically includes:
matching a plurality of reference points corresponding to the current unmanned aerial vehicle based on preset key point cloud data in the 3D map data, wherein the number of the reference points at least comprises three;
and obtaining the position data based on the reference point and the positioning data, wherein the position data at least comprises a horizontal coordinate parameter value, a vertical coordinate parameter value and a deflection angle parameter value.
It should be noted that, in this embodiment, when the unmanned aerial vehicle flies in an actual scene, an electronic map of the actual scene is obtained in the acquired 3D map data, the reference point corresponding to the unmanned aerial vehicle at present is matched through the key point cloud data preset in the 3D map data, the number of the reference points at least includes three, because three reference points can determine one point cloud, and then the position data of the unmanned aerial vehicle in the 3D map data can be obtained based on the reference points and the positioning data, where the position data at least includes a horizontal and vertical coordinate parameter value, a vertical coordinate parameter value, and a yaw angle parameter value, where the horizontal and vertical coordinate parameter value corresponds to the unmanned aerial vehicle longitude value and the unmanned aerial vehicle latitude value, the vertical coordinate parameter value corresponds to the unmanned aerial vehicle ground flight height value, and the yaw angle parameter value corresponds to the unmanned aerial vehicle flight angle value.
According to the embodiment of the present invention, the obtaining the position data based on the reference point and the positioning data specifically includes:
obtaining the horizontal and vertical coordinate parameter values of the unmanned aircraft in a space coordinate system in the 3D map data based on the reference point in combination with the longitude value and the latitude value of the unmanned aircraft;
obtaining the vertical coordinate parameter value of the unmanned aerial vehicle in a spatial coordinate system in the 3D map data based on the reference point and the ground flying height value of the unmanned aerial vehicle;
and obtaining the deflection angle parameter value of the space coordinate system of the unmanned aircraft in the 3D map data based on the reference point and the flight angle value of the unmanned aircraft.
In this embodiment, as shown in fig. 2, the 3D map data includes the spatial coordinate system thereof for labeling the spatial position of different objects in the current 3D map data, x is a horizontal axis of the spatial coordinate system, y is a vertical axis of the spatial coordinate system, z is a vertical axis of the spatial coordinate system, and α is a horizontal deflection angle of the spatial coordinate system, where, for an unmanned aircraft in the spatial coordinate system, the abscissa and ordinate parameter values may be obtained by combining the longitude value of the unmanned aircraft and the latitude value of the unmanned aircraft through the reference point pair; the vertical coordinate parameter value can be obtained by combining the ground flying height value of the unmanned aerial vehicle; and obtaining the deflection angle parameter value by combining the flight angle value of the unmanned aircraft.
According to an embodiment of the present invention, the acquiring panoramic image data of the unmanned aerial vehicle, and correcting a flight path of the unmanned aerial vehicle based on the panoramic image data and the reference point specifically includes:
matching the key point cloud data in the corresponding 3D map data based on the panoramic image data;
identifying the corresponding reference points based on the matching result and marking, wherein the number of the marked reference points at least comprises three;
calculating the linear distance between each reference point and the unmanned aerial vehicle, and obtaining point position data of the current unmanned aerial vehicle in the space coordinate system based on at least three linear distances;
and judging a deviation value between the unmanned aerial vehicle and a preset track based on the point location data, and correcting the flight path of the unmanned aerial vehicle based on the point location data when the deviation value exceeds a limit threshold value.
It should be noted that, in this embodiment, when the unmanned aerial vehicle travels along a preset trajectory, because a GPS positioning or a beidou positioning is relied on, and a physical deviation exists, in this embodiment, a point location of the unmanned aerial vehicle is defined by the reference point in the 3D map data to correct a flight path of the unmanned aerial vehicle, and a multipoint positioning method is specifically applied, specifically as shown in fig. 3, reference points a and B of the unmanned aerial vehicle on a horizontal plane of the 3D map data, reference points on different planes of the other two concentric spheres are points C and D, and position data of the current unmanned aerial vehicle in the 3D map data can be determined by calculating distances between the unmanned aerial vehicle and the different reference points, after the point location data is accurate to the corresponding point location, calculating based on a deviation value of the point location data and a preset track, wherein the deviation value is a distance between the current point location of the unmanned aerial vehicle and the corresponding point location on the track, and the calculation of the distance between the point location data and the point in the space is well known to those skilled in the art, and is not described herein again, after the deviation value is obtained, the magnitude of the deviation value and the limit threshold value is determined, and if the deviation value is greater than the limit threshold value, the position of the unmanned aerial vehicle is corrected based on the point location data (the accurate point location calculated by the reference point), so as to correct the flight path, wherein the limit threshold value may be "10cm".
