Unmanned aerial vehicle multi-terminal cooperation system based on big data

Abstract

The invention discloses an unmanned aerial vehicle multi-terminal cooperation system based on big data, which comprises an unmanned aerial vehicle main body, a portable base station, a mobile command vehicle, a centralized control dispatching center and a big data server, and is characterized in that the unmanned aerial vehicle main body is provided with an airborne controller, an airborne modulation platform and airborne communication equipment; according to the invention, the multi-terminal control system of the unmanned aerial vehicle main body determines the multi-control source type of the unmanned aerial vehicle main body, enables the unmanned aerial vehicle main body to be compatible with multi-source control, provides a cooperative operation strategy for automatic control and manual operation control of the unmanned aerial vehicle main body, determines the priority of the control sources and the switching opportunity of the control modes, enables the unmanned aerial vehicle main body to better adapt to multi-scene operation, and improves the working efficiency. And the airborne communication equipment on the unmanned aerial vehicle main body can be connected with the remote control handle through radio frequency signals, so that a user can manually take over the work of the unmanned aerial vehicle main body when the unmanned aerial vehicle main body is far away from a monitoring center or communication fails, the working flexibility of the unmanned aerial vehicle main body is improved, and the working range of the unmanned aerial vehicle main body is also expanded.

Description

Technical Field

[0001] The present invention relates to the technical field of drone main body operation, and in particular to a drone multi-terminal collaborative system based on big data. Background Art

[0002] The most common way to control drones is by remote control. However, this type of drone control is relatively simple. Users can only control the drone through a handheld remote control, that is, a remote controller. Moreover, the remote control distance is greatly limited. Since its signal transmission method is relatively simple, for example, the signal transmission between the drone and the remote control terminal is only achieved through radio frequency signals, the radio frequency signal will weaken or even disconnect when the distance is too far, causing the drone to lose control, which causes great inconvenience to the drone operation.

[0003] Secondly, this single control source is inconvenient to use, making it impossible to control the drone by other means except the remote control. This limits the flexibility of the drone control operation, makes collaborative operation impossible, and makes it difficult to be compatible with multi-source control and adapt to more scenarios.

[0004] In view of the above problems, the present invention makes improvements. Summary of the Invention

[0005] The present invention proposes a multi-terminal UAV collaborative system based on big data, which solves the above-mentioned problems existing in the use process of the prior art.

[0006] The technical solution of the present invention is implemented as follows: a multi-terminal collaborative system for unmanned aerial vehicles based on big data, comprising a unmanned aerial vehicle body, a portable base station, a mobile command vehicle, a centralized control and dispatching center, and a big data server, wherein the unmanned aerial vehicle body is provided with an airborne controller, an airborne modulation platform, and an airborne communication device, the portable base station is provided with a base station controller and a base station communication device, the mobile command vehicle is provided with a vehicle-mounted controller, a vehicle-mounted control panel, and a vehicle-mounted communication device, the centralized control and dispatching center is provided with a centralized control server, a centralized control control panel, and a centralized control communication device, the unmanned boat is provided with a ship-mounted controller and a ship-mounted communication device, the airborne modulation platform, the base station communication device, the vehicle-mounted communication device, the centralized control communication device, and the ship-mounted communication device constitute a multi-terminal control source of the unmanned aerial vehicle body, the airborne modulation platform can directly send control instructions to the airborne controller, and the airborne modulation platform, the base station communication device, the vehicle-mounted communication device, the centralized control communication device, and the ship-mounted communication device are all communicatively connected to the big data server;

[0007] When the onboard controller completes the multi-terminal control source identification, it will determine the controllability of the signal source through "operation mode, confidentiality requirements, and communication strength" to obtain the optimal control channel. The identification steps are as follows:

[0008] 1. Determine the multi-terminal control source, which includes airborne modulation platform, base station communication equipment, vehicle-mounted communication equipment, centralized control communication equipment, and ship-mounted communication equipment;

[0009] 2. Determine the operation mode and controllability. The operation modes include functional testing, loading / unloading, autonomous cruise / return, automatic operation, and collaborative operation. Then determine the controllability between the multi-terminal control source and the operation mode. The controllable range is 1 to 2.

