A cluster unmanned aerial vehicle "air mobile base station" autonomous positioning method in a denial environment

Abstract

The application discloses a kind of cluster unmanned aerial vehicle "air mobile base station" autonomous positioning method under denial environment, belong to unmanned aerial vehicle cooperative positioning field, this method is in different stages of task execution, change cluster unmanned aerial vehicle in cooperative positioning system Identity, i.e. let different unmanned aerial vehicle act as "air mobile base station" at appropriate time, construct cluster coordinate system, according to the distance between the rest unmanned aerial vehicle in cluster coordinate system and unmanned aerial vehicle as "air mobile base station", the position coordinates of the rest unmanned aerial vehicle in cluster coordinate system are solved using least square method, realize cooperative positioning of cluster unmanned aerial vehicle system in denial environment not dependent on external equipment deployment, improve the flexibility of unmanned aerial vehicle to execute task, effectively widen the application scenario of cluster unmanned aerial vehicle.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of cooperative positioning of unmanned aerial vehicles, and more particularly relates to a method for autonomous positioning of a cluster of unmanned aerial vehicles as "airborne mobile base stations" in a denial environment. BACKGROUND

[0002] Unmanned aerial vehicles can carry various sensors and perform tasks in various scenarios. With the development of microprocessor technology, sensor technology and manufacturing technology, unmanned aerial vehicles are becoming increasingly intelligent and small. However, due to the poor survivability of a single unmanned aerial vehicle, it cannot perform complex tasks, so it is often used in the form of a cluster of unmanned aerial vehicles to perform tasks cooperatively. Unmanned aerial vehicle clusters play an increasingly important role in cooperative detection, global attack and tactical deception, but in complex battlefield environments, there are incomplete information situations such as electromagnetic interference and GNSS (Global Navigation Satellite System) denial, making it difficult to guarantee the inter-vehicle positioning and self-positioning of the cluster of unmanned aerial vehicles. In order to provide reliable position information data during task execution, all unmanned aerial vehicles in the cluster must have a common position reference frame.

[0003] Most of the current mainstream cooperative positioning schemes use anchor-based ultra-wideband (UWB) positioning, laser radar and vision-based sensors. Traditional anchor-based ultra-wideband (UWB) positioning requires the deployment of UWB anchor base stations in advance, but the cluster of unmanned aerial vehicles often faces unknown areas and environments when performing tasks, so it is not possible to deploy base stations in advance. Although VIO systems can be used in various environments without bulky external devices, vision-based schemes are not ideal or even fail in dim environments, rainy and snowy weather, fast motion and other situations, and their state estimation has serious drift, which can cause damage to multi-unmanned aerial vehicle systems.

[0004] Therefore, there is an urgent need for a cooperative positioning strategy that does not rely on external device deployment and can cope with various environmental factor disturbances to ensure the execution of tasks by a cluster of unmanned aerial vehicles in a denial environment. SUMMARY

[0005] In view of the above defects or improvement needs of the prior art, the present application provides a method for autonomous positioning of a cluster of unmanned aerial vehicles in a denial environment, which realizes cooperative positioning of a cluster of unmanned aerial vehicles in a denial environment without relying on external device deployment, improves the flexibility of unmanned aerial vehicles in performing tasks, and effectively broadens the application scenarios of a cluster of unmanned aerial vehicles.

[0006] To achieve the above-mentioned purpose, according to a first aspect of the present application, a method for autonomous positioning of a cluster of unmanned aerial vehicles in a denial environment is provided, comprising:

[0007] S1, three unmanned aerial vehicles P0, P1, P2 are selected from the unmanned aerial vehicle cluster to fly to three different positions not in a line, and the relative positions of the three unmanned aerial vehicles are kept unchanged, an initial two-dimensional coordinate system is established with P0 as a coordinate origin, a line between P0 and P1 as an x axis, and a vertical line of P2 to the line as a y axis; wherein the flight heights of all the unmanned aerial vehicles in the unmanned aerial vehicle cluster are the same;

