CN111983936A - Semi-physical simulation system and evaluation method for unmanned aerial vehicle - Google Patents
Semi-physical simulation system and evaluation method for unmanned aerial vehicle Download PDFInfo
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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 are stored; the simulation data comprises 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 the flight characteristic parameters; constructing a first simulation scene based on the test scene and/or the environmental data; and carrying out simulation test on the first aircraft model in the first simulation scene based on the flight track, and further 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 the first aircraft model is constructed and the simulation test is performed. Through this mode, can effectual simulation simulate out the actual flight state of unmanned aerial vehicle, and then can be accurate carry out the simulation aassessment to unmanned aerial vehicle's flight control precision.
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 industry realized intelligence and makes the upgrading, plays important role in a plurality of fields such as survey and drawing, intelligent production, wisdom agriculture.
However, currently, research on flight control performance and evaluation technologies (measuring equipment, detection and evaluation systems and the like) of the unmanned aerial vehicle is insufficient, and especially key technical problems such as detection, metering, authentication and the like in the industrial development of the unmanned aerial vehicle always face dilemmas such as 'undetected state, undetected state and inaccurate detection', and quality improvement and application field expansion of the unmanned aerial vehicle are influenced. In the test to unmanned aerial vehicle of current mainstream, the semi-physical simulation system of adoption, its test object (the simulation of the attitude of unmanned aerial vehicle, position, speed isoparametric is big much) is mostly directly to it through the software module in the system to define, lacks the real-time hardware measured data access of test scene, leads to the actual flight state of simulation system can not reflect unmanned aerial vehicle, and then the influence is to unmanned aerial vehicle's detection.
Disclosure of Invention
An object of the embodiment of the application is to provide an unmanned aerial vehicle semi-physical simulation system and an evaluation method, so as to improve the problem that most of test objects of the existing semi-physical simulation system are directly defined by software modules in the system, and the detection result of the unmanned aerial vehicle is influenced.
The invention is realized by the following steps:
in a first aspect, an embodiment of the present application provides an unmanned aerial vehicle semi-physical simulation system, including: an autopilot; analog data are stored; the simulation data comprise flight data and environment data of the unmanned aerial vehicle in a test scene; the flight data comprises flight characteristic parameters and flight tracks; the semi-physical simulation platform is connected with the automatic pilot 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 scenario based on the test scenario and/or the environmental data; and carrying out simulation test on the first aircraft model in the first simulation scene based on the flight track, and further 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 the first aircraft model is constructed and the simulation test is performed. Through this mode, can effectual simulation simulate out the actual flight state of unmanned aerial vehicle, and then can be accurate carry out the simulation aassessment to unmanned aerial vehicle's flight control precision.
With reference to the technical solution provided by the first aspect, in some possible implementation manners, the semi-physical simulation platform includes a control module, and the control module is configured to control the first aircraft model in a simulation test process of the first aircraft model.
With reference to the technical solution provided by 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, flight paths 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 parameter included in the test result are also in accordance with the actual attitude angle information, the flight path and the obstacle avoidance parameter, and the accuracy of the evaluation result is further improved.
With reference to the technical solution provided by the first aspect, in some possible implementation manners, the preset first evaluation parameter includes a preset expected attitude angle; correspondingly, the feedback sensing module is used for comparing the attitude angle information with the preset expected attitude angle, and then evaluating the first aircraft model according to a comparison result.
In the embodiment of the application, by comparing the attitude angle information with the preset expected attitude angle, the effective quantitative evaluation of the first flight model can be realized.
With reference to the technical solution provided by 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 between the attitude angle information and the preset expected attitude angle; and adjusting the attitude of the first aircraft model through the deviation value.
In this application embodiment, through updating unmanned aerial vehicle's flight gesture, can be convenient for follow-up to the simulation test that carries out of the first flight model after the update gesture, and then carry out the analysis and evaluation to first flight model according to the simulation result.
With reference to the technical solution provided by 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 then evaluating the path planning capability 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 capability of the first flight model can be realized.
With reference to the technical solution provided by 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 then 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 capability of the first flight model can be realized.
