CN216748542U - Unmanned aerial vehicle self-driving instrument system - Google Patents
Unmanned aerial vehicle self-driving instrument system Download PDFInfo
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- CN216748542U CN216748542U CN202220289775.5U CN202220289775U CN216748542U CN 216748542 U CN216748542 U CN 216748542U CN 202220289775 U CN202220289775 U CN 202220289775U CN 216748542 U CN216748542 U CN 216748542U
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Abstract
The application provides an unmanned aerial vehicle self-driving appearance system has made clear the relation of connection of each device, is favorable to realizing unmanned aerial vehicle's control. This unmanned aerial vehicle self-driving appearance system includes: the system comprises a data chain, a first processor, an execution device, a second processor, a positioning device, a combined navigation device and a remote control device; the first processor is connected with the remote control device through a data chain, the first processor is respectively connected with the execution device and the second processor, and the second processor is respectively connected with the positioning device and the combined navigation device; the positioning device is used for: sending the first positioning data to the second processor; the integrated navigation device is used for: sending the first flight status data to a second processor; the second processor is configured to: performing fusion calculation on the first positioning data and the first flight state data to obtain first navigation calculation data; the first processor is configured to: and controlling an executive device to realize the flight according to the remote control instruction, the first navigation resolving data and a preset air route plan.
Description
Technical Field
The utility model relates to the field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle self-driving instrument system.
Background
The unmanned aerial vehicle is the most widely used flight equipment at present, and is mainly used in the fields of aerial photography, resource detection, disaster relief, military, social security and the like. The autopilot is the core of an unmanned aerial vehicle avionics system, is equipment for automatically controlling the track of an aircraft according to task requirements, and is widely applied to modern aircrafts.
The existing unmanned aerial vehicle autopilot system generally processes various input information by a processor, and outputs a processing result to each peripheral interface to drive the peripheral to work so as to realize unmanned aerial vehicle autopilot, wherein the architecture of the processor can be advanced reduced instruction set machine (ARM) architecture, ARM + Field Programmable Gate Array (FPGA) architecture, ARM + ARM architecture, and the like. In order to improve the reliability of the unmanned aerial vehicle system, an advanced reduced instruction set (advanced RISC-performance computing, PowerPC) architecture with optimal ARM + performance computing is proposed at present, and under the architecture, how to specifically deploy the connection relationship between the ARM, the PowerPC and other devices is a technical problem which needs to be solved urgently.
SUMMERY OF THE UTILITY MODEL
The utility model provides an unmanned aerial vehicle self-driving instrument system which adopts an ARM + PowerPC framework, and defines the connection relation between the ARM and the PowerPC and other devices, thereby being beneficial to realizing the control of an unmanned aerial vehicle.
The utility model provides an unmanned aerial vehicle autopilot system, which comprises: the system comprises a data chain, a first processor, an execution device, a second processor, a positioning device, a combined navigator and a remote control device; the first processor is connected with the remote control device through a data chain, the first processor is respectively connected with the execution device and the second processor, and the second processor is respectively connected with the positioning device and the combined navigation device; the positioning device is used for: acquiring first positioning data and sending the first positioning data to a second processor; the integrated navigation device is used for: acquiring first flight state data and sending the first flight state data to a second processor; the second processor is configured to: receiving first positioning data and first flight state data, performing fusion calculation on the first positioning data and the first flight state data to obtain first navigation calculation data, and sending the first navigation calculation data to a first processor; the first processor is configured to: and receiving the first navigation resolving data, receiving a remote control instruction from the remote control device through a data link, and controlling the execution device to realize flight according to the remote control instruction, the first navigation resolving data and a preset air route plan.
Optionally, the integrated navigation device includes: the device comprises an inertial sensor, a magnetic sensor, an acceleration sensor, a gyroscope, a first barometer and a first atmospheric data processing device.
Optionally, the first flight state data includes a first flight direction, a first flight deflection, a first flight speed, a first flight acceleration, a first flight position, and a first flight altitude; the inertial sensor is used for: detecting the flight direction and the flight deflection of an unmanned aerial vehicle autopilot system to obtain a first flight direction and a first flight deflection; the magnetic sensor is used for: detecting the flight position of an unmanned aerial vehicle autopilot system to obtain a first flight position; the acceleration sensor is used for: detecting the flight acceleration of an unmanned aerial vehicle autopilot system to obtain a first flight acceleration; the gyroscope is used for: detecting the flight speed of an unmanned aerial vehicle autopilot system to obtain a first flight speed; the first barometer is to: the method comprises the steps of detecting the atmospheric pressure of an unmanned aerial vehicle autopilot system during flying to obtain a first atmospheric pressure, and sending the first atmospheric pressure to a first atmospheric data processing device; the first atmospheric data processing device is for: a first barometric pressure is received, and a first fly height is determined based on the first barometric pressure.