[0008] S2, other unmanned aerial vehicles respectively solve their own position coordinates in the initial two-dimensional coordinate system, and perform tasks in a denial environment according to the own position coordinates;

[0009] S3, three other unmanned aerial vehicles P0', P1', P2' not in a line are selected, the relative positions of the three unmanned aerial vehicles are kept unchanged, a new two-dimensional coordinate system is established with P0' as a coordinate origin, a line between P0' and P1' as an x axis, and a vertical line of P2' to the line as a y axis;

[0010] S4, P0, P1, P2 respectively solve their own position coordinates in the new two-dimensional coordinate system, and perform tasks in a denial environment according to the own position coordinates.

[0011] According to a second aspect of the present application, an electronic device is provided, comprising: a computer readable storage medium and a processor;

[0012] The computer readable storage medium is used to store executable instructions;

[0013] The processor is used to read the executable instructions stored in the computer readable storage medium, and execute the method according to the first aspect.

[0014] According to a third aspect of the present application, a computer readable storage medium is provided, the computer readable storage medium stores computer instructions, and the computer instructions are used to make the processor execute the method according to the first aspect.

[0015] According to a fourth aspect of the present application, a computer program product is provided, comprising a computer program or instructions, and the computer program or instructions are executed by the processor to realize the method according to the first aspect.

[0016] Overall, compared with the prior art, the above technical solutions conceived by the present application can achieve the following beneficial effects:

[0017] The method provided by the application changes the identity of the cluster unmanned aerial vehicle in the cooperative positioning system at different stages of task execution, that is, different unmanned aerial vehicles serve as an "air mobile base station" at appropriate times, constructs a cluster coordinate system, and calculates the position coordinates of the remaining unmanned aerial vehicles in the cluster coordinate system according to the distance between the remaining unmanned aerial vehicles and the unmanned aerial vehicle serving as the "air mobile base station" in the cluster coordinate system, thereby realizing cooperative positioning of the cluster unmanned aerial vehicle system in a denial environment independent of external device deployment, improving the flexibility of the unmanned aerial vehicle in executing tasks, and effectively widening the application scenarios of the cluster unmanned aerial vehicle.

[0018] Further, considering that the distance information between the unmanned aerial vehicles is obtained by sensors and has certain errors, the Pythagorean theorem and the least square method are used to calculate the position coordinates of the unmanned aerial vehicles in the cluster coordinate system, thereby improving the calculation accuracy. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 Fig. 1 is a cooperative positioning schematic diagram provided by an embodiment of the application;

[0020] Figure 2 Fig. 2 is another cooperative positioning schematic diagram provided by an embodiment of the application;

[0021] Figure 3 Fig. 3 is a third cooperative positioning schematic diagram provided by an embodiment of the application;

[0022] Figure 4 Fig. 4 is a fourth cooperative positioning schematic diagram provided by an embodiment of the application;

[0023] Figure 5 Fig. 5 is a hardware system block diagram of a quad-rotor unmanned aerial vehicle provided by an embodiment of the application;

[0024] Figure 6 Fig. 6 is a hardware system block diagram of a cluster quad-rotor unmanned aerial vehicle provided by an embodiment of the application. DETAILED DESCRIPTION

[0025] In order to make the objectives, technical solutions and advantages of the application clearer, the following further describes the application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the application and do not limit the application. In addition, the technical features involved in each embodiment of the application described below can be combined with each other as long as they do not conflict with each other.

