A control system and unmanned aerial vehicle equipment for unmanned swarm

Abstract

The present invention discloses a control system and unmanned aerial vehicle equipment applied to unmanned aerial vehicle clusters. The system includes: a perception module, which is used to scan in a specified band to obtain the interference intensity of each frequency band in the specified band, and transmit the interference intensity of each frequency band to a control platform; a first control system, which is used to determine the working frequency band of the unmanned aerial vehicle according to the interference intensity of each frequency band, and send the working frequency band to a communication module; a second control system, which is used to collect environmental information through an external interface, identify the environmental information, and instruct the communication module to use the working frequency band for collaborative control of the unmanned aerial vehicle cluster according to the identification result. The signal interference intensity of the surrounding scene is obtained through the perception module, the working frequency band of the unmanned aerial vehicle is determined through scene recognition through the control platform, and target recognition is performed based on the environmental information collected from the external interface. According to the result of target recognition, the cluster can be notified in time to perform collaborative rescue, thereby realizing efficient and accurate rescue of forest fires.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control technology, and in particular to a control system applied to unmanned clusters. Background Art

[0002] my country has a vast territory, and the task of forest and grassland fire prevention and control is arduous. Professional casualties caused by fire fighting and disaster relief often occur. With the development of artificial intelligence, drones, unmanned vehicles and radio communication technology, more technical means are provided for forest and grassland fire fighting and rescue. For example, unmanned clusters are used to replace manual fire fighting and rescue of forest fires, so as to achieve the extinguishing of forest and grassland fires while ensuring the safety of users.

[0003] However, my country's unmanned swarm technology is still in the early research stage. UAV firefighting is mainly operated by remote control, and the firefighting and rescue area is limited, which cannot cope with large-scale forest and grassland fires. Unmanned swarms use a clustered broadband ad hoc network communication architecture, which can only work in small areas and has a limited rescue area. In addition, each drone in the swarm lacks a unified planning and design for performing various tasks, resulting in high power consumption of drones and the inability to accurately extinguish fires. Therefore, the existing unmanned swarms cannot achieve efficient and accurate rescue of forest fires. Summary of the invention

[0004] The present invention provides a control system and unmanned aerial vehicle equipment applied to unmanned clusters to achieve efficient and accurate fire extinguishing and rescue of forest fires.

[0005] According to one aspect of the present invention, a control system applied to an unmanned cluster is provided, comprising: a control platform, a communication module, a perception module and an external interface respectively connected to the control platform, wherein the control platform comprises: a computing power module set, a first control system and a second control system;

[0006] A sensing module, used for scanning in a specified band to obtain the interference intensity of each frequency band in the specified band, and transmitting the interference intensity of each frequency band to the control platform;

[0007] The first control system is used to determine the working frequency band of the drone according to the interference intensity of each frequency band through one or more computing power modules in the computing power module set, and send the working frequency band to the communication module;

[0008] The second control system is used to collect environmental information through the external interface, and to perform target recognition on the environmental information through one or more computing modules in the computing module set, and to instruct the communication module to use the working frequency band for collaborative control of the unmanned cluster based on the recognition result.

[0009] According to another aspect of the present invention, there is provided an unmanned aerial vehicle device, in which the control system for unmanned aerial vehicle clustering according to the present embodiment is configured.

[0010] The technical solution of the embodiment of the present invention obtains signal interference information of the surrounding scene through the perception module, and determines the working frequency band of the drone through scene recognition through the control platform, and performs target identification based on the environmental information collected from the external interface. According to the result of target identification, information sharing and real-time collaboration can be carried out based on communication interaction between nodes, and high-efficiency large-area precision firefighting is carried out with optimized grouping configuration, which can effectively improve firefighting efficiency, reduce fire losses, and reduce casualties.

[0011] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. 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 creative work.