Optionally, the unmanned aerial vehicle autopilot system further comprises a combined inertial navigation device; the combined inertial navigation device is connected with the first processor; the combined inertial navigation device is used for: obtaining second positioning data and second flight state data, performing fusion calculation on the second positioning data and the second flight state data to obtain second navigation calculation data, and sending the second navigation calculation data to the first processor; the first processor is further configured to: and receiving second navigation calculation data, and controlling an execution device to realize flight according to the remote control instruction, the second navigation calculation data and a preset air route plan under the condition that the first navigation calculation data does not accord with the preset condition.
Optionally, the combined inertial navigation device includes a second barometer, a second atmospheric data processing device, and an inertial navigation device.
Optionally, the second flight state data includes a second flight direction, a second flight deflection, a second flight speed, a second flight acceleration, a second flight position, and a second flight altitude; the inertial navigation device is used for: detecting the flight direction, the flight deflection, the flight position and the flight acceleration of the unmanned aerial vehicle autopilot system to obtain a second flight direction, a second flight deflection, a second flight position and a second flight acceleration; the second barometer is to: detecting the atmospheric pressure of the unmanned aerial vehicle autopilot system during flying to obtain second atmospheric pressure, and sending the second atmospheric pressure to a second atmospheric data processing device; a second atmospheric data processing device: for receiving a second barometric pressure and determining a second altitude based on the second barometric pressure.
Optionally, the unmanned aerial vehicle self-driving instrument system further comprises a system state monitoring device; the system state monitoring device is connected with the first processor; the system state monitoring device is used for: acquiring state data of an unmanned aerial vehicle autopilot system, and sending the state data to a first processor, wherein the state data comprises at least one of oil mass data, temperature data and vibration data; the first processor is further configured to: and receiving the state data, and controlling an executive device to realize flight according to the state data, the remote control instruction, the first navigation resolving data and a preset air route plan.
Optionally, the unmanned aerial vehicle autopilot system further comprises a load device; the load equipment is connected with the second processor; the load device is for: sending payload data to a second processor; the second processor is further configured to: receiving load data, processing the load data to obtain processed load data, and sending the processed load data to a first processor; the first processor is further configured to: receiving the processed load data, and sending the processed load data to the remote control device through a data link; the remote control device is further configured to: receiving the processed load data, and sending a load control instruction to the first processor through a data link; the first processor is further configured to: receiving a load control instruction and sending the load control instruction to a second processor; the second processor is further configured to: receiving a load control instruction, and sending the load control instruction to load equipment; the load device is for: and receiving a load control command, and executing a flight task according to the load control command.
Optionally, the unmanned aerial vehicle autopilot system further comprises a maintenance interface; the second processor is further configured to: the method comprises the steps of storing flight data of the unmanned aerial vehicle autopilot system in the flight process of the unmanned aerial vehicle autopilot system, and sending the flight data to maintenance equipment through a maintenance interface after the unmanned aerial vehicle autopilot system stops flying.
Optionally, the unmanned aerial vehicle autopilot system further comprises a power distribution module; the power distribution module is used for: and supplying power to the unmanned aerial vehicle self-driving instrument system.
According to the unmanned aerial vehicle autopilot system provided by the utility model, the first processor is respectively connected with the remote control device and the execution device, the first processor can control the execution device to realize flight according to a remote control command sent by the remote control device, so that the flight reliability can be ensured, the second processor is respectively connected with the positioning device and the combined navigation device, the first navigation data can be resolved according to the first positioning data sent by the positioning device and the flight state data sent by the combined navigation device, the function of resolving large calculation force can be completed, meanwhile, the first processor is connected with the second processor, so that real-time communication can be carried out, the first processor can control flight more accurately, the safety and reliability of flight can be ensured, the demand on calculation force can be ensured, and the control of the unmanned aerial vehicle can be realized.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
Fig. 1 is a schematic block diagram of an unmanned aerial vehicle autopilot system provided in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention in light of the teachings of the present embodiments, are within the scope of the present invention.
The unmanned aerial vehicle is the most widely used flight equipment at present, and is mainly used in the fields of aerial photography, resource detection, disaster relief, military, social security and the like. The autopilot is the core of an unmanned aerial vehicle avionics system, is equipment for automatically controlling the track of an aircraft according to task requirements, and is widely applied to modern aircrafts.
In the existing unmanned aerial vehicle autopilot system, a microprocessor can be used as a Central Processing Unit (CPU) to process various input information, and simultaneously, a processing result is output to each peripheral interface to drive the peripheral to work so as to realize unmanned aerial vehicle autopilot. The microprocessor may be a single chip microcomputer, (advanced RISC machine, ARM) or a Digital Signal Processing (DSP) chip.
Unmanned aerial vehicle self-driving appearance system uses single microprocessor to realize unmanned aerial vehicle autopilot, can lead to this microprocessor to gather promptly and handle various sensor data, again will export the stability control in order to navigate to unmanned aerial vehicle's peripheral hardware, can make this microprocessor be in the state of full load work or even overload work, and then seriously influence the response speed of unmanned aerial vehicle self-driving appearance system.
