CN113447028A - Unmanned aerial vehicle's inertial navigation system and unmanned aerial vehicle - Google Patents
Unmanned aerial vehicle's inertial navigation system and unmanned aerial vehicle Download PDFInfo
- Publication number
- CN113447028A CN113447028A CN202110859460.XA CN202110859460A CN113447028A CN 113447028 A CN113447028 A CN 113447028A CN 202110859460 A CN202110859460 A CN 202110859460A CN 113447028 A CN113447028 A CN 113447028A
- Authority
- CN
- China
- Prior art keywords
- module
- gps
- data
- inertial navigation
- aerial vehicle
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 230000000007 visual effect Effects 0.000 claims abstract description 60
- RZVHIXYEVGDQDX-UHFFFAOYSA-N 9,10-anthraquinone Chemical compound C1=CC=C2C(=O)C3=CC=CC=C3C(=O)C2=C1 RZVHIXYEVGDQDX-UHFFFAOYSA-N 0.000 claims abstract description 33
- 238000003745 diagnosis Methods 0.000 claims description 17
- 238000004891 communication Methods 0.000 claims description 10
- 230000001133 acceleration Effects 0.000 claims description 3
- 238000007689 inspection Methods 0.000 description 10
- 238000000034 method Methods 0.000 description 9
- 238000010586 diagram Methods 0.000 description 4
- 230000005540 biological transmission Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 241000282414 Homo sapiens Species 0.000 description 1
- 208000004350 Strabismus Diseases 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000011897 real-time detection Methods 0.000 description 1
- 230000008707 rearrangement Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 239000007921 spray Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
- G01C21/1656—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments with passive imaging devices, e.g. cameras
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
- G01S19/47—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Computer Networks & Wireless Communication (AREA)
- Navigation (AREA)
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
Abstract
The embodiment of the invention discloses an inertial navigation system of an unmanned aerial vehicle and the unmanned aerial vehicle. The inertial navigation system of the unmanned aerial vehicle comprises a flight control module, an inertial navigation module, a GPS module and a visual navigation module; the GPS module is used for acquiring GPS data in flight; the visual navigation module is used for acquiring visual image data in flight; the flight control module is used for judging whether the signal intensity of the GPS module is greater than a threshold value or not and correcting the navigation data of the inertial navigation module by using the GPS data when the signal intensity of the GPS module is greater than the threshold value; when the signal intensity of the GPS module is smaller than or equal to the threshold value, the navigation data of the inertial navigation module is corrected through the visual image data; and the inertial navigation module is used for controlling the navigation flight of the unmanned aerial vehicle according to the corrected navigation data. Therefore, navigation of the unmanned aerial vehicle can be realized when the signal is interfered.
Description
Technical Field
The embodiment of the invention relates to the navigation control technology of an unmanned aerial vehicle, in particular to an inertial navigation system of the unmanned aerial vehicle and the unmanned aerial vehicle.
Background
At present, various inspection flying robots gradually become research hotspots in various fields, the inspection flying robots can be used conveniently and effectively to replace manpower to execute inspection tasks with high difficulty, have the advantages of high intelligence, flexible and stable aerial operation and the like, are widely used in the aspects of military fields, forest fire fighting, national grid power line inspection and the like, and more inspection flying robots are used for replacing human beings to execute various operations.
The inspection flying robot in the traditional concept adopts the GPS for navigation, however, when the GPS is interfered, the flying robot shakes or deviates from the original flying route, and the flying robot loses control in severe cases, so that the workload of performing outdoor operation every time is very large, when the flying environment is complex, the inspection flying robot depends on the single GPS for navigation, and the stability of the inspection flying robot hardly meets the requirement of air inspection.
Disclosure of Invention
The invention provides an inertial navigation system of an unmanned aerial vehicle and the unmanned aerial vehicle, which can realize navigation of the unmanned aerial vehicle when signals are interfered.
