CN111983936B - Unmanned aerial vehicle semi-physical simulation system and evaluation method - Google Patents
Unmanned aerial vehicle semi-physical simulation system and evaluation method Download PDFInfo
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- G—PHYSICS
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- G—PHYSICS
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
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Abstract
The application provides an unmanned aerial vehicle semi-physical simulation system and an evaluation method. The system comprises: an autopilot; analog data is stored; the simulation data comprise flight data and environment data of the unmanned aerial vehicle in a test scene; the semi-physical simulation platform is used for constructing a first aircraft model based on flight characteristic parameters; constructing a first simulation scene based on the test scene and/or the environmental data; and performing simulation test on the first aircraft model in the first simulation scene based on the flight track, thereby obtaining a simulation test result. In the embodiment of the application, when the simulation test of the unmanned aerial vehicle is performed through the semi-physical simulation system, the flight data input of the autopilot is acquired through the hardware interface, so that a first aircraft model is constructed and the simulation test is performed. Through the method, the actual flight state of the unmanned aerial vehicle can be effectively simulated, and further the flight control precision of the unmanned aerial vehicle can be accurately simulated and evaluated.
Description
Technical Field
The application relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle semi-physical simulation system and an evaluation method.
Background
Unmanned aerial vehicle is one of the core equipment that the industry realized intelligent manufacturing and upgrading, plays important role in a plurality of fields such as survey and drawing, intelligent production, intelligent agriculture.
However, the existing unmanned aerial vehicle has insufficient research on flight control performance and evaluation technologies (measuring equipment, detection and evaluation systems and the like) thereof, and especially has the key technical problems of detection, metering, authentication and the like in the development of unmanned aerial vehicle industry, and the like, which always face the dilemma of 'no detection, no detection precision' and the like, and influence the quality improvement and the application field expansion of unmanned aerial vehicles. In the existing mainstream test of unmanned aerial vehicles, the adopted semi-physical simulation system mostly defines a test object (simulation of parameters such as the gesture, the position and the speed of the unmanned aerial vehicle) directly through a software module in the system, and the real-time hardware measurement data access of a test site is lacking, so that the simulation system cannot reflect the actual flight state of the unmanned aerial vehicle, and further the detection of the unmanned aerial vehicle is affected.
Disclosure of Invention
The embodiment of the application aims to provide a semi-physical simulation system and an evaluation method of an unmanned aerial vehicle, so as to solve the problem that the test objects of the current semi-physical simulation system are mostly directly defined by software modules in the system, and the detection result of the unmanned aerial vehicle is affected.
The invention is realized in the following way:
in a first aspect, an embodiment of the present application provides an unmanned aerial vehicle semi-physical simulation system, including: an autopilot; analog data is stored; the simulation data comprise flight data and environment data of the unmanned aerial vehicle in a test scene; the flight data comprise flight characteristic parameters and flight tracks; the semi-physical simulation platform is connected with the autopilot through a hardware interface; the semi-physical simulation platform is used for constructing a first aircraft model based on the flight characteristic parameters; constructing a first simulation scene based on the test scene and/or the environmental data; and performing simulation test on the first aircraft model in the first simulation scene based on the flight track, so as to obtain a simulation test result.
In the embodiment of the application, when the simulation test of the unmanned aerial vehicle is performed through the semi-physical simulation system, the flight data input of the autopilot is acquired through the hardware interface, so that a first aircraft model is constructed and the simulation test is performed. Through the method, the actual flight state of the unmanned aerial vehicle can be effectively simulated, and further the flight control precision of the unmanned aerial vehicle can be accurately simulated and evaluated.
With reference to the foregoing technical solution of the first aspect, in some possible implementation manners, the semi-physical simulation platform includes a control module, where the control module is configured to control the first aircraft model during a simulation test of the first aircraft model.
With reference to the foregoing technical solution provided in the first aspect, in some possible implementation manners, the semi-physical simulation platform includes a feedback sensing module; the feedback perception module is used for evaluating the first aircraft model according to the test parameters of the first aircraft model and preset first evaluation parameters; the test parameters comprise attitude angle information, a flight path and obstacle avoidance parameters.
In the embodiment of the application, because the simulation test is performed based on the flight data input by the autopilot as the simulation data, the attitude angle information, the flight path and the obstacle avoidance parameters included in the test result are also in accordance with the actual conditions, and the accuracy of the evaluation result is further improved.
With reference to the foregoing technical solution provided in the first aspect, in some possible implementation manners, the preset first evaluation parameter includes a preset desired attitude angle; correspondingly, the feedback sensing module is used for comparing the attitude angle information with the preset expected attitude angle, and further evaluating the first aircraft model according to the comparison result.
In the embodiment of the application, the attitude angle information is compared with the preset expected attitude angle, so that effective quantitative evaluation of the first flight model can be realized.
