Communication method based on unmanned aerial vehicle and unmanned aerial vehicle

Abstract

The embodiment of the invention provides a communication method based on an unmanned aerial vehicle and the unmanned aerial vehicle, and relates to the technical field of unmanned aerial vehicles. The method is applied to a first unmanned aerial vehicle, and comprises the steps that a data packet sent by a second unmanned aerial vehicle is received, the second unmanned aerial vehicle is the last hop of the first unmanned aerial vehicle, the second unmanned aerial vehicle is source end equipment of the data packet or the Nth hop of the source end equipment, N is larger than or equal to 1, and identification information of target end equipment is packaged in the data packet; determining a transmission path from the first unmanned aerial vehicle to the target end equipment according to the identification information; and forwarding the data packet to the next hop of the transmission path, so that the data packet is sent to the target end equipment according to the transmission path.

Description

Technical Field

[0001] The present application relates to the field of drone technology, and in particular to a drone-based communication method and device. Background Art

[0002] With the rapid development of low-altitude unmanned flying equipment such as drones, their applications in logistics and transportation, agricultural monitoring, environmental protection, urban management and emergency rescue are becoming more and more extensive. These low-altitude flying drones usually rely on ground communication facilities (such as ground base stations connected by optical fiber networks) to communicate with ground stations, thereby accepting the control and dispatch of ground stations and performing corresponding flight missions according to the routes indicated by the ground stations.

[0003] However, the coverage and performance of ground communication facilities are often unable to meet the communication needs of UAVs at different flight altitudes and in wide areas, and cannot support the normal operation of UAVs. Summary of the invention

[0004] The embodiments of the present application provide a drone-based communication method, device, drone, drone cluster, computer storage medium and computer program product, which can improve the communication capability of the drone when it is difficult to communicate with ground communication equipment.

[0005] In a first aspect, an embodiment of the present application provides a communication method based on a drone, which is applied to a first drone, where the first drone is a base station drone or a relay drone, and the method includes: receiving a data packet sent by a second drone, where the second drone is the previous hop of the first drone, where the second drone is the source device of the data packet or is the Nth hop relay drone of the source device, where N≥1, and the data packet is encapsulated with identification information of the target device; determining a transmission path from the first drone to the target device based on the identification information; and forwarding the data packet to the next hop of the transmission path so that the data packet is sent to the target device along the transmission path.

[0006] In this embodiment, the source device is a data collection drone, which forms a drone cluster with one or more base station drones and one or more relay drones. The data packets collected by the source device can be forwarded to the base station drone through one or more relay drones, and then forwarded by the base station drone to the target device, that is, the ground station or cloud server. Therefore, in this embodiment, for any base station drone or relay drone, that is, the first drone, when it receives a data packet sent by the previous hop drone (the second drone), it can automatically determine the transmission path from itself to the target device according to the target device identifier in the data packet. In this way, the first drone forwards the data packet to the next hop according to this transmission path until the data packet is transmitted to the target device along the transmission path formed by these drones.

[0007] The transmission path includes M hops of drones, where M ≥ 0. It can be understood that if the first drone is a relay drone, the M-hop transmission path it determines may include ≥ 0 hops of other relay drones and one hop of a base station drone; if the first drone is a base station drone, the M-hop transmission path it determines does not include other drones (i.e., 0 hops of drones) and directly transmits to the target end device.

[0008] In this way, based on the navigation and communication capabilities of drones, functions such as data collection, relay, and base station are divided, and communication links are flexibly deployed. In some special geographical environments (such as remote locations or complex terrains) or emergency disaster scenarios, it is not necessary to rely on ground communication facilities or satellite equipment, which can meet the fast and stable communication requirements between the source drone and the ground station (target end), with low communication costs and high real-time performance.

[0009] In some possible implementation manners, before receiving the data packet sent by the second drone, the method includes: receiving the first beacon information broadcast by the neighbor drones, where the neighbor drones include the second drone, and the first beacon information includes the identifier and network status information of the neighbor drones; if the network status information indicates that the neighbor drone is in a network state capable of connection, establish a communication connection with the neighbor drone according to the identifier to form an ad hoc network including the first drone and the neighbor drones.

[0010] In this implementation manner, all drones in the drone cluster can be divided into data collection drones, relay drones, and base station drones according to the functions they are responsible for. And from the network level, for any drone in the cluster, the other drones that can be sensed are its neighbor drones (or neighbor nodes). In other words, for any drone, its neighbor nodes refer to other drones, ground stations, or cloud servers that are in the same geographical area as itself and can directly perform wireless communication with it on the same frequency band or channel. In addition, please understand that in order to distinguish the drone executing this method from the drones other than this drone for the convenience of description, in this article, the base station / relay drone executing this method is also called the first drone, and the drone that is the previous hop of the first drone is called the second drone. In this embodiment, if there is no special distinction in functions, network relationships, objects, etc., and it is directly called a "drone", it can be considered that this "drone" is one of the drones in the cluster.

[0011] In this implementation manner, before forwarding data packets, for example, after the first drone starts or during flight, the first drone can periodically or continuously monitor the surrounding wireless signals, and when receiving the beacon information broadcast by a neighbor drone, establish a communication connection with the neighbor drone according to the beacon information. In this way, any relay drone, base station drone, and data collection drone in the cluster can communicate with their neighbor drones, and thus these drones can dynamically form an ad-hoc network. In this way, on the one hand, during the data packet transmission process of the data collection drone, multi-hop relaying can be performed to achieve wide-area coverage in practical applications. On the other hand, the ad-hoc network has the ability to automatically adjust the network topology when a drone drops out or joins, improving the stability of the cluster relay network.

[0012] In some possible implementation manners, a routing table is configured in the first drone, and the routing table includes routing information from the first drone to each neighbor drone in the ad-hoc network and to the target end device; determining the transmission path from the first drone to the target end device according to the identification information includes: determining the optimal transmission path from the first drone to the target end device from the routing table according to the identification information.

[0013] In this implementation manner, the first drone can automatically match the optimal path to the target end device according to its own routing table, and the optimal path can be a path with characteristics such as the shortest path, the lowest latency, and the highest bandwidth, so as to improve the transmission efficiency.

[0014] In some possible implementation manners, before determining the transmission path from the first drone to the target end device according to the identification information, the method includes: broadcasting a routing request in the ad-hoc network; receiving a response message to the broadcast routing request, where the response message includes the routing information from the first drone to the target end device, and the response message is returned by a neighbor drone or the target end device of the first drone; updating the routing table according to the response message.

[0015] In this way, the first drone can monitor the changes of neighbor drones in the ad-hoc network by broadcasting messages in the flight state, and achieve dynamic update and maintenance of the routing.

[0016] In some possible implementation manners, monitor the alarm information in the ad-hoc network, where the alarm information comes from a drone to exit the ad-hoc network, and the alarm information includes the identification of the drone to exit the ad-hoc network; delete the routing information about the drone to exit the ad-hoc network from the routing table of the first drone according to the alarm information.

[0017] In this way, the first drone can monitor the situation of drones exiting the ad-hoc network in the flight state, and perform dynamic update and maintenance of the routing to ensure the reliability when determining the data packet transmission path.

[0018] In some possible implementations, the method further includes: listening for second beacon information of a drone to be added to the ad hoc network, where the second beacon information includes the identifier and network status information of the drone to be added to the ad hoc network; if the network status information indicates that the drone is in a network state capable of connection, establishing a communication connection with the drone according to the identifier and updating the routing table of the first drone.

[0019] In this way, the first drone can listen for the joining situation of drones in the ad hoc network during flight, perform dynamic update and maintenance of the routing to ensure determining the optimal transmission path for data packets and guarantee the transmission efficiency.

[0020] In this embodiment, the networking and network update of drones in the cluster do not require the intervention of the upper-layer ground station or cloud server, greatly improving the task response speed and network redundancy, and ensuring that the entire system can still operate stably when individual drones join or fail.

[0021] In some possible implementations, the method further includes: in the flight state, obtaining target data, where the target data is the remaining battery power data of the first drone and / or the environmental condition data collected by the first drone; adjusting the flight path of the first drone according to the target data.

[0022] In this way, although each first drone can hover for a long time in the low-power mode based on the intelligent power management module to maintain the stability of the communication network, in this embodiment, the flight path and working mode can also be dynamically adjusted according to the real-time environmental data and power consumption situation to ensure the continuous operation of the system and avoid task interruption caused by battery depletion. This enables the drone cluster to operate efficiently during long-term task execution and makes the most of resources.