In a first aspect, an embodiment of the present invention provides an inertial navigation system of an unmanned aerial vehicle, where the inertial navigation system of the unmanned aerial vehicle includes a flight control module, an inertial navigation module, a GPS module, and a visual navigation module; the flight control module is in communication connection with the inertial navigation module, the GPS module and the visual navigation module;
the GPS module is used for acquiring GPS data in flight;
the visual navigation module is used for acquiring visual image data in flight;
the flight control module is used for judging whether the signal intensity of the GPS module is greater than a threshold value or not, and correcting the navigation data of the inertial navigation module by using the GPS data when the signal intensity of the GPS module is greater than the threshold value; correcting navigation data of the inertial navigation module through the visual image data when the signal intensity of the GPS module is less than or equal to the threshold value;
and the inertial navigation module is used for controlling the navigation flight of the unmanned aerial vehicle according to the corrected navigation data.
Optionally, the inertial navigation system of the drone further includes a predictor, the predictor is configured to perform delay compensation on GPS data to generate GPS prediction data, and the correcting navigation data of the inertial navigation module using the GPS data includes:
and correcting the navigation data of the inertial navigation module by using the GPS data after the time delay compensation.
Optionally, the inertial navigation module comprises an accelerometer, a gyroscope, and a barometer; wherein, the accelerometer is used for calculating unmanned aerial vehicle's acceleration, the gyroscope is used for calculating unmanned aerial vehicle's angular velocity, the barometer is used for calculating unmanned aerial vehicle's height.
Optionally, the inertial navigation system of the unmanned aerial vehicle further includes a fault diagnosis determination module, where the fault diagnosis determination module is configured to perform fault diagnosis on the measurement data (including GPS data and air pressure data) and the GPS prediction data when the signal intensity of the GPS module is greater than the threshold value, and shield the GPS prediction data of the fault according to a fault diagnosis result.
Optionally, the inertial navigation module is further configured to input the time stamp of the delay compensation and the fault diagnosis result into an extended kalman filter to predict the position and the speed information of the drone.
Optionally, the GPS module includes a geomagnetic meter and a GPS, and the geomagnetic meter is connected to the GPS.
Optionally, the visual navigation module is a visual camera.
Optionally, the flight control module includes a first control unit and a second control unit, where the first control unit is configured to determine whether the signal strength of the GPS module is greater than the threshold, and correct the navigation data of the inertial navigation module using the GPS data when the signal strength of the GPS module is greater than the threshold; the second control unit is used for correcting the navigation data of the inertial navigation module through the visual image data when the signal intensity of the GPS module is smaller than or equal to the threshold value.
Optionally, the first control unit is an STM control chip, and the second control unit is an industrial personal computer.
In a second aspect, an embodiment of the present invention further provides a drone including the inertial navigation system of the drone according to the first aspect.
The invention provides an inertial navigation system of an unmanned aerial vehicle and the unmanned aerial vehicle, wherein the inertial navigation system of the unmanned aerial vehicle comprises a flight control module, an inertial navigation module, a GPS module and a visual navigation module; the flight control module is in communication connection with the inertial navigation module, the GPS module and the visual navigation module; the GPS module is used for acquiring GPS data in flight; the visual navigation module is used for acquiring visual image data in flight; the flight control module is used for judging whether the signal intensity of the GPS module is greater than a threshold value or not and correcting the navigation data of the inertial navigation module by using the GPS data when the signal intensity of the GPS module is greater than the threshold value; when the signal intensity of the GPS module is smaller than or equal to the threshold value, the navigation data of the inertial navigation module is corrected through the visual image data; and the inertial navigation module is used for controlling the navigation flight of the unmanned aerial vehicle according to the corrected navigation data. Therefore, the signal intensity of the GPS module is judged in real time through the flight control module, the navigation of the unmanned aerial vehicle is realized through the combination of the inertial navigation module and the GPS when the signal of the GPS module is good, and the inertial navigation data can be corrected through the GPS data when the unmanned aerial vehicle is in a yaw state; when GPS module signal is poor or even no signal, realize the navigation to unmanned aerial vehicle through the combination of vision navigation module and inertial navigation module to can revise inertial navigation data through visual image data when unmanned aerial vehicle is navigated, thereby can realize also realizing the navigation to unmanned aerial vehicle when the signal receives the interference.