[0013] Figure 1 This is a schematic diagram of a control system structure applied to an unmanned cluster provided according to Embodiment 1 of the present invention;

[0014] Figure 2 This is a schematic diagram of a control system technology architecture applied to an unmanned cluster provided according to Embodiment 1 of the present invention;

[0015] Figure 3 This is a schematic diagram of the structure of a control system applied to an unmanned cluster provided according to Embodiment 2 of the present invention;

[0016] Figure 4 It is a structural schematic diagram of a drone device provided according to Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0017] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0018] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0019] Embodiment 1

[0020] Figure 1 This is a schematic diagram of a control system structure applied to an unmanned cluster provided in the first embodiment of the present invention. This embodiment can be applied to the situation of extinguishing and rescuing forest fires in an unmanned cluster. Figure 1 As shown, the system includes: a control platform 10, a communication module 20, a perception module 30 and an external interface 40 respectively connected to the control platform 10, wherein the control platform 10 includes a computing power module set, a first control system and a second control system;

[0021] The sensing module 20 is used to scan the specified band to obtain the interference strength of each frequency band in the specified band, and transmit the interference strength of each frequency band to the control platform 10;

[0022] A first control system, used to determine the working frequency band of the drone according to the interference intensity of each frequency band through one or more computing modules in the computing module set, and send the working frequency band to the communication module 20;

[0023] The second control system is used to collect environmental information through the external interface 40, and to identify targets of the environmental information through one or more computing modules in the computing module set, and to instruct the communication module to use the working frequency band for collaborative control of the unmanned cluster according to the identification results.

[0024] Specifically, in this embodiment, by setting up a system including a control platform, a communication module, and a perception module, an unmanned cluster integrating communication, perception, computing, processing, and control can be realized. In addition, the communication module and the perception module in this embodiment can specifically use a software defined radio (SDR) chip as a processing unit for wireless spectrum perception channel analysis and interference analysis. Of course, this embodiment is only an example, and does not limit the specific type of chip used by the communication module and the perception module.

[0025] Specifically, the computing power module set of this embodiment can specifically adopt a system-on-chip (System on Chip, SOC), and the computing power modules contained in the computing power module set can specifically include CPU and NPU, wherein the CPU supports general computing power and the NPU supports AI computing power. Of course, this embodiment is only an example, and the specific type of the computing power module is not limited. In addition, the first control system in this embodiment can be a non-real-time system, the second control system can be a real-time system, and the computing power module set is applied to the micro-kernel unified operating system in the drone, the CPU mainly supports the non-real-time system and the real-time system in the micro-kernel unified operating system, and the NPU mainly supports the non-real-time operating system in the micro-kernel unified operating system. In addition, the drone applications corresponding to the real-time system and the non-real-time system in this embodiment are different. The real-time system is mainly used for applications with relatively high real-time requirements such as fire bomb control, flight control and cluster coordination; and the non-real-time system is mainly used for scene recognition, target recognition and decision planning, etc., which have relatively low real-time requirements. Of course, this embodiment is only an example, and the specific application types of drones corresponding to the real-time system and the non-real-time system are not limited.

[0026] It is worth mentioning that the perception module, communication module and control platform in this embodiment mainly exchange information through the internal bus. After the perception module obtains the interference intensity of each frequency band in the specified band through scanning, it will transmit it to the first control system through the internal bus. The first control system receives the interference intensity of each frequency band through the NPU for scene recognition processing to determine the specific scene of the band where the drone is located. Specifically, it can be realized by using a neural network model, a reinforcement learning model or a decision tree model to realize the recognition of the wireless communication scene. Of course, this embodiment is only an example, and the type of algorithm model used for wireless communication scene recognition is not limited. The perception module will sort out the interference intensity according to the corresponding band and transmit it to the CPU, and specifically compare the interference intensity of each frequency band with the threshold through the CPU. When there is a situation that exceeds the threshold, the working frequency band is re-screened, and the communication module is notified through the internal bus to communicate in the unmanned cluster according to the updated working frequency band; when the interference intensity of each frequency band does not exceed the threshold, the communication module is notified to maintain the current working frequency band for communication in the unmanned cluster.