With reference to the foregoing technical solution provided in the first aspect, in some possible implementation manners, the feedback sensing module is further configured to obtain a deviation value of the attitude angle based on a comparison result of the attitude angle information and the preset desired attitude angle; and adjusting the attitude of the first aircraft model by the deviation value.
In the embodiment of the application, the flight attitude of the unmanned aerial vehicle is updated, so that the follow-up simulation test of the first flight model after the attitude updating can be conveniently performed, and further the first flight model is analyzed and evaluated according to the simulation result.
With reference to the foregoing technical solution of the first aspect, in some possible implementation manners, the preset first evaluation parameter includes a preset flight path; correspondingly, the feedback sensing module is used for comparing the flight path with the preset flight path, and further evaluating the path planning capacity of the first aircraft model according to the comparison result.
In the embodiment of the application, the flight path is compared with the preset flight path, so that effective quantitative evaluation on the path track capacity of the first flight model can be realized.
With reference to the foregoing technical solution provided in the first aspect, in some possible implementation manners, the first evaluation parameter includes a preset obstacle avoidance duration, and correspondingly, the obstacle avoidance parameter includes an obstacle avoidance duration; the feedback sensing module is used for comparing the preset obstacle avoidance time length with the obstacle avoidance time length, and further evaluating the obstacle avoidance capacity of the first aircraft model according to the comparison result.
In the embodiment of the application, the flight path is compared with the preset flight path, so that effective quantitative evaluation on the path track capacity of the first flight model can be realized.
With reference to the foregoing technical solution provided in the first aspect, in some possible implementation manners, the first evaluation parameter includes a preset safety distance, and correspondingly, the obstacle avoidance parameter includes an obstacle avoidance distance; the feedback sensing module is used for comparing the preset safety distance with the obstacle avoidance distance, and further evaluating the safety obstacle avoidance capacity of the first aircraft model according to the comparison result.
In the embodiment of the application, the obstacle avoidance distance is compared with the preset safety distance, so that the effective quantitative evaluation of the safety obstacle avoidance capacity of the first flight model can be realized.
With reference to the foregoing technical solution provided in the first aspect, in some possible implementation manners, the unmanned aerial vehicle semi-physical simulation system further includes: the photoelectric test equipment is arranged in a ground station mode; the optoelectronic testing apparatus includes: imaging device, laser range finder and inertial measurement unit; the imaging device is used for detecting obstacles in the test scene and tracking the flight of the unmanned aerial vehicle so as to acquire a flight image of the unmanned aerial vehicle; the laser range finder is used for obtaining a first distance from the unmanned aerial vehicle; the inertial measurement unit is arranged on the imaging equipment and is used for measuring the real-time gesture of the imaging equipment; the semi-physical simulation platform is connected with the photoelectric test equipment and is used for acquiring the geographic position of the unmanned aerial vehicle, the speed of the unmanned aerial vehicle and the distance between the unmanned aerial vehicle and the obstacle in the test scene according to the flight image, the first distance and the real-time gesture, and constructing a second aircraft model according to the geographic position of the unmanned aerial vehicle, the speed of the unmanned aerial vehicle and the distance between the unmanned aerial vehicle and the obstacle in the test scene; and constructing a second simulation scene based on the test scene, and performing simulation test on the second aircraft model in the second simulation scene, thereby obtaining a simulation test result.
In the embodiment of the application, the semi-physical simulation platform can be used for inputting the data detected by the photoelectric test equipment as the flight data of the unmanned aerial vehicle, and constructing the second aircraft model and performing simulation test by the same.
In a second aspect, an embodiment of the present application provides an evaluation method, which is applied to the semi-physical simulation platform in the unmanned aerial vehicle semi-physical simulation system described in the above embodiment, where the unmanned aerial vehicle semi-physical simulation system further includes an autopilot, and the autopilot stores analog data; the simulation data comprise flight data and environment data of the unmanned aerial vehicle in a test scene; wherein, the flight data comprises flight characteristic parameters and flight tracks, and the method comprises the following steps: acquiring the flight characteristic parameters; constructing a first aircraft model based on the flight characteristic parameters, and performing simulation test on the first aircraft model in a first simulation scene based on the flight track to obtain a simulation test result; the first simulation scene is a scene constructed by the semi-physical simulation platform based on the test scene and/or the environment data.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a structural block diagram of a semi-physical simulation system of an unmanned aerial vehicle provided in an embodiment of the present application.
Fig. 2 is a structural block diagram of a semi-physical simulation platform according to an embodiment of the present application.
Fig. 3 is a schematic structural view of an attitude angle according to an embodiment of the present application.
Fig. 4 is a flowchart of steps of an evaluation method according to an embodiment of the present application.
Icon: 100-an unmanned aerial vehicle semi-physical simulation system; 10-autopilot; 20-a semi-physical simulation platform; 201-a processor; 202-memory; 203-a display.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
Referring to fig. 1, an embodiment of the present application provides a semi-physical simulation system 100 of an unmanned aerial vehicle, including: autopilot 10 and semi-physical simulation platform 20.
