CN117516531A - Unmanned plane control and navigation method, system, terminal and storage medium - Google Patents
Unmanned plane control and navigation method, system, terminal and storage medium Download PDFInfo
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- G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
- G01C21/1656—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments with passive imaging devices, e.g. cameras
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Abstract
A control and navigation method, system, terminal and storage medium of unmanned plane, the control method includes: the unmanned plane acquires a first waypoint and a second waypoint, flies from the first waypoint to the second waypoint by using inertial navigation based on a road network, and corrects a flight track according to a road image photographed in real time in the flight process; if the second waypoint is an intersection, when the unmanned aerial vehicle reaches a preset area corresponding to the second waypoint, comparing the intersection image of the second waypoint shot by the unmanned aerial vehicle in real time with the corresponding intersection image in the database, and adjusting the position of the intersection image to the center of the intersection. The navigation method comprises the following steps: the method comprises the steps of obtaining a starting point and an ending point of navigation, making a flight route based on a road network, wherein each intersection through which the flight route passes is a waypoint, and enabling the unmanned aerial vehicle to sequentially pass through each waypoint from the starting point to reach the ending point by using the control method of the unmanned aerial vehicle. Compared with the prior art, the control and navigation method improves the accuracy of GPS-free navigation.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle control and navigation method.
Background
Unmanned aerial vehicles are widely applied to various fields at present, and research on unmanned aerial vehicle navigation is becoming a hotspot gradually. The most common method in unmanned aerial vehicle navigation at present is that satellite positioning navigation and inertial navigation are combined, the method utilizes satellite information receiving equipment and an inertial measurement device carried on the unmanned aerial vehicle to acquire related data, and the real-time position of the unmanned aerial vehicle is acquired through calculation, so that the accurate positioning of the unmanned aerial vehicle is realized, and the navigation function of the unmanned aerial vehicle is further realized; satellite positioning navigation has the characteristics of all-weather positioning, high positioning precision, short observation time, simple operation and the like, and is widely applied to navigation positioning systems of different devices.
However, in the method combining satellite positioning navigation and inertial navigation, the navigation precision is affected by the satellite positioning precision, and the satellite positioning has a certain deviation due to the climate condition, so that the positioning is inaccurate; in addition, satellite positioning generally requires equipment to work in an open environment, and in a closed space or a city environment with more buildings, satellite positioning accuracy can be greatly influenced, so that unmanned aerial vehicle navigation accuracy is influenced.
Disclosure of Invention
The invention provides a control and navigation method, a system, a terminal and a storage medium for an unmanned aerial vehicle, which enable unmanned aerial vehicle navigation to be independent of a GPS positioning system and solve the problem of inaccurate unmanned aerial vehicle navigation caused by inaccurate GPS positioning under specific conditions.
In order to solve the above technical problems, in a first aspect, an embodiment of the present invention provides a method for controlling an unmanned aerial vehicle, including:
the unmanned aerial vehicle acquires a first waypoint and a second waypoint, wherein the first waypoint and the second waypoint are positioned in a road network of a target area, and the first waypoint is the current position of the unmanned aerial vehicle;
the unmanned aerial vehicle determines the flight direction and the flight distance of inertial navigation from the first waypoint to the second waypoint according to a road topological graph of a target area;
the unmanned aerial vehicle flies from the first navigation point to the second navigation point according to the inertial navigation, and the flight track is corrected in real time according to the road image shot by the unmanned aerial vehicle in real time in the flight process;
if the second waypoint is an intersection in the road network, when the unmanned aerial vehicle reaches a preset area corresponding to the second waypoint, comparing an intersection image of the second waypoint shot by the unmanned aerial vehicle in real time with an intersection image of a corresponding place in a preset database, and adjusting the position of the unmanned aerial vehicle to the center of the intersection in the road network according to a comparison result; the preset area corresponding to the second waypoint is determined according to the position of the second waypoint on the road topological graph.
The embodiment of the invention provides an unmanned aerial vehicle control method which is used for controlling an unmanned aerial vehicle to fly between two waypoints, determining the flying direction and the flying distance of the unmanned aerial vehicle through inertial navigation, and correcting the flying track of the unmanned aerial vehicle in real time according to a road image shot by the unmanned aerial vehicle in the flying process, so that the unmanned aerial vehicle does not depend on a GPS positioning system in the flying process, and meanwhile, the flying accuracy of the unmanned aerial vehicle unmanned GPS is ensured. When the unmanned aerial vehicle arrives near the intersection, the intersection image shot by the unmanned aerial vehicle is compared with the corresponding intersection image in the preset database, the position of the unmanned aerial vehicle is accurately corrected, the unmanned aerial vehicle accurately arrives at the center point of the intersection, the flight error generated in inertial navigation is reduced, and the unmanned aerial vehicle unmanned GPS flight accuracy is further improved.
In one possible implementation manner, the flight track is corrected in real time according to the road image shot by the unmanned aerial vehicle in real time during the flight, specifically: and extracting a first road in the image under the unmanned aerial vehicle by using a computer vision algorithm through the image under the unmanned aerial vehicle which is shot in real time, and correcting the flight track in real time according to the position of the unmanned aerial vehicle in the first road.