[0023] In a second aspect, an embodiment of the present application further provides a communication method based on drones. The method is applied to data collection drones and includes: encapsulating the data collected in the flight state into data packets, where the data packets include the identifier information of the target end device; determining the transmission path to the target end device according to a preset routing table; sending the data packets to the next-hop first drone on the transmission path according to the transmission path, so that the first drone forwards the data packets to the target end device, and the first drone is a relay drone or a base station drone.

[0024] In a third aspect, an embodiment of the present application further provides a drone, including: at least one memory for storing a program; at least one processor for executing the program stored in the memory; wherein, when the program stored in the memory is executed, the processor is used to execute the method described in the first aspect or any one of the possible implementations of the first aspect, or execute the method described in the second aspect or any one of the possible implementations of the second aspect.

[0025] Fourth aspect, an embodiment of the present application further provides a drone cluster, including: a data collection drone, configured to collect data in a flight state and encapsulate it into a data packet; a first drone, configured to obtain the data packet from a second drone, where the second drone is the previous hop of the first drone, and the second drone is the data collection drone or the Nth hop of the data collection drone, N≥1, and the identification information of the target device is encapsulated in the data packet; the first drone is further configured to determine the transmission path from the first drone to the target device according to the identification information; the first drone is further configured to forward the data packet to the next hop of the transmission path, so that the data packet is sent to the target device according to the transmission path.

[0026] Fifth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a processor, the processor is caused to execute the method described in the first aspect or any one of the possible implementation manners of the first aspect.

[0027] Sixth aspect, an embodiment of the present application provides a computer program product, characterized in that when the computer program product runs on a processor, the processor is caused to execute the method described in the first aspect or any one of the possible implementation manners of the first aspect.

[0028] Seventh aspect, an embodiment of the present application provides a chip, characterized by including at least one processor and an interface; at least one processor obtains program instructions or data through the interface; at least one processor is configured to execute the program line instructions to implement the method described in the first aspect or any one of the possible implementation manners of the first aspect.

[0029] It can be understood that the beneficial effects of the above second aspect to seventh aspect can refer to the relevant descriptions in the first aspect above, and will not be elaborated here. Description of the Drawings

[0030] Figure 1A is a schematic architecture diagram of a drone cluster provided by an embodiment of the present application;

[0031] Figure 1B is a schematic structural diagram of a drone cluster provided by an embodiment of the present application;

[0032] Figure 2 is a schematic bus connection diagram of a drone provided by an embodiment of the present application;

[0033] Figure 3 is a schematic architecture diagram of a drone cluster provided by an embodiment of the present application;

[0034] Figure 4 is a flowchart of a communication method based on a drone provided by an embodiment of the present application;

[0035] Figure 5 It is a flowchart of a communication method based on an unmanned aerial vehicle provided by an embodiment of the present application;

[0036] Figure 6 It is a schematic structural diagram of a chip provided by an embodiment of the present application. Detailed implementation manners

[0037] The term "and / or" in this document is an association relationship describing associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. The symbol " / " in this document represents an "or" relationship between associated objects. For example, A / B represents A or B.

[0038] In the embodiments of the present application, words such as "exemplary" or "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "exemplary" or "for example" is intended to present relevant concepts in a specific manner.

[0039] In the description of the embodiments of the present application, unless otherwise specified, the meaning of "a plurality of" refers to two or more. For example, a plurality of processing units refers to two or more processing units, etc.; a plurality of elements refers to two or more elements, etc.

[0040] In the related art, low-altitude unmanned aerial vehicles are scheduled and controlled by a ground station to perform flight operations. The distance between the ground station and the unmanned aerial vehicle can reach ten kilometers or even more than one hundred kilometers. To ensure the stability of long-distance communication, unmanned aerial vehicles usually need to rely on ground communication facilities such as ground base stations to communicate with the ground station. In some special geographical environments (such as remote locations or complex terrains) or emergency disaster scenarios, unmanned aerial vehicles need to operate in this environment, but ground communication facilities often cannot support the communication requirements of unmanned aerial vehicles due to the difficulty of deployment or vulnerability to damage. Although some unmanned aerial vehicles can achieve long-distance communication with the ground station by leveraging the wide-area coverage ability of satellite communication, the communication cost is high and the latency is large, making it difficult to meet the requirements of real-time control and data transmission of low-altitude unmanned aerial vehicles.

[0041] In order to cover the network communication in the low-altitude flight area of the unmanned aerial vehicle (UAV) and meet the requirements of reliable and low-latency communication for the UAV, an embodiment of the present application provides a communication method based on the UAV. This method mainly realizes the self-organizing network and multi-hop relay among UAVs based on the intelligent flight ability and network adjustment ability of the UAVs in the UAV cluster, so as to forward the data packets of the UAV responsible for data collection to the base station UAV via multi-hop relay UAVs, and then be transmitted to the ground station by the base station UAV. The entire communication network topology is flexibly and conveniently deployed, can overcome the restriction of the geographical environment on the deployment of communication facilities, and provides high-reliability and low-latency communication support for the data collection UAV.

[0042] To facilitate the understanding of the technical solution of the present application, the following introduces a UAV cluster provided in an embodiment of the present application with reference to the accompanying drawings.

[0043] Exemplarily, Figure 1A shows a schematic architecture diagram of a UAV cluster provided in an embodiment of the present application. As Figure 1A shown, the UAV cluster 00 may include several UAVs 10, and these UAVs 10 may also be referred to as unmanned aircraft and aerial robots. They are unmanned aircraft using radio remote control equipment and self-prepared program control devices, and can complete aerial flight tasks and various load tasks under unmanned conditions. The UAVs 10 in the embodiments of the present application may be fixed-wing aircraft, multi-rotor aircraft, unmanned airships, unmanned parafoil aircraft; may also include near-space aircraft, such as stratospheric airships, high-altitude balloons, solar UAVs, etc.; may also be UAVs in various forms such as quad-rotor, hex-rotor, single-rotor, and vector control. The UAVs in the embodiments of the present application can be used in military, industrial, civil, agricultural, construction, film and television, environmental protection and other fields as well as special industries that use UAV operations, such as using UAVs for military reconnaissance, patrol, aerial photography, environmental monitoring, border control, delivering express, power inspection, right confirmation, flood control and drought relief, post-disaster rescue, etc. The embodiments of the present application do not limit this.

[0044] It should be understood that the specific types of the UAVs 10 are not limited herein. With the development of intelligence, for applications in different scenarios or to complete different aerial flight tasks, the names of the devices with the functions of unmanned aircraft may be different. For the convenience of description, in all embodiments of the present application, the above-mentioned devices capable of having the functions of unmanned aircraft are collectively referred to as UAVs.

[0045] Exemplarily, as Figure 1A shown, several UAVs 10 in the UAV cluster 00 can be divided into base station UAVs 10A, relay UAVs 10B, and data collection UAVs 10C according to their functions. Among them:

[0046] The base station drone 10A is the core node of the drone cluster 00. It not only has basic navigation capabilities but can also serve as a base station transmitter to achieve the purpose of an aerial communication base station. Exemplarily, one or more base station drones 10A can be set in the drone cluster 00. Multiple base station drones 10A can all be scheduled by the ground station 20 or the cloud server 30 to be deployed in different areas. The base station drone 10A in any area can listen to the data packets sent by other drones 10 (including relay drones 10B and data collection drones 10C), and after listening to the data packets, transmit these data packets to the ground station 20 or the cloud server 30.

[0047] A number of relay drones 10B can be set in the drone cluster 00. As relay nodes, a number of relay drones 10B can form multiple relay transmission paths. Each relay transmission path can be a transmission path formed by multi-hop relay drones 10B. This transmission path allows the data packets of the data collection drone 10C (source end) to be transmitted through this path to the base station drone 10A, and then transmitted by the base station drone 10A to the ground station 20 or the cloud server 30.

[0048] As a working node in the drone cluster 00, the data collection drone 10C can be used to obtain real-time images, videos, and environmental condition data (such as temperature, humidity, wind speed, etc.) on-site, and transmit these data in the form of data packets directly or through the relay drone 10B to the base station drone 10A, and then uploaded by the base station drone 10A to the command center.

[0049] Next, the structures of these drones 10 will be introduced in combination with the accompanying drawings.

[0050] In this embodiment, continue to refer to Figure 1A As shown, each drone 10 can include a sensor component 101, a communication processing module 103, an aircraft platform 102, and a power management module 104. These components and modules are in communication and / or circuit connection. The power management module 104 provides power management functions to supply power to the various components of the drone 10. These components (including components and modules) are carried by the body of the drone 10. As an example, the outer shape of the body can be made of lightweight and durable materials, such as titanium alloy, aluminum alloy, or carbon fiber reinforced plastic, etc., but not limited to this, to have the ability to resist wind, water, and lightning, and adapt to various harsh weather conditions.