[0010] 3. Determine the communication strength based on communication delay, packet loss rate, and effective bandwidth, with the strength range from 5% to 100%; 4. Determine the communication feasibility of each control source based on controllability and communication strength;

[0011] 5. Determine the primary control channel and backup control channel based on communication feasibility, with the optimal control channel being the primary control channel;

[0012] The drone body can also switch to manual control. Manual control is remote control through manual operation of the base station controller, vehicle-mounted controller, centralized control server, and ship-mounted controller. When manual control is performed, the control source control instructions such as the airborne modulation platform, base station communication equipment, vehicle-mounted communication equipment, centralized control communication equipment, and ship-mounted communication equipment will be locked.

[0013] The big data server includes a processor 1, a machine-readable storage medium and a network interface. The machine-readable storage medium, the network interface and the processor are connected via a bus system. The network interface is used to communicate with at least one service terminal. The machine-readable storage medium is used to store programs, instructions or codes, and the processor is used to execute the programs, instructions or codes in the machine-readable storage medium.

[0014] The present invention is as described above for a multi-terminal collaborative system for drones based on big data, further: the processor is used to execute the program, instructions or code in the machine-readable storage medium to execute the information feedback instructions required by the drone body, airborne modulation platform, base station communication equipment, vehicle-mounted communication equipment, centralized control communication equipment and ship-mounted communication equipment.

[0015] The present invention is for a multi-terminal collaborative system for drones based on big data as described above, further comprising: the feedback information instruction to be executed may be a picture of the environment captured during the operation of the drone body.

[0016] The present invention is as described above for a multi-terminal collaborative system for drones based on big data, further: the executed feedback information instructions can be instruction information manually input by an airborne modulation platform, a base station communication device, a vehicle-mounted communication device, or a centralized control communication device.

[0017] The present invention as described above is for a multi-terminal collaborative system for drones based on big data, further: the airborne communication equipment adopts a wireless communication mode to receive monitoring information of base station communication equipment, vehicle-mounted communication equipment, centralized control communication equipment and ship-mounted communication equipment, and transmits it to the airborne controller via a wired transmission method, and the airborne controller completes the multi-terminal control source identification, thereby realizing the optimal collaborative operation of the drone body.

[0018] The present invention further provides a system for multi-terminal collaboration of drones based on big data, further comprising: the onboard communication device also includes radio frequency signal communication, enabling manual operation of the drone body via a remote controller. The present invention further provides a system for multi-terminal collaboration of drones based on big data, further comprising: the computer-readable storage medium contains pre-set instructions that, when executed, cause the computer to execute any one of the possible design examples of the stored instructions for controlling the drone body.

[0019] In summary, the beneficial effects of the present invention are:

[0020] 1. The multi-terminal control system of the drone body clarifies the multi-control source types of the drone body and makes it compatible with multi-source control.

[0021] 2. The present invention provides a coordinated operation strategy for automatic control and manual control of the UAV body, clarifies the priority of the control source and the timing of switching the control mode, and enables the UAV body to better adapt to multi-scenario operations.

[0022] 3. The present invention can also use radio frequency signals to connect the remote control handle through the airborne communication equipment on the drone body. In this way, when the user is far away from the monitoring center or the communication fails, the user can manually take over the work of the drone body, thereby improving the working flexibility of the drone body and also increasing the operating range of the drone body. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0024] Figure 1 This is a system block diagram of the present invention.

[0025] In the figure: 1. UAV body, 2. Airborne controller, 3. Airborne modulation platform, 4. Airborne communication equipment, 5. Portable base station, 6. Base station controller, 7. Base station communication equipment, 8. Mobile command vehicle, 9. Vehicle-mounted controller, 10. Vehicle-mounted control panel, 11. Vehicle-mounted communication equipment, 12. Centralized control and dispatch center, 13. Centralized control server, 14. Centralized control control panel, 15. Centralized control communication equipment, 16. Unmanned boat, 17. Ship-mounted controller, 18. Ship-mounted communication equipment. DETAILED DESCRIPTION

[0026] The following is a combination of the embodiments of the present invention Figure 1 The technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0027] Example