Therefore, the information processing capacity and the loading capacity of the unmanned aerial vehicle self-driving instrument system using the single microprocessor are limited, and the performance of the unmanned aerial vehicle self-driving instrument system is low.
In order to solve the problem of a single microprocessor, the drone autopilot system can use two processors (namely two processors) to realize drone autopilot, and communication between the two processors needs to add a communication interface to perform coordination. The two processors may be two ARM processors, and may be referred to as an ARM + ARM architecture, or one processor may be an ARM and one processor may be a Field Programmable Gate Array (FPGA), and may be referred to as an ARM + FPGA architecture. When the unmanned aerial vehicle autopilot system uses an ARM + FPGA architecture, the unmanned aerial vehicle autopilot system can enable the ARM to be used as a main processor to take charge of control and calculation, enable the FPGA to be used as a coprocessor to take charge of signal acquisition and output, enable the coprocessor to be designed as a peripheral of the main processor, and enable the main processor to operate the coprocessor in a mode of operating a storage space of the main processor.
In the method, the FPGA is equivalent to the ARM, so that although the ARM + FPGA architecture and the ARM + ARM architecture can relieve the information processing pressure and the loading pressure of a single processor, the ARM + FPGA architecture and the ARM + ARM architecture are complex in operation, so that the logic structures of the unmanned aerial vehicle self-driving instrument system on software and hardware become more complex, the processor overhead is additionally increased, and the debugging of the system becomes difficult.
In addition, along with the application of unmanned aerial vehicles is more and more extensive, the weight and the volume of unmanned aerial vehicles are also larger and larger, and the requirement on the safety of unmanned aerial vehicle self-driving instrument systems is also higher and higher.
ARM has advanced technology and excellent product performance, such as characteristics of small volume, low power consumption, low cost, high performance and the like, so that ARM obtains numerous intellectual property authorized users, including top-level semiconductors and system companies in the world. Microprocessors adopting the ARM technology are distributed in various electronic products, such as automobiles, consumer entertainment, images, industrial control, mass storage, networks, security, wireless and other markets. Although the ARM can meet the requirement of security, the ARM is not completely suitable for use in highly reliable use scenarios, such as military industry, electric power, aviation, and the like, due to its own architecture.
For the field with higher reliability, a PowerPC architecture with higher integration degree is generally selected to improve the reliability of the whole system. The unmanned aerial vehicle self-driving instrument system can realize unmanned aerial vehicle automatic driving by using a PowerPC framework, but with the development of an integrated circuit technology, more and more schemes related to inertial navigation are provided, meanwhile, the unmanned aerial vehicle structure is more and more complicated with the increase of the weight and the volume of the unmanned aerial vehicle, if only a PowerPC processor which meets the requirement of airworthiness safety level at present is used, the inertial navigation, control of each actuating mechanism and load are completed, or calculation is seriously insufficient, and the unmanned aerial vehicle self-driving instrument system is in full load work or even overload work, the response speed of the unmanned aerial vehicle self-driving instrument system is influenced, and the flight safety is influenced. If choose a plurality of powerPC treater to share the power of calculating, because the powerPC treater price is several times to tens of times of ARM treater, the cost of improvement unmanned aerial vehicle system that can be great loses economic nature.
Therefore, the single processor ARM, ARM + FPGA architecture, and ARM + ARM architecture schemes can meet the security requirement, but are limited by reliability. The solution using the PowerPC architecture can meet the requirement of reliability, but is limited by security. If the scheme of ARM + PowerPC architecture is used, the requirement of security and the requirement of reliability can be met, but how to specifically deploy the connection relationship between ARM, PowerPC and other devices under the architecture is a technical problem that needs to be solved urgently.
In view of this, the embodiment of the application provides an unmanned aerial vehicle self-driving instrument system, has adopted ARM + PowerPC framework to the relation of connection of ARM, PowerPC and other devices has been made clear, is favorable to realizing the control to unmanned aerial vehicle.
In order to make the purpose and the technical scheme of the present application clearer and more intuitive, the following will explain in detail the unmanned aerial vehicle autopilot system provided by the embodiment of the present application with reference to the accompanying drawings and the embodiment. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
Fig. 1 is a schematic block diagram illustrating connection of components of an unmanned aerial vehicle autopilot system 100 according to an embodiment of the present disclosure. As shown in fig. 1, the drone autopilot system 100 may include: a data link 101, a first processor 102, an execution device 103, a second processor 104, a positioning device 105, a combined navigation device 106 and a remote control device 107.
The first processor 102 may be a performance optimization with enhanced RISC-performance computing (PowerPC), the second processor may be an Advanced RISC Machine (ARM), the first processor 102 is connected to the remote control device 107 through the data link 101, the first processor 102 is connected to the execution device 103 and the second processor 104, and the second processor 104 is connected to the positioning device 105 and the integrated navigation device 106.