[0051] These components on the drone 10 will be introduced one by one below.

[0052] In this embodiment, in combination with Figure 1BAs shown, the sensor assembly 101 can be used to monitor the flight status of the affiliated drone 10 and the environmental conditions where it is located in real time. Exemplarily, the sensor assembly 101 may include, but is not limited to, a Global Positioning System (GPS) 1011, a barometer 1012, a lidar 1013, an Inertial Measurement Unit (IMU) 1014, and an optical flow sensor, etc. The sensor assembly 101 is used to monitor the flight status data of the affiliated drone 10. Among them, the GPS 1011 can achieve the positioning of the horizontal position and altitude, the barometer 1012 can be used to sense the hovering altitude, the lidar 1013 can be used to sense the low-altitude precise altitude and obstacle detection, etc., the IMU 1014 can be used to sense the attitude and position information of the airframe, and the optical flow sensor can be used to sense the hovering horizontal position, and so on. In addition, the sensor assembly 101 can also include sensors such as a temperature sensor, a humidity sensor, and a wind speed sensor, etc., for collecting environmental status data, which will not be enumerated one by one.

[0053] Optionally, the sensor assembly 101 may further include a vision camera 1015, and the vision camera 1015 is used to collect environmental image data in real time. In some possible examples, in combination with Figure 1B As shown, the drone 10 serving as the data collection drone 10C may have a vision camera 1015, and the drone 10 serving as the relay drone 10B and the base station drone 10A may or may not have a vision camera 1015. And, as Figure 2 shown in the schematic diagram of the bus connection, the vision camera 1015 can be connected to the aircraft platform 102 in the drone 10 through an Inter-Integrated Circuit (I2C), a Serial Peripheral Interface (SPI) bus, or a Universal Serial Bus (USB) interface to transmit these environmental image data to the aircraft platform 102.

[0054] In this embodiment, continue to refer to Figure 1A and 1B , the aircraft platform 102 of the drone 10 may include a flight controller 1021 (Flight Controller, FC), a power system 1022, and an energy source 1023 provided in the airframe 1024. Among them:

[0055] The flight controller 1021 is the core control unit of the UAV 10 and can be used to control the attitude of the UAV 10 where it is located according to the data collected by the sensor assembly 101, etc., but is not limited thereto. Exemplarily, the flight controller 1021 can be an embedded processor, such as a microcontroller unit (MCU) or a digital signal processor (DSP), etc., but is not limited thereto. And, in combination with Figure 2 As shown in the schematic diagram of the bus connection, the flight controller 1021 can be connected to the sensor assembly 101 through the I2C or SPI bus, and can also be connected to the communication processing module 103 through a universal asynchronous receiver / transmitter (UART), a controller area network (CAN) bus, an SPI bus, and / or an Ethernet interface (ETH), etc., to send and receive instructions or data.

[0056] The power system 1022 can include a motor and a propeller, etc. The power system 1022 can be used to provide the lift and thrust required for flight according to the instructions of the flight controller 1021, so that the UAV 10 can hover stably in the air and move to perform flight tasks. Among them, the motor is the power source of the UAV 10 and can include, but is not limited to, a brushless DC motor (BLDC) or a brushed DC motor, etc., to convert electrical energy into mechanical energy and drive the propeller to rotate. The propeller can be installed on the shaft of the motor and generate lift and thrust by rotating.

[0057] The energy source 1023 can include a battery and / or a solar panel, etc., and is used to provide the electrical energy required for the UAV 10. Exemplarily, the battery can be a lithium polymer battery (Li-Po) or a lithium-ion battery (Li-ion), etc., but is not limited thereto. The solar panel can be used to convert sunlight into electrical energy, reduce the dependence of the UAV 10 on the battery, and improve the endurance of the UAV 10 in flight. The energy source 1023 can supply power to all components on the UAV 10 where it is located through a power management module 104 (Power Management Unit, PMU).

[0058] Continuing to combine Figure 1A 、 1B and Figure 2As shown, the Power Management Unit (PMU) 104 is an integrated circuit used to manage and optimize the power usage of a device. Exemplarily, the power management module 104 supplies electrical energy from the energy source 1023 to the flight controller 1021 and others via a power line to ensure continuous power supply for flight control. Moreover, it can also provide status information of the energy source 1023 (such as battery level, temperature, voltage, etc.) through a data bus (such as I2C, UART), enabling the flight controller 1021 to decide whether to execute energy-saving modes or automatic return operations based on the status of the energy source. For example, during the flight of the drone 10, if the battery level is lower than a preset threshold, the flight controller 1021 activates the energy-saving mode or automatic return. It should be understood that the energy-saving mode refers to a series of operation settings (such as low-speed cruising, maintaining altitude, etc.) designed to reduce energy consumption, extend flight time, and improve energy efficiency.

[0059] Optionally, the power management module 104 may include a power control system 1041 and an intelligent power distributor 1042 that are electrically connected to each other. Among them, the power control system 1041 is a circuit used to monitor and manage the overall power demand of the drone 10, and can dynamically adjust the power distribution strategy according to the flight state and mission requirements of the drone 10. For example, when the drone 10 is in the high-speed cruising mode, the power supply to some high-power-consuming modules or components (such as the power system) can be increased to meet the power demand. The intelligent power distributor 1042 can be used to assist the power control system 1041 in achieving intelligent power distribution according to real-time needs. For example, it can prioritize ensuring the power supply to critical components (such as the flight controller 1021), while optimizing the power supply to other non-critical modules (such as sensors or the camera 1015 (if any)). When certain sensors do not need to work or high-resolution video transmission is not required, the power supply to these non-critical components can be reduced, thereby saving energy.

[0060] In this embodiment, the communication processing module 103 may include one or more communication modules and a data processing module 1031. Among them, the communication module can be used to provide external communication capabilities to enable the drone 10 to communicate with satellites, ground stations 20, cloud servers, and other drones 10, and the data processing module 1031 can be used to process the data received and transmitted by the communication module.

[0061] Exemplarily, the communication module can be a functional module integrating multiple communication technologies, including but not limited to a cellular network module (such as a fifth generation (5G) module or a 4G module), a Wi-Fi module, a LoRa (Long Range) wireless communication module, a dedicated radio frequency band (such as an Ultra High Frequency (UHF) band or an L band (referring to the frequency range between 1 - 2 GHz)), and / or a satellite communication module, etc. These communication modules allow the drone 10 to communicate with external systems or devices during operation.

[0062] Exemplarily, the data processing module 1031 can be a software and / or hardware module, and the data processing module 1031 can be used to perform local processing based on the data or information obtained by the communication module and / or the sensor assembly 101. By way of example but not as the only limitation, the data processing module 1031 can be used for:

[0063] According to the signal strength (RSSI, Received Signal Strength Indicator) of other drones 10 received by the communication module, calculate the communication connection quality (stability) with these drones 10 based on a preset algorithm;

[0064] It can also regularly send detection data packets to other drones 10, the ground station 20 or the cloud server 30 through the communication module, and calculate the packet loss rate based on the number of returned data packets. If a large number of data packets are lost, it indicates that the current network connection is unstable;

[0065] It can also detect the data transmission delay situation through the data packets received by each communication module. If the transmission time of the data packets received from other drones 10 or transmitted to other drones 10 is relatively long, it means that the drone 10 to which the data processing module 1031 belongs has a higher delay. On the contrary, the delay is lower.

[0066] In this way, the data processing module 1031 can make decisions on whether to switch the network and whether to broadcast an alarm message about its own network abnormality to other drones 10 or the ground station 20 / cloud server 30 according to the detection results of signal stability, delay, and packet loss rate.

[0067] In addition, the data processing module 1031 can also be used to compress and encode the images or videos collected by the sensor assembly 101 to reduce the amount of data transmitted, ensuring the timeliness and reliability of data transmission; or encapsulate various flight state data or environmental image data collected by the sensor assembly 101 according to the corresponding wireless communication protocol for transmission to the ground station 20 / cloud server 30, etc., but not limited to this.

[0068] In this example, the data processing module 1031 can also send the acquired data (from the sensor component 101) to the ground station or the cloud server through the communication module, so that the ground station or the cloud server can perform more complex calculations and analyses on this data. For example, it is convenient for the cloud server 30 and the ground station 20 to monitor the flight status of the UAV 10 in real time and perform management task scheduling, or it is convenient for the cloud server 30 and the ground station 20 to perform large-scale UAV 10 data analysis and decision support, and so on.

