Multi-uav cooperative slam method

Abstract

The application discloses a multi-unmanned aerial vehicle cooperation SLAM method, comprising the following steps: obtaining hardware support data of all unmanned aerial vehicles, and grouping the unmanned aerial vehicles according to functions based on the hardware support data; generating a release order and a plurality of cruising paths corresponding to the unmanned aerial vehicles based on the grouping result; releasing the unmanned aerial vehicles based on the release order, and controlling the unmanned aerial vehicles to reach target positions based on the grouping result; controlling the unmanned aerial vehicles to move along the cruising paths starting from the target positions; taking real-time images during the movement of the unmanned aerial vehicles, and uploading the real-time images to a ground data control station; and generating a three-dimensional map by using the ground data control station and a SLAM algorithm. The unmanned aerial vehicles with different performances cooperate with each other, the unmanned aerial vehicles in a high-altitude and large-range shooting group can accurately grasp the real-time positions of the unmanned aerial vehicles in a low-altitude and small-range shooting group, the shooting positions of the unmanned aerial vehicles in the low-altitude and small-range shooting group are accurately determined, and the accuracy of the three-dimensional map is fully ensured.

Description

Technical Field

[0001] This invention relates to the field of real-time localization and mapping technology, specifically a multi-UAV collaborative SLAM method. Background Technology

[0002] SLAM (Simultaneous Localization and Mapping) is a technology that enables machines to locate themselves in unknown environments and build environmental maps in real time using sensors. The core principle of SLAM is to fuse measurement data from sensors (such as LiDAR, cameras, and millimeter-wave radar) to simultaneously estimate the device's own trajectory and the coordinates of environmental features, thereby generating a map. With the rapid development of drone technology, using drones to implement SLAM is gradually becoming a mainstream technology. Drones offer wide coverage, high flexibility, and are suitable for various complex environments.

[0003] In existing technologies, multiple drones of the same model are mainly used in combination for SLAM to facilitate control. However, to improve accuracy, the performance of all drones needs to be improved overall, resulting in high costs. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a multi-UAV collaborative SLAM method that utilizes UAVs with different performance characteristics to cooperate with each other. During the shooting process, the UAVs in the high-altitude, large-scale shooting group can accurately grasp the real-time positions of the UAVs in the low-altitude, small-scale shooting group. Furthermore, by combining a position mutual verification mechanism, the shooting positions of the UAVs in the low-altitude, small-scale shooting group can be determined with sufficient accuracy. This ensures the accuracy of the 3D map when the SLAM algorithm is subsequently executed to generate the 3D map.

[0005] To achieve the above objectives, the specific solution adopted by the present invention is as follows: A multi-UAV cooperative SLAM method includes the following steps: Obtain hardware support data for all drones, and group all drones by function based on the hardware support data.

[0006] Based on the results of the functional grouping, a launch sequence and multiple cruise paths corresponding to the UAV are generated.

[0007] The drone is launched according to the launch sequence, and the drone is controlled to reach the target location based on the result of the functional grouping.

[0008] The drone is controlled to move along the cruise path, starting from the target location.

[0009] The drone captures real-time images during its movement and uploads these images to the ground data control station.

[0010] The ground data control station is used to generate a 3D map using the SLAM algorithm.

[0011] Preferably, the hardware support data includes flight support data and image support data, wherein the flight support data includes altitude and the image support data includes image resolution.

[0012] Preferably, the method for functionally grouping all the UAVs based on the hardware support data includes: When the altitude meets the preset first requirement, the drone is assigned to the high-altitude wide-range shooting group.

[0013] Of all the remaining drones, those whose image resolution meets the preset second requirement are classified into a low-altitude, small-range shooting group.

[0014] Preferably, after functionally grouping all the drones, the high-altitude wide-range shooting group and the low-altitude small-range shooting group are assigned positions, and the target position is assigned to each drone.

[0015] Preferably, the method for assigning the target location to each of the drones includes: Determine the coverage area, and based on the coverage area, determine the target location of the UAV in the high-altitude wide-range shooting group.

[0016] The target position of the drone in the low-altitude small-range shooting group is determined based on the target position of the drone in the high-altitude large-range shooting group, so that the drone in the high-altitude large-range shooting group can capture images of at least one drone in the low-altitude small-range shooting group.