[0028] Example 1

[0029] A multi-terminal collaborative system for unmanned aerial vehicles based on big data includes a unmanned aerial vehicle body 1, a portable base station 5, a mobile command vehicle 8, a centralized control and dispatching center 12, and a big data server. The unmanned aerial vehicle body 1 is provided with an airborne controller 2, an airborne modulation platform 3, and an airborne communication device 4. The portable base station 5 is provided with a base station controller 6 and a base station communication device 7. The mobile command vehicle 8 is provided with a vehicle-mounted controller 9, a vehicle-mounted control panel 10, and a vehicle-mounted communication device 11. The centralized control and dispatching center 12 is provided with a centralized control server 13, a centralized control control panel 14, and a centralized control communication device 15. The unmanned boat 16 is provided with a shipboard controller 17 and a shipboard communication device 18. The airborne modulation platform 3, the base station communication device 7, the vehicle-mounted communication device 11, the centralized control communication device 15, and the shipboard communication device 18 constitute a multi-terminal control source of the unmanned aerial vehicle body 1. The airborne modulation platform 3 can directly send control instructions to the airborne controller 2. The airborne modulation platform 3, the base station communication device 7, the vehicle-mounted communication device 11, the centralized control communication device 15, and the shipboard communication device 18 are all communicatively connected to the big data server.

[0030] When the onboard controller 2 completes the multi-terminal control source identification, it will determine the controllability of the signal source through "operation mode, confidentiality requirements, and communication strength" to obtain the optimal control channel. The identification steps are as follows:

[0031] 1. Determine the multi-terminal control source, which includes the airborne modulation platform 3, base station communication equipment 7, vehicle-mounted communication equipment 11, centralized control communication equipment 15, and ship-mounted communication equipment 18;

[0032] 2. Determine the operation mode and controllability. The operation modes include functional testing, loading / unloading, autonomous cruise / return, automatic operation, and collaborative operation. Then determine the controllability between the multi-terminal control source and the operation mode. The controllable range is 1 to 2.

[0033] 3. Determine the communication strength based on communication delay, packet loss rate, and effective bandwidth, with the strength range from 5% to 100%; 4. Determine the communication feasibility of each control source based on controllability and communication strength;

[0034] 5. Determine the primary control channel and backup control channel based on communication feasibility, with the optimal control channel being the primary control channel;

[0035] The UAV body 1 can also switch to manual control. Manual control is remote control by manually operating the base station controller 6, vehicle controller 9, centralized control server 13, and shipboard controller 17. When manually controlled, the control source control instructions such as the airborne modulation platform 3, base station communication equipment 7, vehicle communication equipment 11, centralized control communication equipment 15 and shipboard communication equipment 18 will be locked.

[0036] The big data server includes a processor 1, a machine-readable storage medium and a network interface. The machine-readable storage medium, the network interface and the processor are connected via a bus system. The network interface is used to communicate with at least one service terminal. The machine-readable storage medium is used to store programs, instructions or codes, and the processor is used to execute the programs, instructions or codes in the machine-readable storage medium.

[0037] It should be noted that it should be understood that the division of the various modules of the above device is only a division of logical functions. In actual implementation, they can be fully or partially integrated into a physical entity object, or they can be physically separated, and these modules can all be implemented in the form of software called by processing elements, or all in the form of hardware, or some modules can be implemented in the form of software called by processing elements, and some modules can be implemented in the form of hardware. For example, the acquisition module can be a separately established processing element, or it can be integrated in a chip of the above device. In addition, it can also be stored in the memory of the above device in the form of program code, and called and executed by a processing element of the above device to perform the function of the above acquisition module. The implementation of other modules is similar. In addition, these modules can be fully or partially integrated together, or implemented independently. The processing element described here can be an integrated circuit with signal processing capabilities. In the implementation process, the steps of the above method or the above modules can be completed by the hardware integrated logic circuit in the processor element or software instructions. The processor is used to execute the program, instructions or code in the machine-readable storage medium to execute the information feedback instructions required by the drone body 1, the airborne modulation platform 3, the base station communication equipment 7, the vehicle-mounted communication equipment 11, the centralized control communication equipment 15 and the ship-mounted communication equipment 18.