With reference to the technical solution provided by 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 safe distance with the obstacle avoidance distance, and then evaluating the safe obstacle avoidance capability 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 safe distance, so that the safe obstacle avoidance capability of the first flight model can be effectively and quantitatively evaluated.
With reference to the technical solution provided by the first aspect, in some possible implementation manners, the semi-physical simulation system for an unmanned aerial vehicle further includes: the photoelectric test equipment is arranged in a ground station form; the optoelectronic test device comprises: the device comprises an imaging device, a laser range finder and an inertia measuring 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 acquiring a first distance from the unmanned aerial vehicle; the inertial measurement unit is arranged on the imaging equipment and used for measuring the real-time attitude of the imaging equipment; the semi-physical simulation platform is connected with the photoelectric test equipment and 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 an obstacle in the test scene according to the flight image, the first distance and the real-time attitude, 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 to further obtain a simulation test result.
In this application embodiment, semi-physical simulation platform can be based on the data that photoelectric test equipment detected as unmanned aerial vehicle's flight data input to construct the second aircraft model and carry out the emulation test with this, through this mode, can effectually carry out the simulation to the unmanned aerial vehicle in testing, and effectual emulation simulates out the actual flight state of the unmanned aerial vehicle in testing, and then has improved the aassessment of unmanned aerial vehicle's flight control precision.
In a second aspect, an embodiment of the present application provides an evaluation method, which is applied to a semi-physical simulation platform in a semi-physical simulation system of an unmanned aerial vehicle as described in the above embodiments, where the semi-physical simulation system of the unmanned aerial vehicle further includes an autopilot, and analog data is stored in the autopilot; 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, 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 trajectory to obtain a simulation test result; wherein the first simulation scenario is a scenario constructed by the semi-physical simulation platform based on the test scenario and/or the environmental data.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used 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 therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a block diagram of a semi-physical simulation system of an unmanned aerial vehicle according to an embodiment of the present application.
Fig. 2 is a block diagram of a semi-physical simulation platform according to an embodiment of the present disclosure.
Fig. 3 is a schematic structural diagram of an attitude angle according to an embodiment of the present application.
Fig. 4 is a flowchart illustrating steps of an evaluation method according to an embodiment of the present application.
Icon: 100-unmanned aerial vehicle semi-physical simulation system; 10-autopilot; 20-a semi-physical simulation platform; 201-a processor; 202-a memory; 203-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 an unmanned aerial vehicle semi-physical simulation system 100, including: an autopilot 10 and a semi-physical simulation platform 20.
The autopilot 10 stores therein simulation data. 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 for unmanned aerial vehicle control. It is composed of sensitive element, computer and executing mechanism. The unmanned aerial vehicle is matched with other navigation equipment to complete a specified flight task, when the unmanned aerial vehicle deviates from the original attitude, the sensing element detects the change, the computer calculates the corrected rudder deflection, and the actuating mechanism steers the rudder surface to a required position.
As an embodiment, the autopilot 10 is connected to an embedded hardware component (where the optoelectronic testing device is described later) required for field testing, such as an optoelectronic testing device, so that the autopilot 10 can acquire and store the flight data and the environment data. Flight characteristic parameters include, but are not limited to, attitude, direction, velocity, acceleration, altitude, positioning of the drone while in flight. Of course, the flight characteristic parameters may also include the size, weight, type, function, and usage of the preset drone. Environmental data includes geographic environment, weather, wind speed, environmental electromagnetism, obstacles, and the like. Optionally, the simulation data further includes hardware parameters of the autopilot 10 itself, such as hardware interface parameters, sensor parameters, and the like, which is not limited in this application.
In other embodiments, the semi-physical simulation platform 20 may be connected to embedded hardware components required for field tests such as a photoelectric test device, and the simulation data in the autopilot may also be derived from data in a standard, once similar real flight case. The present application is also not limited thereto.
The semi-physical simulation platform 20 is connected to the autopilot 10 through a hardware interface. Due to the diversification of the hardware development interfaces of the autopilot 10, in order to realize the data intercommunication between the autopilot 10 and the semi-physical simulation platform 20, the hardware interfaces may include, but are not limited to, data input/output interfaces, such as a multi-channel PWM (Pulse Width Modulation) input/output interface, a multi-channel motor control interface, and data exchange interfaces, such as an RS-2202 interface and an RS-485 interface.
