CN114355983A - Distributed unmanned aerial vehicle cluster control system - Google Patents
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Abstract
The invention discloses a cluster control system based on a distributed unmanned aerial vehicle, which comprises: the communication layer comprises a flight control communication module, a ground station communication module and a node communication module, and is respectively communicated with the flight control module, the ground station and the node; the basic control layer is in direct communication with the communication layer and is used for acquiring node data from the node communication module, native data from the flight control communication module and instructions from the ground station communication module, the basic control layer comprises a target position updating module and a basic control module, the target position is updated according to the native data and the instructions, and updated target position information is provided for the basic control module; the basic control module feeds back information to the flight control communication module; the task control layer comprises a task position updating module used for receiving the node data and the local data, updating the position and sending the updated task position to the target position updating module. The invention ensures the real-time performance of communication and improves the utilization rate of the broadband.
Description
Technical Field
The invention relates to the field of unmanned aerial vehicles. Specifically, the invention relates to a distributed unmanned aerial vehicle cluster control system.
Background
The application and development of unmanned fleet vehicles, particularly military applications, dates back to the early 1990 s (Kelly 1994; Andrew et al 2017; Condliffe 2017). Nevertheless, the drone swarm is still in a launch phase. As technology has evolved and become more readily available, research, development and integration efforts in unmanned fleet development have begun to attract attention in a wider and commercial application. Notably, 300 drones developed by intel were deployed as the 51 st super bowl and the 2018 winter olympic (Molina 2017) coordination light show. In addition to these examples, there are other presentations of the drone swarm, however, in most presentations, the level of autonomous operation is relatively low.
In most cases, each individual drone is controlled simultaneously by a ground control system. Conventional unmanned aerial vehicles utilize a computer as a GCS (ground station control system) running ground control software. These computers are equipped with a transceiver that can send and receive telemetry data from the connected drones. Traditionally, telemetry data includes GPS information, ground speed, and other parameters collected from payload sensors. Traditionally, these transceivers use an unlicensed radio frequency band (e.g., 900 MHz) to transmit and receive data. A higher level of autonomy would enable the drone to make decisions using the onboard computer. Current demonstrations of UAV (unmanned aerial vehicle) groups utilize one of two general forms of group communication architectures. Both forms are infrastructure-based group architectures and ad-hoc network-based architectures.
(1) Infrastructure-based cluster architecture (as in FIG. 1)
The infrastructure-based architecture consists of a GCS that receives telemetry information from all drones in the cluster and sends commands back to each drone separately. In some cases, the GCS will communicate with individual drones in real time, sending commands to flight controllers on each drone. In other cases, flight operations are preprogrammed on each UAV, which are running simultaneously, while the GCS is used only for the observation system. These unmanned clusters are considered semi-autonomous because they still require centrally controlled guidance to complete a given operation (Bekmezci et al, 2013).
Fig. 1 illustrates an infrastructure-based group architecture. The infrastructure-based group architecture relies on the GCS to coordinate all drones. This dependency leads to a lack of system redundancy. If any operation of the GCS is attacked or fails, the operability of the entire cluster is affected. The infrastructure-based approach requires that all drones are within the propagation range of the GCS. One drawback of unlicensed radio frequency communications is that communications may be susceptible to interference. Due to the light payload capability of the uas (small unmanned aerial vehicle system), the hardware required to establish reliable communication with the infrastructure may limit the utility of the infrastructure-based group. Another disadvantage is the lack of distributed decision making. In an infrastructure-based architecture, the GCS coordinates the decision of all UAVs according to the calculations and algorithms developed in the GCS.
(2) Flight ad hoc network (FANET) architecture (as shown in figure 2)
It is proposed in (Bekmezci et al 2013) to use FANET to coordinate communications between all drones in the network. FANET is a group of drones that can communicate with each other without access points, but at least one of which must be connected to a ground base or satellite. Drones perform tasks without human assistance, just like autopilots. In recent years, many research fields in academia and industry have focused on FANETs due to cheaper and smaller wireless communication devices. FANET is now used in a variety of applications, such as military and civilian applications, managing wildfires, and disaster monitoring. Since each type of network has its own specification, it is important to use a reliable protocol according to the specification and to check its performance by simulation.
A wireless ad hoc network is a wireless network that does not rely on existing infrastructure to establish a network. Ad-hoc networks do not require routers or access points. Instead, the nodes are dynamically assigned and reassigned based on a dynamic routing algorithm. Various ad-hoc communication network configurations have been proposed in the M2M communication system (Walter et al, 2006; Lamont et al, 2007; Teague and Kewly 2008; Elston et al, 2009; burkle et al, 2011; Sahingoz 2014). In FANET, all drones are part of the communication network established between drones. The network allows real-time communication between drones, as shown in fig. 2.