According to the embodiment of the invention, the acquiring of the spatial data of the unmanned aerial vehicle during flying and the performing of the obstacle avoidance control of the unmanned aerial vehicle flying by combining with the 3D map data specifically include:
acquiring the spatial data based on point location data of the unmanned aerial vehicle in the spatial coordinate system, wherein the spatial data comprises the point location data and trajectory data formed by the point location data;
and identifying relative relation data of the unmanned aerial vehicle and obstacles in the 3D map data based on the spatial data, and performing obstacle avoidance control based on the relative relation data.
It should be noted that, in this embodiment, in the 3D map data, there are many objects occupying space that may affect the flight of the unmanned aerial vehicle, after point location data and/or trajectory data of the unmanned aerial vehicle are obtained, relative relationship data between the unmanned aerial vehicle and the obstacle may be determined, where the relative relationship data is a distance between the unmanned aerial vehicle and the obstacle, and similarly calculating a distance between two points is well known by those skilled in the art and is not described herein, and a point-taking position of the obstacle and the unmanned aerial vehicle is a central point corresponding to each object, after a relative distance is calculated, the relative distance and the safe distance are determined, and if the relative distance is smaller than the safe distance, the unmanned aerial vehicle is controlled to be away from the obstacle to perform obstacle avoidance control, where the safe distance may be "10m".
It is worth mentioning that the method further comprises identifying environmental data in the 3D map data for controlling the unmanned aerial vehicle.
It should be noted that, in this embodiment, the corresponding environment data is identified through the 3D map data, where the environment data includes weather data, temperature data, and humidity data, the unmanned aerial vehicle is controlled to sample the weather data of the field environment by identifying cloud layer transformation in the 3D map data, and the unmanned aerial vehicle is controlled to sample the temperature data of the field environment by identifying an outdoor temperature type in the 3D map data.
It is worth mentioning that the method further comprises identifying marker data in the 3D map data for controlling the unmanned aerial vehicle.
It should be noted that, in this embodiment, the 3D map data is transformed in real time, so that in this embodiment, the unmanned aerial vehicle can be controlled by identifying the tag data in the 3D map data, where the tag data at least includes: the unmanned aerial vehicle can be controlled to go to a corresponding place for monitoring by identifying corresponding marking data.
It is worth mentioning that the method further comprises identifying pop-up information in the 3D map data for controlling the unmanned aerial vehicle.
In this embodiment, when the unmanned aerial vehicle flies according to the 3D map data, the content of the pop-up window information popped up from the 3D map data may be identified to control the unmanned aerial vehicle, and for example, if the content of the pop-up window information is "recall to hangar", the unmanned aerial vehicle is controlled to return to hangar.
FIG. 4 shows a block diagram of a 3D map based unmanned aircraft flight control system of the present invention.
As shown in fig. 4, the present invention discloses a 3D map-based unmanned aerial vehicle flight control system, which includes a memory and a processor, wherein the memory includes a 3D map-based unmanned aerial vehicle flight control method program, and when executed by the processor, the 3D map-based unmanned aerial vehicle flight control method program implements the following steps:
acquiring 3D map data and positioning data of the unmanned aerial vehicle;
identifying and obtaining position data of the unmanned aircraft in the 3D map data based on a plurality of preset reference points in the 3D map data in combination with the positioning data;
acquiring panoramic image data of the unmanned aircraft in the flying process of the unmanned aircraft, and correcting the flying path of the unmanned aircraft based on the panoramic image data and the reference point;
and acquiring the position data of the unmanned aerial vehicle based on the flight path during flight, and performing obstacle avoidance control on the unmanned aerial vehicle in flight by combining the 3D map data.