Of course, the hardware components of the autopilot 10 may also include: the device comprises a three-axis angular rate gyroscope, a double-mouth airspeed sensor, an air pressure altimeter, a three-axis accelerometer, a three-axis 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 combined sensor, an ultrasonic altimeter, a PWM signal and discrete signal expander, a flight data recorder, an oil mass sensor and a GNSS (Global Navigation Satellite System) receiver.
Structurally, referring to fig. 2, the semi-physical simulation platform 20 includes, in addition to the hardware interface: a processor 201, a memory 202, and a display 203.
The processor 201 is electrically connected to the memory 202 and the display 203 directly or indirectly to transmit or interact data, for example, the components can 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 carrying out simulation test on the first aircraft model in a first simulation scene based on the flight trajectory to obtain a simulation test result.
The processor 201 may be an integrated circuit chip having signal processing capabilities. The Processor 201 may also be a general-purpose Processor, for example, a Central Processing Unit (CPU), a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a discrete gate or transistor logic device, or a discrete hardware component, which can implement or execute the methods, steps, and logic blocks disclosed in the embodiments of the present Application. Further, a general purpose processor may be a microprocessor or any conventional processor or the like.
The Memory 202 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), and an electrically Erasable Programmable Read-Only Memory (EEPROM). The memory 202 is used for storing a program, and the processor 201 executes the program after receiving the execution instruction.
The display 203 may be, but is not limited to, a liquid crystal display, a LED (Light Emitting Diode) display, an integrated display and control platform, and the like. The display 203 is used for displaying the simulation process and the evaluation result.
After receiving the flight data transmitted by the autopilot 10 through the hardware interface, the semi-physical simulation platform 20 constructs 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 the attitude, speed, acceleration and other parameters of the unmanned aerial vehicle during flight, and then a first aircraft module simulating the unmanned aerial vehicle is constructed. A first simulation scenario is then constructed based on the test scenario 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 method is to construct a first simulation scene based on a test scene only; the method can be used for constructing the same simulation scene according to the same test data of the previous outdoor scene. The method can also be constructed by data of a scene collected by various sensors (such as photoelectric testing equipment), and can also be constructed based on a two-dimensional image or a three-dimensional image in the collected scene. The second is to construct a first simulated scene based only on environmental data. That is, this approach builds a first simulated scene with the aid of data integrated on the autopilot. And the third method is to combine the test scene and the environmental data to construct the first simulation scene. When the same simulation scene is constructed based on the environmental data, the simulation scene can be constructed by combining the geographic environment, the weather, the wind speed, the environmental electromagnetism, the obstacles and the like, as well as the map. After the first simulation scene is built, a simulation test is carried out on the first aircraft model in the first simulation scene based on the flight track of the unmanned aerial vehicle, and then a simulation test result is obtained.
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 10 is acquired through the hardware interface, so that the first aircraft model is constructed and the simulation test is performed. Through this mode, can effectual simulation simulate out the actual flight state of unmanned aerial vehicle, and then can be accurate carry out the simulation aassessment to unmanned aerial vehicle's flight control precision.
The semi-physical simulation platform 20 further includes a control module, and the control module is configured to control the first aircraft model in a simulation test process of the first aircraft model. The control module may include, but is not limited to, an operation switch, an emergency switch, a control panel, and obstacle avoidance path optimization and selection.
Wherein the semi-physical simulation platform 20 comprises 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, flight paths and obstacle avoidance parameters.
In the embodiment of the present 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 parameter included in the test result also conform to the reality, and the accuracy of the evaluation result is further 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 then evaluating the first aircraft model according to the comparison result.
It should be noted that the attitude angle of the drone is defined according to the euler concept, and is also called euler angle.