Drawings
Fig. 1 is a block diagram of an inertial navigation system of an unmanned aerial vehicle according to a first embodiment of the present invention;
fig. 2 is a block diagram of an inertial navigation system of an unmanned aerial vehicle according to a second embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a block diagram of an inertial navigation system of an unmanned aerial vehicle according to a first embodiment of the present invention. Referring to fig. 1, the inertial navigation system of the unmanned aerial vehicle includes a flight control module 10, an inertial navigation module 20, a GPS module 30, and a visual navigation module 40; the flight control module 10 is in communication connection with the inertial navigation module 20, the GPS module 30 and the visual navigation module 40; the GPS module 30 is used to acquire GPS data in flight; the visual navigation module 40 is used for acquiring visual image data in flight; the flight control module 10 is configured to determine whether the signal strength of the GPS module 30 is greater than a threshold, and correct the navigation data of the inertial navigation module 20 using the GPS data when the signal strength of the GPS module 30 is greater than the threshold; correcting the navigation data of the inertial navigation module 20 through the visual image data when the signal intensity of the GPS module 30 is less than or equal to the threshold value; the inertial navigation module 20 is used for controlling the navigation flight of the unmanned aerial vehicle according to the corrected navigation data.
Wherein, visual image data can include the flight status, height etc. of unmanned aerial vehicle, and wherein, flight status is for example whether unmanned aerial vehicle seriously squints, image data such as upset. The flight control module 10 CAN be in communication connection with the inertial navigation module 20, the GPS module 30, and the visual navigation module 40 through CAN communication.
The threshold is a critical signal strength of the GPS module 30 when the signal strength is weakened, and the specific signal strength value may be set according to an actual situation, which is not specifically limited herein. Specifically, when the signal intensity of the GPS module 30 is greater than the threshold value, it indicates that the signal state of the GPS module 30 is good at this time, and the inertial navigation module 20 may be assisted by the GPS module 30 to implement navigation of the unmanned aerial vehicle; when the signal strength of the GPS module 30 is less than or equal to the threshold, it indicates that the signal of the GPS module 30 is poor or even none, and the inertial navigation module 20 may be assisted by the visual navigation module 40 to navigate the unmanned aerial vehicle.
Generally, in the flight process of an unmanned aerial vehicle, due to the influence of factors such as wind power and signal interference, the unmanned aerial vehicle often shakes or deviates from an original air route, and in the serious case, the unmanned aerial vehicle loses control to cause that flight operation cannot be finished. For this reason, the flight control module 10 of the present embodiment corrects for such a jitter or yaw phenomenon during the flight of the drone. Specifically, when the flight control module 10 controls the GPS module 30 to assist the inertial navigation module 20 to control the unmanned aerial vehicle to navigate, the GPS data received by the GPS module 30 is used to correct the navigation data of the inertial navigation module 20, so as to solve the problem of unmanned aerial vehicle shaking or yawing; when the control visual navigation module 40 assists the inertial navigation module 20 to control the unmanned aerial vehicle to navigate, the visual image data acquired by the visual navigation module 40 is used to correct the navigation data of the inertial navigation module 20, so as to solve the problem of the unmanned aerial vehicle shaking or yawing.