Direct communication between drones forces distributed decision making because it is not necessary for an infrastructure-based decision engine. This also provides built-in redundancy, as the entire cluster does not rely on infrastructure to perform the required operations. This is a major advantage of FANET.
Some of the drawbacks of FANET are related to size, weight and power considerations. To establish FANET, networking hardware is required on each drone. The distance at which drones reliably communicate with each other in FANET is the limiting factor in their implementation (Bekmezci et al, 2013; Sahingoz 2014). Dynamic reconfiguration of drone swarm application routes is a challenging task that can lead to packet loss (Zhou et al, 2012; Bekmezci et al, 2013). For applications where accurate telemetry data between drones is crucial, establishing reliable FANET is difficult (Bekmezci et al, 2013; Sahingoz 2014).
Disclosure of Invention
The invention provides a solution based on a distributed unmanned aerial vehicle cluster control system, and the solution is mainly characterized in communication among unmanned aerial vehicles. And realizing the communication between the local machine and other airplanes by adopting a multicast mode.
Specifically, the invention provides a cluster control system based on a distributed unmanned aerial vehicle, which comprises:
the communication layer comprises a flight control communication module, a ground station communication module and a node communication module, and is respectively communicated with the flight control module, the ground station and the node;
a base control layer in direct communication with the communication layer for obtaining node data from the node communication module, native data from the flight control communication module, and instructions from the ground station communication module,
the basic control layer comprises a target position updating module and a basic control module, and is used for updating the target position according to the native data from the flight control communication module and the instruction from the ground station communication module and providing the updated target position for the basic control module; the basic control module feeds back information to the flight control communication module through communication; and
and the task control layer comprises a task position updating module, receives node data and local data from a basic control layer, performs position updating according to the node data and the local data, and sends the updated task position to the target position updating module.
In the present invention, there are two types of communication nodes:
1. and the control station mainly completes the functions of issuing instructions to the cluster and obtaining the state of each node.
2. The unmanned aerial vehicle node mainly completes the functions of releasing the node state of the unmanned aerial vehicle and acquiring the states of other nodes. The cluster platform can adopt a long-distance wifi technology to realize communication between the unmanned aerial vehicles, and utilizes the 4G cellular wireless communication equipment to realize a monitoring function with the ground station. Meanwhile, data synchronization between the drones can be realized by adopting a DDS (middleware protocol and application program interface) mode, for example. And meanwhile, the anti-interference performance of the unmanned aerial vehicle is improved by adopting a group decision technology.
That is to say, unmanned aerial vehicle, ground station are collectively called the node, and node communication means unmanned aerial vehicle and unmanned aerial vehicle, unmanned aerial vehicle and ground station communication function. The node data includes unmanned aerial vehicle GPS position, relative position, speed, battery voltage, time synchronization.
In the present invention, the local data contains what data the attitude of the drone, GPS position, relative position, speed, battery voltage, etc.
In the present invention, the instructions from the ground station communication module generally include takeoff, landing, hovering, starting tasks, parameter settings.
In some preferred embodiments of the present invention, the flight control communication module adopts a mavlink protocol, and the adoption of the mavlink protocol has the advantage of adopting an unmanned aerial vehicle universal protocol, thereby reducing the limitation on a hardware platform; the ground station communication module and the node communication module both adopt a UDP broadcast form and a zylink protocol, and the adoption of the protocol has the advantage that compared with a mavlik, the communication efficiency is higher by reducing unnecessary data.
In some preferred embodiments of the present invention, the target location updating module mainly completes control of the flight status, attitude, relative position, GPS position, and safety protection (e.g., takeoff, landing, hovering, and battery voltage) of the drone, and sends the updated target location result to the basic control module.
In some preferred embodiments of the present invention, the task control layer mainly performs user-defined control functions, such as a track function, a formation function, a collision avoidance function, and the like.
In some preferred embodiments of the present invention, the base control layer may call a function from a task location update module in the task control layer at a fixed frequency through the target location update module to implement the custom control.
In some preferred embodiments of the present invention, the basic control layer calls the LocMsg function to call back the flight state, attitude, relative position, GPS position and battery voltage of the machine to the task layer class function, and the calling frequency is 30 Hz.
In some preferred embodiments of the invention, the base control layer obtains the data of the unmanned nodes in the network by calling NetMsg function, and the data type is a dictionary. The key of the dictionary is the unmanned plane sysid, the value is of a list type (including flight state, attitude, relative position, GPS position, battery voltage and the like), and the calling frequency is 30 Hz.
In some preferred embodiments of the present invention, when a ground instruction is received to enter task control, the base control layer may call an initMission function of the task control layer to initialize the task module. The parameters of the function include the current drone position, trajectory instructions, formation instructions and collision avoidance instructions.