[0069] Optionally, if the UAV 10 to which the data processing module 1031 belongs is the master node in the UAV cluster 00, then the data processing module 1031 can also obtain the task instructions (such as monitoring instructions for real-time acquisition of disaster area images or topographic mapping instructions, or emergency rescue instructions for searching for people, etc.) sent by the ground station 20 / cloud server 30 to this cluster 00 through the communication module, and execute these task instructions or distribute these task instructions to other UAVs 10 (slave nodes) in the UAV cluster 00. For example, the ground station 20 sends a task instruction to the data processing module 1031 of a master node (which can be the base station UAV 10A, the relay UAV 10B, or the data acquisition UAV 10C) as "acquire images of area S1 and environmental data of area S2". Then, the data processing module 1031 of this master node can decompose this instruction into two tasks, namely "acquire images of area S1" and "acquire environmental data of area S2", and distribute these two decomposed tasks to two slave nodes (which can be the data acquisition UAV 10C) to execute respectively. As an example, the master and slave nodes in the UAV cluster 00 can perform self-election using a consensus algorithm. That is to say, multiple UAVs 10 (i.e., their data processing modules 1031) can interact through information and adopt a consensus mechanism such as the Paxos algorithm or the Raft algorithm to elect a master node to be responsible for receiving task instructions from the ground station 20 / cloud server 30 and distributing them to the slave nodes.

[0070] Optionally, continue to refer to Figure 1BAs shown in the figure, in order to further ensure the communication reliability of each drone 10 during operation, each drone 10 may also include a satellite communication device 105. The satellite communication device 105 is a terminal device configured on the drone 10, which is used to provide satellite communication services with regional or global coverage and can establish a direct communication link with the ground station 20 / cloud server 30. In this example, the communication processing module 103 of the drone 10 can be connected to the satellite communication device 105 through a high-bandwidth data interface (such as Ethernet or a dedicated radio frequency (RF) interface). In this way, although the cost of communicating based on the satellite communication device 105 is relatively high and there is a certain delay, in some special scenarios (for example, when communication modules such as the above 5G / 4G module, Wi-Fi module, and LoRa cannot provide stable communication signals), it is still possible to communicate with the ground station 20 / cloud server 30 through the satellite communication device 105 in remote areas or areas without ground network coverage.

[0071] In addition, in this embodiment, in addition to the above components 101-105, the relay drone 10B may also include a relay communication device 106. The relay communication device 106 may include a signal amplifier and a relay module. The function of the signal amplifier is to enhance the received signal strength, thereby expanding the communication range. The relay module is responsible for processing the reception, storage, and forwarding of data packets. That is to say, the relay module can receive data packets from the source end or other relay nodes, select the optimal next-hop node according to the current network conditions, and then forward the data packets to the next relay node or the final destination node. In this way, through multi-hop relay transmission, it is ensured that signal transmission is carried out between multiple drone nodes, and the signal coverage range in complex terrains can be effectively enhanced.

[0072] Optionally, in this example, in addition to the above components 101-105, the data collection drone 10C may also include a video processing module 107. The video processing module 107 can be implemented as software and / or hardware and is used to process images or videos to improve quality or facilitate transmission. By way of example rather than limitation, the video processing module 107 can perform preprocessing such as denoising and color correction on images or videos to improve the image quality; or perform streaming media processing such as buffering and fragmentation to ensure the stability and smoothness of the video stream.

[0073] In this way, in this embodiment, based on the components 101-107 as shown in Figure 1A , 1B and Figure 2 , the base station drone 10A, relay drone 10B, and data collection drone 10C in the drone cluster 00 can have basic flight capabilities, communication capabilities, data collection capabilities, and data processing capabilities. On this basis, reference can be made to Figure 4As shown, these base station drones 10A, relay drones 10B, and data collection drones 10C in the drone cluster 00 may also include an intelligent control system 100 deployed in their software layer. The intelligent control system 100 can be run by a flight controller 1021 or other control or processor to achieve corresponding control functions. In this example, the intelligent control system 100 may include a flight control module 110, a networking module 120, and a network control module 130, enabling self-networking and dynamic relay transmission cooperation among the base station drones 10A, relay drones 10B, and data collection drones 10C through the intelligent control system 100. Among them:

[0074] The flight control module 110 can be used to achieve autonomous flight and mission planning of the drone 10 according to the data collected by the sensor assembly 101, so as to adjust the flight altitude, position, route, etc. according to environmental changes or mission requirements.

[0075] Exemplarily, the flight control module 110 can be based on sensors such as the IMU 1014 to obtain the acceleration, angular velocity, and attitude (such as pitch angle, roll angle, and yaw angle) of the affiliated drone 10 in real time, and determine the rotational speed of the motor, etc. according to these data to control the flight attitude of the drone 10 and keep it stable. Moreover, in the power-on state or flight state of the drone 10, the flight control module 110 is also used to receive attitude control instructions or messages from the ground station 20, the cloud server 30, or other drones 10 through the communication processing module 103, and adjust its own flight attitude according to these control instructions / messages. For example, correspondingly adjust the flight direction, aileron, elevator, tilt, speed, throttle, flap, etc. according to the control instructions, and can also control actions such as turning, climbing, diving, rolling, hovering, taking off, and landing of the drone 10. The embodiments of the present application do not make any limitations in this regard. In addition, the flight control module 110 is also used to transmit these flight state data to external systems such as the ground station or the cloud server through the communication processing module 103, facilitating the analysis and supervision of the ground station or the cloud server.

[0076] Exemplarily, the flight control module 110 is further configured to determine the positioning data of the drone 10 in real time based on the obtained flight mission (which may come from the ground station 20 or the cloud server 30) through the GPS 1011 and other sensors (such as the barometer 1012, magnetic compass, etc.), so as to perform path planning and navigation based on this positioning information, and thus automatically execute various flight missions, such as hovering, cruising, automatic return, etc. These positioning data and the above-mentioned flight status data, etc. can also be transmitted to other drones 10, so as to facilitate other drones 10 to adjust their own flight positions, altitudes and / or routes using preset algorithms, thereby reducing the overlap of monitoring areas / airspaces between drones 10 in scenarios such as disaster relief and improving the cruising search efficiency. Similarly, when the drones 10 are flying in a cluster, the communication processing module 103 of the drone 10 can also receive the positioning data and flight status data of other drones 10 and transmit them to the flight control module, so that the flight control module can use preset algorithms to adjust the position, altitude and / or route according to these data of other drones 10, realizing the coordination of the drone 10 cluster.

[0077] Optionally, the flight control module 110 can also manage various payload devices (including but not limited to the vision camera 1015, various sensors, etc.) on the drone 10 according to the working instructions of the ground station 20 or the cloud server 30, so that these devices work according to the set time and position. During the flight, the flight control module 110 can also adjust the flight path and attitude according to the data fed back by the vision camera 1015 (such as obstacle distance, environmental image, etc.), avoid obstacles, and ensure the safe flight and mission execution of the drone 10.

[0078] Continuing to refer to Figure 3 As shown, the networking module 120 can be used to autonomously form a communication network (Mesh Network) with other drones 10, and automatically readjust the network topology structure and network transmission path of the self-organizing network (Mesh Network) when a node is out of contact, fails or newly joins, maintaining communication stability.

[0079] Exemplarily, the networking module 120 can broadcast Beacon messages externally through the communication module, and at the same time listen for the Beacon messages broadcast by other UAVs 10 to discover and establish connections with other UAVs 10. Among them, the Beacon message can include the source address, timestamp, signal strength, network parameters, and sequence number, etc. The source address is the identifier of the UAV 10 that sends this Beacon message (such as the MAC address). The timestamp is used to synchronize time to ensure that the clocks in the network are consistent. The signal strength describes the strength of the signal sent by the UAV 10, which helps to determine the distance between UAVs 10. The network parameters can include the ID of the network, security settings, etc., to facilitate the establishment of connections. The sequence number can be used to identify the freshness of the Beacon message to prevent old messages from interfering with the establishment of new connections. By broadcasting such Beacon messages, the networking modules 120 of UAVs 10 can sense the presence of other UAVs 10 in the network and establish connections accordingly. At the same time, the networking module 120 also listens for the Beacon messages from other UAVs 10 to understand the changes in the surrounding network environment and thus dynamically adjust its own network connection status.