The embodiment of the invention provides a method for correcting a flight track in a flight process, which is used for extracting a road according to an image shot by a camera of an unmanned aerial vehicle in real time, correcting the flight track of the unmanned aerial vehicle in real time according to the position of the unmanned aerial vehicle in the road, realizing the unmanned aerial vehicle along the road, ensuring that the unmanned aerial vehicle can smoothly reach the next intersection and further improving the unmanned aerial vehicle GPS flight accuracy.
In one possible implementation manner, if the second waypoint is an intersection in the road network, when the unmanned aerial vehicle reaches a preset area corresponding to the second waypoint, comparing an intersection image of the second waypoint, which is shot by the unmanned aerial vehicle in real time, with an intersection image of a corresponding place in a preset database, and adjusting the position of the unmanned aerial vehicle to an intersection center in the road network according to a comparison result, wherein the specific steps are as follows:
when the unmanned aerial vehicle judges that the unmanned aerial vehicle reaches a preset area corresponding to the second navigation point according to the flying distance of the inertial navigation, transmitting a first image right below the unmanned aerial vehicle, which is shot in real time, into a preset intersection recognition model so that the intersection recognition model judges whether the first image right below the unmanned aerial vehicle contains a first intersection or not, and if the first intersection is not contained, continuing to fly according to the flying direction of the inertial navigation by the unmanned aerial vehicle; if the first intersection is included, the unmanned aerial vehicle continuously compares the image under the real-time shooting with the intersection image of the corresponding place in the database, and translates to the center of the first intersection according to the comparison result until the unmanned aerial vehicle reaches the center of the first intersection.
The embodiment of the invention provides a method for enabling an unmanned aerial vehicle to accurately translate to the center of an intersection near the intersection, wherein after the unmanned aerial vehicle is confirmed to reach the vicinity of the intersection by using an intersection identifier, a database is called for comparison, so that invalid call of the database in the navigation process of the unmanned aerial vehicle is reduced, and system resources are saved; and secondly, continuously comparing the real-time shooting image with the image in the database, and repeatedly adjusting the position of the unmanned aerial vehicle, so that the unmanned aerial vehicle can more accurately reach the center of the intersection, and the flying accuracy of the unmanned aerial vehicle unmanned GPS is further improved.
Further, the database is obtained by automatically shooting each intersection image of the target area by the unmanned aerial vehicle according to each intersection GPS coordinate of the target area and a preset shooting height, and recording and warehousing.
The embodiment of the invention provides a method for establishing an intersection image database, wherein an unmanned aerial vehicle automatically shoots each intersection image according to GPS coordinates of each intersection in a target area and a preset shooting height, so that the labor cost is saved, and the working efficiency of early-stage data preparation work is improved.
Further, the intersection recognition model is obtained by training according to the intersection images in the database and a neural network algorithm.
The embodiment of the invention provides a method for training an intersection recognition model, which uses a neural network algorithm to train the intersection recognition model according to an intersection image in a database, improves the accuracy of the intersection recognition model in recognizing an intersection, enables an unmanned aerial vehicle to recognize the intersection more accurately in the flight process, and further improves the accuracy of unmanned aerial vehicle unmanned GPS flight.
In a second aspect, an embodiment of the present invention provides a method for navigating an unmanned aerial vehicle, including:
the unmanned aerial vehicle acquires a starting point and an ending point of navigation, and formulates a flight route according to a road topological graph of a target area, wherein the starting point and the ending point are positioned in a road network of the target area; the flight route comprises a plurality of waypoints, wherein the waypoints comprise the starting point, the ending point and various intersections in the road network;
and the unmanned aerial vehicle executes the unmanned aerial vehicle control method based on the road network according to the navigation sequence of the flight navigation, and sequentially flies from the current waypoint to the next waypoint from the starting point until the unmanned aerial vehicle reaches the end point.
The embodiment of the invention provides an unmanned aerial vehicle navigation method, which takes an intersection, a starting point and a terminal point, through which a flight route of an unmanned aerial vehicle passes, as waypoints, and splits the whole flight path of the unmanned aerial vehicle into a plurality of sections of flight paths by the waypoints, so that the flight process of the unmanned aerial vehicle is simplified, the unmanned aerial vehicle can directly fly between adjacent waypoints by using inertial navigation, and the unmanned aerial vehicle control method is used for controlling the unmanned aerial vehicle to fly between the adjacent waypoints, thereby realizing unmanned aerial vehicle GPS navigation and ensuring the unmanned aerial vehicle GPS navigation accuracy.
In one possible implementation manner, a flight route is formulated according to a road topology map of a target area, specifically:
and acquiring a first intersection closest to the starting point and a second intersection closest to the end point from a road topological graph of a target area, acquiring the shortest path from the first intersection to the second intersection by using a shortest path algorithm in the road topological graph, and merging the path from the starting point to the first intersection, the shortest path from the first intersection to the second intersection and the path from the second intersection to the end point to serve as the flight route.
The embodiment of the invention provides a method for making a route of an unmanned aerial vehicle based on a road network of a target area, which is characterized in that a first intersection and a second intersection near a starting point and an ending point are positioned according to a road topological graph of the target area, and a shortest path from the first intersection to the second intersection is generated by using a shortest path algorithm, so that the making of the route is realized, the route is ensured to be the shortest route from the starting point to the ending point under the condition of the road network, invalid flight of the unmanned aerial vehicle is avoided, and the navigation efficiency of the unmanned aerial vehicle is improved.