[0027] Optionally, the second control system is used to collect environmental information through an external interface, perform target recognition on the environmental information to obtain recognition results, wherein the recognition results include rescue location and rescue intensity.

[0028] Optionally, the second control system is used to instruct the communication module to use the working frequency band to perform collaborative rescue of the unmanned cluster in the intra-cluster self-organizing network or the inter-cluster self-organizing network when it is determined that the rescue intensity exceeds the specified intensity; the second control system is used to determine the planned path according to the rescue location, and perform flight control for the UAV according to the planned path; the second control system is used to execute fire extinguishing bomb projection control for the UAV according to the rescue intensity when controlling the UAV to reach the rescue location.

[0029] Specifically, the external interface in the implementation mode of the present application includes a Gigabit Multimedia Serial Links (GMSL) interface, an Ethernet EHT communication interface or a controller area network CAN interface, etc. Each external interface is connected to a different form of peripherals, specifically a camera, a radar, etc. Of course, this implementation mode is only for illustrative purposes, and does not limit the specific type of the external interface.

[0030] In a specific implementation, the environmental information collected through the external interface will be transmitted to the second control system of the control platform through the internal bus. The second control system performs target recognition on the environmental information to obtain recognition results, specifically, to identify the specific fire point in the forest and grassland environmental information, that is, the rescue location, and the firepower value of the fire point, and determine the fire extinguishing and rescue intensity according to the firepower value. The second control system makes decisions based on the recognition results, determines the flight control for the drone, the projection control of the fire extinguishing bomb, and the coordinated rescue control of the unmanned cluster, etc. For example, the designated intensity set by the drone is level 3, that is, the rescue intensity level 3 is within the rescue range of the drone itself. When it is higher than level 3, it is determined that the drone itself cannot complete the rescue work of the fire point within the specified time. Therefore, when the rescue intensity is determined to be level 6, the communication module will be instructed through the internal bus to send an assistance request in the intra-cluster self-organizing network or the inter-cluster self-organizing network based on the previously determined working frequency band, so as to carry out the coordinated rescue of the unmanned cluster. On the other hand, for the drone itself, when the rescue location is determined to be point A, it will determine the optimal planned path to point A based on the current location, point A, and the actual flight environment, and execute flight control for the drone according to the determined planned path to accurately and timely reach the rescue location point A. At point A, the amount of fire-extinguishing bombs to be released is determined according to the rescue intensity, and fire-extinguishing bombs are released to point A according to the release amount. In this way, there is no need for manual control. When a large-scale forest fire occurs, the coordinated control of the unmanned cluster can also be used to achieve timely rescue of the dangerous situation.

[0031] It is worth mentioning that Figure 2As shown, it is a schematic diagram of the technical architecture in this implementation. The technical architecture is the underlying design that supports the work of the system, and mainly includes the cognitive communication and sensor layer, the computing power platform layer, the system software layer and the functional software layer. The cognitive communication and sensor layer adopts a software radio architecture, which meets the requirements of unmanned cluster networking and wireless cognition by loading different waveforms, and mainly supports the normal operation of external interfaces, communication modules and perception modules; the computing power platform layer provides AI computing power for cognitive communication, target recognition, and decision-making planning, and provides general computing power for flight control, fire bomb control, and cluster collaborative control, mainly supporting the normal operation of the computing power module; the system software layer realizes the heterogeneous integration of real-time operating systems and non-real-time operating systems through hypervisor, and supports the normal operation of the operating system used by drones; the functional software layer includes safety-critical flight control, fire bomb control, cluster collaborative control, and the normal execution of mission-critical cognitive communication, target recognition, decision-making planning and other applications.