[0080] Exemplarily, the networking module 120 can interact with each other based on the communication connection with other UAVs 10 to maintain or update the corresponding routing table. This routing table can be used to record the path information from the local UAV 10 to other UAVs 10 or the ground station 20. As a specific example, this routing table can include the destination node, the next-hop node, the number of hops, and the communication cost. Among them, the destination node is the identifier of the node to be reached (for example, the ground station or other UAVs 10), the next-hop node is the next node to go to the destination node, the number of hops is the number of hops required to reach the destination node (that is, how many intermediate nodes are passed through), and the communication cost is the cost to reach the destination node (such as transmission delay, energy consumption, required bandwidth, etc.).

[0081] In addition, if the network topology changes (for example, a certain UAV 10 drops off or a new one joins), then the UAV 10 that discovers this change will dynamically update its own routing table according to the new topology structure and broadcast the updated routing information to other UAVs 10, so as to update the routing table of the entire cluster network topology.

[0082] In this embodiment, continue to refer to Figure 3 As shown, the network control module 130 of the intelligent control system 100 can be used to manage the communication network between the UAV 10 and other UAVs 10 in the same cluster. This management includes dynamically adjusting signal relay, channel allocation, bandwidth (traffic) management, etc. according to real-time communication requirements to ensure the efficient operation of the communication network and facilitate the dynamic maintenance of self-organizing networking.

[0083] Exemplarily, when there is a communication requirement (which can come from the networking module 120), the network control module 130 can determine available dedicated radio frequency bands through the communication processing module 103 and dynamically adjust the channels used according to the determined results. For example, if the communication processing module 103 detects that a certain frequency band is occupied by other components or the drone 10, this drone 10 can automatically switch to another idle frequency band.

[0084] Exemplarily, the network control module 130 can also dynamically manage the bandwidth according to the current task situation. For example, when the search area is dense, the drone 10 may require a higher bandwidth to transmit more video and sensor data. Then, in the case of low load (the currently used bandwidth is far from reaching its maximum capacity that it can handle), the network control module 130 can release the excess bandwidth to other tasks. By way of example and not limitation, when allocating bandwidth, the bandwidth can be increased for high-priority tasks (such as positioning, navigation, flight tasks, etc.) and decreased for low-priority tasks (such as daily maintenance tasks).

[0085] Exemplarily, the network control module 130 can also determine the best path from the routing table according to a preset adaptive routing protocol. For example, routing protocols such as distance vector routing protocol (DVRP) and link state routing protocol (LSR) can be used to dynamically select the best path.

[0086] The following uses a specific example to illustrate the process of data transmission between the data collection drone 10C, the relay drone 10B, and the base station drone 10A through their respective intelligent control systems 100. This example includes three drones a, b, and c. Among them, the flight tasks sent by the ground station to the intelligent control systems 100 of these three drones 10 are: drone a is responsible for collecting terrain data in a specified area, drone b, as a relay node, is responsible for transmitting the terrain data collected by drone a to the base station drone c, and this drone c is responsible for transmitting the collected data to the ground station 20. Then, the interaction process of these three drones a, b, and c can include:

[0087] In the initialization stage, after drones a, b, and c are powered on, the networking modules 120 of these drones a, b, and c will broadcast their own identifiers (such as a, b, c) and current status (such as "connectable" or non-connectable) through the communication module and automatically search for surrounding wireless signals, so as to discover the existence of each other and establish a communication connection. And the routing table maintained by drone a can be represented as Table 1 below:

[0088] Table 1

[0089] Destination Node Next Hop Hop Count Cost b b 1 Low c b 2 Medium Ground Station b 3 High

[0090] The routing table maintained by drone b can be represented as Table 2 below:

[0091] Table 2

[0092] Destination Node Next Hop Hop Count Cost a a 1 Low c c 1 Low Ground Station c 2 Medium

[0093] The routing table for the maintenance of UAV c can be represented as Table 3 below:

[0094] Table 3

[0095] Destination Node Next Hop Hop Count Cost a b 2 Medium b b 1 Low Ground Station Ground Station 1 Low

[0096] Thus, after UAVs a, b, and c discover each other's presence, when UAV a needs to transmit the collected terrain data to the ground station 20, it can query its own routing table through the network control module 130 for route selection to find the best path. For example, it can find the best path of "a→b→c→ground station". In this way, after the network control module 130 of UAV a determines that UAV b is the next-hop node of the best path, it notifies its communication processing module 103 to package the collected terrain data into data packets and send them to UAV b. After receiving the data packets, UAV b confirms successful reception and forwards the data packets to the next-hop node c, and so on until the data packets are forwarded to the ground station.

[0097] In addition, in this example, if the networking module 120 of UAV b discovers that a UAV has dropped off or a new UAV has joined, it will dynamically update its own routing table according to the new topology structure and send the updated routing information to UAVs a and c, thereby updating the routing tables of the entire cluster network topology. In this way, when UAV a sends data next time, it will re-select the best path according to the updated routing table.

[0098] In this way, the base station UAV 10A, the relay UAV 10B, and the data collection UAV 10C can transmit data packets through multi-hop relay, especially in complex terrain or long-distance communication environments, to achieve efficient signal coverage and data transmission, greatly enhancing the coverage range and stability of the communication network. Specifically, in remote or extreme environments (such as disaster areas, remote mining areas, complex terrain, etc.) where traditional ground communication facilities cannot cover or are damaged, the UAV 10 cluster of this embodiment can solve the problems of unstable or no network coverage of traditional ground communication facilities. Thus, when it is difficult for ground signals to directly reach in complex terrains such as mountains and canyons, signal coverage can be enhanced through relay means. Compared with the disadvantages of high construction costs and long deployment times of traditional communication facilities, the flexibility of the UAV 10 cluster of this embodiment can achieve efficient and rapid deployment at a relatively low cost. In addition, the UAV 10 cluster of this embodiment can also ensure the real-time nature of the communication network in case of disasters or emergencies to quickly transmit rescue information and instructions, thereby improving the reliability of emergency communication.

[0099] In addition, it should be noted that for any UAV 10, it can be assigned one or more functions. That is to say, any UAV 10 can act as a base station UAV 10A and / or a relay UAV 10B and / or a data collection UAV 10C.

[0100] In addition, continuing to refer to Figure 3 , in this embodiment, the ground station 20 and the edge / cloud server 30 form a background management system for the UAV 10 cluster 00. Among them, the ground station 20 can serve as a ground data processing and command center, and can communicate with the base station UAV 10A through satellite communication or other means to obtain in real time the flight status data, environmental condition data, image data, etc. of each UAV 10 in the cluster 00, and perform remote operations and issue commands. Exemplarily, the ground station 20 can be a control center formed by one or more computing devices, and the computing device can be a physical machine or a virtualized device (such as a virtual machine or a container, etc.). The ground station 20 can preset an emergency response strategy to analyze and process these received data, so as to trigger corresponding strategies to achieve the control and scheduling of the UAV 10.

[0101] For example, the ground station 20 monitors in real time the flight status, communication network performance, remaining battery power, etc. of the UAV cluster 00, and automatically schedules the replacement or replenishment of the UAV 10 according to the development of the disaster situation, etc., to ensure the continuous stability of the communication network. It should be noted that the instructions issued by the ground station 20 can be given to the base station UAV 10A, and the base station UAV 10A can forward them to the designated UAV (which can be a master node or a slave node) via the relay UAV 10B, so as to reduce communication costs and communication delays in the long-distance communication between the ground station 20 and the UAV 10.

[0102] In addition, exemplarily, the configuration of the specific number of UAVs 10 in the cluster 00 depends on the task scale and actual requirements, and the background management system can also dynamically adjust this to expand or reduce the number of UAVs 10 according to the task. The above-mentioned cluster 00 can cover an area of 50 - 100 square kilometers under open and flat terrain conditions. In complex terrain areas, the coverage range will be reduced, possibly around 30 - 50 square kilometers.

[0103] In this embodiment, the edge / cloud server 30 can be deployed on the edge side or the cloud side, and is used to store, analyze and process the data collected by the UAV 10. Combining big data analysis and AI algorithms for optimization, it provides optimization suggestions, improves the operation efficiency and intelligent scheduling ability of the system, and helps the UAV 10 system complete tasks in complex scenarios.

[0104] The edge / cloud server 30 can perform real-time processing and analysis on the data collected by the UAV 10 through the background system, determine the task allocation strategy for the UAV 10 cluster, so as to support the ground station to remotely control the task scheduling of the UAV 10. At the same time, it can also analyze the performance of the communication network and adjust the flight parameters of the UAV 10 in real time.

[0105] In addition, the UAV 10 adopts a distributed control architecture, combining local autonomous control with a cloud scheduling system to adjust the flight tasks and communication paths in real time, avoiding the bottleneck of traditional centralized control, greatly improving the task response speed and network redundancy, ensuring that even if an individual UAV 10 fails, the entire system can still operate stably, and through real-time cloud monitoring and adjustment, dynamic scheduling and allocation of tasks are achieved.