In a third aspect, an embodiment of the present invention provides an unmanned aerial vehicle control system, including an acquisition module, a navigation module, a track correction module, and a position correction module;
The acquisition module is used for acquiring a first waypoint and a second waypoint of the unmanned aerial vehicle, wherein the first waypoint and the second waypoint are positioned in a road network of a target area, and the first waypoint is the current position of the unmanned aerial vehicle;
the navigation module is used for acquiring a road topological graph of a target area, and determining the flight direction and the flight distance of inertial navigation of the unmanned aerial vehicle from the first navigation point to the second navigation point;
the track correction module is used for enabling the unmanned aerial vehicle to fly from the first navigation point to the second navigation point according to the inertial navigation, and correcting the flight track in real time according to the road image shot by the unmanned aerial vehicle in real time in the flight process;
the position correction module is used for comparing the intersection image of the second waypoint shot by the unmanned aerial vehicle in real time with the intersection image of the corresponding place in a preset database when the unmanned aerial vehicle reaches a preset area corresponding to the second waypoint if the second waypoint is an intersection in the road network, and adjusting the position of the unmanned aerial vehicle to the center of the intersection in the road network according to a comparison result; the preset area corresponding to the second waypoint is determined according to the position of the second waypoint on the road topological graph.
In one possible implementation manner, the track correction module is configured to correct, in real time, a flight track according to a road image captured by the unmanned aerial vehicle in real time during a flight process, specifically: and extracting a first road in the image under the unmanned aerial vehicle by using a computer vision algorithm through the image under the unmanned aerial vehicle which is shot in real time, and correcting the flight track in real time according to the position of the unmanned aerial vehicle in the first road.
In one possible implementation manner, if the second waypoint is an intersection in the road network, when the unmanned aerial vehicle reaches a preset area corresponding to the second waypoint, the position correction module compares an intersection image of the second waypoint, which is shot in real time by the unmanned aerial vehicle, with an intersection image of a corresponding place in a preset database, and adjusts the position of the intersection image to an intersection center in the road network according to a comparison result, specifically:
when the unmanned aerial vehicle judges that the unmanned aerial vehicle reaches a preset area corresponding to the second navigation point according to the flying distance of the inertial navigation, transmitting a first image right below the unmanned aerial vehicle, which is shot in real time, into a preset intersection recognition model so that the intersection recognition model judges whether the first image right below the unmanned aerial vehicle contains a first intersection or not, and if the first intersection is not contained, continuing to fly according to the flying direction of the inertial navigation by the unmanned aerial vehicle; if the first intersection is included, the unmanned aerial vehicle continuously compares the image under the real-time shooting with the intersection image of the corresponding place in the database, and translates to the center of the first intersection according to the comparison result until the unmanned aerial vehicle reaches the center of the first intersection.
Further, the database is obtained by automatically shooting each intersection image of the target area by the unmanned aerial vehicle according to each intersection GPS coordinate of the target area and a preset shooting height, and recording and warehousing.
Further, the intersection recognition model is obtained by training according to the intersection images in the database and a neural network algorithm.
In a fourth aspect, an embodiment of the present invention provides an unmanned aerial vehicle navigation system, including a route making module and an execution route module;
the navigation system comprises a navigation establishing module, a navigation establishing module and a navigation information processing module, wherein the navigation establishing module is used for acquiring a starting point and a destination point of navigation of an unmanned aerial vehicle, and establishing a flight route according to a road topological graph of a target area, wherein the starting point and the destination point are positioned in a road network of the target area; the flight route comprises a plurality of waypoints, wherein the waypoints comprise the starting point, the ending point and various intersections in the road network;
the execution route module is used for executing the unmanned aerial vehicle control method based on the road network according to the navigation sequence of the flight navigation of the unmanned aerial vehicle, and the unmanned aerial vehicle sequentially flies from the current waypoint to the next waypoint from the starting point until the unmanned aerial vehicle reaches the ending point.
Further, the route making module makes a flight route according to a road topological graph of the target area, specifically:
and acquiring a first intersection closest to the starting point and a second intersection closest to the end point from a road topological graph of a target area, acquiring the shortest path from the first intersection to the second intersection by using a shortest path algorithm in the road topological graph, and merging the path from the starting point to the first intersection, the shortest path from the first intersection to the second intersection and the path from the second intersection to the end point to serve as the flight route.
In a fifth aspect, an embodiment of the present invention provides a terminal, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, where the processor implements the road network-based unmanned aerial vehicle control method or the road network-based unmanned aerial vehicle navigation method when executing the computer program.
In a sixth aspect, an embodiment of the present invention provides a computer readable storage medium, where the computer readable storage medium includes a stored computer program, and when the computer program runs, controls a device where the computer readable storage medium is located to execute the method for controlling a road network-based unmanned aerial vehicle or the method for navigating a road network-based unmanned aerial vehicle.
Drawings
Fig. 1: the invention provides a flow diagram of an embodiment of a control method for an unmanned aerial vehicle.
Fig. 2: the flow diagram for accurately correcting the position of the unmanned aerial vehicle near the intersection is provided for the invention.
Fig. 3: the invention provides a flow diagram for constructing an intersection image database and training an intersection recognition model.
Fig. 4: the invention provides a flow diagram of an embodiment of a navigation method of an unmanned aerial vehicle.