It should be noted that, in this embodiment, first, the 3D map data and the positioning data are obtained, where the 3D map data is data input in advance or by human, and the positioning data is obtained based on GPS and/or beidou navigation, specifically, the positioning data at least includes a longitude value, a latitude value, a ground altitude value, and a flight angle value of an unmanned aerial vehicle, after the 3D map data and the positioning data are obtained, the position data of the unmanned aerial vehicle in the 3D map data may be obtained based on a plurality of reference points preset on the 3D map data and the positioning data, so that the position of the unmanned aerial vehicle may be identified based on the 3D map data, and then, during the flight of the unmanned aerial vehicle, the image data corresponding to the unmanned aerial vehicle is obtained, so that the flight path of the unmanned aerial vehicle is modified based on the panoramic image data and the reference point, so as to reduce the problem of collision avoidance of the unmanned aerial vehicle, and the problem of the flight of the unmanned aerial vehicle caused by combining the collision avoidance of the unmanned aerial vehicle with the positioning data and the unmanned aerial vehicle is reduced.
According to an embodiment of the present invention, the acquiring of the 3D map data and the positioning data of the unmanned aerial vehicle specifically includes:
establishing communication connection with a preset communication base station and/or a preset information transceiver to acquire the 3D map data;
establishing a communication connection with the unmanned aerial vehicle to identify the positioning data, wherein the positioning data includes at least an unmanned aerial vehicle longitude value, an unmanned aerial vehicle latitude value, an unmanned aerial vehicle ground altitude value, and an unmanned aerial vehicle angle of flight value.
In this embodiment, the 3D map data is obtained by establishing a communication connection with the communication base station and/or the information transceiver device, such as a router, and the 3D map data may be stored in advance by the communication base station or the information transceiver device, or may be obtained by forwarding the 3D map data through the communication base station or the information transceiver device; the positioning data corresponding to the unmanned aerial vehicle is identified by establishing a communication connection with the unmanned aerial vehicle, the communication connection is established by means of wireless Bluetooth and/or WiFi connection or wired connection, and the identified positioning data at least comprises an unmanned aerial vehicle longitude value, an unmanned aerial vehicle latitude value, an unmanned aerial vehicle ground flying height value and an unmanned aerial vehicle flying angle value, preferably, the heading value of the unmanned aerial vehicle and the like.
According to the embodiment of the present invention, the identifying and obtaining the position data of the unmanned aerial vehicle in the 3D map data based on a plurality of preset reference points in the 3D map data in combination with the positioning data specifically includes:
matching a plurality of reference points corresponding to the current unmanned aerial vehicle based on key point cloud data preset in the 3D map data, wherein the number of the reference points at least comprises three;
and obtaining the position data based on the reference point and the positioning data, wherein the position data at least comprises a horizontal coordinate parameter value, a vertical coordinate parameter value and a deflection angle parameter value.
It should be noted that, in this embodiment, when the unmanned aerial vehicle flies in an actual scene, an electronic map of the actual scene is obtained in the acquired 3D map data, the reference point corresponding to the unmanned aerial vehicle at present is matched through the key point cloud data preset in the 3D map data, the number of the reference points at least includes three, because three reference points can determine one point cloud, and then the position data of the unmanned aerial vehicle in the 3D map data can be obtained based on the reference points and the positioning data, where the position data at least includes a horizontal and vertical coordinate parameter value, a vertical coordinate parameter value, and a yaw angle parameter value, where the horizontal and vertical coordinate parameter value corresponds to the unmanned aerial vehicle longitude value and the unmanned aerial vehicle latitude value, the vertical coordinate parameter value corresponds to the unmanned aerial vehicle ground flight height value, and the yaw angle parameter value corresponds to the unmanned aerial vehicle flight angle value.
According to the embodiment of the present invention, the obtaining the position data based on the reference point and the positioning data specifically includes:
obtaining the horizontal and vertical coordinate parameter values of the unmanned aircraft in a space coordinate system in the 3D map data based on the reference point in combination with the longitude value and the latitude value of the unmanned aircraft;
obtaining the vertical coordinate parameter value of the unmanned aerial vehicle in a spatial coordinate system in the 3D map data based on the reference point and the ground flying height value of the unmanned aerial vehicle;
and obtaining the deflection angle parameter value of the space coordinate system of the unmanned aircraft in the 3D map data based on the reference point and the flight angle value of the unmanned aircraft.