Specifically, referring to fig. 3, a fixed coordinate system Oxyz and a coordinate system Ox ' y ' z ' attached to the first model of the aircraft are defined by the fixed point O. The axes Oz and Oz ' are taken as basic axes, and the vertical planes Oxy and Ox ' y ' are taken as basic planes. The angle θ from the axis Oz to Oz' is called the pitch angle. The perpendicular ON to the plane zOz ' is called the pitch line, which in turn is the intersection of the base planes Ox ' y ' and Oxy. In the right-hand coordinate system, the angle θ should be measured in the counterclockwise direction, as viewed from the positive end of the ON. The angle ψ measured 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 moving axis Ox
Referred to as roll angle. Viewed from the positive end of the axes Oz and Oz', the angles ψ and
are also all measured in a counter clockwise direction.
The attitude angle of the unmanned aerial vehicle can be represented by three Euler angles of a course angle, a pitch angle and a roll angle. Different rotation sequences form different coordinate transformation matrices, and the spatial rotation of the body coordinate system with respect to the geographic coordinate system is usually expressed in the order of heading angle, pitch angle, and roll angle. It can also be understood that the attitude angle is the rotation angle of the drone around three coordinate axes (i.e. x-axis, y-axis, z-axis) of the coordinate system. Therefore, in the embodiment of the present application, the flight control accuracy of the first aircraft model can be evaluated according to the attitude angle information.
For example, when the first aircraft model sets a smooth flight during flight, the preset expected attitude angles are respectively: the course angle is 10 degrees, the pitch angle is 10 degrees and the roll angle is 10 degrees. And then evaluating the first aircraft model based on a deviation value between the acquired attitude angle information and a preset expected attitude angle. The evaluation of the first aircraft model can be classified into the following two levels:
1. flight 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, determining that the flight control performance of the first aircraft model is strong. The preset deviation value may be set to 2 °, 3 °, and the like, and the preset deviation value is not limited in the present application, but specifically needs to be associated according to the flight speed class.
2. Flight control fluctuation level: and when the deviation value of the attitude angle information and the preset expected attitude angle is larger than the preset deviation value, determining that the flight control stability of the first aircraft model is weaker.
It is understood that since the attitude angle includes a heading angle, a pitch angle, and a roll angle. Therefore, when the first aircraft model is evaluated, the first aircraft model may be evaluated as a flight control stability level when the deviation values of all three angles are smaller than the preset deviation value, and correspondingly, the first aircraft model may be evaluated as a 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 the flight control stability level as long as the deviation value of two angles is smaller than the preset deviation value. The present application is not limited thereto.
In addition, since the first aircraft model is constructed based on the flight data transmitted by the autopilot 10, the evaluation of the first aircraft model is an evaluation of the drone 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 configured to compare the course angle in the acquired attitude angle information with the preset course angle, calculate a deviation value between the course angle and the preset course angle, and further evaluate whether the unmanned aerial vehicle is yawing. Or only including the preset pitch angle in the first evaluation parameter, correspondingly, the feedback perception module is used for comparing the pitch angle in the acquired attitude angle information with the preset pitch angle, calculating the deviation value of the pitch angle and the preset pitch angle, and then evaluating whether the unmanned aerial vehicle deviates. Or the first evaluation parameter only includes a preset roll angle, and correspondingly, the feedback sensing module is used for comparing the roll angle in the acquired attitude angle information with the preset roll angle, calculating a deviation value of the roll angle and the preset roll angle, and further evaluating whether the unmanned aerial vehicle rolls laterally. The present application is not limited thereto.
Optionally, an actuator (steering engine) is also included in the autopilot 10. After the feedback sensing module obtains the deviation value, the feedback sensing module is further used for sending an attitude adjusting instruction to the executing mechanism through the hardware interface based on the deviation value, so that the executing mechanism updates the flight attitude of the unmanned aerial vehicle, and further updates the attitude of the first flight model.
In the embodiment of the application, the attitude adjusting instruction is sent to the executing mechanism, so that the executing mechanism updates the flight attitude of the unmanned aerial vehicle, the hardware-in-the-loop simulation environment 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 then evaluating the first aircraft model according to the comparison result.
It should be noted that the preset flight path is an optimal flight path set by the unmanned aerial vehicle in an environment facing an obstacle. The feedback sensing module can determine whether the flight path is the optimal flight path according to the comparison result by comparing the flight path with the preset flight path, and the path planning capability of the first aircraft model can be effectively evaluated by the method. As an implementation mode, the preset flight path can be extracted through a big data deep learning method according to the field information collected by the photoelectric testing equipment.