Fig. 5: the flow diagram for making the flight route of the unmanned aerial vehicle according to the starting point and the ending point is provided for the unmanned aerial vehicle.
Fig. 6: the invention provides a detailed flow diagram of an embodiment of a navigation method of an unmanned aerial vehicle.
Fig. 7: the invention provides a structural schematic diagram of an embodiment of a control system of an unmanned aerial vehicle.
Fig. 8: the invention provides a structural schematic diagram of an embodiment of a navigation system of an unmanned aerial vehicle.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be noted that, the step numbers herein are only for convenience of explanation of the specific embodiments, and are not used as limiting the order of execution of the steps.
Embodiment one:
an embodiment one provides a control method of an unmanned aerial vehicle, as shown in fig. 1, including steps S1 to S4:
s1, an unmanned aerial vehicle acquires a first waypoint and a second waypoint, wherein the first waypoint and the second waypoint are positioned in a road network of a target area, and the first waypoint is the current position of the unmanned aerial vehicle;
s2, determining the flight direction and the flight distance of inertial navigation from the first waypoint to the second waypoint according to a road topological graph of a target area by the unmanned aerial vehicle;
s3, the unmanned aerial vehicle flies from the first navigation point to the second navigation point according to the inertial navigation, and the flight track is corrected in real time according to the road image shot by the unmanned aerial vehicle in real time in the flight process;
s4, if the second waypoint is an intersection in the road network, comparing the intersection image of the second waypoint shot by the unmanned aerial vehicle in real time with the intersection image of the corresponding place in a preset database when the unmanned aerial vehicle reaches a preset area corresponding to the second waypoint, and adjusting the position of the unmanned aerial vehicle to the center of the intersection in the road network according to a comparison result; the preset area corresponding to the second waypoint is determined according to the position of the second waypoint on the road topological graph.
The embodiment of the invention provides an unmanned aerial vehicle control method which is used for controlling an unmanned aerial vehicle to fly between two waypoints, determining the flying direction and the flying distance of the unmanned aerial vehicle through inertial navigation, and correcting the flying track of the unmanned aerial vehicle in real time according to a road image shot by the unmanned aerial vehicle in the flying process, so that the unmanned aerial vehicle does not depend on a GPS positioning system in the flying process, and meanwhile, the flying accuracy of the unmanned aerial vehicle unmanned GPS is ensured. When the unmanned aerial vehicle arrives near the intersection, the intersection image shot by the unmanned aerial vehicle is compared with the corresponding intersection image in the preset database, the position of the unmanned aerial vehicle is accurately corrected, the unmanned aerial vehicle accurately arrives at the center point of the intersection, the flight error generated in inertial navigation is reduced, and the unmanned aerial vehicle unmanned GPS flight accuracy is further improved.
In step S2, the road topology map is obtained by acquiring a map of a target area using a map source disclosed by a Goldmap, a Google map, etc., extracting a road network including intersections of roads, directions of roads, etc., and performing line thinning processing on the road network in the earlier stage.
In step S3, the real-time correction of the flight track according to the road image captured by the unmanned aerial vehicle in real time during the flight specifically includes: and extracting a first road in the image under the unmanned aerial vehicle by using a computer vision algorithm through the image under the unmanned aerial vehicle which is shot in real time, and correcting the flight track in real time according to the position of the unmanned aerial vehicle in the first road.
The embodiment of the invention provides a method for correcting a flight track in a flight process, which is used for extracting a road according to an image shot by a camera of an unmanned aerial vehicle in real time, correcting the flight track of the unmanned aerial vehicle in real time according to the position of the unmanned aerial vehicle in the road, realizing the unmanned aerial vehicle along the road, ensuring that the unmanned aerial vehicle can smoothly reach the next intersection and further improving the unmanned aerial vehicle GPS flight accuracy.
In step S4, if the second waypoint is an intersection in the road network, when the unmanned aerial vehicle reaches a preset area corresponding to the second waypoint, comparing the intersection image of the second waypoint, which is shot by the unmanned aerial vehicle in real time, with an intersection image of a corresponding place in a preset database, and adjusting the position of the unmanned aerial vehicle to the center of the intersection in the road network according to a comparison result, wherein the specific steps are as follows:
as shown in fig. 2, when the unmanned aerial vehicle judges that the unmanned aerial vehicle reaches the preset area corresponding to the second waypoint according to the flying distance of the inertial navigation, transmitting a first image directly below the unmanned aerial vehicle, which is shot in real time, into a preset intersection recognition model, so that the intersection recognition model judges whether the first image directly below the unmanned aerial vehicle contains a first intersection, and if the first intersection is not contained, continuing to fly according to the flying direction of the inertial navigation; if the first intersection is included, the unmanned aerial vehicle continuously compares the image under the real-time shooting with the intersection image of the corresponding place in the database, and translates to the center of the first intersection according to the comparison result until the unmanned aerial vehicle reaches the center of the first intersection.
The embodiment of the invention provides a method for enabling an unmanned aerial vehicle to accurately translate to the center of an intersection near the intersection, wherein after the unmanned aerial vehicle is confirmed to reach the vicinity of the intersection by using an intersection identifier, a database is called for comparison, so that invalid call of the database in the navigation process of the unmanned aerial vehicle is reduced, and system resources are saved; and secondly, continuously comparing the real-time shooting image with the image in the database, and repeatedly adjusting the position of the unmanned aerial vehicle, so that the unmanned aerial vehicle can more accurately reach the center of the intersection, and the flying accuracy of the unmanned aerial vehicle unmanned GPS is further improved.