[0032] It should be noted that, in this embodiment, an example is given of an unmanned cluster composed of drones for forest fire rescue. In actual applications, the unmanned cluster can also be an unmanned cluster composed of vehicles to perform rescue operations in other specific scenarios. Of course, this embodiment is only an example and does not limit the specific form of the unmanned cluster.

[0033] In the embodiment of the present application, the signal interference intensity of the surrounding scene is acquired through the perception module, the operating frequency band of the drone is determined through scene recognition through the control platform, and target identification is performed based on the environmental information collected from the external interface. According to the result of target identification, information sharing and real-time collaboration can be performed based on communication interaction between nodes, and high-efficiency and large-area precision firefighting can be performed with optimized grouping configuration, which can effectively improve firefighting efficiency, reduce fire losses, and reduce casualties.

[0034] Embodiment 2

[0035] Figure 3 The present invention provides a control system structure diagram of an unmanned cluster application. This embodiment is based on the above embodiment and mainly describes the communication module and the perception module in detail. Figure 3 As shown, the communication module includes an intra-cluster communication module 21 and an inter-cluster communication module 22 , and the perception module includes an intra-cluster perception module 31 and an inter-cluster perception module 32 .

[0036] Optionally, the intra-cluster sensing module 31 is used to scan the C band matched by the intra-cluster self-organizing network of the drone to obtain the interference intensity of each frequency band in the C band, and transmit the interference intensity of each frequency band in the C band to the first control system; the inter-cluster sensing module 32 is used to scan the L band matched by the inter-cluster self-organizing network of the drone, obtain the interference intensity of each frequency band in the L band, and transmit the interference intensity of each frequency band in the L band to the first control system; wherein the frequency of each frequency band in the C band is higher than the frequency of each frequency band in the L band.

[0037] Specifically, in this embodiment, the drones in the unmanned cluster are clustered according to the distance, and the drones with a relatively close distance are divided into a cluster, thereby being divided into multiple clusters, and each cluster contains multiple drones. The unmanned cluster corresponds to the C band, the frequency is high frequency, and the frequency range is 4-8GHz; the unmanned cluster corresponds to the L band, the frequency is low frequency, and the frequency range is 1-2GHz. Of course, this embodiment is only an example, and does not limit the specific bands used in the cluster and between clusters. As long as different bands are used for communication within the cluster and between clusters, they are all within the protection scope of this application, and the embodiment of this application does not limit them. And different perception modules are used for scanning within the cluster and between clusters, and the scanning within the cluster and between clusters does not interfere with each other, thereby improving the scanning efficiency and the accuracy of perception. The interference intensity of each frequency band in the C band is obtained by scanning through the intra-cluster perception module, and the interference intensity of each frequency band in the L band is obtained by scanning through the inter-cluster perception module. Each perception module transmits the interference intensity of each frequency band under the corresponding band obtained to the first control system through the internal bus.

[0038] Optionally, the first control system is used to, when it is determined that the interference intensity of each frequency band in the C band is less than a first preset threshold, keep the current working frequency band of the UAV in the intra-cluster self-organizing network unchanged; when it is determined that the interference intensity of each frequency band in the C band is greater than the first preset threshold, use the frequency band with the smallest interference intensity in the C band as the current working frequency band of the UAV in the intra-cluster self-organizing network; when it is determined that the interference intensity of each frequency band in the L band is less than a second preset threshold, keep the current working frequency band of the UAV in the inter-cluster self-organizing network unchanged; when it is determined that the interference intensity of each frequency band in the L band is greater than the second preset threshold, use the frequency band with the smallest interference intensity in the L band as the current working frequency band of the UAV in the inter-cluster self-organizing network.

[0039] Optionally, the communication module includes: an intra-cluster communication module and an inter-cluster communication module, a computing power module, which is used to transmit the current working frequency band of the intra-cluster self-organizing network to the intra-cluster communication module through an internal bus; and a computing power module, which is used to transmit the current working frequency band of the inter-cluster self-organizing network to the inter-cluster communication module through an internal bus.