[0106] It should be understood that the names of the modules or hardware configured in the above UAV 10 cluster or background management system are only examples. In specific implementations, each functional module may have other names, and the embodiments of the present application do not limit this. The UAV 10 in the embodiments of the present application may also have more or fewer functional modules, and may also implement more or fewer functions, etc., and the embodiments of the present application do not make any limitations on this

[0107] Next, based on the content described above, a UAV-based communication method provided by the embodiments of the present application will be introduced. It can be understood that this method is proposed based on the content described above, and some or all of the content in this method can refer to the description above.

[0108] Please refer to Figure 4 , Figure 4 which is a schematic flowchart of a UAV-based communication method provided by the embodiments of the present application. It can be understood that this method can be executed by a device, equipment, platform with computing and processing capabilities on the UAV, or a UAV equipment cluster. In this embodiment, it is described by taking execution on the relay UAV or base station UAV described in the above example. For ease of description, the UAV executing this method is also referred to as the first UAV. As Figure 4 shown, this method may include:

[0109] S401, receiving a data packet sent by a second UAV.

[0110] In this embodiment, the UAV cluster can be divided into data collection UAVs, relay UAVs, and base station UAVs according to their functions, and these UAVs are deployed in designated areas based on their flight capabilities. For example, the data collection UAV can fly along a designated flight route to collect data, and the relay UAVs and base station UAVs can fly in a certain area or hover at a designated position based on their flight capabilities. The data collected by the data collection UAV can be sent to the ground station or the edge / cloud server in the form of data packets via the relay UAVs and / or base station UAVs. Then, the data collection UAV can be used as the source device, and the ground station or the edge / cloud server can be the target device.

[0111] Exemplarily, the data packets collected by the data collection UAV can be forwarded to the base station UAV through the transmission path formed by one or more relay UAVs, and then forwarded to the target device by the base station UAV. Therefore, the relay UAV or the base station UAV responsible for forwarding the data packets of the data collection UAV, that is, the first UAV, can be one or more in the UAV cluster. Thus, the first UAV can communicate with other UAVs in the cluster.

[0112] Exemplarily, the first UAV can receive the data packets sent by its previous-hop UAV (also referred to as the second UAV in this article), and the second UAV can be the data collection UAV or the Nth-hop UAV of the data collection UAV, where N≥1.

[0113] In this step, when the data collection UAV sends the data packet, it can encapsulate the identification information of the target device (such as a unique identifier (Media Access Control Address, MAC address)) in the data packet and pass the data packet to the next-hop UAV of the data collection UAV, so that when the data packet reaches the next-hop UAV, it can be continuously transmitted hop by hop according to the best path in its own routing table. Thus, the next-hop UAV or any UAV on the best path can be used as the first UAV. In a possible example, the first UAV can be Figure 1A the base station UAV 10A or the relay UAV 10B shown in Figure 1A or 1B.

[0114] Exemplarily, the data collection UAV can be equipped with a high-definition camera 1015 and a lidar 1013 to collect real-time disaster area images, videos, and terrain data, which are encapsulated into data packets and transmitted to the target device, so as to provide detailed environmental information for rescue operations. Among them, the data collection UAV can achieve autonomous flight through the flight controller and conduct environmental monitoring along the preset route to obtain the required monitoring data in some emergency disaster relief scenarios or some scenarios with complex working conditions such as mining areas. In a possible example, the data collection UAV can beFigure 1A or the data collection drone 10C shown in 1A or 1B.

[0115] S402. Determine the transmission path from the first drone to the target device according to the identification information.

[0116] In this step, the first drone can determine the target device according to the identification information of the target device in the data packet, and thus query the transmission path from itself to the target device in the current network from the routing table maintained by itself, so as to determine the drones and the hop count M that the data packet needs to pass through from the first drone to the target device, where the hop count M≥0.

[0117] That is to say, if the first drone is a relay drone and needs to pass through M hops (including relay drones with 0 hops or more and one-hop base station drones) to reach the target device, the data packet will be transmitted hop by hop from the first drone; if the first drone is a base station drone, then the target device can be directly reached from the first drone, that is, the transmission path includes 0-hop drones.

[0118] S403. Forward the data packet to the next hop of the transmission path so that the data packet is sent to the target device according to the transmission path.

[0119] In this step, after the first drone determines the transmission path, it forwards the data packet to the next hop of the transmission path according to the transmission path so that the data packet is sent to the target device according to the transmission path.

[0120] In this way, since base station drones or relay drones can hover at a specific altitude (such as 500 meters) or a designated position based on their own navigation capabilities and maintain stable flight, the communication coverage range can be expanded, the ground network limit can be broken through, more stable communication support can be provided for data collection drones in complex mission environments, and the deployment is highly flexible, fast and easy to implement. Especially in scenarios such as emergency rescue and remote area communication, the reliability and scalability of the communication network are ensured. In addition, since the communication network can be quickly deployed and the drones can adjust their flight and communication strategies in real time, the communication recovery time in disaster rescue can be greatly shortened, thereby improving the efficiency of post-disaster emergency response and reducing information transmission delay.

[0121] Next, a communication method based on drones provided by the embodiments of the present application will be introduced in detail.

[0122] Exemplarily, as Figure 5 shown, this method may include:

[0123] S500. The first drone receives beacon information broadcast by neighbor drones.

[0124] In this step, the first drone can achieve autonomous flight through the above-mentioned components such as the sensor assembly 101, the aircraft platform 102, the communication processing module 103, and the battery management system 104. During the flight of the first drone, its networking module can periodically broadcast its own beacon information and simultaneously receive the beacon information broadcast by drones in other flight states (i.e., the second drones) to discover and establish connections with each other.

[0125] Exemplarily, the beacon information received by the first drone may include the identifier of the second drone (such as the source address), network status information (whether it is connectable), timestamp, signal strength, network parameters, and sequence number, etc. In this way, by broadcasting such beacon messages between drones, they can perceive the existence of other drones in the network and establish connections accordingly.

[0126] S501, if the network status information indicates that the second drone is in a connectable network state, establish a communication connection with the second drone according to the identifier to form an ad-hoc network including the first drone and the second drone.

[0127] In this embodiment, if the networking module of the first drone determines that the second drone is connectable according to the network status information in the beacon information of the second drone, the first drone can request the second drone to establish a communication connection according to the identifier in the beacon information of the second drone. In this way, ad-hoc networks can be formed among all the drones in the drone cluster, that is, an ad-hoc network including the first drone and the second drone.

[0128] Exemplarily, if a first drone determines that a certain second drone is not connectable according to the network status information in the beacon information of the second drone, the first drone will not establish a connection with the second drone for the time being. However, if there are other second drones that are connectable at the same time, the first drone will connect with these other second drones and join the topology of the ad-hoc network together.

[0129] In this way, compared with relying on traditional ground networks or fixed base stations to achieve communication between drones and ground stations, the method of this embodiment can flexibly expand the communication coverage range through ad-hoc network technology (Mesh Network), greatly improving the stability and expandability of the network.

[0130] In addition, optionally, after the ad-hoc network is formed, the drones in the ad-hoc network also establish and maintain routes through communication interactions. Taking the communication interaction between the first drone and the connected second drone as an example, the method may further include:

[0131] S5011, broadcast a route request in the ad-hoc network.

[0132] In this step, since the first drone and the neighbor drones in the ad-hoc network have sensed each other, the networking module of the first drone can check the local routing table. If there is no route to the target device in the routing table, a route request message is initiated. The route request message may include the source address (the IP address of the first drone), the target address (the IP address of the target device), and the broadcast ID (used to prevent duplicate forwarding), but is not limited thereto.

[0133] Next, this route request will be broadcast by the first drone to all adjacent drones in the ad-hoc network.

[0134] S5012. Receive the response message of the broadcast route request, which includes the routing information from the first drone to the target device.

[0135] In this step, the networking modules of the drones in the ad-hoc network that receive this broadcast route message will each check whether their local area contains a route to the target address. If it does, the networking modules of these drones will construct a route response message and return it to the first drone. If not, the networking modules of these drones will forward this broadcast route request to their adjacent nodes (including drones and ground stations or cloud servers) until the target device receives this request. In this way, after the target device responds to this request, it will also construct a response message and send it to the first drone through the reverse path (i.e., the path from the second drone pointed to by the target address to the first drone pointed to by the source address).