Further, in step S4, the database is obtained by automatically shooting each intersection image of the target area by the unmanned aerial vehicle according to each intersection GPS coordinate of the target area and a preset shooting height, and recording and warehousing. The crossing recognition model is obtained by training according to crossing images in the database and a neural network algorithm. As shown in fig. 3, a road network is extracted from a disclosed map source in a preliminary data preparation work, and a road topology map is generated. And acquiring GPS coordinates of each intersection from the road topological graph, and designing different shooting heights so as to formulate an intersection image acquisition route. And the unmanned aerial vehicle flies according to the acquisition route and vertically shoots the pictures downwards, acquires the intersection images, records and stores the intersection images, and completes the establishment of an intersection image database. Finally, an intersection image in an intersection image database is utilized and a neural network algorithm is combined to establish an intersection identifier, the specific method is that the intersections in the intersection image are marked manually, a YOLO v5s model is used for training, and finally the intersection identifier is generated.
Embodiment two:
as shown in fig. 4, a second embodiment provides a navigation method for an unmanned aerial vehicle, including steps A1 and A2:
a1, acquiring a starting point and an ending point of navigation by an unmanned aerial vehicle, and making a flight route according to a road topological graph of a target area, wherein the starting point and the ending point are positioned in a road network of the target area; the flight route comprises a plurality of waypoints, wherein the waypoints comprise the starting point, the ending point and various intersections in the road network;
and A2, executing the unmanned aerial vehicle control method based on the road network according to the navigation sequence of the flight navigation, and sequentially flying from the current waypoint to the next waypoint from the starting point until the unmanned aerial vehicle reaches the ending point.
The embodiment of the invention provides an unmanned aerial vehicle navigation method, which takes an intersection, a starting point and a terminal point, through which a flight route of an unmanned aerial vehicle passes, as waypoints, and splits the whole flight path of the unmanned aerial vehicle into a plurality of sections of flight paths by the waypoints, so that the flight process of the unmanned aerial vehicle is simplified, the unmanned aerial vehicle can directly fly between adjacent waypoints by using inertial navigation, and the unmanned aerial vehicle control method is used for controlling the unmanned aerial vehicle to fly between the adjacent waypoints, thereby realizing unmanned aerial vehicle GPS navigation and ensuring the unmanned aerial vehicle GPS navigation accuracy.
In step A1, a flight route is formulated according to a road topology map of a target area, specifically:
as shown in fig. 5, a first intersection closest to the start point and a second intersection closest to the end point are obtained from a road topology of a target area, a shortest path from the first intersection to the second intersection is obtained in the road topology using a shortest path algorithm such as Djikstra algorithm, and the paths from the start point to the first intersection, the shortest path from the first intersection to the second intersection, and the path from the second intersection to the end point are combined as the flight route.
The embodiment of the invention provides a method for making a route of an unmanned aerial vehicle based on a road network of a target area, which is characterized in that a first intersection and a second intersection near a starting point and an ending point are positioned according to a road topological graph of the target area, and a shortest path from the first intersection to the second intersection is generated by using a shortest path algorithm, so that the making of the route is realized, the route is ensured to be the shortest route from the starting point to the ending point under the condition of the road network, invalid flight of the unmanned aerial vehicle is avoided, and the navigation efficiency of the unmanned aerial vehicle is improved.
Fig. 6 is a detailed flowchart of a method for unmanned aerial vehicle navigation according to an embodiment of the present invention in one possible implementation. After the unmanned aerial vehicle acquires the starting point and the ending point of navigation, a flight route is formulated based on a road network, an intersection through which the flight route passes and the starting point and the ending point are taken as each waypoint in the route, and the whole flight route is decomposed into a multi-section process of flying from the current waypoint to the next waypoint. And calculating the inertial navigation direction and distance according to the relative positions of the current waypoint and the next waypoint in the course of executing the route, and driving the unmanned aerial vehicle to fly from the current waypoint to the next waypoint by using the inertial navigation. In the flight process, correcting the flight track in real time according to the road image shot by the unmanned aerial vehicle in real time; when the unmanned aerial vehicle arrives near the waypoint, the intersection image shot by the unmanned aerial vehicle in real time is compared with the image in the database, and the accurate position correction is carried out, so that the unmanned aerial vehicle can accurately arrive at the waypoint. The above process is repeatedly performed until the unmanned aerial vehicle reaches the destination.