Wherein the autopilot 10 has analog data stored therein. The simulation data comprise flight data and environment data of the unmanned aerial vehicle in a test scene, and the flight data comprise flight characteristic parameters and flight tracks.
It should be noted that the autopilot 10 refers to a device that simulates the actions of a driver to perform unmanned aerial vehicle control. It consists of sensitive element, computer and executing mechanism. And the control surface is controlled to a required position by the actuating mechanism by calculating the corrected rudder deflection amount through the computer when the unmanned aerial vehicle deviates from the original gesture.
As an embodiment, the autopilot 10 is connected to an embedded hardware component (hereinafter, referred to as a photoelectric test device) required for a field test, such as a photoelectric test device, so that the autopilot 10 can acquire and store the above-mentioned flight data and environmental data. Flight characteristic parameters include, but are not limited to, attitude, direction, speed, acceleration, altitude, positioning of the unmanned aerial vehicle while in flight. Of course, the flight characteristic parameters may include a predetermined size, weight, type, function, use, and the like of the unmanned aerial vehicle. The environmental data includes geographical environment, weather, wind speed, environmental electromagnetic, obstructions, and the like. Optionally, the simulation data further includes hardware parameters of the autopilot 10, such as hardware interface parameters, sensor parameters, and the like, which are not limited in this application.
In other embodiments, the semi-physical simulation platform 20 may be connected to embedded hardware components required for field testing such as photoelectric testing equipment, and the simulation data in the autopilot may also be derived from data in standard, once similar real flight cases. The present application is not limited thereto.
The semi-physical simulation platform 20 is connected with the autopilot 10 through a hardware interface. Because of the variety of hardware development interfaces for autopilot 10, to enable data interworking between autopilot 10 and semi-physical simulation platform 20, the hardware interfaces may include, but are not limited to, data input/output interfaces such as multiple PWM (Pulse Width Modulation ) input/output, multiple motor control interfaces, data exchange interfaces such as RS-2202 interfaces and RS-485 interfaces, and the like.
Of course, the hardware components of the autopilot 10 may also include: a triaxial angular rate gyro, a double-mouth airspeed sensor, an barometer, a triaxial accelerometer, a triaxial magnetometer, a 10-20Hz GPS receiver, a temperature sensor, a plurality of RS-485 (ABIR protocol), a plurality of RS-2202 (NMEA protocol), an airspeed altitude combination sensor, an ultrasonic altimeter, a PWM signal and discrete signal expander, a flight data recorder, an oil quantity sensor, a GNSS (Global Navigation Satellite System ) receiver.
Structurally, referring to fig. 2, the semi-physical simulation platform 20 includes, in addition to hardware interfaces: a processor 201, a memory 202, and a display 203.
The processor 201 is electrically connected directly or indirectly to the memory 202 and the display 203 for data transmission or interaction, for example, the components may be electrically connected to each other through one or more communication buses or signal lines. The processor 201 is configured to execute an executable program stored in the memory 202, for example, the processor 201 obtains the flight characteristic parameter; and constructing a first aircraft model based on the flight characteristic parameters, and performing simulation test on the first aircraft model in a first simulation scene based on the flight track to obtain a simulation test result.
The processor 201 may be an integrated circuit chip with signal processing capabilities. The processor 201 may also be a general purpose processor, for example, a central processing unit (Central Processing Unit, CPU), digital signal processor (Digital Signal Processor, DSP), application specific integrated circuit (Application Specific Integrated Circuit, ASIC), discrete gate or transistor logic, discrete hardware components, and may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present application. Further, the general purpose processor may be a microprocessor or any conventional processor or the like.
The Memory 202 may be, but is not limited to, random access Memory (Random Access Memory, RAM), read Only Memory (ROM), programmable Read Only Memory (Programmable Read-Only Memory, PROM), erasable programmable Read Only Memory (Erasable Programmable Read-Only Memory, EPROM), and electrically erasable programmable Read Only Memory (Electric Erasable Programmable Read-Only Memory, EEPROM). The memory 202 is used for storing a program, and the processor 201 executes the program after receiving an execution instruction.
The display 203 may be, but is not limited to, a liquid crystal display, an LED (Light Emitting Diode ) display, an integrated display control platform, or the like. The display 203 is used to display the simulation process and the evaluation result.