The remote control device 107 may be understood as a control terminal for controlling the drone, the connection between the remote control device 107 and the drone autopilot system 100 is a wireless communication connection, and specifically may be as described above, and the remote control device 107 is connected to the first processor 102 in the drone autopilot system 100 through the data link 101.
The actuator 103 may also be referred to as an actuator, which is not limited in the embodiments of the present application. The positioning device 105 is any device capable of performing positioning, for example, the positioning device 105 may be a Global Navigation Satellite System (GNSS).
The drone autopilot system 100 may include a variety of other implementations in addition to the components described above.
In one possible implementation, the drone autopilot system 100 may further include a combined inertial navigation device 108, and the combined inertial navigation device 108 is connected to the first processor 102.
In another possible implementation, the drone autopilot system 100 may further include a system status monitoring device 109, and the system status monitoring device 109 is connected to the first processor 102.
In this case, the drone autopilot system 100 may further include a combined inertial navigation device 108 and a system status monitoring device 109, and the combined inertial navigation device 108 and the system status monitoring device 109 may be connected to the first processor 102, respectively.
In yet another possible implementation, the drone autopilot system 100 may further include a power distribution module 111, the power distribution module 111 being connected to the first processor 102.
In this case, the drone autopilot system 100 may further include a combined inertial navigation device 108, a system state monitoring device 109, and a power distribution module 111 at the same time, and the combined inertial navigation device 108, the system state monitoring device 109, and the power distribution module 111 may be connected to the first processor 102 respectively.
In another possible implementation, the drone autopilot system 100 may further include a load device 110, the load device 110 being coupled to the second processor 104.
In this case, the drone autopilot system 100 may include the combined inertial navigation device 108, the system state monitoring device 109, the power distribution module 111, and the load device 110 at the same time, and the combined inertial navigation device 108, the system state monitoring device 109, and the power distribution module 111 may be connected to the first processor 102, and the load device 110 is connected to the second processor 104, respectively.
Alternatively, the connections between the first processor 102, the execution means 103, the second processor 104, the positioning means 105 and the combined navigation means 106 in the drone autopilot system 100 may be through an interface or a bus connection.
The connection between the first processor 102 and the remote control device 107 may be via a data link 101 via an interface. Illustratively, the first processor 102 may be connected to the remote control device 107 through the data link 101 via a recommended interface (RS) 422, an RS232, or a Reduced Media Independent Interface (RMII).
The first processor 102 may provide any one or more of the three interfaces, and in an application, the corresponding interface may be selected to connect according to actual requirements. For example, the first processor 102 may provide three interfaces of RS422, RS232 and RMII, and when the drone autopilot system 100 is a large drone, the first processor 102 may be connected to the remote control device 107 through the data link 101 via the RS422 or the RS 232. When the drone autopilot system 100 is a passenger aircraft, the first processor 102 may be implemented via RMII to interface with the remote control device 107 via the data link 101.
The connection between the first processor 102 and the execution device 103 may be through a bus or an interface. Illustratively, the first processor 102 may be connected to the execution device 103 through a Controller Area Network (CAN), or the first processor 102 may be connected to the execution device 103 through a Pulse Width Modulation (PWM) interface. Among them, CAN is one of the most widely used field buses internationally.
The connection between the second processor 104 and the positioning device 105 may be through an interface connection. Illustratively, the second processor 104 may be connected via a Universal Asynchronous Receiver Transmitter (UART) transmission interface.
The connection between the second processor 104 and the integrated navigation device 106 may be through a bus connection. The second processor 104 may be connected, for example, by a Serial Peripheral Interface (SPI) or an I2C (inter-integrated circuit) bus.
The connection between the second processor 104 and the first processor 102 may be through an interface connection. Illustratively, the second processor 104 may be connected with the first processor 102 through a UART transmission interface and an input-output interface.
In case the drone autopilot system 100 comprises a data link 101, a first processor 102, an execution means 103, a second processor 104, a positioning means 105 and a combined navigation means 106, the positioning means 105 is configured to: acquiring first positioning data and sending the first positioning data to the second processor 104; the integrated navigation device 106 is configured to: acquiring first flight state data and sending the first flight state data to the second processor 104; the second processor 104 is configured to: receiving the first positioning data and the first flight state data, performing fusion calculation on the first positioning data and the first flight state data to obtain first navigation calculation data, and sending the first navigation calculation data to the first processor 102; the first processor 102 is configured to: receiving the first navigation calculation data, receiving a remote control instruction from a remote control device 107 through a data link 101, and controlling an execution device 103 to realize flight according to the remote control instruction, the first navigation calculation data and a preset route plan.