In this embodiment, as shown in fig. 2, the 3D map data includes the spatial coordinate system thereof for labeling the spatial position of different objects in the current 3D map data, x is a horizontal axis of the spatial coordinate system, y is a vertical axis of the spatial coordinate system, z is a vertical axis of the spatial coordinate system, and α is a horizontal deflection angle of the spatial coordinate system, where, for an unmanned aircraft in the spatial coordinate system, the abscissa and ordinate parameter values may be obtained by combining the longitude value of the unmanned aircraft and the latitude value of the unmanned aircraft through the reference point pair; the vertical coordinate parameter value can be obtained by combining the ground flying height value of the unmanned aerial vehicle; and obtaining the deflection angle parameter value by combining the flight angle value of the unmanned aerial vehicle.
According to the embodiment of the invention, the acquiring of the panoramic image data of the unmanned aerial vehicle and the correcting of the flight path of the unmanned aerial vehicle based on the panoramic image data and the reference point specifically comprise:
matching the key point cloud data in the corresponding 3D map data based on the panoramic image data;
identifying the corresponding reference points based on the matching result and marking, wherein the number of the marked reference points at least comprises three;
calculating the linear distance between each reference point and the unmanned aerial vehicle, and obtaining point position data of the current unmanned aerial vehicle in the space coordinate system based on at least three linear distances;
and judging a deviation value between the unmanned aerial vehicle and a preset track based on the point location data, and correcting the flight path of the unmanned aerial vehicle based on the point location data when the deviation value exceeds a limit threshold value.
It should be noted that, in this embodiment, when the unmanned aerial vehicle travels along a preset trajectory, because a GPS positioning or a beidou positioning is relied on, and a physical deviation exists, in this embodiment, a point location of the unmanned aerial vehicle is defined by the reference point in the 3D map data to correct a flight path of the unmanned aerial vehicle, and a multipoint positioning method is specifically applied, specifically as shown in fig. 3, reference points a and B of the unmanned aerial vehicle on a horizontal plane of the 3D map data, reference points on different planes of the other two concentric spheres are points C and D, and position data of the current unmanned aerial vehicle in the 3D map data can be determined by calculating distances between the unmanned aerial vehicle and the different reference points, after the point location data is accurate to the corresponding point location, calculating based on a deviation value of the point location data and a preset track, wherein the deviation value is a distance between the current point location of the unmanned aerial vehicle and the corresponding point location on the track, and the calculation of the distance between the point location data and the point in the space is well known to those skilled in the art, and is not described herein again, after the deviation value is obtained, the magnitude of the deviation value and the limit threshold value is determined, and if the deviation value is greater than the limit threshold value, the position of the unmanned aerial vehicle is corrected based on the point location data (the accurate point location calculated by the reference point), so as to correct the flight path, wherein the limit threshold value may be "10cm".
According to the embodiment of the invention, the acquiring of the spatial data of the unmanned aerial vehicle during flight and the performing of the obstacle avoidance control of the unmanned aerial vehicle during flight by combining the 3D map data specifically comprise:
acquiring the spatial data based on point location data of the unmanned aerial vehicle in the spatial coordinate system, wherein the spatial data comprises the point location data and trajectory data formed by the point location data;
and identifying relative relation data of the unmanned aerial vehicle and obstacles in the 3D map data based on the spatial data, and performing obstacle avoidance control based on the relative relation data.
It should be noted that, in this embodiment, in the 3D map data, there are many objects occupying space that may affect the flight of the unmanned aerial vehicle, and after point location data and/or the trajectory data of the unmanned aerial vehicle are obtained, relative relationship data between the unmanned aerial vehicle and the obstacle may be determined, where the relative relationship data is a distance between the unmanned aerial vehicle and the obstacle, and similarly, calculating a distance between two points is well known by those skilled in the art, and is not described in detail, where the point-taking position between the obstacle and the unmanned aerial vehicle is a central point corresponding to each object, and after a relative distance is calculated, the size of the relative distance and the safe distance is determined, and if the relative distance is smaller than the safe distance, the unmanned aerial vehicle is controlled to be away from the obstacle for obstacle avoidance control, where the safe distance may be "10m".
It is worth mentioning that the method further comprises identifying environmental data in the 3D map data for controlling the unmanned aerial vehicle.