The semi-physical simulation platform 20, upon receiving the flight data transmitted by the autopilot 10 via the hardware interface, builds a first aircraft module based on the flight characteristic parameters in the flight data. That is, parameters of the first aircraft model are defined based on parameters such as the attitude, the speed, the acceleration and the like of the unmanned aerial vehicle during flight, and then the first aircraft module simulating the unmanned aerial vehicle is constructed. A first simulated scene is then constructed based on the test scene and/or the environmental data. It should be noted that, constructing the first simulation scenario based on the test scenario and/or the environmental data includes three schemes: the first is to construct a first simulation scene based only on the test scene; the mode can be based on the same test data of the outdoor scene in the past, and then the same simulation scene is constructed. The mode can also be constructed by data of a scene acquired by various sensors (such as photoelectric test equipment), and can also be constructed based on a two-dimensional image or a three-dimensional image in the acquired scene. The second is to construct the first simulation scene based only on the environment data. That is, the approach builds the first simulation scenario by means of data integrated on the autopilot. And thirdly, constructing a first simulation scene by combining the test scene and the environment data. When the same simulation scene is constructed based on the environmental data, the map is not only simulated, but also the simulation scene can be constructed in combination with the geographic environment, weather, wind speed, environmental electromagnetism, obstacles and the like. After the first simulation scene is built, performing simulation test on the first aircraft model in the first simulation scene based on the flight track of the unmanned aerial vehicle, and further obtaining a simulation test result.
In the embodiment of the present application, when the simulation test of the unmanned aerial vehicle is performed by the semi-physical simulation system, the flight data input of the autopilot 10 is obtained through the hardware interface, so as to construct the first aircraft model and perform the simulation test. Through the method, the actual flight state of the unmanned aerial vehicle can be effectively simulated, and further the flight control precision of the unmanned aerial vehicle can be accurately simulated and evaluated.
The semi-physical simulation platform 20 further includes a control module, where the control module is configured to control the first aircraft model during the simulation test of the first aircraft model. The control module can include, but is not limited to, an operation switch, an emergency switch, a control panel, obstacle avoidance path optimization and selection, and the like.
Wherein the semi-physical simulation platform 20 includes a feedback awareness module. The feedback perception module is used for evaluating the first aircraft model according to the test parameters of the first aircraft model and preset first evaluation parameters. The test parameters include attitude angle information, flight path and obstacle avoidance parameters.
In the embodiment of the application, because the simulation test is performed based on the flight data input by the autopilot 10 as the simulation data, the attitude angle information, the flight path and the obstacle avoidance parameters included in the test result are also in accordance with the actual situation, so that the accuracy of the evaluation result is improved.
Optionally, the preset first evaluation parameter comprises a preset desired attitude angle. Correspondingly, the feedback sensing module is used for comparing the attitude angle information with a preset expected attitude angle, and further evaluating the first aircraft model according to the comparison result.
It should be noted that, the attitude angle of the unmanned aerial vehicle is defined according to the euler concept, so it is also called euler angle.
Specifically, referring to FIG. 3, the method is performed by the fixed point OFixed coordinate system Oxyz and coordinate system Ox ' y ' z ' fixedly connected to the first aircraft model. The axes Oz and Oz ' are taken as basic axes, and the vertical planes Oxy and Ox ' y ' thereof are taken as basic planes. The angle θ measured from the axis Oz to Oz' is referred to as the pitch angle. The perpendicular ON to plane zOz ' is referred to as the pitch line, which is in turn the intersection of the basic planes Ox ' y ' and Oxy. In the right hand coordinate system, the angle θ should be measured in a counter-clockwise direction, viewed from the positive end of ON. The angle ψ from the fixed axis Ox to the pitch line ON is called the heading angle, and the angle from the pitch line ON to the axis Ox' is called the heading angleKnown as roll angle. The angles ψ and +.>Are also measured in a counter-clockwise direction.
The attitude angle of the unmanned aerial vehicle can be represented by three Euler angles, namely a course angle, a pitch angle and a roll angle. Different rotation sequences form different coordinate transformation matrixes, and the spatial rotation of the machine body coordinate system relative to the geographic coordinate system is generally expressed in the sequence of course angle, pitch angle and roll angle. It is also understood that the attitude angle is the rotation angle of the drone about three coordinate axes (i.e., x-axis, y-axis, z-axis) of the coordinate system. Therefore, in the embodiment of the application, the flight control accuracy of the first aircraft model may be evaluated according to the attitude angle information.
The following examples illustrate, for example, when the first aircraft model sets a stable flight during the flight, the preset expected attitude angles are respectively: heading angle is 10 degrees, pitch angle is 10 degrees, roll angle is 10 degrees. And then evaluating the first aircraft model based on the deviation value of the obtained attitude angle information and a preset expected attitude angle. The evaluation of the first aircraft model can be divided into the following two classes:
1. fly control stability level: and when the deviation value of the attitude angle information and the preset expected attitude angle is smaller than the preset deviation value, the flight control performance of the first aircraft model is determined to be strong. The preset deviation value may be set to 2 °, 3 °, etc., which is not limited in this application, but specifically needs to be related according to the flying speed level.
2. Flight control fluctuation level: when the deviation value of the attitude angle information and the preset expected attitude angle is larger than the preset deviation value, the flight control stability of the first aircraft model is determined to be weaker.
It is understood that since the attitude angle includes the heading angle, the pitch angle, and the roll angle. Therefore, when the first aircraft model is evaluated, the first aircraft model may be evaluated as the flight control stability level when the deviation values of the three angles are smaller than the preset deviation value, and correspondingly, the first aircraft model may be evaluated as the flight control fluctuation level as long as the deviation value of one angle is smaller than the preset deviation value. Of course, the first aircraft model may be evaluated as a flight control stability level whenever the deviation value of the two angles is smaller than the preset deviation value. The present application is not limited thereto.