Embodiment III:
as shown in fig. 7, an embodiment of the present invention provides a control system for an unmanned aerial vehicle, which includes an acquisition module 10, a navigation module 20, a track correction module 30, and a position correction module 40;
the acquiring module 10 is configured to acquire a first waypoint and a second waypoint of the unmanned aerial vehicle, where the first waypoint and the second waypoint are located in a road network of a target area, and the first waypoint is a current location of the unmanned aerial vehicle;
the navigation module 20 is configured to obtain a road topology map of a target area, and determine a flight direction and a flight distance of inertial navigation of the unmanned aerial vehicle from the first waypoint to the second waypoint;
the track correction module 30 is configured to enable the unmanned aerial vehicle to fly from the first waypoint to the second waypoint according to the inertial navigation, and correct a flight track in real time according to a road image captured by the unmanned aerial vehicle in real time during the flight;
the position correction module 40 is configured to compare an intersection image of the second waypoint captured by the unmanned aerial vehicle in real time with an intersection image of a corresponding place in a preset database when the unmanned aerial vehicle reaches a preset area corresponding to the second waypoint if the second waypoint is an intersection in the road network, and adjust the position of the unmanned aerial vehicle to an intersection center in the road network according to a comparison result; the preset area corresponding to the second waypoint is determined according to the position of the second waypoint on the road topological graph.
In one possible implementation manner, the track correction module 30 is configured to correct, in real time, a flight track according to a road image captured by the unmanned aerial vehicle in real time during the flight, specifically: and extracting a first road in the image under the unmanned aerial vehicle by using a computer vision algorithm through the image under the unmanned aerial vehicle which is shot in real time, and correcting the flight track in real time according to the position of the unmanned aerial vehicle in the first road.
In a possible implementation manner, if the second waypoint is an intersection in the road network, when the unmanned aerial vehicle reaches a preset area corresponding to the second waypoint, the position correction module 40 compares an intersection image of the second waypoint, which is captured by the unmanned aerial vehicle in real time, with an intersection image of a corresponding place in a preset database, and adjusts the position of the intersection image to an intersection center in the road network according to a comparison result, specifically:
when the unmanned aerial vehicle judges that the unmanned aerial vehicle reaches a preset area corresponding to the second navigation point according to the flying distance of the inertial navigation, transmitting a first image right below the unmanned aerial vehicle, which is shot in real time, into a preset intersection recognition model so that the intersection recognition model judges whether the first image right below the unmanned aerial vehicle contains a first intersection or not, and if the first intersection is not contained, continuing to fly according to the flying direction of the inertial navigation by the unmanned aerial vehicle; if the first intersection is included, the unmanned aerial vehicle continuously compares the image under the real-time shooting with the intersection image of the corresponding place in the database, and translates to the center of the first intersection according to the comparison result until the unmanned aerial vehicle reaches the center of the first intersection.
Further, the database is obtained by automatically shooting each intersection image of the target area by the unmanned aerial vehicle according to each intersection GPS coordinate of the target area and a preset shooting height, and recording and warehousing.
Further, the intersection recognition model is obtained by training according to the intersection images in the database and a neural network algorithm.
The embodiment of the invention provides an unmanned aerial vehicle control system which is used for controlling an unmanned aerial vehicle to fly between two waypoints, determining the flying direction and the flying distance of the unmanned aerial vehicle through inertial navigation, and correcting the flying track of the unmanned aerial vehicle in real time according to a road image shot by the unmanned aerial vehicle in the flying process, so that the unmanned aerial vehicle does not depend on a GPS positioning system in the flying process, and meanwhile, the flying accuracy of the unmanned aerial vehicle unmanned GPS is ensured. When the unmanned aerial vehicle arrives near the intersection, the intersection image shot by the unmanned aerial vehicle is compared with the corresponding intersection image in the preset database, the position of the unmanned aerial vehicle is accurately corrected, the unmanned aerial vehicle accurately arrives at the center point of the intersection, the flight error generated in inertial navigation is reduced, and the unmanned aerial vehicle unmanned GPS flight accuracy is further improved.
Embodiment four:
as shown in fig. 8, an embodiment of the present invention provides a unmanned aerial vehicle navigation system, including a route making module 50 and an executing module 60;
The route making module 50 is configured to obtain a starting point and an ending point of navigation by the unmanned aerial vehicle, and make a flight route according to a road topology map of the target area, where the starting point and the ending point are located in a road network of the target area; the flight route comprises a plurality of waypoints, wherein the waypoints comprise the starting point, the ending point and various intersections in the road network;
the execution route module 60 is configured to execute the unmanned aerial vehicle control method based on the road network according to the navigation sequence of the flight navigation, and sequentially fly from the current waypoint to the next waypoint from the start point until the unmanned aerial vehicle reaches the end point.
Further, the route planning module 50 plans a flight route according to the road topology map of the target area, specifically:
and acquiring a first intersection closest to the starting point and a second intersection closest to the end point from a road topological graph of a target area, acquiring the shortest path from the first intersection to the second intersection by using a shortest path algorithm in the road topological graph, and merging the path from the starting point to the first intersection, the shortest path from the first intersection to the second intersection and the path from the second intersection to the end point to serve as the flight route.
The embodiment of the invention provides an unmanned aerial vehicle navigation system, which takes an intersection, a starting point and a terminal point, through which a flight route of an unmanned aerial vehicle passes, as waypoints, and splits the whole flight path of the unmanned aerial vehicle into a plurality of sections of flight paths by the waypoints, so that the flight process of the unmanned aerial vehicle is simplified, the unmanned aerial vehicle can directly fly between adjacent waypoints by using inertial navigation, and the unmanned aerial vehicle control method is used for controlling the unmanned aerial vehicle to fly between the adjacent waypoints, thereby realizing unmanned aerial vehicle GPS navigation and ensuring the unmanned aerial vehicle GPS navigation accuracy.