As an alternative embodiment, the path planning capability of the first aircraft model may be evaluated according to the similarity between the flight path and the preset flight path. The evaluation of the first aircraft may also be classified into the following two levels:
1. route accuracy level: and when the similarity between the flight path and the preset flight path exceeds a similarity threshold value, determining that the path planning capability of the second aircraft model is strong. The similarity threshold may be 80%, 90%, and the like, and the method is not limited in this application, but specifically needs to be associated according to the type of the unmanned aerial vehicle.
2. Route deviation level: and when the similarity between the flight path and the preset flight path is lower than the similarity threshold value, determining that the path planning capacity of the second aircraft model is weak.
Optionally, the presetting of 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 parameters and the preset obstacle avoidance parameters.
The preset obstacle avoidance parameter may be a preset obstacle avoidance duration, and correspondingly, the obstacle avoidance parameter also includes an obstacle avoidance duration in the simulation process. The feedback sensing module is used for comparing the obstacle avoidance time length with the preset obstacle avoidance time length, and then evaluating the obstacle avoidance capacity of the unmanned aerial vehicle according to the comparison result.
It can be understood that the obstacle avoidance duration of the unmanned aerial vehicle is the total time consumed for the unmanned aerial vehicle to complete the obstacle avoidance task. The obstacle avoidance time length of the unmanned aerial vehicle and the preset obstacle avoidance time length can be used for evaluating the obstacle avoidance efficiency of the unmanned aerial vehicle. When the obstacle avoidance duration of the unmanned aerial vehicle is less than the preset obstacle avoidance duration, the obstacle avoidance capability of the unmanned aerial vehicle is strong; when the obstacle avoidance duration of the unmanned aerial vehicle is longer than the preset obstacle avoidance duration, it can be shown that the avoidance capability of the unmanned aerial vehicle is weaker. For example, when the preset avoidance duration is 0.8 second and the obstacle avoidance time of the first aircraft model (corresponding to the unmanned aerial vehicle) is 0.7 second, it can be said that the obstacle avoidance capability of the unmanned aerial vehicle is strong; when the obstacle avoidance time of the first aircraft model is 1.2 seconds, it can be shown that the obstacle avoidance capability of the unmanned aerial vehicle is strong. The above numerical values are merely exemplary values, and the present application is not limited thereto.
The preset obstacle avoidance parameter can also be a preset safety distance. Wherein, predetermine safe distance and can understand the relative safe distance of presetting between unmanned aerial vehicle and the barrier. For example, the preset safety distance may be 5 meters, 8 meters, 12 meters, etc. Correspondingly, the obstacle avoidance parameters also include the obstacle avoidance distance in the simulation process. Can assess unmanned aerial vehicle's safe obstacle avoidance ability through predetermineeing safe distance. For example, when the obstacle avoidance distance of the unmanned aerial vehicle is smaller than the pre-safety distance, it can be said that the safety obstacle avoidance capability of the unmanned aerial vehicle is weak; when the obstacle avoidance distance of the unmanned aerial vehicle is greater than the preset safety distance, the safe obstacle avoidance capability of the unmanned aerial vehicle can be strong. For example, when the preset safe distance is 10 meters and the obstacle avoidance distance of the first aircraft model (corresponding to the unmanned aerial vehicle) is 11 meters, it can be said that the safe obstacle avoidance capability of the unmanned aerial vehicle is strong; when the obstacle avoidance distance of the first aircraft model is 6 meters, it can be shown that the safety obstacle avoidance capability of the unmanned aerial vehicle is weak. The above numerical values are merely exemplary values, and the present application is not limited thereto.
In this embodiment of the present application, the semi-physical simulation system 100 of the unmanned aerial vehicle further includes: the photoelectric test equipment is arranged in a ground station mode. The optoelectronic testing device comprises: imaging device, laser range finder and inertial measurement unit.