[0026] An autonomous positioning method for a cluster unmanned aerial vehicle in a denial environment provided by an embodiment of the application comprises:

[0027] S1, select three unmanned aerial vehicles P0, P1, P2 from the unmanned aerial vehicle cluster to fly to three different positions, and keep the relative positions unchanged, establish an initial two-dimensional coordinate system with P0 as the coordinate origin, the connecting line between P0 and P1 as the x-axis, and the vertical line of the connecting line parallel to the y-axis; wherein the flight heights of each unmanned aerial vehicle in the unmanned aerial vehicle cluster are the same;

[0028] First, select three unmanned aerial vehicles in the unmanned aerial vehicle cluster as initial "air mobile base stations", fly to any three positions relying on inertial navigation light flow rate, and establish an initial cluster coordinate system (i.e. initial two-dimensional coordinate system). As shown in Figure 1 , assuming that the coordinate information of the three unmanned aerial vehicles as initial "air mobile base stations" is P0(x0, y0)P1(x1, y1)P2(x2, y2), the height information is obtained from the information of the external sensor downward-looking laser radar, and the horizontal position information is determined by the distance information between the three unmanned aerial vehicles. In the present application, the flight heights of each unmanned aerial vehicle in the unmanned aerial vehicle cluster are the same, so the cluster coordinate system is established only on a two-dimensional plane, P0 is the coordinate origin, and the position coordinates of P1 and P2 in the initial two-dimensional coordinate system can be calculated according to the distances between P0, P1 and P2 by using the Pythagorean theorem, and the calculation formula is:

[0029] (x0, y0) = (0, 0)

[0030] (x1, y1) = (d 01 , 0)

[0031]

[0032] S2, other unmanned aerial vehicles respectively solve their own position coordinates in the initial two-dimensional coordinate system, and execute tasks in a denial environment according to their own position coordinates.

[0033] The other unmanned aerial vehicles solve their own position coordinates in the initial two-dimensional coordinate system according to the distance information of each unmanned aerial vehicle from P0, P1 and P2, and the position coordinates of P0, P1 and P2 in the initial two-dimensional coordinate system, and execute tasks in a denial environment according to their own position coordinates; that is, the other unmanned aerial vehicles solve their own position coordinates in the initial cluster coordinate system according to the distance information obtained from the three base stations, and flexibly execute their respective tasks in a denial environment.

[0034] Suppose the position coordinates of the remaining unmanned aerial vehicles with unknown position coordinates are P n (x n ,y n ), and the distances to the three mobile base stations are d 0n , d 1n , and d 2n , respectively, as Figure 2As shown, the position coordinates of the UAV in the cluster coordinate system can be calculated by using the Pythagorean theorem.

[0035] Further, considering that the distance information between the UAVs is usually obtained by sensors (for example, by a UWB module loaded on the UAV), there is a certain error, and based on this, preferably, the position coordinates of the UAV in the cluster coordinate system are calculated according to the Pythagorean theorem (i.e., the Pythagorean theorem) and the least square method, and the calculation formula is:

[0036]

[0037] According to the calculated position information, the remaining UAVs can execute their respective tasks in the denial area.

[0038] S3, select three other UAVs P0', P1', P2', keep the relative positions unchanged, take P0' as the coordinate origin, the connecting line between P0' and P1' as the x-axis, and the vertical line of the connecting line to P2' as the y-axis, and establish a new two-dimensional coordinate system.

[0039] After the aircraft to be executed complete the task and arrive at the respective target points, the identity of the cluster UAV in the cooperative positioning system is changed, that is, the "air mobile base station" at this time is replaced, three UAVs arriving at the target point are selected as the new "air mobile base station", such as the UAVs beside the signs 1, 2 and 3 in Figure 3 , a new cluster coordinate system is constructed. The coordinates of the new three air mobile base stations are P0'(x0', y0') P1'(x1', y1') P2'(x2', y2'), the initial position coordinates are determined by the distance information between the three aircrafts, and the calculation formula is the same as S1.

[0040] S4, P0, P1, P2 respectively solve their own position coordinates in the new two-dimensional coordinate system, and execute tasks in the denial environment according to their own position coordinates.