In the technical scheme of this embodiment, the implementation process of the inertial navigation system of the unmanned aerial vehicle is as follows: referring to fig. 1, the flight control module 10 is in communication connection with the inertial navigation module 20, the GPS module 30 and the visual navigation module 40, wherein the inertial navigation module 20 acquires navigation data of the unmanned aerial vehicle in real time and sends the navigation data to the flight control module 10, the GPS module 30 acquires GPS data of the unmanned aerial vehicle in flight in real time and sends the GPS data to the flight control module 10, and the visual navigation module 40 acquires visual image data of the unmanned aerial vehicle in flight in real time and sends the visual image data to the flight control module 10. The flight control module 10 detects the signal intensity of the GPS module 30 in real time and judges the intensity of the signal, and when the signal intensity of the GPS module 30 is detected and judged to be greater than a threshold value, controls the GPS module 30 to assist the inertial navigation module 20 in navigating the unmanned aerial vehicle, and corrects the navigation data of the inertial navigation module 20 through GPS data to realize navigation of the unmanned aerial vehicle; when the signal intensity of the GPS module 30 is detected and determined to be less than or equal to the threshold, the visual navigation module 40 is controlled to assist the inertial navigation module 20 in navigating the unmanned aerial vehicle, and the navigation data of the inertial navigation module is corrected by the visual image data, so as to realize navigation of the unmanned aerial vehicle. Therefore, by arranging the navigation combination module of the inertial navigation module 20, the GPS module 30 and the visual navigation module 40 and detecting and judging the signal intensity of the GPS module 30, the navigation of the unmanned aerial vehicle is realized by combining the inertial navigation module 20 and the GPS module 30 when the signal of the GPS module 30 is good, and the inertial navigation data can be corrected by the GPS data when the unmanned aerial vehicle is in a yaw state; when GPS module 30 signal is poor even no signal, realize the navigation to unmanned aerial vehicle through the combination of visual navigation module 40 and inertial navigation module 20, and can revise inertial navigation data through visual image data when unmanned aerial vehicle navigates, thereby can realize also realizing the navigation to unmanned aerial vehicle when the signal receives the interference, the error rate of unmanned aerial vehicle navigation has been reduced, and can effectively reduce unmanned aerial vehicle operation in-process staff's input, the intellectuality of unmanned aerial vehicle operation has been improved, thereby ensure that unmanned aerial vehicle's operation task can go on smoothly.
According to the technical scheme of the embodiment, the inertial navigation system of the unmanned aerial vehicle is provided, and comprises a flight control module, an inertial navigation module, a GPS module and a visual navigation module; the flight control module is in communication connection with the inertial navigation module, the GPS module and the visual navigation module; the GPS module is used for acquiring GPS data in flight; the visual navigation module is used for acquiring visual image data in flight; the flight control module is used for judging whether the signal intensity of the GPS module is greater than a threshold value or not and correcting the navigation data of the inertial navigation module by using the GPS data when the signal intensity of the GPS module is greater than the threshold value; when the signal intensity of the GPS module is smaller than or equal to the threshold value, the navigation data of the inertial navigation module is corrected through the visual image data; and the inertial navigation module is used for controlling the navigation flight of the unmanned aerial vehicle according to the corrected navigation data. Therefore, the signal intensity of the GPS module is judged in real time through the flight control module, the navigation of the unmanned aerial vehicle is realized through the combination of the inertial navigation module and the GPS when the signal of the GPS module is good, and the inertial navigation data can be corrected through the GPS data when the unmanned aerial vehicle is in a yaw state; when GPS module signal is poor or even no signal, realize the navigation to unmanned aerial vehicle through the combination of vision navigation module and inertial navigation module to can revise inertial navigation data through visual image data when unmanned aerial vehicle is navigated, thereby can realize also realizing the navigation to unmanned aerial vehicle when the signal receives the interference. Because the main body for realizing navigation in the technical scheme is inertial navigation, real-time data required by navigation can be greatly reduced, the frequency of data acquisition of the GPS module 30 or the visual navigation module 40 can be relatively low, and the requirement on the performance of the processor is not high, so that the inertial navigation system of the unmanned aerial vehicle has lower cost compared with the prior art in which the inertial navigation module 20 is used as the navigation main body and the GPS module 30 or the visual navigation module 40 is used as the navigation main body, the real-time data quantity required to be corrected in the navigation process is lower, errors are not easy to make in calculation, the navigation process is more accurate, and the anti-interference capability is stronger.
Example two
Fig. 2 is a block diagram of an inertial navigation system of an unmanned aerial vehicle according to a second embodiment of the present invention. On the basis of the first embodiment, optionally, referring to fig. 2, the inertial navigation system of the drone further includes a predictor 50, where the predictor 50 is configured to perform delay compensation on GPS data to generate GPS prediction data, and the correcting the navigation data of the inertial navigation module 20 using the GPS data includes:
the GPS data after the delay compensation is used to correct the navigation data of the inertial navigation module 20.