[0136] Exemplarily, the response message may include the target address, the source address, the number of hops from the target address to the source address, etc., but is not limited thereto. After the first drone receives this response message, it will create a route to the target device in the routing table maintained by the networking module. At the same time, the networking modules of each drone along the way from the response message to the first drone will also update their routing tables accordingly. The routing table in the drone networking module may include content similar to that shown in Table 1, Table 2, or Table 3 above, and will not be elaborated further.

[0137] In this example, after forming the ad-hoc network, that is, after the above S501 or S5012, this method further includes:

[0138] S502. The first drone receives the data packet sent by the second drone.

[0139] Exemplarily, the execution principle of this step S502 can refer to the description of S401 in the above example and will not be elaborated further.

[0140] S503. Determine the optimal transmission path from the first drone to the target device from the routing table according to the identification information.

[0141] In this step, since the networking module of the first UAV is configured with a routing table, which includes the routing information from the first UAV to each UAV in the ad-hoc network and to the target device, after the communication processing module of the first UAV receives a data packet, it can parse the target address of the target device from the data packet, and its network control module will find the optimal transmission path from itself to the target device according to its own routing table of the first UAV. It can be understood that the optimal transmission path can be the shortest transmission path, the path with the minimum delay, the path with the minimum energy consumption, or the path with the maximum bandwidth, etc., so that the data packet can be transmitted to the target device as fast as possible or at the optimal link cost.

[0142] Alternatively, exemplarily, the network control module of the first UAV can also find the best next-hop UAV to reach the target address through the routing table according to the target address in the data packet, and use this as the optimal transmission path of the first UAV.

[0143] Alternatively, exemplarily, the path information from the source UAV to the target device can also be encapsulated in the data packet, and the network control module of the first UAV can use this path information as its own optimal transmission path for transmitting the data packet, and then find the next hop corresponding to this routing information from its own routing table.

[0144] In this way, the best path is automatically selected among the UAVs in the ad-hoc network for multi-hop communication, ensuring the signal strength and stability under complex terrain and long-distance communication conditions.

[0145] S504. Forward the data packet to the next hop of the optimal transmission path so that the data packet is sent to the target device according to the transmission path.

[0146] In this step, after the network control module of the first UAV determines the optimal transmission path, it forwards the data packet to the next-hop node in the optimal transmission path through the communication processing module. The next-hop node can be a relay UAV, a base station UAV or the target device. Among them, if the next hop is a relay UAV or a base station UAV, the next hop can perform steps similar to the above S502 to S504 until the data packet is transmitted to the target device.

[0147] In this way, drones with different functions (such as base station drones, node drones, and monitoring drones) can autonomously cooperate, have a real-time monitoring and feedback mechanism without human intervention, and coordinate task allocation and working paths respectively to achieve swarm intelligent operation. The system can monitor the cluster status in real time during task execution and dynamically adjust the cluster structure to adapt to different communication requirements or environmental changes. In scenarios such as emergency rescue and natural disasters, through real-time monitoring and data transmission functions, the data information at the front line can be quickly transmitted back to the command center to support timely decision-making and actions. And during the transmission process, multi-hop relay can ensure that the signal can penetrate complex terrains or maintain the stability of the communication link within a long distance.

[0148] In some possible implementation manners, the self-organizing network formed by the drone cluster may change the network topology due to the withdrawal or joining of drones. Therefore, this method may further include:

[0149] S505, monitor the alarm information in the self-organizing network. The alarm information comes from the drone to withdraw from the self-organizing network, and the alarm information includes the identifier of the drone to withdraw from the self-organizing network.

[0150] In this step, in the self-organizing network formed by the drone cluster, if a certain drone wants to withdraw from the network, for example, due to insufficient battery power and needs to return or withdraw from the network due to other abnormalities, it broadcasts an alarm message to the self-organizing network to inform other drones (including the first drone) in the network of its information to withdraw from the network. The alarm message may include the identifier of the drone (i.e., the drone withdrawing from the self-organizing network), etc., but is not limited thereto.

[0151] S506, according to the alarm information, the first drone deletes the routing information about the drone to withdraw from the self-organizing network from the routing table.

[0152] In this step, when the networking module of the first drone receives the alarm message, it can delete the routing information about the drone to withdraw from the self-organizing network from its own routing table.

[0153] In this way, compared with the disadvantage that once a certain base station or node fails in the ground communication facilities, the entire communication system may be interrupted, this method can ensure a high degree of redundancy of the network through multi-hop and dynamic scheduling of the drone cluster. Even if a certain drone fails, other drones can quickly fill the gap to ensure the continuous and stable operation of the network.

[0154] S507, monitor the beacon information of the drone to join the self-organizing network. The beacon information includes the identifier of the drone to join the self-organizing network and the network status information.

[0155] The principle of this step is similar to that of the above step S500 and will not be elaborated here.

[0156] S508. If the network status information indicates that the UAV to be added to the ad-hoc network is in a network state where it can be connected, establish a communication connection with the UAV to be added to the ad-hoc network according to the identifier and update the routing table.

[0157] The principle of this step is similar to the above step S501 and will not be elaborated here.

[0158] Optionally, during the mission execution of the first UAV, it may also encounter situations such as insufficient battery power or deteriorating environment, and needs to return or avoid urgently. Therefore, this method may further include:

[0159] S509. In the flight state, obtain target data, where the target data is the remaining battery power data and / or environmental condition data of the first UAV.

[0160] In this step, when the first UAV is in the flight state, its data processing module can monitor its remaining battery power through its own battery management system and collect the surrounding environment conditions through the sensor component, such as wind speed, temperature and humidity, etc., so as to obtain the corresponding target data.

[0161] S510. Adjust the flight path of the first UAV according to the target data.

[0162] In this step, if according to the target data, the data processing module of the first UAV determines that its remaining battery power is lower than the preset threshold, it can adjust the flight path to return by itself. Or, if the first UAV determines that the current environmental condition is bad, the wind speed exceeds the preset wind speed upper limit / temperature is lower than the temperature lower limit or higher than the temperature upper limit / humidity is greater than the humidity upper limit, etc., resulting in the UAV being unable to perform the flight mission normally, it can adjust the flight path to return by itself or avoid to other areas.

[0163] In this way, although each UAV can hover for a long time in the low-power mode based on the intelligent power management module to maintain the stability of the communication network, in this embodiment, it can also dynamically adjust the flight path and working mode according to the real-time environmental data and power consumption situation, ensure the continuous operation of the system, and avoid mission interruption caused by battery depletion. This enables the UAV cluster to operate efficiently during long-term mission execution and makes the most of resources. In contrast, the traditional UAV scheduling method is usually a preset route or manual control, lacking the ability of automatic task adjustment. Through the intelligent scheduling function of the cloud management system, the command center can allocate the UAVs in real time, ensure the continuous coverage of the communication network and the optimal configuration of UAV resources, which is conducive to shortening the communication recovery time in disaster rescue, thus improving the efficiency of post-disaster emergency response and reducing information transmission delay.

[0164] To more clearly understand the application scenario of the method provided by the embodiments of the present application, the following is illustrated with examples.

[0165] For example. In some remote mining areas, due to their remote locations and complex surrounding terrains, traditional communication means such as optical fibers and ground base stations are difficult to achieve communication coverage within the mining areas, resulting in extremely unstable communication networks in the mining areas. In order to ensure the safety of mining operations and the real-time nature of production management, a stable communication network needs to be established to ensure real-time data transmission between the mining area and the headquarters. Therefore, high-altitude base station drones in the drone cluster can be responsible for hovering in the air at high altitudes to provide wide-area communication coverage, connecting each work point in the mining area with the company headquarters. Moreover, low-altitude relay drones are also deployed to be responsible for transmitting signals through complex terrains (such as canyons and mountains), so as to transmit the signals from the high-altitude base station drones to the ground workstations or remote operation points, ensuring the continuity of the communication network. In addition, data collection drones are deployed at each operation point to achieve real-time monitoring and patrol of the mining area. The data collection drones collect data of these operation points (such as mine temperature and gas concentration) through sensor components, and transmit them to the low-altitude relay drones through short-range wireless communication technology, and then the relay drones converge them to the high-altitude base station drones for centralized processing, enabling the base station drones to upload these image data to the ground station (company headquarters) or cloud server through the satellite communication module.