The imaging device is used for detecting obstacles in a test scene and tracking the flight of the unmanned aerial vehicle, and further acquiring 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 device and used for measuring the real-time attitude 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. Can also set up different weather effects in the test scene, like rainy day effect, snow day effect, strong wind effect etc. through different types of test scenes, provide more diversified condition for unmanned aerial vehicle's test, be convenient for make the aassessment to unmanned aerial vehicle's under the different scenes flight control performance.
The imaging device may be, but is not limited to, a visible light camera, an infrared thermal imager.
The semi-physical simulation platform 20 may be connected to the above-mentioned optoelectronic testing device through a hardware interface, that is, the semi-physical simulation platform 20 is connected to the imaging device, the laser range finder and the inertial measurement unit through hardware interfaces respectively. Semi-physical simulation platform 20 is used for obtaining the geographical position of unmanned aerial vehicle, the speed of unmanned aerial vehicle and the distance of unmanned aerial vehicle and the barrier in the test scene according to flight image, first distance and real-time gesture, and then constructs the second aircraft model based on the geographical position of unmanned aerial vehicle, the speed of unmanned aerial vehicle and the distance of the barrier in unmanned aerial vehicle and the test scene. And carrying out simulation test on the second aircraft model in a 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 trajectory of the unmanned aerial vehicle can be determined through the geographical position of the unmanned aerial vehicle at different moments, and then the simulation test is performed on the second aircraft model in the second simulation scene according to the flight trajectory 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 geographical 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 inertia measurement unit.
In this embodiment of the application, semi-physical simulation platform 20 can be based on the data that photoelectric test equipment detected as unmanned aerial vehicle's flight data input to construct the second aircraft model and carry out the emulation test with this, through this mode, can effectually carry out the analog simulation to the unmanned aerial vehicle in testing, and the actual flight state of unmanned aerial vehicle in testing is simulated in effectual emulation, and then has improved the aassessment of unmanned aerial vehicle's flight control precision.
In addition, when adopting above-mentioned mode to simulate the emulation, can also carry out accurate aassessment to unmanned aerial vehicle's perception and obstacle avoidance ability. At this time, a distribution principle of feasibility and a threshold weight need to be established for quantitative evaluation. For example, setting a parameter of sensing a static obstacle, a parameter of sensing a dynamic obstacle, and a parameter of obstacle avoidance response characteristics.
Wherein, the static barrier parameter of perception includes unmanned aerial vehicle and the safe distance of presetting of static barrier, unmanned aerial vehicle and the safe relative altitude of presetting of static barrier. Correspondingly, the semi-physical simulation platform 20 is configured to evaluate the perception and avoidance ability of the static obstacle according to the geographical position of the unmanned aerial vehicle, the distance between the unmanned aerial vehicle and the obstacle in the test scene, and the static obstacle perception parameter.
Wherein, perception movement barrier parameter includes unmanned aerial vehicle and movement barrier's the safe distance of presetting, unmanned aerial vehicle and movement barrier's the safe relative altitude of presetting and unmanned aerial vehicle and movement barrier's the safe relative speed of presetting. Correspondingly, the semi-physical simulation platform 20 is used for evaluating the perception avoiding capability of the dynamic perceived obstacle of the unmanned aerial vehicle according to the geographical 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 perceived moving obstacle parameters.
The obstacle avoidance response characteristic parameters comprise: the unmanned aerial vehicle and the obstacle preset safe relative distance, the unmanned aerial vehicle and the obstacle preset safe relative altitude difference, the unmanned aerial vehicle and the obstacle preset safe relative speed and the unmanned aerial vehicle and the obstacle preset safe response time. The preset safe response time is the quotient of the preset safe relative distance between the unmanned aerial vehicle and the obstacle and the preset safe relative speed between the unmanned aerial vehicle and the obstacle. Correspondingly, the semi-physical simulation platform 20 is used for evaluating the perception and avoidance capability of the unmanned aerial vehicle according to the geographical 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 method is used for evaluating an open outdoor airspace scene of a real flying unmanned aerial vehicle in a laboratory environment. The open outdoor airspace scene is a first constructed simulation scene. Namely, the evaluation method is used for evaluating the normal flight state of the unmanned aerial vehicle in the outdoor airspace in the limited environment of the laboratory. That is, in the above-described embodiment, the second aircraft model simulates the flight of the drone in an indoor environment, and the first aircraft model simulates the flight of the drone in an outdoor environment. Wherein, follow-up flight data through first aircraft model simulation unmanned aerial vehicle under outdoor environment can also be used for updating the data of autopilot.