Fifth embodiment:
the embodiment of the invention provides a terminal, which comprises a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, wherein the processor realizes the unmanned aerial vehicle control method based on a road network or the unmanned aerial vehicle navigation method based on the road network when executing the computer program.
The processor may be a central processing unit (Central Processing Unit, CPU), other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, which is a control center of the terminal, connecting various parts of the entire terminal using various interfaces and lines.
The memory may be used to store the computer program, and the processor may implement various functions of the terminal by running or executing the computer program stored in the memory and invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data (such as audio data, phonebook, etc.) created according to the use of the handset, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart Media Card (SMC), secure Digital (SD) Card, flash Card (Flash Card), at least one disk storage device, flash memory device, or other volatile solid-state storage device.
Example six:
the embodiment of the invention provides a computer readable storage medium, which comprises a stored computer program, wherein when the computer program runs, equipment where the computer readable storage medium is located is controlled to execute the unmanned aerial vehicle control method based on a road network or the unmanned aerial vehicle navigation method based on the road network.
The modules integrated by the unmanned aerial vehicle control method based on the road network or the unmanned aerial vehicle navigation method based on the road network can be stored in a computer readable storage medium if the modules are realized in the form of software functional units and sold or used as independent products. Based on such understanding, the present invention may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth.
The foregoing embodiments have been provided for the purpose of illustrating the general principles of the present invention, and are not to be construed as limiting the scope of the invention. It should be noted that any modifications, equivalent substitutions, improvements, etc. made by those skilled in the art without departing from the spirit and principles of the present invention are intended to be included in the scope of the present invention.
Claims (16)
1. A method of unmanned aerial vehicle control, comprising:
the unmanned aerial vehicle acquires a first waypoint and a second waypoint, wherein the first waypoint and the second waypoint are positioned in a road network of a target area, and the first waypoint is the current position of the unmanned aerial vehicle;
the unmanned aerial vehicle determines the flight direction and the flight distance of inertial navigation from the first waypoint to the second waypoint according to a road topological graph of a target area;
the unmanned aerial vehicle flies from the first navigation point to the second navigation point according to the inertial navigation, and the flight track is corrected in real time according to the road image shot by the unmanned aerial vehicle in real time in the flight process;
if the second waypoint is an intersection in the road network, when the unmanned aerial vehicle reaches a preset area corresponding to the second waypoint, comparing an intersection image of the second waypoint shot by the unmanned aerial vehicle in real time with an intersection image of a corresponding place in a preset database, and adjusting the position of the unmanned aerial vehicle to the center of the intersection in the road network according to a comparison result; the preset area corresponding to the second waypoint is determined according to the position of the second waypoint on the road topological graph.
2. The unmanned aerial vehicle control method of claim 1, wherein the real-time correction of the flight trajectory during the flight according to the road image captured by the unmanned aerial vehicle in real time is specifically: and extracting a first road in the image under the unmanned aerial vehicle by using a computer vision algorithm through the image under the unmanned aerial vehicle which is shot in real time, and correcting the flight track in real time according to the position of the unmanned aerial vehicle in the first road.
3. The unmanned aerial vehicle control method according to claim 1, wherein if the second waypoint is an intersection in the road network, when the unmanned aerial vehicle reaches a preset area corresponding to the second waypoint, comparing an intersection image of the second waypoint photographed by the unmanned aerial vehicle in real time with an intersection image of a corresponding place in a preset database, and adjusting the position of the unmanned aerial vehicle to an intersection center in the road network according to a comparison result, wherein the method comprises the following steps:
when the unmanned aerial vehicle judges that the unmanned aerial vehicle reaches a preset area corresponding to the second navigation point according to the flying distance of the inertial navigation, transmitting a first image right below the unmanned aerial vehicle, which is shot in real time, into a preset intersection recognition model so that the intersection recognition model judges whether the first image right below the unmanned aerial vehicle contains a first intersection or not, and if the first intersection is not contained, continuing to fly according to the flying direction of the inertial navigation by the unmanned aerial vehicle; if the first intersection is included, the unmanned aerial vehicle continuously compares the image under the real-time shooting with the intersection image of the corresponding place in the database, and translates to the center of the first intersection according to the comparison result until the unmanned aerial vehicle reaches the center of the first intersection.
4. A control method of an unmanned aerial vehicle according to claim 3, wherein the database is obtained by the unmanned aerial vehicle automatically shooting each intersection image of the target area according to each intersection GPS coordinate of the target area and a preset shooting height, and recording and warehousing.
5. A method of unmanned aerial vehicle control according to claim 3, wherein the crossing recognition model is obtained by training based on crossing images in the database and a neural network algorithm.
6. A method of unmanned aerial vehicle navigation, comprising:
the unmanned aerial vehicle acquires a starting point and an ending point of navigation, and formulates a flight route according to a road topological graph of a target area, wherein the starting point and the ending point are positioned in a road network of the target area; the flight route comprises a plurality of waypoints, wherein the waypoints comprise the starting point, the ending point and various intersections in the road network;
the unmanned aerial vehicle executes the unmanned aerial vehicle control method based on the road network according to any one of claims 1 to 5 according to the navigation sequence of the flight navigation, and sequentially flies from the current waypoint to the next waypoint from the starting point until the unmanned aerial vehicle reaches the ending point.