[0040] Specifically, the first control system will make a decision analysis based on the interference intensity of each frequency band obtained, and determine the working frequency bands of the UAV within the cluster and between clusters respectively. For example, the first preset threshold set for intra-cluster communication is -110dBm. When it is determined that the interference intensity of each frequency band in the C band is less than -110dBm, it is determined that the current intra-cluster communication of the UAV is not affected, so the intra-cluster communication module will be notified to continue to maintain the current working frequency band for intra-cluster communication; and when the interference intensity of each frequency band in the C band is greater than -110dBm, it is determined that the current intra-cluster communication of the UAV is affected. At this time, the frequency band with the smallest interference intensity in the C band, such as 6GHz-6.1GHz, will be used as the new working frequency band, and the current working frequency band of the intra-cluster self-organizing network, 6GHz-6.1GHz, will be transmitted to the intra-cluster communication module for intra-cluster communication.

[0041] In addition, the second preset threshold set for inter-cluster communication is -120dBm. When it is determined that the interference intensity of each frequency band in the L-band is less than 60dB, it is determined that the current inter-cluster communication of the drone is not affected, so the inter-cluster communication module will be notified to continue to maintain the current working frequency band for inter-cluster communication; and when the interference intensity of each frequency band in the L-band is greater than 60dB, it is determined that the current inter-cluster communication of the drone is affected. At this time, the frequency band with the smallest interference intensity in the L-band, such as 1.5GHz-1.6GHz, will be used as the new working frequency band, and the current working frequency band of the inter-cluster self-organizing network 1.5GHz-1.6GHz will be transmitted to the inter-cluster communication module for inter-cluster communication.

[0042] In the embodiment of the present application, the signal interference intensity of the surrounding scene is obtained through the perception module, the scene recognition is performed through the control platform to determine the working frequency band of the drone, and the target is identified based on the environmental information collected from the external interface. According to the result of target identification, information sharing and real-time collaboration can be performed based on the communication interaction between nodes, and high-efficiency large-area precision firefighting can be performed with optimized grouping configuration, which can effectively improve the efficiency of firefighting, reduce fire losses, and reduce casualties. Different perception modules are used to scan the interference intensity within and between clusters, and different communication modules are used for communication, so as to accurately obtain the working frequency bands within and between clusters, and use the determined working frequency bands to control the drone to communicate effectively within and between clusters of the unmanned cluster.

[0043] Embodiment 3

[0044] Figure 4 This is a schematic diagram of the structure of a UAV device provided in an embodiment of the present invention, in which a control system applied to an unmanned cluster according to any of the above embodiments is configured.

[0045] Among them, the control system applied to the unmanned swarm of this embodiment can be installed at the geometric center of the drone, and because the control system has a simple structure, light weight and small size, it will not increase the load-bearing pressure of the drone too much, nor will it occupy too much power consumption of the drone. Of course, this embodiment is only an example, and does not limit the specific installation location of the system on the drone. As long as the normal flight of the drone can be guaranteed, it is within the protection scope of this application, and it will not be repeated in the embodiment of this application.

[0046] It should be noted that each drone in the unmanned swarm will Figure 4 As shown, a control system for unmanned clusters is configured, and also includes basic structures such as a directional servo, an engine controller, and a communication antenna required for the normal flight of the UAV, so that each UAV in the unmanned cluster can achieve efficient and accurate coordinated firefighting and rescue of forest fires without manual control.

[0047] In the embodiment of the present application, the signal interference intensity of the surrounding scene is acquired through the perception module, the scene recognition is performed through the computing power module to determine the working frequency band of the drone, and target identification is performed based on the environmental information collected from the external interface. According to the result of target identification, the cluster can be notified in time for coordinated rescue, thereby realizing efficient and accurate forest fire extinguishing and rescue.