In the flight process of the unmanned aerial vehicle autopilot system 100, after the positioning device 105 determines the first positioning data, the first positioning data can be sent to the second processor 104, meanwhile, the integrated navigation device 106 determines a first flight state, and sends first flight state data to the second processor 104, and after the second processor 104 receives the first positioning data and the first flight state data, the first positioning data and the first flight state data can be fused and resolved to obtain first navigation resolving data. The remote control device 107 may send a remote control instruction to the first processor 102 through the data link 101, where the remote control instruction may be used to instruct the drone to fly, and the first processor 102 may receive the remote control instruction, may obtain the first navigation solution data from the second processor 104, and control the execution device 103 to implement the flight according to the remote control instruction, the first navigation solution data, and a preset route plan.
The unmanned aerial vehicle self-driving instrument system provided by the embodiment of the application, first processor 102 is connected with remote control device 107 and executive device 103 respectively, first processor 102 can control executive device 103 to realize flight according to the remote control command that remote control device 107 sent, be favorable to guaranteeing flight reliability, second processor 104 is connected with positioning device 105 and combination navigation device 106 respectively, can be according to the first positioning data that positioning device 105 sent and the flight status data that combination navigation device 106 sent, resolve first navigation data, can accomplish the function that great computing power was resolved, and simultaneously, first processor 102 is connected with second processor 104, real-time communication can be carried out, can make the flight of first processor 102 more accurate control, be favorable to guaranteeing flight's safe and reliable, also can guarantee the demand to the computing power, be favorable to realizing the control to unmanned aerial vehicle.
As an alternative embodiment, the integrated navigation device 106 may include: the device comprises an inertial sensor, a magnetic sensor, an acceleration sensor, a gyroscope, a first barometer and a first atmospheric data processing device.
The integrated navigation device 106 may include an inertial sensor, a magnetic sensor, an acceleration sensor, a gyroscope, a first barometer, and a first atmospheric data processing device, and the integrated navigation device 106 may determine the first flight status data according to data obtained by the inertial sensor, the magnetic sensor, the acceleration sensor, the gyroscope, the first barometer, and the first atmospheric data processing device.
In this example, the connection relationship of the devices in the combined navigation device 106 is not limited in the embodiment of the present application.
Optionally, the first flight status data may include a first flight direction, a first flight deflection, a first flight velocity, a first flight acceleration, a first flight position, and a first flight altitude.
The inertial sensor is configured to: detecting the flight direction and the flight deflection of an unmanned aerial vehicle autopilot system to obtain a first flight direction and a first flight deflection; the magnetic sensor is used for: detecting the flight position of an unmanned aerial vehicle autopilot system to obtain a first flight position; the acceleration sensor is used for: detecting the flight acceleration of an unmanned aerial vehicle autopilot system to obtain a first flight acceleration; the gyroscope is used for: detecting the flight speed of an unmanned aerial vehicle autopilot system to obtain a first flight speed; the first barometer is to: the method comprises the steps that atmospheric pressure of an unmanned aerial vehicle autopilot system during flying is detected, first atmospheric pressure is obtained, and the first atmospheric pressure is sent to a first atmospheric data processing device; the first atmospheric data processing device is configured to: a first barometric pressure is received, and a first fly height is determined based on the first barometric pressure.
While the integrated navigation device 106 may include an inertial sensor, a magnetic sensor, an acceleration sensor, a gyroscope, and a first barometric pressure, the first flight status data may include a first flight direction, a first flight deflection, a first flight velocity, a first flight acceleration, a first flight position, and a first barometric pressure, the integrated navigation device 106 may be configured to: sending the first flight status data to the second processor 104, the second processor 104 may be configured to: and receiving the first flight state data, determining a first flight altitude according to a first atmospheric pressure in the first flight state data, and then determining first navigation solution data according to a first flight direction, a first flight deflection, a first flight speed, a first flight acceleration, a first flight position, a first flight altitude and positioning data.
As an alternative embodiment, in a case that the drone autopilot system 100 may further include the combined inertial navigation device 108, the combined inertial navigation device 108 may interface with the first processor 102, for example, the combined inertial navigation device 108 may interface with the first processor 102 through RS422 or RS 232.
The combined inertial navigation device 108 is used for: obtaining second positioning data and second flight state data, performing fusion calculation on the second positioning data and the second flight state data to obtain second navigation calculation data, and sending the second navigation calculation data to the first processor 102; the first processor 102 is further configured to: and receiving the second navigation calculation data, and controlling the execution device 103 to realize flight according to the remote control instruction, the second navigation calculation data and the preset air route plan under the condition that the first navigation calculation data does not accord with the preset condition.
The second navigation solution data determined by the combined inertial navigation device 108 and the first navigation solution data are backed up with each other and are redundancy. Under the condition that the second navigation solution data is backup data of the first navigation solution data, when the first navigation solution data does not meet a preset condition, the first processor 102 may further control the execution device 103 to realize flight according to the remote control instruction, the second navigation solution data, and a preset route plan.