7. The unmanned aerial vehicle navigation method of claim 6, wherein the making of the flight route according to the road topology map of the target area is specifically:
and acquiring a first intersection closest to the starting point and a second intersection closest to the end point from a road topological graph of a target area, acquiring the shortest path from the first intersection to the second intersection by using a shortest path algorithm in the road topological graph, and merging the path from the starting point to the first intersection, the shortest path from the first intersection to the second intersection and the path from the second intersection to the end point to serve as the flight route.
8. The unmanned aerial vehicle control system is characterized by comprising an acquisition module, a navigation module, a track correction module and a position correction module;
the acquisition module is used for acquiring a first waypoint and a second waypoint of the unmanned aerial vehicle, wherein the first waypoint and the second waypoint are positioned in a road network of a target area, and the first waypoint is the current position of the unmanned aerial vehicle;
the navigation module is used for acquiring a road topological graph of a target area, and determining the flight direction and the flight distance of inertial navigation of the unmanned aerial vehicle from the first navigation point to the second navigation point;
The track correction module is used for enabling the unmanned aerial vehicle to fly from the first navigation point to the second navigation point according to the inertial navigation, and correcting the flight track in real time according to the road image shot by the unmanned aerial vehicle in real time in the flight process;
the position correction module is used for comparing the intersection image of the second waypoint shot by the unmanned aerial vehicle in real time with the intersection image of the corresponding place in a preset database when the unmanned aerial vehicle reaches a preset area corresponding to the second waypoint if the second waypoint is an intersection in the road network, and adjusting the position of the unmanned aerial vehicle to the center of the intersection in the road network according to a comparison result; the preset area corresponding to the second waypoint is determined according to the position of the second waypoint on the road topological graph.
9. The unmanned aerial vehicle control system of claim 8, wherein the trajectory correction module is configured to correct the flight trajectory in real time according to the road image captured by the unmanned aerial vehicle in real time during the flight, specifically: and extracting a first road in the image under the unmanned aerial vehicle by using a computer vision algorithm through the image under the unmanned aerial vehicle which is shot in real time, and correcting the flight track in real time according to the position of the unmanned aerial vehicle in the first road.
10. The unmanned aerial vehicle control system of claim 8, wherein the position correction module is configured to compare an intersection image of the second waypoint captured by the unmanned aerial vehicle in real time with an intersection image of a corresponding place in a preset database when the unmanned aerial vehicle reaches a preset area corresponding to the second waypoint if the second waypoint is an intersection in the road network, and adjust the position of the unmanned aerial vehicle to an intersection center in the road network according to a comparison result, specifically:
when the unmanned aerial vehicle judges that the unmanned aerial vehicle reaches a preset area corresponding to the second navigation point according to the flying distance of the inertial navigation, transmitting a first image right below the unmanned aerial vehicle, which is shot in real time, into a preset intersection recognition model so that the intersection recognition model judges whether the first image right below the unmanned aerial vehicle contains a first intersection or not, and if the first intersection is not contained, continuing to fly according to the flying direction of the inertial navigation by the unmanned aerial vehicle; if the first intersection is included, the unmanned aerial vehicle continuously compares the image under the real-time shooting with the intersection image of the corresponding place in the database, and translates to the center of the first intersection according to the comparison result until the unmanned aerial vehicle reaches the center of the first intersection.
11. The unmanned aerial vehicle control system of claim 10, wherein the database is obtained by the unmanned aerial vehicle automatically capturing images of each intersection of the target area according to GPS coordinates of each intersection of the target area and a preset capturing height and recording the images in a warehouse.
12. The unmanned aerial vehicle control system of claim 10, wherein the crossing recognition model is trained from crossing images in the database and a neural network algorithm.
13. The unmanned aerial vehicle navigation system is characterized by comprising a route making module and an executing module;
the navigation system comprises a navigation establishing module, a navigation establishing module and a navigation information processing module, wherein the navigation establishing module is used for acquiring a starting point and a destination point of navigation of an unmanned aerial vehicle, and establishing a flight route according to a road topological graph of a target area, wherein the starting point and the destination point are positioned in a road network of the target area; the flight route comprises a plurality of waypoints, wherein the waypoints comprise the starting point, the ending point and various intersections in the road network;
the execution route module is configured to execute the unmanned aerial vehicle control method based on the road network according to the navigation sequence of the flight navigation, as set forth in any one of claims 1 to 5, from the starting point, sequentially flying from the current waypoint to the next waypoint until the unmanned aerial vehicle reaches the end point.
14. The unmanned aerial vehicle navigation system of claim 13, wherein the route planning module plans a flight route according to a road topology map of the target area, specifically:
and acquiring a first intersection closest to the starting point and a second intersection closest to the end point from a road topological graph of a target area, acquiring the shortest path from the first intersection to the second intersection by using a shortest path algorithm in the road topological graph, and merging the path from the starting point to the first intersection, the shortest path from the first intersection to the second intersection and the path from the second intersection to the end point to serve as the flight route.
15. A terminal comprising a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, the processor implementing a drone control method according to any one of claims 1 to 5 or a drone navigation method according to any one of claims 1 to 7 when executing the computer program.
16. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored computer program, wherein the computer program, when run, controls a device in which the computer readable storage medium is located to perform a drone control method according to any one of claims 1 to 5 or to perform a drone navigation method according to any one of claims 1 to 7.
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