Technical effects
The invention adopts a distributed communication architecture to realize the real-time performance of communication between the unmanned aerial vehicles. Has higher bandwidth utilization than the traditional mode (such as UDP). The test result shows that the maximum cluster number is 7 in the traditional UDP mode, but the cluster number can reach 40 in the mode of the invention.
The adoption of the group decision technology can effectively reduce the condition of single machine data abnormity caused by interference. In the test, the ground station sends command data. The unmanned aerial vehicle cluster data error rate under the condition that the decision-making technology is not adopted is 20%, and the error rate is reduced to 0 after the decision-making technology is adopted.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical means of the present invention more clearly understood, the present invention may be implemented in accordance with the content of the description, and in order to make the above and other objects, features, and advantages of the present invention more clearly understood, the following preferred embodiments are described in detail with reference to the accompanying drawings.
Drawings
FIG. 1 is a schematic block diagram of a prior art infrastructure-based group architecture;
fig. 2 is a schematic diagram of a FANET-based unmanned aerial vehicle cluster communication architecture in the prior art;
fig. 3 is a schematic block diagram of a cluster control system based on distributed drones according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a hardware dependency relationship based on a distributed unmanned aerial vehicle cluster control system according to an embodiment of the present invention.
Detailed Description
To further illustrate the technical means and effects of the present invention adopted to achieve the predetermined object, the following detailed description will be given to a specific implementation and effects of a distributed type unmanned aerial vehicle cluster control system according to the present invention with reference to the accompanying drawings and preferred embodiments.
As shown in fig. 3, the present invention provides a cluster control system based on distributed unmanned aerial vehicles, including:
the layer of communication is the layer of communication,
the communication layer comprises a flight control communication module, a ground station communication module and a node communication module which are respectively communicated with a flight control module, a ground station and a node;
wherein the communication node comprises: and the control station mainly completes the functions of issuing instructions to the cluster and obtaining the state of each node. The unmanned aerial vehicle node mainly completes the functions of releasing the node state of the unmanned aerial vehicle and acquiring the states of other nodes.
In this embodiment, the long-distance wifi technology is adopted to realize communication between the unmanned aerial vehicles, and the 4G cellular wireless communication equipment is used to realize the monitoring function with the ground station. Meanwhile, data synchronization is realized between the unmanned aerial vehicles by adopting a DDS (direct digital synthesis) mode. And meanwhile, the anti-interference performance of the unmanned aerial vehicle is improved by adopting a group decision technology.
Wherein, the node data includes unmanned aerial vehicle GPS position, relative position, speed, battery voltage and time synchronization.
Base control layer
Which is in direct communication with the communication layer for obtaining node data from the node communication module, native data from the flight control communication module, and instructions from the ground station communication module,
the basic control layer comprises a target position updating module and a basic control module, and is used for updating the target position according to the native data from the flight control communication module and the instruction from the ground station communication module and providing the updated target position for the basic control module; the basic control module feeds back information to the flight control communication module through communication; wherein, the data of the unmanned aerial vehicle comprises the attitude, the GPS position, the relative position, the speed, the battery voltage and the like of the unmanned aerial vehicle; the instructions from the ground station communication module generally include takeoff, landing, hovering, starting tasks and parameter setting.
And a task control layer
The task control layer comprises a task position updating module, and the task position updating module is used for receiving node data and local data from a basic control layer, updating positions according to the node data and the local data, and sending the updated task position to the target position updating module.
In this embodiment, the flight control communication module adopts a mavlink protocol; the ground station communication module and the node communication module both adopt a UDP broadcast form and a zylink protocol.
In this embodiment, the target location update module mainly completes control of the flight state, attitude, relative position, GPS position, and safety protection (e.g., takeoff, landing, hovering, and battery voltage) of the drone, and sends the updated target location result to the basic control module.
In this embodiment, the task control layer mainly completes a user-defined track function, a formation function, and an anti-collision function. The system calls data from a track library, a formation library and an anti-collision library to complete corresponding track, formation or anti-collision control.
In this embodiment, the basic control layer may call a function from a task location update module in the task control layer at a fixed frequency through the target location update module to implement the custom control.
In the embodiment, the basic control layer calls the LocMsg function to call back the flight state, attitude, relative position, GPS position and battery voltage of the local machine to the task layer function, and the calling frequency is 30 Hz.
In this embodiment, the base control layer obtains the data of the nodes of the unmanned aerial vehicle in the network by calling the NetMsg function, and the data type is a dictionary. The key of the dictionary is the unmanned plane sysid, the value is of a list type (including flight state, attitude, relative position, GPS position, battery voltage and the like), and the calling frequency is 30 Hz.