[0017] Preferably, after assigning the target location to each of the UAVs, multiple auxiliary communication nodes are selected from all the UAVs based on the target location, and each auxiliary communication node is communicatively connected to multiple of the UAVs.

[0018] Preferably, the order of launching the drones in the high-altitude wide-range shooting group takes precedence over the order of launching the drones in the low-altitude small-range shooting group.

[0019] Preferably, when launching the drones according to the launch sequence, the drones in the low-altitude small-range shooting group are launched after the drones in the high-altitude wide-range shooting group reach the target position.

[0020] Preferably, during the process of controlling the UAV to move along the cruise path from the target location, the UAVs mutually verify their real-time positions based on the results of the functional grouping.

[0021] Preferably, after the drones acquire real-time images during their movement, they back up the real-time images to each other.

[0022] This invention enables drones with different performance levels to cooperate with each other and to group drones by function based on their hardware support data, so that the drones can cooperate better. During the shooting process, the drones in the high-altitude large-scale shooting group can accurately grasp the real-time position of the drones in the low-altitude small-scale shooting group. Then, combined with the position mutual verification mechanism, the shooting position of the drones in the low-altitude small-scale shooting group can be determined with sufficient accuracy. This ensures the accuracy of the 3D map when the SLAM algorithm is executed to generate a 3D map. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a spatial location diagram of the high-altitude wide-range shooting group and the low-altitude small-range shooting group. Detailed Implementation

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] Please see Figure 1 and Figure 2 , Figure 1 This is a flowchart of the method of the present invention. Figure 2 This is a spatial location diagram of the high-altitude wide-range shooting group and the low-altitude small-range shooting group.

[0027] like Figure 1 and Figure 2 As shown, a multi-UAV cooperative SLAM method includes the following steps: S1: Obtain hardware support data for all drones and group all drones by function based on the hardware support data.

[0028] Existing multi-drone SLAM methods often use drones of the same specifications or models. To ensure overall accuracy, high-performance drones are required, leading to high costs. To address this issue, this invention combines drones of different specifications, using hardware-supported data to functionally group drones. This allows drones with different hardware and performance to perform different tasks, thereby reducing the number of high-performance drones needed while maintaining overall accuracy, and ultimately lowering costs.

[0029] More specifically, in step S1, the hardware support data includes flight support data and image support data. The flight support data includes the service ceiling, which is used to determine the altitude of the UAV. The image support data includes the image resolution, which is used to determine the UAV's shooting target.

[0030] The method for functionally grouping all drones based on hardware support data specifically includes: S11: When the service ceiling meets the preset first requirement, the drone is assigned to the high-altitude wide-range shooting group. When the service ceiling meets the first requirement, it means that the drone can fly to a higher altitude, thereby obtaining a wider field of view. Therefore, these drones are assigned to the high-altitude wide-range shooting group, enabling them to shoot a wider area from a higher altitude.

[0031] S12: Among all the remaining drones, those whose image resolution meets the preset second requirement are assigned to the low-altitude, small-range shooting group. When the image resolution meets the second requirement, it means that the drone can capture sufficiently clear images to obtain more details. Therefore, these drones are assigned to the low-altitude, small-range shooting group, enabling them to take clearer pictures at lower altitudes and closer distances.