[0041] P0, P1, P2 respectively solve their own position coordinates in the new two-dimensional coordinate system according to the distance information of P0', P1', P2' and the position coordinates of P0', P1', P2' in the new two-dimensional coordinate system, and execute tasks in the denial environment according to their own position coordinates.

[0042] The initial three UAVs (i.e., the three UAVs in S1) solve their own position coordinates in the newly constructed cluster coordinate system and execute their respective tasks, as shown in Figure 4 . The calculation formula for solving the own position coordinates is the same as S2.

[0043] In S1 and S3, it should be ensured that the area of the triangle formed by the three UAVs as the "air mobile base station" is large enough to avoid other UAVs being located at the boundary of the triangle; if other UAVs are located near the edge of the triangle, position solving instability (multiple solutions) or large solving error may occur.

[0044] Therefore, preferably, in S1, the distance between any two of the UAVs P0, P1 and P2 is greater than a threshold after the UAVs fly to three different positions.

[0045] Preferably, in S3, the area of the triangle formed by P0', P1' and P2' is the largest.

[0046] That is, among the UAVs reaching the target, the three UAVs forming the triangle with the largest area are taken as P0', P1' and P2'.

[0047] If the UAV task needs to use a ground tag, in order to ensure the effectiveness of the global position of the ground tag, the absolute positions of P0, P1 and P2 in S1 remain unchanged, and the absolute positions of P0', P1' and P2' in S2 remain unchanged.

[0048] It can be understood that the relative positions of P0, P1 and P2 in S1 remain unchanged, and the relative positions of P0', P1' and P2' in S2 remain unchanged, in order to avoid the problem of UAV collision caused by the scale transformation of the cluster coordinate system and improve safety.

[0049] Taking a quadrotor UAV as an example, the hardware system thereof is shown in FIG. 1. Figures 5-6 The multi-UAV system interacts based on ROS, and the UAVs with communication links can obtain information transmitted by neighboring UAVs. Each UAV is configured with a UWB ranging sensor.

[0050] NVIDIA Jetson TX2 is used as the host computer to receive information transmitted from the flight control module, the UWB module and the like, generate expected control instructions in combination with the current flight task, and transmit the control instructions to the flight control board for execution.

[0051] The sensor modules used include a magnetometer, a gyroscope, a laser ranging radar, an optical flow, an accelerometer and a UWB. The magnetometer, the gyroscope and the accelerometer are built-in integrated sensors of the flight control board. The magnetometer provides heading information for the system, and the gyroscope and the accelerometer data are fused to provide attitude angle and three-axis acceleration information for the UAV system. The optical flow and the laser ranging radar are external sensors. The optical flow is a low-resolution downward camera, which can estimate the speed information of the UAV system in the horizontal plane by running an optical flow algorithm in combination with the height of the UAV. The laser ranging radar can measure accurate height information after being placed downward. The UWB is used to obtain the distance between the UWB module and other UWB modules.

[0052] PIXHWAK mini6 c is used as a flight control board, a data fusion algorithm of sensors is run, accurate state information of the unmanned aerial vehicle system is obtained by fusing data of built-in sensors such as magnetometers, gyroscopes and accelerometers and external sensors such as optical flow and laser ranging radar, and control signals are generated by combining the received control instructions from the host computer with the state information.

[0053] The ranging mode used by the application is UWB according to application and performance requirements, and the ranging module model is NooploopLinkTrack P-BP, which can provide centimeter-level precision distance measurement within a range of 500 meters. The distributed ranging mode of DR Mode is adopted, so that the distance information between the module and other ranging modules can be obtained.

[0054] The method provided by the application provides that each unmanned aerial vehicle in the cluster is equipped with a UWB module in a GNSS denial environment, and the data of optical flow, an inertial measurement unit and a downward-looking laser is fused, the identity of the cluster unmanned aerial vehicle in the cooperative positioning system is changed in different stages of task execution, that is, different unmanned aerial vehicles serve as "air mobile base stations" at appropriate times, a cluster coordinate system is constructed, the relative position coordinates between the remaining unmanned aerial vehicles are calculated by using the least square method according to the data obtained by the UWB, cooperative positioning of the cluster unmanned aerial vehicle system in the denial environment independent of external equipment deployment is realized, the flexibility of the unmanned aerial vehicle in executing tasks is improved, and the application scenarios of the cluster unmanned aerial vehicle are effectively widened.