Referring to fig. 4, based on the same inventive concept, an evaluation method is further provided in the embodiment of the present application, and is applied to the semi-physical simulation platform 20 in the semi-physical simulation system 100 of the unmanned aerial vehicle in the above embodiment. The method comprises the following steps: step S101-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 trajectory to obtain a simulation test result; wherein the first simulation scenario is a scenario constructed by the semi-physical simulation platform based on the test scenario and/or the environmental data.
It should be noted that the above method steps have been described in an embodiment of the unmanned aerial vehicle awareness avoidance capability evaluation system. In order to avoid redundancy, the same parts are referred to each other without repeated explanation.
Based on the same inventive concept, the present application further provides a storage medium, on which a semi-physical simulation platform and a computer program for measurement evaluation are stored, and when the computer program is executed, the computer program 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 of an integrated server, data center, cloud storage, and the like. 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)), among others.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical functional division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another subsystem and be used as embedded data units, etc., or some features may be omitted or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
Furthermore, the functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
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 above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. The utility model provides an unmanned aerial vehicle semi-physical simulation system which characterized in that includes:
an autopilot; analog data are stored; the simulation data comprise flight data and environment data of the unmanned aerial vehicle in a test scene; the flight data comprises flight characteristic parameters and flight tracks;
the semi-physical simulation platform is connected with the automatic pilot 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 scenario based on the test scenario and/or the environmental data; and carrying out simulation test on the first aircraft model in the first simulation scene based on the flight track, and further obtaining a simulation test result.
2. The semi-physical simulation system of unmanned aerial vehicle of claim 1, wherein the semi-physical simulation platform comprises a control module for controlling the first aircraft model during simulation testing of the first aircraft model.
3. The semi-physical simulation system of unmanned aerial vehicle of claim 1, wherein the semi-physical simulation platform comprises 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 comprise attitude angle information, flight paths and obstacle avoidance parameters.
4. The semi-physical simulation system of unmanned aerial vehicle 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 then evaluating the first aircraft model according to a comparison result.
5. The semi-physical simulation system of the unmanned aerial vehicle of claim 4, wherein 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 expected attitude angle; and adjusting the attitude of the first aircraft model through the deviation value.
6. The semi-physical simulation system of unmanned aerial vehicle 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 then evaluating the path planning capability of the first aircraft model according to the comparison result.
7. The semi-physical simulation system of the unmanned aerial vehicle of claim 3, wherein the first evaluation parameter comprises a preset obstacle avoidance duration, and correspondingly, the obstacle avoidance parameter comprises 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 then evaluating the obstacle avoidance capacity of the first aircraft model according to the comparison result.
8. The semi-physical simulation system of unmanned aerial vehicle 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 safe distance with the obstacle avoidance distance, and then evaluating the safe obstacle avoidance capability of the first aircraft model according to the comparison result.
9. The semi-physical simulation system of unmanned aerial vehicle of claim 1, further comprising: the photoelectric test equipment is arranged in a ground station form; the optoelectronic test device comprises: the device comprises an imaging device, a laser range finder and an inertia measuring 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 acquiring a first distance from the unmanned aerial vehicle; the inertial measurement unit is arranged on the imaging equipment and used for measuring the real-time attitude of the imaging equipment;
the semi-physical simulation platform is connected with the photoelectric test equipment and 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 an obstacle in the test scene according to the flight image, the first distance and the real-time attitude, 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 to further obtain a simulation test result.
10. An evaluation method, which is applied to the semi-physical simulation platform in the semi-physical simulation system of the unmanned aerial vehicle according to claim 1, wherein the semi-physical simulation system of the unmanned aerial vehicle 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; the flight data comprise 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 trajectory to obtain a simulation test result; wherein the first simulation scenario is a scenario constructed by the semi-physical simulation platform based on the test scenario and/or the environmental data.
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