It should be noted that, in this embodiment, the corresponding environment data is identified through the 3D map data, where the environment data includes weather data, temperature data, and humidity data, the unmanned aerial vehicle is controlled to sample the weather data of the field environment through identifying cloud layer transformation in the 3D map data, and the unmanned aerial vehicle is controlled to sample the temperature data of the field environment through identifying an outdoor temperature type in the 3D map data.
It is worth mentioning that the method further comprises identifying marker data in the 3D map data for controlling the unmanned aerial vehicle.
It should be noted that, in this embodiment, the 3D map data is transformed in real time, so that in this embodiment, the unmanned aerial vehicle can be controlled by identifying the tag data in the 3D map data, where the tag data at least includes: the unmanned aerial vehicle can be controlled to go to a corresponding place for monitoring by identifying corresponding marking data.
It is worth mentioning that the method further comprises identifying pop-up information in the 3D map data for controlling the unmanned aerial vehicle.
It should be noted that, in this embodiment, when the unmanned aerial vehicle flies according to the 3D map data, the content of the pop-up information popped up in the 3D map data may be identified to control the unmanned aerial vehicle, for example, if the content popped up by the pop-up information is "recall to hangar", the unmanned aerial vehicle is controlled to return to hangar.
A third aspect of the invention provides a computer-readable storage medium, in which a 3D map-based unmanned aircraft flight control method program is included, and when executed by a processor, the 3D map-based unmanned aircraft flight control method program implements the steps of a 3D map-based unmanned aircraft flight control method as described in any one of the above.
The invention discloses a 3D map-based pilotless aircraft flight control method, a system and a medium, which can be used for positioning the pilotless aircraft and correcting a flight path based on 3D map data, and can be used for carrying out obstacle avoidance control to reduce the damage of the pilotless aircraft in the automatic flight process of the pilotless aircraft.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units; can be located in one place or distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, all the functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
Those of ordinary skill in the art will understand that: all or part of the steps of implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer-readable storage medium, and when executed, executes the steps including the method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic or optical disk, or various other media capable of storing program code.
Claims (10)
1. A flight control method of an unmanned aerial vehicle based on a 3D map is characterized by comprising the following steps:
acquiring 3D map data and positioning data of the unmanned aerial vehicle;
based on a plurality of preset reference points in the 3D map data and the positioning data, identifying and obtaining position data of the unmanned aerial vehicle in the 3D map data;
acquiring panoramic image data of the unmanned aircraft in the flying process of the unmanned aircraft, and correcting the flying path of the unmanned aircraft based on the panoramic image data and the reference point;
and acquiring spatial data of the unmanned aircraft during flight, and performing obstacle avoidance control of the unmanned aircraft in flight by combining the 3D map data.
2. The method according to claim 1, wherein the acquiring of the 3D map data and the positioning data of the unmanned aerial vehicle specifically comprises:
establishing communication connection with a preset communication base station and/or a preset information transceiver device to acquire the 3D map data;
establishing a communication connection with the unmanned aerial vehicle to identify the positioning data, wherein the positioning data includes at least an unmanned aerial vehicle longitude value, an unmanned aerial vehicle latitude value, an unmanned aerial vehicle ground altitude value, and an unmanned aerial vehicle angle of flight value.
3. The method as claimed in claim 2, wherein the identifying the position data of the unmanned aerial vehicle in the 3D map data based on a plurality of reference points preset in the 3D map data in combination with the positioning data comprises:
matching a plurality of reference points corresponding to the current unmanned aerial vehicle based on preset key point cloud data in the 3D map data, wherein the number of the reference points at least comprises three;
and obtaining the position data based on the reference point and the positioning data, wherein the position data at least comprises a horizontal coordinate parameter value, a vertical coordinate parameter value and a deflection angle parameter value.
4. The method according to claim 3, wherein the obtaining of the position data based on the reference point in combination with the positioning data comprises:
obtaining the abscissa and ordinate parameter values of the unmanned aircraft in a spatial coordinate system in the 3D map data based on the reference point in combination with the longitude value and the latitude value of the unmanned aircraft;
obtaining the vertical coordinate parameter value of the unmanned aerial vehicle in a spatial coordinate system in the 3D map data based on the reference point and the ground flying height value of the unmanned aerial vehicle;
and obtaining the deflection angle parameter value of the spatial coordinate system of the unmanned aerial vehicle in the 3D map data based on the reference point and the flight angle value of the unmanned aerial vehicle.