[0055] The electronic device provided by the embodiment of the application comprises a computer readable storage medium and a processor.

[0056] The computer readable storage medium is used for storing executable instructions.

[0057] The processor is used for reading the executable instructions stored in the computer readable storage medium and executing the method according to any one of the above embodiments.

[0058] The computer readable storage medium provided by the embodiment of the application stores computer instructions, and the computer instructions are used for causing the processor to execute the method according to any one of the above embodiments.

[0059] The computer program product provided by the embodiment of the application comprises a computer program or instructions, and the computer program or instructions are executed by the processor to realize the method according to any one of the above embodiments.

[0060] Those skilled in the art can easily understand that the above description is only the preferred embodiment of the present application, and is not intended to limit the present application. Any modification, equivalent replacement and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for autonomous positioning of a swarm of unmanned aerial vehicles in a denial environment, the method comprising: The method comprises: S1. Selecting three unmanned aerial vehicles P0, P1 and P2 from a cluster of unmanned aerial vehicles to fly to three different positions that are not collinear, and keeping the relative positions unchanged, establishing an initial two-dimensional coordinate system with P0 as the coordinate origin, the line between P0 and P1 as the x-axis, and the vertical line of P2 to the line as the y-axis; wherein the flight altitudes of the unmanned aerial vehicles in the cluster are all the same; S2. Other unmanned aerial vehicles respectively solve their own position coordinates in the initial two-dimensional coordinate system, and execute tasks in a denial environment according to the own position coordinates; S3. Selecting three other unmanned aerial vehicles P0', P1' and P2' that are not collinear, keeping the relative positions unchanged, establishing a new two-dimensional coordinate system with P0' as the coordinate origin, the line between P0' and P1' as the x-axis, and the vertical line of P2' to the line as the y-axis; S4. P0, P1 and P2 respectively solve their own position coordinates in the new two-dimensional coordinate system, and execute tasks in a denial environment according to the own position coordinates.

2. The method of claim 1, wherein, In S2, the Pythagorean theorem and least square method are used to solve the position of other UAVs P n The position coordinates (x n ,y n ) in the initial two-dimensional coordinate system are calculated by the following formula: wherein (x0, y0) = (0, 0), (x1, y1) = (d 01 , 0), are position coordinates of P0, P1, P2 in the initial two-dimensional coordinate system respectively, d 01 , d 02 , d 12 are distances between P0 and P1, P0 and P2, P1 and P2 respectively, d 0n , d 1n , d 2n are distances between P0, P1, P2 and P n .

3. The method of claim 1, wherein, In S1, the distances between any two of P0, P1 and P2 after flying to the three different positions are all greater than a threshold value.

4. The method of claim 1, wherein, In S3, the area of the triangle formed by P0', P1' and P2' is the largest.

5. The method of claim 1, wherein, If the unmanned aerial vehicle task needs to use a ground tag, the absolute positions of P0, P1 and P2 in S1 remain unchanged, and the absolute positions of P0', P1' and P2' in S2 remain unchanged.

6. An electronic device, comprising: The computer readable storage medium and the processor are included; The computer readable storage medium is used to store executable instructions; The processor is used to read the executable instructions stored in the computer readable storage medium, and execute the method according to any one of claims 1-5. The computer readable storage medium stores computer instructions, and the computer instructions are used to make the processor execute the method according to any one of claims 1-5.

7. A computer readable storage medium characterized in that, The computer program or instructions are executed by the processor to realize the method according to any one of claims 1-5.

8. A computer program product comprising computer programs or instructions, characterized in that, ​

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