For example, the preset condition may be that the altitude landing is greater than 3000 meters, the drone autopilot system flies 1000 meters high, and the first processor 102 determines that the drone needs to fly 6000 meters high according to the remote control instruction, the first navigation solution data and the preset airline plan, and it is difficult to land 6000 meters in a short time, and it may be considered that the first navigation solution data does not meet the preset condition.
Optionally, the combined inertial navigation device 108 may include a second barometer, a second atmospheric data processing device, and an inertial navigation device.
The combined inertial navigation device 108 may determine the second flight status data from data obtained from the second barometer, the second atmospheric data processing device, and the inertial navigation device.
In this example, the embodiment of the present application does not limit the connection relationship of the devices in the combined inertial navigation device 108.
Optionally, the second flight status data includes a second flight direction, a second flight deflection, a second flight speed, a second flight acceleration, a second flight position, and a second flight altitude; the inertial navigation device is used for: detecting the flight direction, the flight deflection, the flight position and the flight acceleration of the unmanned aerial vehicle autopilot system to obtain a second flight direction, a second flight deflection, a second flight position and a second flight acceleration; the second barometer is to: detecting the atmospheric pressure of the unmanned aerial vehicle autopilot system during flying to obtain second atmospheric pressure, and sending the second atmospheric pressure to a second atmospheric data processing device; a second atmospheric data processing device: for receiving a second barometric pressure and determining a second fly height based on the second barometric pressure.
The second flight state data includes a second flight direction, a second flight deflection, a second flight speed, a second flight acceleration, a second flight position, and a second flight altitude, which is just one possible implementation manner, and in another possible implementation manner, the combined inertial navigation device 108 may include a second barometer and an inertial navigation device. The second flight state data may include a second flight direction, a second flight deflection, a second flight velocity, a second flight acceleration, a second flight position, and a second barometric pressure, and the combined inertial navigation device 108 may be configured to send the second flight state data to the first processor 102, and the first processor 102 is further configured to: and receiving the second flight state data, determining a second flight altitude according to a second atmospheric pressure in the second flight state data, and then determining second navigation solution data according to a second flight direction, a second flight deflection, a second flight speed, a second flight acceleration, a second flight position, a second flight altitude and positioning data.
The unmanned aerial vehicle autopilot system that this application embodiment provided can confirm through second treater 104 that first navigation solves data, can confirm through combination inertial navigation device 108 that second navigation solves data, the second navigation solves data and first navigation and solves data backup each other, each other is the redundancy, when one of them data goes wrong, can confirm the flight data of flight according to another data, and then realize accurate flight control, be favorable to further increasing the reliability.
As an alternative embodiment, in the case that the drone autopilot system 100 further includes a system status monitoring device 109, the system status monitoring device 109 is connected to the first processor 102 through an interface, for example, the system status monitoring device 109 may be connected through an RS485 interface or an analog to digital converter (ADC).
The system status monitoring device 109 is configured to: collecting state data of the unmanned aerial vehicle autopilot system 100, and sending the state data to the first processor 102, wherein the state data comprises at least one of oil mass data, temperature data and vibration data; the first processor 102 is further configured to: and receiving the state data, and controlling the executive device 103 to realize the flight according to the state data, the remote control instruction, the first navigation resolving data and the preset air route plan.
The system condition monitoring device 109 may illustratively include a fuel level sensor, a temperature sensor, and a vibration sensor. The oil level sensor can be used for monitoring an oil level and obtaining oil quantity data, the temperature sensor can be used for monitoring temperature and obtaining temperature data, and the vibration sensor can be used for monitoring vibration and obtaining vibration data.
The system status monitoring device 109 may send the status data to the first processor 102 after determining the status data from the data obtained by the oil level sensor, the temperature sensor, and the vibration sensor, and the first processor 102 may control the execution device 103 to implement flight according to the status data, the remote control instruction, the first navigation solution data, and the preset route plan after receiving the status data.
The unmanned aerial vehicle self-driving appearance system that this application embodiment provided can confirm the state data of unmanned aerial vehicle self-driving appearance system through system status monitoring device 109 to can combine state data to further control the flight accurately, can improve the security and the reliability of flight.
As an alternative embodiment, in the case that the drone autopilot system 100 further includes a load device 110, the load device 110 is connected to the second processor 104 by a bus or interface, for example, the load device 110 may be connected to the second processor 104 by an RS422, RS232, CAN, or PWM interface.
The load device 110 is used to: sending payload data to the second processor 104; the second processor 104 is further configured to: receiving the load data, processing the load data to obtain processed load data, and sending the processed load data to the first processor 102; the first processor 102 is further configured to: receiving the processed payload data and sending the processed payload data to the remote control device 107 via the data link 101; the remote control device 107 is also used to: receiving the processed load data and sending a load control instruction to the first processor 102 through the data link 101; the first processor 102 is further configured to: receiving a load control instruction and sending the load control instruction to the second processor 104; the second processor 104 is further configured to: receiving a load control command, and sending the load control command to the load device 110; the load device 110 is used to: and receiving a load control command, and executing a flight task according to the load control command.