5. The method according to claim 4, wherein the acquiring panoramic image data of the unmanned aerial vehicle and correcting the flight path of the unmanned aerial vehicle based on the panoramic image data and the reference point specifically comprises:
matching the key point cloud data in the corresponding 3D map data based on the panoramic image data;
identifying the corresponding reference points based on the matching result and marking, wherein the number of the marked reference points at least comprises three;
calculating the linear distance between each reference point and the unmanned aerial vehicle, and obtaining point position data of the current unmanned aerial vehicle in the space coordinate system based on at least three linear distances;
and judging a deviation value between the unmanned aerial vehicle and a preset track based on the point location data, and correcting the flight path of the unmanned aerial vehicle based on the point location data when the deviation value exceeds a limit threshold value.
6. The method according to claim 5, wherein the obtaining of the spatial data of the unmanned aerial vehicle during flight and the combining of the 3D map data to perform obstacle avoidance control of the unmanned aerial vehicle during flight comprise:
acquiring the spatial data based on point location data of the unmanned aerial vehicle in the spatial coordinate system, wherein the spatial data comprises the point location data and trajectory data formed by the point location data;
and identifying relative relation data of the unmanned aircraft and the obstacles in the 3D map data based on the spatial data, and performing obstacle avoidance control based on the relative relation data.
7. A3D map-based unmanned aircraft flight control system is characterized by comprising a memory and a processor, wherein the memory comprises a 3D map-based unmanned aircraft flight control method program, and the processor executes the 3D map-based unmanned aircraft flight control method program to realize the following steps:
acquiring 3D map data and positioning data of the unmanned aerial vehicle;
based on a plurality of preset reference points in the 3D map data and the positioning data, identifying and obtaining position data of the unmanned aerial vehicle in the 3D map data;
acquiring panoramic image data of the unmanned aircraft in the flying process of the unmanned aircraft, and correcting the flying path of the unmanned aircraft based on the panoramic image data and the reference point;
and acquiring the position data of the unmanned aerial vehicle flying based on the flight path, and combining the 3D map data to perform obstacle avoidance control of the unmanned aerial vehicle flying.
8. The system according to claim 7, wherein the acquiring of the 3D map data and the positioning data of the unmanned aerial vehicle comprises:
establishing communication connection with a preset communication base station and/or a preset information transceiver to acquire the 3D map data;
establishing a communication connection with the unmanned aerial vehicle to identify the positioning data, wherein the positioning data includes at least an unmanned aerial vehicle longitude value, an unmanned aerial vehicle latitude value, an unmanned aerial vehicle ground altitude value, and an unmanned aerial vehicle angle of flight value.
9. The system of claim 8, wherein the identifying the position data of the unmanned aerial vehicle in the 3D map data based on a plurality of reference points preset in the 3D map data in combination with the positioning data comprises:
matching a plurality of reference points corresponding to the current unmanned aerial vehicle based on preset key point cloud data in the 3D map data, wherein the number of the reference points at least comprises three;
and obtaining the position data based on the reference point and the positioning data, wherein the position data at least comprises a longitude and latitude parameter value, an altitude parameter value and a deflection angle parameter value.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium comprises a 3D map-based unmanned aircraft flight control method program, which when executed by a processor implements the steps of a 3D map-based unmanned aircraft flight control method according to any one of claims 1 to 6.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211200326.XA CN115562335A (en) | 2022-09-29 | 2022-09-29 | 3D map-based unmanned aerial vehicle flight control method, system and medium |