Further, since the first aircraft model is constructed based on the flight data transmitted from the autopilot 10, the evaluation of the first aircraft model is an evaluation of the unmanned aerial vehicle on which the autopilot 10 is mounted.
Alternatively, in other embodiments, the first evaluation parameter may include only one of a preset heading angle, a preset pitch angle, and a preset roll angle. For example, the first evaluation parameter only includes a preset course angle, and correspondingly, the feedback sensing module is used for comparing the course angle in the acquired gesture angle information with the preset course angle, calculating the deviation value of the course angle and the preset course angle, and further evaluating whether the unmanned aerial vehicle is yawed or not. Or the first evaluation parameters only comprise preset pitch angles, and correspondingly, the feedback sensing module is used for comparing the pitch angle in the acquired attitude angle information with the preset pitch angle, calculating deviation values of the pitch angle and the preset pitch angle, and further evaluating whether the unmanned aerial vehicle deflects or not. Or the first evaluation parameter only comprises a preset roll angle, and the feedback sensing module is correspondingly used for comparing the roll angle in the acquired attitude angle information with the preset roll angle, calculating the deviation value of the roll angle and the preset roll angle, and further evaluating whether the unmanned aerial vehicle rolls sideways. The present application is not limited thereto.
Optionally, an actuator (steering engine) is also included in the autopilot 10. And after the feedback sensing module acquires the deviation value, the feedback sensing module is further used for sending a gesture adjusting instruction to the execution mechanism through the hardware interface based on the deviation value, so that the execution mechanism updates the flight gesture of the unmanned aerial vehicle, and further updates the gesture of the first flight model.
In the embodiment of the application, the execution mechanism is enabled to update the flight attitude of the unmanned aerial vehicle by sending the attitude adjusting instruction to the execution mechanism, so that the simulation environment of hardware in the loop can be truly realized, and the result of performance analysis of the unmanned aerial vehicle is effectively improved.
Optionally, the preset first evaluation parameter comprises a preset flight path. Correspondingly, the feedback sensing module is used for comparing the flight path with a preset flight path, and further evaluating the first aircraft model according to the comparison result.
The preset flight path is an optimal flight path set by the unmanned aerial vehicle in the environment facing the obstacle. The feedback perception module can compare the flight path with a preset flight path, and then determine whether the flight path is an optimal flight path according to the comparison result, and the path planning capacity of the first aircraft model can be effectively evaluated through the method. As an implementation mode, the preset flight path can be extracted according to field information acquired by the photoelectric test equipment and through a big data deep learning method.
As an alternative embodiment, the path planning capability of the first aircraft model may be evaluated on the basis of the similarity of the flight path to the preset flight path. The evaluation of the first aircraft can also be classified into the following two classes:
1. route accuracy level: and when the similarity of the flight path and the preset flight path exceeds a similarity threshold, the path planning capability of the first aircraft model is determined to be strong. The similarity threshold may be 80%, 90%, etc., which is not limited in this application, but specifically needs to be related according to the type of the unmanned aerial vehicle.
2. Route deviation level: and when the similarity of the flight path and the preset flight path is lower than a similarity threshold value, the path planning capability of the first aircraft model is determined to be weak.
Optionally, presetting the first evaluation parameter includes: and presetting obstacle avoidance parameters. Correspondingly, the feedback sensing module is used for evaluating the obstacle avoidance capability of the first flight model according to the comparison result of the obstacle avoidance parameter and the preset obstacle avoidance parameter.
The preset obstacle avoidance parameter may be a preset obstacle avoidance duration, and the corresponding obstacle avoidance parameter also includes an obstacle avoidance duration in the simulation process. The feedback sensing module is used for comparing according to the obstacle avoidance time length and the preset obstacle avoidance time length, and further evaluating the obstacle avoidance capacity of the unmanned aerial vehicle according to the comparison result.
It can be understood that the obstacle avoidance time of the unmanned aerial vehicle is the total time consumption of the unmanned aerial vehicle for completing the task of avoiding the obstacle. The obstacle avoidance duration of the unmanned aerial vehicle and the preset obstacle avoidance duration can be used for evaluating the obstacle avoidance efficiency of the unmanned aerial vehicle. When the obstacle avoidance time of the unmanned aerial vehicle is smaller than the preset obstacle avoidance time, the unmanned aerial vehicle can be proved to have stronger obstacle avoidance capability; when the obstacle avoidance time of the unmanned aerial vehicle is longer than the preset obstacle avoidance time, the unmanned aerial vehicle can be indicated to have weaker avoidance capability. For example, when the preset avoidance time is 0.8 seconds and the obstacle avoidance time of the first aircraft model (corresponding to the unmanned aerial vehicle) is 0.7 seconds, the unmanned aerial vehicle can be proved to have stronger obstacle avoidance capability; when the obstacle avoidance time of the first aircraft model is 1.2 seconds, the unmanned aerial vehicle can be proved to have stronger obstacle avoidance capability. It should be noted that the above values are merely exemplary values, and the present application is not limited thereto.