The load data may be data obtained by the load device 110 executing a flight mission, and may also be driving state data of the load device 110, which is not limited in this embodiment of the present application.
In this example, the second processor 104 is configured to assume control over execution and task collection of the load equipment 110, and the first processor 102 is only used for transmitting information, and is configured to send load data processed by the second processor 104 to the remote control device 107, and send load control instructions of the remote control device 107 to the second processor 104, so that the load control instructions are transmitted to the load equipment 110.
The unmanned aerial vehicle self-driving instrument system provided by the embodiment of the application can reduce the load of the first processor 102 to the maximum extent by only transmitting information in the process of executing the task by the load equipment 110 without participating in calculation, thereby being beneficial to ensuring that the first processor 102 is in a low-load mode, and ensuring that the system is in a high-response-speed state, and meanwhile, the second processor 104 is utilized to process the task of the unmanned aerial vehicle and the load equipment 110, and the subsequent maintenance cost of the unmanned aerial vehicle system can be reduced.
As an alternative embodiment, the drone autopilot system 100 further includes a maintenance interface; the maintenance interface may be a RMII or Digital In and Out (DIO) interface connection.
The second processor 104 is further configured to: the method comprises the steps of storing flight data of the unmanned aerial vehicle autopilot system in the flight process of the unmanned aerial vehicle autopilot system, and sending the flight data to maintenance equipment through a maintenance interface after the unmanned aerial vehicle autopilot system stops flying.
Before the maintenance equipment is maintained, the information of whether the airplane is healthy, the health degree, whether abnormal flight exists, the flight mileage, whether the device is damaged, whether the device needs to be maintained and the like needs to be acquired, and after the unmanned aerial vehicle autopilot system stops flying, the maintenance equipment can receive flight data through the maintenance interface.
The unmanned aerial vehicle self-driving appearance system that this application embodiment provided can be convenient for follow-up maintenance including the maintenance interface.
As an alternative embodiment, the drone autopilot system 100 further includes a power distribution module 111; the power distribution module 111 is configured to: and supplying power to the unmanned aerial vehicle autopilot system 100.
The power distribution module 111 may be connected to the first processor 102 in addition to supplying power, and transmit power distribution data to the first processor 102, where the power distribution data may include data such as power amount and power supply amount, and the first processor 102 may further control the execution device 103 to implement flight according to the power distribution data, the remote control instruction, the first navigation solution data, and the preset route plan.
Optionally, the first processor 102 may further control the execution device 103 to implement a flight according to the power distribution data, the state data, the remote control instruction, the first navigation solution data, and a preset route plan.
As an alternative embodiment, the ARM processor 104 may be i.mx6q and the PowerPC processor 102 is MPC 5675K. The I.MX6Q is a System On Chip (SOC) of an ARM architecture, and a user can independently develop a load task of the unmanned aerial vehicle by using an open-source LIUNX system, so that the autopilot system is more flexible. In addition, the ARM architecture may also adopt a Micro Controller Unit (MCU), which is not limited in this embodiment.
The embodiment of the application also provides an unmanned aerial vehicle flight control system, can include remote control device 107 and unmanned aerial vehicle autopilot system 100, and remote control device 107 is used for sending remote control command to unmanned aerial vehicle autopilot system 100, and this remote control command is used for the flight of remote control unmanned aerial vehicle autopilot system 100, and unmanned aerial vehicle autopilot system 100 is used for receiving remote control command to fly according to this remote control command. Each device included in the drone autopilot system 100 and the connection relationship between the devices are shown in fig. 1, and are not described herein again.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. An unmanned aerial vehicle autopilot system, comprising: a data link (101), a first processor (102), an execution device (103), a second processor (104), a positioning device (105), a combined navigation device (106) and a remote control device (107);
the first processor (102) is connected with the remote control device (107) through the data link (101), the first processor (102) is respectively connected with the execution device (103) and the second processor (104), and the second processor (104) is respectively connected with the positioning device (105) and the combined navigation device (106);
the positioning means (105) is configured to: acquiring first positioning data and sending the first positioning data to the second processor (104);
the integrated navigation device (106) is configured to: acquiring first flight status data, sending the first flight status data to the second processor (104);
the second processor (104) is configured to: receiving the first positioning data and the first flight state data, performing fusion calculation on the first positioning data and the first flight state data to obtain first navigation calculation data, and sending the first navigation calculation data to the first processor (102);
the first processor (102) is configured to: receiving the first navigation calculation data, receiving a remote control instruction from the remote control device (107) through the data link (101), and controlling the execution device (103) to realize flight according to the remote control instruction, the first navigation calculation data and a preset air route plan.
2. The drone autopilot system of claim 1 wherein the integrated navigation means (106) comprises:
the device comprises an inertial sensor, a magnetic sensor, an acceleration sensor, a gyroscope, a first barometer and a first atmospheric data processing device.