In this embodiment, when a ground instruction is received and task control is performed, the basic control layer calls an initMission function of the task control layer to initialize the task module. The parameters of the function include the current drone position, trajectory instructions, formation instructions and collision avoidance instructions.
By adopting the embodiment, the number of unmanned aerial vehicle clusters which can be simultaneously controlled can reach 40, and the decision error rate is basically 0.
In a further embodiment, the system may be implemented based on an embedded program developed by python. Due to the nature of python, the system may also run on windows systems. The hardware dependency of the system is as shown in fig. 4:
1. the flight control adopts a droneye company to open a source flight control customized development kit based on PX 4;
2. the flight control is connected with the UWB to obtain horizontal positioning information;
3. the flight control is connected with a laser height-fixing TFmini-plus to obtain height information;
4. the flight control is connected with a TX2 board card.
The system mainly depends on a UWB positioning system, so that a UWB positioning base station puts higher requirements and is related to the positioning precision of the system.
The software runs on the TX2 embedded board, according to project requirements. The TX2 board card is connected with the flight control through a serial port, and the Baud rate is 921600 bps. Each unmanned aerial vehicle node is linked by a wifi module in the TX 2.
(1) Communication layer
The communication layer is composed of a flight control communication module, a ground station communication module and a node communication module.
1. The flight control communication module is connected with the TX2 through a serial port. And the data is received by adopting an independent thread, and the data is sent and called by a basic control layer.
2. The ground station communication module adopts a ground station broadcast mode, the TX2 adopts an independent thread to receive instructions, and the port number is 50000.
3. The node communication module adopts a UDP broadcast mode, TX2 adopts a separate thread for receiving, and adopts a frequency of 10Hz to send a port number of 51000.
(2) Base control layer
Depending on the library action, the library mainly completes the position calculation of takeoff, hovering and landing.
(3) Application layer interface function
The base control layer calls the session class of the task control layer.
The basic control layer calls the LocMSg function to call back the flight state, attitude, relative position, GPS position and battery voltage of the machine to the task layer function, and the calling frequency is 30Hz
And the basic control layer obtains the data of the unmanned aerial vehicle node in the network by calling a NetMsg function, wherein the data type is a dictionary. The key of the dictionary is unmanned aerial vehicle sysid, the value is of list type (comprising flight state, attitude, relative position, GPS position and battery voltage), and the calling frequency is 30Hz
When a ground instruction is received and the task control is started, the basic control layer calls an initMission function of the task control layer to initialize the task module. The function parameters comprise the current unmanned aerial vehicle position, a track instruction, a formation instruction and an anti-collision instruction.
After the system enters the task control, the basic control layer calls the update function of the task layer at the frequency of 30Hz to realize the update of the target position.
The application layer calls track, synergy and avoidance routine libraries which mainly complete the track, the collaborative mode and the anti-collision algorithm.
Although the present invention has been described with reference to a preferred embodiment, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A cluster control system based on distributed unmanned aerial vehicles is characterized by comprising:
the communication layer comprises a flight control communication module, a ground station communication module and a node communication module, and is respectively communicated with the flight control module, the ground station and the node;
a base control layer in direct communication with the communication layer for obtaining node data from the node communication module, native data from the flight control communication module, and instructions from the ground station communication module,
the basic control layer comprises a target position updating module and a basic control module, updates the target position according to the native data from the flight control communication module and the instruction from the ground station communication module, and provides the updated target position information to the basic control module; the basic control module feeds back information to the flight control communication module through communication; and
and the task control layer comprises a task position updating module, receives node data and local data from a basic control layer, performs position updating according to the node data and the local data, and sends the updated task position to the target position updating module.
2. The control system of claim 1, wherein the flight control communication module employs a mavlink protocol.
3. The control system of claim 1, wherein the ground station communication module employs a UDP broadcast format, the zylink protocol.
4. The control system of claim 1, wherein the node communication module employs a UDP broadcast format, the zylink protocol.
5. The control system of any one of claims 1-4, wherein the target location update module essentially performs control of the flight status, attitude, relative position, GPS position, and safety protection of the drone and sends the updated target location results to the base control module.
6. The control system of any one of claims 1-4, wherein the task control layer essentially performs user-defined control functions.
7. The control system of claim 6, wherein the control functions include a trajectory function, a formation function, and a collision avoidance function.
8. The control system according to any one of claims 1 to 4, wherein the base control layer calls a function from a task location update module in a task control layer at a fixed frequency through a target location update module to realize custom control.
9. The control system according to any one of claims 1 to 4, wherein upon receiving an instruction from the ground station to enter task control, the base control layer invokes a function of the task control layer to initialize the task module.
10. The control system according to any one of claims 1 to 4, wherein the parameters of the functions of the mission control layer comprise current drone position, trajectory instructions, formation instructions and collision avoidance instructions.
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