The preset obstacle avoidance parameter may also be a preset safety distance. The preset safety distance may be understood as a preset relative safety distance between the unmanned aerial vehicle and the obstacle. For example, the preset safe distance may be 5 meters, 8 meters, 12 meters, etc. Correspondingly, the obstacle avoidance parameters also comprise the obstacle avoidance distance in the simulation process. The safety obstacle avoidance capability of the unmanned aerial vehicle can be evaluated through a preset safety distance. For example, when the obstacle avoidance distance of the unmanned aerial vehicle is smaller than the pre-safety distance, the safety obstacle avoidance capability of the unmanned aerial vehicle can be indicated to be weaker; when the obstacle avoidance distance of the unmanned aerial vehicle is larger than the preset safety distance, the unmanned aerial vehicle can be proved to have stronger safety obstacle avoidance capability. For example, when the preset safety distance is 10 meters and the obstacle avoidance distance of the first aircraft model (corresponding to the unmanned aerial vehicle) is 11 meters, the unmanned aerial vehicle can be proved to have stronger safety obstacle avoidance capability; when the obstacle avoidance distance of the first aircraft model is 6 meters, the unmanned aerial vehicle can be indicated to have weak safety obstacle avoidance capability. It should be noted that the above values are merely exemplary values, and the present application is not limited thereto.
In the embodiment of the present application, the unmanned aerial vehicle semi-physical simulation system 100 further includes: the optoelectronic test equipment is arranged in the form of a ground station. The photoelectric test apparatus includes: imaging device, laser range finder and inertial measurement unit.
The imaging device is used for detecting obstacles in the test scene and tracking the flight of the unmanned aerial vehicle, so that a flight image of the unmanned aerial vehicle is obtained. The laser range finder is used for obtaining the first distance with unmanned aerial vehicle. The inertial measurement unit is disposed on the imaging device for measuring a real-time pose of the imaging device.
The test scene can be a scene built in a laboratory, and the test scene can be correspondingly built according to requirements, such as a forest model, a city model and the like. Different weather effects, such as a rainy day effect, a snowy day effect, a strong wind effect and the like, can be further arranged in the test scene, and more diversified conditions are provided for the test of the unmanned aerial vehicle through different types of test scenes, so that the flight control performance of the unmanned aerial vehicle in different scenes can be conveniently evaluated.
The imaging device described above may be, but is not limited to, a visible light camera, a thermal infrared imager.
The semi-physical simulation platform 20 may be connected to the above-mentioned optoelectronic test apparatus through a hardware interface, that is, the semi-physical simulation platform 20 is connected to the imaging apparatus, the laser rangefinder, and the inertial measurement unit through hardware interfaces, respectively. The semi-physical simulation platform 20 is used for acquiring the geographic position of the unmanned aerial vehicle, the speed of the unmanned aerial vehicle and the distance between the unmanned aerial vehicle and the obstacle in the test scene according to the flight image, the first distance and the real-time gesture, and further constructing a second aircraft model based on the geographic position of the unmanned aerial vehicle, the speed of the unmanned aerial vehicle and the distance between the unmanned aerial vehicle and the obstacle in the test scene. And performing simulation test on the second aircraft model in the second simulation scene to obtain a simulation test result. Wherein the second simulation scenario is constructed based on the test scenario.
It should be noted that, the flight track of the unmanned aerial vehicle can be determined through the geographic positions of the unmanned aerial vehicle at different moments, and then the second aircraft model is subjected to simulation test in the second simulation scene according to the flight track of the unmanned aerial vehicle, so as to obtain a simulation test result. The speed of the unmanned aerial vehicle can be obtained according to the geographic positions of the unmanned aerial vehicle at different time points. The distance between the unmanned aerial vehicle and the obstacle in the test scene can be obtained according to the measurement data of the laser range finder and the inertial measurement unit.
In this embodiment of the present application, the semi-physical simulation platform 20 may be used as flight data input of the unmanned aerial vehicle based on data detected by the photoelectric test device, and construct a second aircraft model and perform a simulation test with the data input of the unmanned aerial vehicle.
In addition, when the simulation is carried out in the mode, the perception and obstacle avoidance capability of the unmanned aerial vehicle can be accurately evaluated. At this time, a distribution principle of feasibility and a threshold weight need to be established for quantitative evaluation. Such as setting a perceived static obstacle parameter, a perceived dynamic obstacle parameter, and an obstacle avoidance response characteristic parameter.