[0048] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A control system applied to unmanned clusters, characterized in that: include: A control platform, a communication module, a perception module and an external interface respectively connected to the control platform, wherein the control platform comprises: a computing power module set, a first control system and a second control system; A sensing module, used for scanning in a specified band to obtain the interference intensity of each frequency band in the specified band, and transmitting the interference intensity of each frequency band to the control platform; The first control system is used to determine the working frequency band of the drone according to the interference intensity of each frequency band through one or more computing power modules in the computing power module set, and send the working frequency band to the communication module; The second control system is used to collect environmental information through the external interface, and perform target recognition on the environmental information through one or more computing modules in the computing module set, and instruct the communication module to use the working frequency band to perform collaborative control of the unmanned cluster according to the recognition result; The sensing module includes: an intra-cluster sensing module and an inter-cluster sensing module; The intra-cluster sensing module is used to scan the C band matched by the intra-cluster self-organizing network of the drone to obtain the interference intensity of each frequency band in the C band, and transmit the interference intensity of each frequency band in the C band to the first control system; The inter-cluster sensing module is used to scan the L band matched by the inter-cluster self-organizing network of the drone, obtain the interference strength of each frequency band in the L band, and transmit the interference strength of each frequency band in the L band to the first control system; Wherein, the frequency of each frequency band in the C band is higher than the frequency of each frequency band in the L band; The first control system is also used to perform deep learning on the interference intensity of each frequency band received, and compare the interference intensity of each frequency band with a threshold after scene recognition processing, determine the operating frequency band of the drone based on the comparison result, and transmit it to the communication module through an internal bus.

2. The system according to claim 1, characterized in that The first control system is used to: When it is determined that the interference intensity of each frequency band in the C band is less than the first preset threshold, the current working frequency band of the drone in the cluster self-organizing network is kept unchanged; When it is determined that the interference intensity of each frequency band in the C band is greater than the first preset threshold, the frequency band with the smallest interference intensity in the C band is used as the current working frequency band of the UAV in the intra-cluster self-organizing network; When it is determined that the interference intensity of each frequency band in the L band is less than the second preset threshold, the current working frequency band of the UAV in the inter-cluster self-organizing network is kept unchanged; When it is determined that the interference intensity of each frequency band in the L band is greater than the second preset threshold, the frequency band with the smallest interference intensity in the L band is used as the current working frequency band of the UAV in the inter-cluster self-organizing network.

3. The system according to claim 2, characterized in that The communication module includes: an intra-cluster communication module and an inter-cluster communication module. The computing power module is used to transmit the current working frequency band of the intra-cluster self-organizing network to the intra-cluster communication module through an internal bus; The computing power module is used to transmit the current working frequency band of the inter-cluster self-organizing network to the inter-cluster communication module through the internal bus.

4. The system according to claim 2, characterized in that The second control system is used to collect the environmental information through the external interface, perform target recognition on the environmental information to obtain a recognition result, wherein the recognition result includes a rescue location and a rescue intensity.

5. The system according to claim 4, characterized in that The second control system is used to instruct the communication module to use the working frequency band to perform unmanned cluster collaborative rescue in an intra-cluster self-organizing network or an inter-cluster self-organizing network when it is determined that the rescue intensity exceeds the specified intensity; The second control system is used to determine a planned path according to the rescue location, and perform flight control on the UAV according to the planned path; The second control system is used to execute fire extinguishing bomb projection control on the drone according to the rescue intensity when controlling the drone to reach the rescue location.

6. The system according to any one of claims 1 to 5, characterized in that The external interface includes a Gigabit Multimedia Serial Link (GMSL) interface, an Ethernet (EHT) communication interface or a Controller Area Network (CAN) interface.

7. A drone device, characterized in that: The drone device is equipped with a control system applied to unmanned clusters as described in any one of claims 1 to 6.

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