[0032] To enable precise control of drones in different groups and ensure their successful completion of their missions—specifically, to ensure that drones in the high-altitude wide-range imaging group capture a larger area and drones in the low-altitude narrow-range imaging group capture clearer images—all drones are functionally grouped. Then, positions are assigned to the high-altitude wide-range imaging group and the low-altitude narrow-range imaging group, assigning a target position to each drone. The method for assigning a target position to each drone specifically includes the following steps: S13: Determine the coverage area and, based on this area, determine the target positions of the drones in the high-altitude wide-area imaging group. The coverage area refers to the region where SLAM needs to be performed, and its location can be determined based on geographic coordinates. After determining the coverage area, the target positions of these drones are determined by combining their field of view (LAD) with that of all drones in the high-altitude wide-area imaging group, using the condition that the combined LAD of all drones in the group can encompass the coverage area. More specifically, first, determine the LAD of all drones in the high-altitude wide-area imaging group when they reach their service ceiling. If the combined LAD of all drones at this point is significantly larger than the coverage area, then lower the altitude of the drones in the high-altitude wide-area imaging group to reduce the LAD of each drone. Although the LAD is smaller at a lower altitude, the image clarity is improved. In this way, the altitude and position of all drones in the high-altitude wide-area imaging group can be continuously adjusted to ensure sufficient coverage of the area while improving the accuracy of the images captured. It should also be noted that if the combined field of view of all drones in the high-altitude wide-range shooting group is smaller than the coverage area when all drones in the high-altitude wide-range shooting group reach their service ceiling, then the number of drones in the high-altitude wide-range shooting group needs to be increased. If the difference between the overall range and the coverage area is small, the altitude of the drones in the high-altitude wide-range shooting group can be reduced, thereby transferring some drones from the low-altitude small-range shooting group to the high-altitude wide-range shooting group, making the overall range larger than the coverage area, without needing to introduce more drones.

[0033] S14: Determine the target position of the drone in the low-altitude small-range shooting group based on the target position of the drone in the high-altitude large-range shooting group, so that the drone in the high-altitude large-range shooting group can capture images of at least one drone in the low-altitude small-range shooting group. In this way, the drone in the low-altitude small-range shooting group can be captured by at least one drone in the high-altitude large-range shooting group during its movement, ensuring precise control of the position of the drone in the low-altitude small-range shooting group, thereby guaranteeing the accuracy of the final result.

[0034] After assigning target locations to each UAV, multiple UAVs are selected as auxiliary communication nodes based on these locations. Each auxiliary communication node communicates with multiple UAVs. To ensure that all UAVs can communicate successfully with the ground data control station and upload the captured images to the station for SLAM algorithm generation, UAVs in the high-altitude wide-range shooting group are selected as the first target when determining auxiliary communication nodes. This is because UAVs in the high-altitude wide-range shooting group can capture images of UAVs in the low-altitude narrow-range shooting group and communicate with them more easily. Based on this, the UAVs in the low-altitude narrow-range shooting group are further grouped according to their target locations. The distance between UAVs in the same group cannot exceed a preset threshold, thus ensuring that all UAVs in the same group are within a certain area. Within each area, one UAV is designated as the second target. All first and second targets are then used as auxiliary communication nodes. During flight, all UAVs prioritize direct communication with the ground data control station. If direct communication is not possible, they first attempt to communicate with the second target in the auxiliary communication node. If communication still fails, they then communicate with the first target in the auxiliary communication node.

[0035] S2: Based on the functional grouping results, a launch order and multiple cruise paths corresponding to the drones are generated. More specifically, the launch order of drones in the high-altitude wide-range shooting group takes precedence over the launch order of drones in the low-altitude small-range shooting group. The cruise paths can be determined according to the actual situation of the coverage area and are planned using existing path planning algorithms, which are mature existing technologies in this field and will not be elaborated further here.

[0036] S3: Launch drones based on the launch sequence and control them to reach the target location based on the results of functional grouping. More specifically, when launching drones based on the launch sequence, after the drones in the high-altitude wide-range shooting group reach the target location, launch the drones in the low-altitude small-range shooting group.

[0037] After all drones in the high-altitude wide-range shooting group and the low-altitude small-range shooting group have reached the target position and are ready, control the drones to move along the cruise path.

[0038] S4: Control the drones to move along the cruise path from the target location. During this process, the drones cross-check their real-time positions based on the results of functional grouping. More specifically, after takeoff, the drones in the high-altitude, wide-range shooting group maintain their positions and determine their absolute positions using BeiDou positioning. They then build a local area network using Wi-Fi technology. The drones in the low-altitude, small-range shooting group use Wi-Fi positioning and other technologies to determine their real-time positions within this local area network. They then share their positions, enabling mutual verification and accurate positioning of each drone. This ensures the accuracy of the generated 3D map when the SLAM algorithm is applied to the footage captured by the drones.

[0039] S5: The drone captures real-time imagery during its movement and uploads it to the ground data control station. Furthermore, after capturing real-time imagery, the drone backs up the images to each other, thus preventing the loss of images captured by the drone and ensuring the accuracy of the final generated 3D map.