The sensing static obstacle parameters comprise a preset safety distance between the unmanned aerial vehicle and the static obstacle and a preset safety relative height between the unmanned aerial vehicle and the static obstacle. Accordingly, the semi-physical simulation platform 20 is configured to evaluate the perceived evasive ability of the unmanned aerial vehicle to perceive a static obstacle according to the geographic location of the unmanned aerial vehicle, the distance between the unmanned aerial vehicle and the obstacle in the test scene, and the perceived static obstacle parameter.
The perceived movement obstacle parameter comprises a preset safety distance between the unmanned aerial vehicle and the movement obstacle, a preset safety relative height between the unmanned aerial vehicle and the movement obstacle and a preset safety relative speed between the unmanned aerial vehicle and the movement obstacle. Correspondingly, the semi-physical simulation platform 20 is configured to evaluate a perceived evasive ability of the unmanned aerial vehicle to perceive a dynamic obstacle according to a geographic location of the unmanned aerial vehicle, a speed of the unmanned aerial vehicle, a distance between the unmanned aerial vehicle and the obstacle in the test scene, and perceived movement obstacle parameters.
Wherein, keep away barrier response characteristic parameter includes: the method comprises the steps of presetting a safety relative distance between the unmanned aerial vehicle and an obstacle, presetting a safety relative height difference between the unmanned aerial vehicle and the obstacle, presetting a safety relative speed between the unmanned aerial vehicle and the obstacle and presetting a safety response time between the unmanned aerial vehicle and the obstacle. The preset safety response time is the quotient of the preset safety relative distance between the unmanned aerial vehicle and the obstacle and the preset safety relative speed between the unmanned aerial vehicle and the obstacle. Correspondingly, the semi-physical simulation platform 20 is used for evaluating the perception evasion capability of the unmanned aerial vehicle according to the geographic position of the unmanned aerial vehicle, the speed of the unmanned aerial vehicle, the distance between the unmanned aerial vehicle and the obstacle in the test scene and the obstacle avoidance response characteristic parameters.
In the embodiment of the application, a further evaluation method is provided, and the evaluation of the open outdoor airspace scene is performed on the unmanned aerial vehicle in real flight in a laboratory environment. The open outdoor airspace scene is the first constructed simulation scene. That is, the evaluation method is to evaluate the normal flight state of the unmanned aerial vehicle in the outdoor airspace in a limited laboratory environment. That is, in the above embodiment, the second aircraft model simulates the flight of the unmanned aerial vehicle in the indoor environment, and the first aircraft model simulates the flight of the unmanned aerial vehicle in the outdoor environment. The flight data of the unmanned aerial vehicle in the outdoor environment can be simulated through the first aircraft model, and the flight data of the autopilot can be updated.
Referring to fig. 4, based on the same inventive concept, the embodiment of the present application further provides an evaluation method applied to the semi-physical simulation platform 20 in the unmanned aerial vehicle semi-physical simulation system 100 in the above embodiment. The method comprises the following steps: step S101 to step S102.
Step S101: and acquiring the flight characteristic parameters.
Step S102: constructing a first aircraft model based on the flight characteristic parameters, and performing simulation test on the first aircraft model in a first simulation scene based on the flight track to obtain a simulation test result; the first simulation scene is a scene constructed by the semi-physical simulation platform based on the test scene and/or the environment data.
It should be noted that the above method steps have been described in the embodiments of the unmanned aerial vehicle perception evasion capability assessment system. In order to avoid redundancy, the description is not repeated here, and the same parts are referred to each other.
Based on the same inventive concept, the embodiments of the present application also provide a storage medium having stored thereon a semi-physical simulation platform, a computer program for measurement evaluation, which when executed performs the method provided in the above embodiments.
The storage medium may be any available medium that can be accessed by a computer or a data storage device comprising one or more servers, data centers, cloud storage, etc. integrated with the available medium. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid State Disk (SSD)), etc.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be another division manner in actual implementation, and for example, multiple units or components may be combined or may be integrated into another subsystem, and may be an embedded data unit, etc., or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
Furthermore, functional modules in various embodiments of the present application may be integrated together to form a single portion, or each module may exist alone, or two or more modules may be integrated to form a single portion.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The foregoing is merely exemplary embodiments of the present application and is not intended to limit the scope of the present application, and various modifications and variations may be suggested to one skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.