3. The drone autopilot system of claim 2 wherein the first flight status data includes a first flight direction, a first flight deflection, a first flight velocity, a first flight acceleration, a first flight position, and a first flight altitude;
the inertial sensor is configured to: detecting the flight direction and the flight deflection of the unmanned aerial vehicle autopilot system to obtain the first flight direction and the first flight deflection;
the magnetic sensor is configured to: detecting the flight position of the unmanned aerial vehicle autopilot system to obtain the first flight position;
the acceleration sensor is used for: detecting the flight acceleration of the unmanned aerial vehicle autopilot system to obtain the first flight acceleration;
the gyroscope is used for: detecting the flight speed of the unmanned aerial vehicle autopilot system to obtain the first flight speed;
the first barometer is to: detecting the atmospheric pressure of the unmanned aerial vehicle autopilot system during flying to obtain a first atmospheric pressure, and sending the first atmospheric pressure to the first atmospheric data processing device;
the first atmospheric data processing device is configured to: receiving the first atmospheric pressure and determining the first flying height according to the first atmospheric pressure.
4. The drone autopilot system of claim 1 further comprising a combined inertial navigation device (108);
the combined inertial navigation device (108) is connected with the first processor (102);
the combined inertial navigation device (108) is configured to: obtaining second positioning data and second flight state data, performing fusion calculation on the second positioning data and the second flight state data to obtain second navigation calculation data, and sending the second navigation calculation data to the first processor (102);
the first processor (102) is further configured to: and receiving the second navigation calculation data, and controlling the execution device (103) to realize flight according to the remote control instruction, the second navigation calculation data and the preset airline plan under the condition that the first navigation calculation data does not accord with the preset condition.
5. The drone autopilot system of claim 4 wherein the combined inertial navigation device (108) includes a second barometer, a second atmospheric data processing device, and an inertial navigation device.
6. The drone autopilot system of claim 5 wherein the second flight status data includes a second flight direction, a second flight deflection, a second flight velocity, a second flight acceleration, a second flight position, and a second flight altitude;
the inertial navigation device is used for: detecting the flight direction, the flight deflection, the flight position and the flight acceleration of the unmanned aerial vehicle autopilot system to obtain a second flight direction, a second flight deflection, a second flight position and a second flight acceleration;
the second barometer is to: detecting the atmospheric pressure of the unmanned aerial vehicle autopilot system during flying to obtain second atmospheric pressure, and sending the second atmospheric pressure to the second atmospheric data processing device;
the second atmospheric data processing device: for receiving the second barometric pressure and determining the second altitude based on the second barometric pressure.
7. The drone autopilot system of claim 1 further comprising system condition monitoring means (109);
the system state monitoring device (109) is connected with the first processor (102);
the system status monitoring device (109) is configured to: collecting state data of the unmanned aerial vehicle autopilot system, and sending the state data to the first processor (102), wherein the state data comprises at least one of oil mass data, temperature data and vibration data;
the first processor (102) is further configured to: and receiving the state data, and controlling the executive device (103) to realize flight according to the state data, the remote control command, the first navigation calculation data and the preset air route plan.
8. The drone autopilot system of claim 1 further comprising a load device (110);
the load device (110) is connected with the second processor (104);
the load device (110) is configured to: sending payload data to the second processor (104);
the second processor (104) is further configured to: receiving the load data, processing the load data to obtain processed load data, and sending the processed load data to the first processor (102);
the first processor (102) is further configured to: receiving the processed payload data and sending the processed payload data to the remote control device (107) via the data link (101);
the remote control device (107) is further configured to: receiving the processed payload data and sending a payload control instruction to the first processor (102) via the data link (101);
the first processor (102) is further configured to: receiving the load control instruction and sending the load control instruction to the second processor (104);
the second processor (104) is further configured to: receiving the load control command, and sending the load control command to the load equipment (110);
the load device (110) is configured to: and receiving the load control command, and executing a flight task according to the load control command.
9. The drone autopilot system of claim 1 wherein the drone autopilot system further includes a maintenance interface;
the second processor (104) is further configured to: and in the flight process of the unmanned aerial vehicle autopilot system, storing flight data of the unmanned aerial vehicle autopilot system, and sending the flight data to maintenance equipment through the maintenance interface after the unmanned aerial vehicle autopilot system stops flying.
10. The drone autopilot system of any one of claims 1 to 9 wherein the drone autopilot system further includes a power distribution module (111);
the power distribution module (111) is configured to: and supplying power to the unmanned aerial vehicle autopilot system.
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| CN114815903A (en) * | 2022-06-29 | 2022-07-29 | 沃飞长空科技(成都)有限公司 | Flight route visual display method and device, aircraft and storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114815903A (en) * | 2022-06-29 | 2022-07-29 | 沃飞长空科技(成都)有限公司 | Flight route visual display method and device, aircraft and storage medium |
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