[0038] The executed feedback information instruction can be the environmental picture captured by the drone body 1 during operation. The executed feedback information instruction can be the instruction information manually input by the airborne modulation platform 3, the base station communication device 7, the vehicle communication device 11, and the centralized control communication device 15.

[0039] The airborne communication device 4 uses a wireless communication mode to receive monitoring information from the base station communication device 7, the vehicle-mounted communication device 11, the centralized control communication device 15 and the ship-mounted communication device 18, and transmits it to the airborne controller 2 through a wired transmission method. The airborne controller 2 completes the multi-terminal control source identification, thereby realizing the optimal coordinated operation of the UAV body.

[0040] The onboard communication device 4 also includes radio frequency signal communication, and the drone body can be manually operated through a remote control handle.

[0041] The computer-readable storage medium is preset with instructions, which, when executed, enable the computer to execute an operation control method for the drone body 1 in any possible design example of the stored instructions.

[0042] Embodiment 2 The present invention further discloses a method for controlling a drone body, which is applied to an airborne controller 2 and includes: reporting a flight route of the drone body to a core network via a base station connected to the controller, so that the base station connected to the controller obtains base stations covered by the flight route from the core network, wherein the flight route is a pre-planned flight route when the drone body is in a fixed mode;

[0043] In response to the need to switch the drone body from a fixed mode to a dynamic mode, control information is sent to the base station to which the controller is connected, so that the base station to which the controller is connected sends a paging signaling carrying the control information to the base stations covered by the flight route.

[0044] Embodiment 3 The present invention further discloses a method for controlling a drone body, which is applied to a base station connected to a controller, and comprises: receiving a flight route of the drone body reported by the controller, where the flight route is a pre-planned flight route when the drone body is in a fixed mode;

[0045] Report flight routes to the core network;

[0046] Receive base stations covered by the flight route returned by the core network;

[0047] receiving control information sent by the controller to the base station in response to a need to switch the drone body from a fixed mode to a dynamic mode;

[0048] A paging signaling carrying control information is sent to the base station covered by the flight route, so that the base station connected to the drone body can send a paging signaling to the drone body.

[0049] Embodiment 4 The vehicle-mounted controller 9 of the present invention comprises:

[0050] Processor 2;

[0051] a memory for storing instructions executable by processor two;

[0052] Processor 2 is configured as follows:

[0053] The flight route of the UAV is reported to the core network through the base station connected by the vehicle-mounted controller 9, so that the base station connected by the vehicle-mounted controller 9 obtains the base stations covered by the flight route from the core network. The flight route is a pre-planned flight route when the UAV is in a fixed mode.

[0054] In response to the need to switch the drone from fixed mode to dynamic mode, control information is sent to the base station connected to the vehicle-mounted controller 9, so that the base station connected to the vehicle-mounted controller 9 sends paging signaling carrying control information to the base stations covered by the flight route.

[0055] The portable base station 5 in the present invention comprises:

[0056] Processor three;

[0057] a memory for storing instructions executable by processor three;

[0058] Among them, processor three is configured as:

[0059] Receive the flight path of the drone reported by the controller. The flight path is the pre-planned flight path when the drone is in fixed mode.

[0060] Report flight routes to the core network;

[0061] Receive base stations covered by the flight route returned by the core network;

[0062] receiving control information sent by the onboard controller 9 to the portable base station 5 in response to a need to switch the drone from a fixed mode to a dynamic mode;

[0063] A paging signaling carrying control information is sent to the base stations covered by the flight route, so that the portable base station 5 connected to the drone can send the paging signaling to the drone.

[0064] It should be noted that the functions to be implemented by the hardware in the present invention are supported by a large number of mature technologies and belong to the existing technology. The essence of the present invention is to optimize the combination of existing hardware and its connection methods for specific application scenarios to meet the adaptation requirements in specific application scenarios and solve the problems raised in the background technology (not involving improvements to the software inside the hardware).