Claims (9)
1. An unmanned aerial vehicle semi-physical simulation system, comprising:
the autopilot stores analog data; the simulation data comprise flight data and environment data of the unmanned aerial vehicle in a test scene; the flight data comprise flight characteristic parameters and flight tracks;
the semi-physical simulation platform is connected with the autopilot through a hardware interface; the semi-physical simulation platform is used for constructing a first aircraft model based on the flight characteristic parameters; constructing a first simulation scene based on the test scene and/or the environmental data; performing simulation test on the first aircraft model in the first simulation scene based on the flight track, and further obtaining a simulation test result;
the unmanned aerial vehicle semi-physical simulation system further comprises: the photoelectric test equipment is arranged in a ground station mode; the optoelectronic testing apparatus includes: the semi-physical simulation platform is respectively connected with the imaging device, the laser range finder and the inertia measurement unit through the hardware interface; the imaging device is used for detecting obstacles in the test scene and tracking the flight of the unmanned aerial vehicle so as to acquire a flight image of the unmanned aerial vehicle; the laser range finder is used for obtaining a first distance from the unmanned aerial vehicle; the inertial measurement unit is arranged on the imaging equipment and is used for measuring the real-time gesture of the imaging equipment; the semi-physical simulation platform is connected with the photoelectric test equipment and is used for acquiring the geographic position of the unmanned aerial vehicle, the speed of the unmanned aerial vehicle and the distance between the unmanned aerial vehicle and the obstacle in the test scene according to the flight image, the first distance and the real-time gesture, and constructing a second aircraft model according to the geographic position of the unmanned aerial vehicle, the speed of the unmanned aerial vehicle and the distance between the unmanned aerial vehicle and the obstacle in the test scene; and constructing a second simulation scene based on the test scene, and performing simulation test on the second aircraft model in the second simulation scene, thereby obtaining a simulation test result.
2. The unmanned aerial vehicle semi-physical simulation system of claim 1, wherein the semi-physical simulation platform comprises a control module for controlling the first aircraft model during a simulation test of the first aircraft model.
3. The unmanned aerial vehicle semi-physical simulation system of claim 1, wherein the semi-physical simulation platform comprises a feedback perception module; the feedback perception module is used for evaluating the first aircraft model according to the test parameters of the first aircraft model and preset first evaluation parameters; the test parameters comprise attitude angle information, a flight path and obstacle avoidance parameters.
4. The unmanned aerial vehicle semi-physical simulation system of claim 3, wherein the preset first evaluation parameter comprises a preset desired attitude angle; correspondingly, the feedback sensing module is used for comparing the attitude angle information with the preset expected attitude angle, and further evaluating the first aircraft model according to the comparison result.
5. The unmanned aerial vehicle semi-physical simulation system of claim 4, wherein the feedback perception module is further configured to obtain a deviation value of the attitude angle based on a comparison result of the attitude angle information and the preset expected attitude angle; and adjusting the attitude of the first aircraft model by the deviation value.
6. The unmanned aerial vehicle semi-physical simulation system of claim 3, wherein the preset first evaluation parameter comprises a preset flight path; correspondingly, the feedback sensing module is used for comparing the flight path with the preset flight path, and further evaluating the path planning capacity of the first aircraft model according to the comparison result.
7. The unmanned aerial vehicle semi-physical simulation system of claim 3, wherein the first evaluation parameter comprises a preset obstacle avoidance time period, and correspondingly, the obstacle avoidance parameter comprises an obstacle avoidance time period; the feedback sensing module is used for comparing the preset obstacle avoidance time length with the obstacle avoidance time length, and further evaluating the obstacle avoidance capacity of the first aircraft model according to the comparison result.
8. The unmanned aerial vehicle semi-physical simulation system of claim 3, wherein the first evaluation parameter comprises a preset safety distance, and correspondingly, the obstacle avoidance parameter comprises an obstacle avoidance distance; the feedback sensing module is used for comparing the preset safety distance with the obstacle avoidance distance, and further evaluating the safety obstacle avoidance capacity of the first aircraft model according to the comparison result.
9. An evaluation method, which is characterized in that the evaluation method is applied to the semi-physical simulation platform in the unmanned aerial vehicle semi-physical simulation system according to claim 1, wherein the unmanned aerial vehicle semi-physical simulation system further comprises an autopilot, and the autopilot stores simulation data; the simulation data comprise flight data and environment data of the unmanned aerial vehicle in a test scene; wherein, the flight data comprises flight characteristic parameters and flight tracks, and the method comprises the following steps:
acquiring the flight characteristic parameters;
constructing a first aircraft model based on the flight characteristic parameters, and performing simulation test on the first aircraft model in a first simulation scene based on the flight track to obtain a simulation test result; the first simulation scene is a scene constructed by the semi-physical simulation platform based on the test scene and/or the environment data.
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| CN113009935B (en) * | 2021-05-24 | 2021-09-10 | 北京三快在线科技有限公司 | Unmanned aerial vehicle simulation test system and method and unmanned aerial vehicle flight controller |
| CN113448349A (en) * | 2021-06-07 | 2021-09-28 | 山东省中通物联网有限公司 | Flight control method and system of multi-dimensional situation perception automatic control algorithm |
| CN113625595A (en) * | 2021-08-02 | 2021-11-09 | 中国人民解放军军事科学院国防科技创新研究院 | Unmanned aerial vehicle deduction and fault diagnosis method and system |
| CN113867178B (en) * | 2021-10-26 | 2022-05-31 | 哈尔滨工业大学 | Virtual and real migration training system for multi-robot confrontation |
| CN117075496A (en) * | 2023-09-18 | 2023-11-17 | 广东昊一航空科技有限公司 | Unmanned aerial vehicle square matrix operation simulation system |
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