[0166] In this way, through the hybrid communication method, the problem of unstable communication networks in the mining areas is solved, real-time communication between operation points and the headquarters is ensured, and then the safety of the mining area and production management are guaranteed. In some emergency situations (such as cave-ins and equipment failures), the drone cluster can quickly reach the scene, transmit videos and data in real time, and quickly convey them to the rescue team and the headquarters command center, achieving an efficient emergency response, helping to formulate rescue plans, and reducing the impact of accidents. Compared with building traditional communication infrastructure, the deployment of the drone cluster in this implementation significantly reduces costs, especially in complex terrains or remote areas, where its flexibility and rapid deployment capabilities are particularly prominent.

[0167] For another example. In some disaster areas or remote areas, the ground communication infrastructure has been damaged or is insufficient, and a communication network needs to be quickly established to support rescue missions. In this case, a drone cluster can be deployed, and each drone is equipped with communication equipment. Some drones in the cluster are configured as low-altitude integrated air base stations, and other drones work in coordination as mobile nodes in the cluster network.

[0168] Moreover, one of the drones is designated as the main control node, which is responsible for managing the communication and flight paths of the entire drone cluster. It maintains communication with other drones via wireless signals, aggregates the data, and uploads it to the ground command center or directly relays it to a remote server. Additionally, multi-hop relaying can be configured because, due to the wide geographical range, the signal may not be able to directly reach all drones in the cluster. Therefore, communication in the cluster adopts a multi-hop manner. Drone A transmits data to Drone B, and B then passes the data to the base station drone or other drone nodes until the data reaches the target location.

[0169] In this way, each drone node has the ability to autonomously form a network. When a certain node loses contact or fails, other drones can automatically adjust the path and network connection to ensure the continuous operation of the network.

[0170] Based on the method in the above embodiments, an embodiment of the present application provides an electronic device. The electronic device may include: at least one memory for storing programs; at least one processor for executing the programs stored in the memory; wherein, when the programs stored in the memory are executed, the processor is used to execute the method in the above embodiments.

[0171] Based on the method in the above embodiments, an embodiment of the present application provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program runs on a processor, it causes the processor to execute the method in the above embodiments.

[0172] Based on the method in the above embodiments, an embodiment of the present application provides a computer program product, characterized in that when the computer program product runs on a processor, it causes the processor to execute the method in the above embodiments.

[0173] Based on the method in the above embodiments, an embodiment of the present application further provides a chip. Please refer to Figure 6 , Figure 6 which is a schematic structural diagram of a chip provided by an embodiment of the present application. As Figure 6 shown, the chip 900 includes one or more processors 901 and an interface circuit 902. Optionally, the chip 900 may further include a bus 903. Among them:

[0174] The processor 901 may be an integrated circuit chip with the ability to process signals. In the implementation process, each step of the above method can be completed by the integrated logic circuit in the hardware of the processor 901 or by instructions in the form of software. The above-mentioned processor 901 may be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods and steps disclosed in the embodiments of the present application. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0175] The interface circuit 902 can be used for sending or receiving data, instructions, or information. The processor 901 can utilize the data, instructions, or other information received by the interface circuit 902 for processing and can send the processed information through the interface circuit 902.

[0176] Optionally, the chip 900 further includes a memory. The memory may include a read-only memory and a random access memory and provides operation instructions and data to the processor. A part of the memory may also include a non-volatile random access memory (NVRAM).

[0177] Optionally, the memory stores executable software modules or data structures. The processor can execute corresponding operations by calling the operation instructions stored in the memory (the operation instructions may be stored in the operating system).

[0178] Optionally, the interface circuit 902 can be used to output the execution result of the processor 901.

[0179] It should be noted that the respective functions corresponding to the processor 901 and the interface circuit 902 can be implemented through hardware design, can also be implemented through software design, or can be implemented through a combination of software and hardware. There is no limitation here.

[0180] It should be understood that each step of the above method embodiment can be completed by the logic circuit in the form of hardware in the processor or by instructions in the form of software.

[0181] It can be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The execution order of each process should be determined according to its function and internal logic and should not constitute any limitation to the implementation process of the embodiments of the present application. In addition, in some possible implementation manners, the steps in the above embodiments can be selectively executed according to the actual situation, can be partially executed, or can be fully executed. There is no limitation here.

[0182] It can be understood that the processor in the embodiments of the present application may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. The general-purpose processor may be a microprocessor or any conventional processor.

[0183] The method steps in the embodiments of the present application may be implemented in a hardware manner or by a processor executing software instructions. The software instructions may be composed of corresponding software modules, and the software modules may be stored in a random access memory (RAM), flash memory, read-only memory (ROM), programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), registers, hard disks, removable hard disks, CD-ROMs, or any other form of storage medium well-known in the art. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium may also be a component of the processor. The processor and the storage medium may be located in the ASIC.

[0184] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center in a wired manner (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wirelessly (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more integrated available media. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid state disk (SSD)), etc.

[0185] It can be understood that the various numerical numbers involved in the embodiments of the present application are only for convenience of description and are not used to limit the scope of the embodiments of the present application.

Claims

1. A communication method based on an unmanned aerial vehicle, characterized in that, The method is applied to a first unmanned aerial vehicle (UAV), where the first UAV is a base station UAV or a relay UAV. The method includes: Receiving a data packet sent by a second UAV, where the second UAV is the previous hop of the first UAV. The second UAV is the source device of the data packet or the Nth-hop relay UAV of the source device, N≥1. The data packet encapsulates the identification information of the target device. Determining the transmission path from the first UAV to the target device according to the identification information. Forwarding the data packet to the next hop of the transmission path so that the data packet is sent to the target device according to the transmission path.

2. The method according to claim 1, characterized in that, Before receiving the data packet sent by the second UAV, the method includes: Receiving first beacon information broadcast by neighbor UAVs, where the neighbor UAVs include the second UAV. The first beacon information includes the identification of the neighbor UAVs and network status information. If the network status information indicates that the neighbor UAV is in a connectable network state, establishing a communication connection with the neighbor UAV according to the identification to form an ad-hoc network including the first UAV and the neighbor UAVs.

3. The method according to claim 2, characterized in that A routing table is configured in the first UAV. The routing table includes the routing information from the first UAV to each of the neighbor UAVs in the ad-hoc network and to the target device. The determining the transmission path from the first UAV to the target device according to the identification information includes: Determining the optimal transmission path from the first UAV to the target device from the routing table according to the identification information.

4. The method according to claim 2 or 3, characterized in that, Before determining the transmission path from the first UAV to the target device according to the identification information, the method includes: Broadcasting a routing request to the ad-hoc network. Receiving a response message to the broadcast routing request. The response message includes the routing information from the first UAV to the target device. The response message is returned by a neighbor UAV of the first UAV or the target device. Updating the routing table according to the response message.

5. The method according to any one of claims 2-4, characterized in that, The method further includes: Listening for alarm information in the ad-hoc network. The alarm information comes from a UAV to exit the ad-hoc network. The alarm information includes the identification of the UAV to exit the ad-hoc network. Deleting the routing information about the UAV to exit the ad-hoc network from the routing table of the first UAV according to the alarm information.

6. The method according to any one of claims 1-5, characterized in that, The method further includes: Listening for second beacon information of a UAV to join the ad-hoc network. The second beacon information includes the identification and network status information of the UAV to join the ad-hoc network. If the network status information indicates that the UAV is in a connectable network state, establishing a communication connection with the UAV according to the identification and updating the routing table of the first UAV.

7. The method according to any one of claims 1-6, characterized in that The method further includes: In the flight state, acquiring target data, where the target data is the remaining battery power data of the first UAV and / or the environmental condition data collected by the first UAV. Adjusting the flight path of the first UAV according to the target data.

8. A communication method based on an unmanned aerial vehicle, characterized in that, The method is applied to a data collection drone, and the method includes: Encapsulating the data collected in the flight state into a data packet, where the data packet includes the identification information of the target device; Determining the transmission path to the target device according to a preset routing table; Sending the data packet to the first drone at the next hop of the transmission path according to the transmission path, so that the first drone forwards the data packet to the target device, and the first drone is a relay drone or a base station drone.

9. A drone, characterized in that, It includes: At least one memory for storing programs; At least one processor for executing the programs stored in the memory; Wherein, when the programs stored in the memory are executed, the processor is used to execute the method according to any one of claims 1-6.

10. A drone swarm, characterized in that, It includes: A data collection drone for collecting data in the flight state and encapsulating it into a data packet; A first drone for obtaining the data packet from a second drone, where the second drone is the previous hop of the first drone, the second drone is the data collection drone or the Nth hop of the data collection drone, N≥1, and the data packet is encapsulated with the identification information of the target device; The first drone is further configured to determine the transmission path from the first drone to the target device according to the identification information; The first drone is further configured to forward the data packet to the next hop of the transmission path, so that the data packet is sent to the target device according to the transmission path.

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