[0040] S6: Generate a 3D map using the SLAM algorithm with ground data control stations. The SLAM algorithm is a mature existing technology in this field and will not be described in detail here.

[0041] This invention enables drones with different performance levels to cooperate with each other and to group drones by function based on their hardware support data, so that the drones can cooperate better. During the shooting process, the drones in the high-altitude large-scale shooting group can accurately grasp the real-time position of the drones in the low-altitude small-scale shooting group. Then, combined with the position mutual verification mechanism, the shooting position of the drones in the low-altitude small-scale shooting group can be determined with sufficient accuracy. This ensures the accuracy of the 3D map when the SLAM algorithm is executed to generate a 3D map.

[0042] In practical implementation, the ground data control station may include a memory and a processor, wherein the processor is used to process the real-time images transmitted by the high-altitude wide-range shooting group and the low-altitude small-range shooting group and to run the SLAM algorithm, and the memory is used to store the SLAM results.

[0043] It should be understood that the processor in the embodiments of the present invention can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0044] It should also be understood that the memory in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0045] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage system such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0046] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0047] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0048] In the embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0049] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer system (which may be a personal computer, server, or network system, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0050] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0051] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A multi-UAV cooperative SLAM method, characterized in that, Includes the following steps: Obtain hardware support data for all drones, and group all drones by function based on the hardware support data; Based on the results of the functional grouping, a launch sequence and multiple cruise paths corresponding to the UAV are generated; The drone is launched according to the launch sequence, and the drone is controlled to reach the target location based on the result of the functional grouping. Control the drone to move along the cruise path, starting from the target location; The drone captures real-time images during its movement and uploads the real-time images to the ground data control station. The ground data control station is used to generate a 3D map using the SLAM algorithm.

2. The multi-UAV cooperative SLAM method as described in claim 1, characterized in that, The hardware support data includes flight support data and image support data. The flight support data includes the altitude, and the image support data includes the image resolution.

3. The multi-UAV cooperative SLAM method as described in claim 2, characterized in that, The method for functionally grouping all the UAVs based on the hardware support data includes: When the altitude meets the preset first requirement, the drone will be assigned to the high-altitude wide-range shooting group; Of all the remaining drones, those whose image resolution meets the preset second requirement are classified into a low-altitude, small-range shooting group.

4. The multi-UAV cooperative SLAM method as described in claim 3, characterized in that, After functionally grouping all the drones, the high-altitude wide-range shooting group and the low-altitude small-range shooting group are assigned positions, and the target position is assigned to each drone.

5. The multi-UAV cooperative SLAM method as described in claim 4, characterized in that, The method for assigning the target location to each of the drones includes: Determine the coverage area, and based on the coverage area, determine the target location of the UAV in the high-altitude wide-range shooting group; The target position of the drone in the low-altitude small-range shooting group is determined based on the target position of the drone in the high-altitude large-range shooting group, so that the drone in the high-altitude large-range shooting group can capture images of at least one drone in the low-altitude small-range shooting group.

6. The multi-UAV cooperative SLAM method as described in claim 4, characterized in that, After assigning the target location to each of the UAVs, multiple auxiliary communication nodes are selected from all the UAVs based on the target location, and each auxiliary communication node is connected to multiple UAVs for communication.

7. The multi-UAV cooperative SLAM method as described in claim 3, characterized in that, The order in which the drones are launched in the high-altitude, wide-range shooting group takes precedence over the order in which the drones are launched in the low-altitude, small-range shooting group.

8. A multi-UAV cooperative SLAM method as described in claim 7, characterized in that, When the drones are launched according to the launch sequence, after the drones in the high-altitude wide-range shooting group reach the target position, the drones in the low-altitude small-range shooting group are launched.

9. A multi-UAV cooperative SLAM method as described in claim 1, characterized in that, During the process of controlling the drone to move along the cruise path starting from the target location, the drones mutually verify their real-time positions based on the results of the functional grouping.

10. A multi-UAV cooperative SLAM method as described in claim 1, characterized in that, The drones take real-time images during their movement and then back up the real-time images to each other.

Images