[0065] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A multi-terminal UAV collaborative system based on big data, characterized by: The invention comprises an unmanned aerial vehicle (UAV) body (1), a portable base station (5), a mobile command vehicle (8), a centralized control and dispatching center (12) and a big data server, wherein the UAV body (1) is provided with an airborne controller (2), an airborne modulation platform (3) and an airborne communication device (4), the portable base station (5) is provided with a base station controller (6) and a base station communication device (7), the mobile command vehicle (8) is provided with an onboard controller (9), an onboard control panel (10) and an onboard communication device (11), and the centralized control and dispatching center (12) is provided with a centralized control server (13), a centralized control control panel (14) and a centralized control communication device (15). The unmanned boat (16) is provided with a shipboard controller (17) and a shipboard communication device (18); the airborne modulation platform (3), the base station communication device (7), the vehicle communication device (11), the centralized control communication device (15) and the shipboard communication device (18) constitute a multi-terminal control source of the unmanned aerial vehicle body (1); the airborne modulation platform (3) can directly send control instructions to the airborne controller (2); the airborne modulation platform (3), the base station communication device (7), the vehicle communication device (11), the centralized control communication device (15) and the shipboard communication device (18) are all connected to the big data server for communication; When the onboard controller (2) completes the multi-terminal control source identification, it determines the controllability of the signal source through "operation mode, confidentiality requirements, and communication strength" to obtain the optimal control channel. The identification steps are as follows:

1. Determine the multi-terminal control source, which includes an airborne modulation platform (3), a base station communication device (7), a vehicle-mounted communication device (11), a centralized control communication device (15), and a ship-mounted communication device (18); 2. Determine the operation mode and controllability. The operation modes include functional testing, loading / unloading, autonomous cruise / return, automatic operation, and collaborative operation. Then determine the controllability between the multi-terminal control source and the operation mode. The controllable range is 1 to 2.

3. Determine the communication strength based on communication delay, packet loss rate, and effective bandwidth, with the strength range from 5% to 100%; 4. Determine the communication feasibility of each control source based on controllability and communication strength; 5. Determine the primary control channel and backup control channel based on communication feasibility, with the optimal control channel being the primary control channel; The UAV body (1) can also be switched to manual control. Manual control is remote control through manual operation of the base station controller (6), the vehicle controller (9), the centralized control server (13), and the ship-borne controller (17). During manual control, the control source control instructions of the airborne modulation platform (3), the base station communication equipment (7), the vehicle communication equipment (11), the centralized control communication equipment (15), and the ship-borne communication equipment (18) will be locked; the big data server includes a processor, a machine-readable storage medium, and a network interface. The machine-readable storage medium, the network interface, and the processor are connected through a bus system. The network interface is used to communicate with at least one service terminal. The machine-readable storage medium is used to store programs, instructions, or codes. The processor is used to execute the programs, instructions, or codes in the machine-readable storage medium.

2. The big data-based multi-terminal UAV collaborative system according to claim 1, characterized in that: The processor is used to execute the program, instruction or code in the machine-readable storage medium to execute the information feedback instructions required by the unmanned aerial vehicle body (1), the airborne modulation platform (3), the base station communication equipment (7), the vehicle-mounted communication equipment (11), the centralized control communication equipment (15) and the ship-mounted communication equipment (18).

3. The big data-based multi-terminal UAV collaborative system according to claim 2, characterized in that: The feedback information instruction to be executed may be a picture of the environment captured by the drone body (1) during operation.

4. The big data-based multi-terminal UAV collaborative system according to claim 3, characterized in that: The feedback information instruction to be executed may be instruction information manually input by an onboard modulation platform (3), a base station communication device (7), an onboard communication device (11), or a centralized control communication device (15).

5. The big data-based UAV multi-terminal collaborative system according to claim 1, characterized in that: The airborne communication device (4) receives monitoring information from the base station communication device (7), the vehicle-mounted communication device (11), the centralized control communication device (15) and the ship-mounted communication device (18) in a wireless communication mode, and transmits the monitoring information to the airborne controller (2) via a wired transmission mode. The airborne controller (2) completes multi-terminal control source identification, thereby achieving optimal coordinated operation of the UAV body.

6. The big data-based multi-terminal UAV collaborative system according to claim 5, characterized in that: The onboard communication device (4) also includes radio frequency signal communication, and the drone body can be manually operated through a remote control handle.

7. The big data-based multi-terminal UAV collaborative system according to claim 6, characterized in that: The computer-readable storage medium is pre-set with instructions, which, when executed, enable the computer to execute an operation control method for the drone body (1) in any possible design example of the stored instructions.

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