| PCT/CN2023/118878 WO2024067133A1 (en) | 2022-09-29 | 2023-09-14 | 3d-map-based flight control method and system for unmanned aircraft, and medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211200326.XA CN115562335A (en) | 2022-09-29 | 2022-09-29 | 3D map-based unmanned aerial vehicle flight control method, system and medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115562335A true CN115562335A (en) | 2023-01-03 |
Family
ID=84742646
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211200326.XA Pending CN115562335A (en) | 2022-09-29 | 2022-09-29 | 3D map-based unmanned aerial vehicle flight control method, system and medium |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN115562335A (en) |
| WO (1) | WO2024067133A1 (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2024067133A1 (en) * | 2022-09-29 | 2024-04-04 | 亿航智能设备（广州）有限公司 | 3d-map-based flight control method and system for unmanned aircraft, and medium |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101598557B (en) * | 2009-07-15 | 2012-05-23 | 北京航空航天大学 | Integrated navigation system applied to pilotless aircraft |
| CN107643762A (en) * | 2017-08-07 | 2018-01-30 | 中国兵器工业计算机应用技术研究所 | The UAS and its air navigation aid of independent navigation |
| KR102096262B1 (en) * | 2017-12-11 | 2020-04-02 | 숭실대학교 산학협력단 | Device for flight simulating of unmanned aerial vehicle, and system for flight simulating of unmanned aerial vehicle using thereof |
| CN109443368A (en) * | 2019-01-14 | 2019-03-08 | 轻客小觅智能科技（北京）有限公司 | Air navigation aid, device, robot and the storage medium of unmanned machine people |
| CN112114593A (en) * | 2020-09-21 | 2020-12-22 | 飞的科技有限公司 | Control system |
| CN115562335A (en) * | 2022-09-29 | 2023-01-03 | 亿航智能设备（广州）有限公司 | 3D map-based unmanned aerial vehicle flight control method, system and medium |
-
2022
- 2022-09-29 CN CN202211200326.XA patent/CN115562335A/en active Pending
-
2023
- 2023-09-14 WO PCT/CN2023/118878 patent/WO2024067133A1/en unknown
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2024067133A1 (en) * | 2022-09-29 | 2024-04-04 | 亿航智能设备（广州）有限公司 | 3d-map-based flight control method and system for unmanned aircraft, and medium |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2024067133A1 (en) | 2024-04-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11709491B2 (en) | Dynamically adjusting UAV flight operations based on radio frequency signal data | |
| Alam et al. | A survey of safe landing zone detection techniques for autonomous unmanned aerial vehicles (UAVs) | |
| CN108132678B (en) | Flight control method of aircraft and related device | |
| US9562771B2 (en) | Analysis of sensor data | |
| US7269513B2 (en) | Ground-based sense-and-avoid display system (SAVDS) for unmanned aerial vehicles | |
| US20220074744A1 (en) | Unmanned Aerial Vehicle Control Point Selection System | |
| CN113296537B (en) | Electric power unmanned aerial vehicle inspection method and system based on electric power pole tower model matching | |
| CN213302860U (en) | Three-dimensional visual obstacle avoidance system of unmanned aerial vehicle | |
| WO2024067133A1 (en) | 3d-map-based flight control method and system for unmanned aircraft, and medium | |
| US11967091B2 (en) | Detection of environmental changes to delivery zone | |
| CN116048117B (en) | Intelligent real-time monitoring system and method applied to unmanned aerial vehicle | |
| CN110823223A (en) | Path planning method and device for unmanned aerial vehicle cluster | |
| CN112286228A (en) | Unmanned aerial vehicle three-dimensional visual obstacle avoidance method and system | |
| CN112119428A (en) | Method, device, unmanned aerial vehicle, system and storage medium for acquiring landing position | |
| CN111104861B (en) | Method and apparatus for determining wire position and storage medium | |
| CN115790610B (en) | Unmanned aerial vehicle accurate positioning system and method | |
| WO2021237535A1 (en) | Collision processing method and device, and medium | |
| CN116400730B (en) | Low-altitude flight range calibration method and system for aircraft | |
| CN115602003A (en) | Unmanned aerial vehicle flight obstacle avoidance method, system and readable storage medium | |
| Kim et al. | Field evaluation of UAV‐based tracking method for localization of small insects | |
| Lee et al. | Real‐time collision‐free landing path planning for drone deliveries in urban environments | |
| CN114740885A (en) | Unmanned aerial vehicle return method, device, equipment and storage medium | |
| CN114527779A (en) | Control method and system of cargo distribution unmanned aerial vehicle and storage medium | |
| CN115061492B (en) | Campus takeout distribution system and progressive three-dimensional space path planning method | |
| KR102515245B1 (en) | Method and apparatus for preventing loss of unmanned air vehicle |
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 |