The GPS data of the GPS module may have a delay with respect to the navigation data of the inertial navigation module 20, so that the predictor 50 is configured to calculate delay data of the GPS data with respect to the navigation data of the inertial navigation module 20, perform delay compensation on the GPS data using the delay data, and fuse the delay compensated GPS data with the navigation data of the inertial navigation module 20 to correct the navigation data. For example, taking the distance or position information in the navigation data as an example, the delay time of the GPS data may be calculated first, then the average speed at the current time is taken, and then the delay time is multiplied by the average speed to calculate the current delay distance, so that it can be ensured that the GPS data and the navigation data of the inertial navigation module 20 obtain the same time position, and the position at the same time is obtained and then subjected to data fusion to obtain a fused position, where the calculation accuracy is higher than the position accuracy when the navigation data using the GPS data or the single inertial navigation module 20 is used for navigation. Therefore, by setting the predictor 50, the navigation of the unmanned aerial vehicle can be realized, and the navigation precision of the unmanned aerial vehicle can be improved.
Optionally, with continued reference to fig. 2, the inertial navigation module 20 includes an accelerometer 21, a gyroscope 22, and a barometer 23; wherein, accelerometer 21 is used for calculating unmanned aerial vehicle's acceleration, and gyroscope 22 is used for calculating unmanned aerial vehicle's angular velocity, and barometer 23 is used for calculating unmanned aerial vehicle's height.
Among them, the accelerometer 21, the gyroscope 22, and the barometer 23 may be integrated in the inertial navigation module 20, so that the volume of the module may be reduced.
Optionally, with continued reference to fig. 2, the inertial navigation system of the unmanned aerial vehicle further includes a fault diagnosis determining module 60, where the fault diagnosis determining module 60 is configured to perform fault diagnosis on the measured data and the GPS predicted data when the signal strength of the GPS module 30 is greater than a threshold value, and shield the faulty GPS predicted data according to a fault diagnosis result.
Wherein, when the signal intensity of GPS module 30 is greater than the threshold value, flight control module 10 control GPS module 30 and inertial navigation module 20 combination control unmanned aerial vehicle's navigation, because GPS data can drift in the short time, in order to prevent unmanned aerial vehicle from taking place navigation failure, set up failure diagnosis judging module 60, real-time detection obtains the measured data (GPS data promptly) of GPS module, and compare measured data and GPS prediction data, explain when the two are inconsistent to break down, flight control module 10 can control unmanned aerial vehicle hover at this moment, and send fault information for the user, in order to indicate relevant personnel to take corresponding measure.
Optionally, the inertial navigation module 20 is further configured to input the time stamp of the delay compensation and the fault diagnosis result into the extended kalman filter to predict the position and the speed information of the drone.
Specifically, a model is established for the unmanned aerial vehicle, a state space expression is used for expressing, then corresponding variables (such as time stamps of delay compensation and fault diagnosis results) and the like are input into a Kalman filter according to the state space expression, the state after the variables are updated can be obtained, and in the updating process of the Kalman filter, information such as positions, attitude angles, speeds and the like can be deduced through the Kalman filter.
Alternatively, referring to fig. 2, the GPS module 30 includes a magnetometer 31 and a GPS32, and the magnetometer 31 and the GPS32 are connected.
Optionally, the visual navigation module 40 is a visual camera.
The vision camera has the advantages of high resolution, high scanning speed, high precision and the like.
When GPS signals do not exist or the signals are weak in the environment, in the system, based on the SLAM technology, a nonlinear optimization method is adopted to fuse image data of the visual camera and navigation data of the inertial navigation module, and therefore position and attitude information of the unmanned aerial vehicle can be obtained. Because the vision camera and the inertial navigation module can only measure the relative position information of the unmanned aerial vehicle, when the unmanned aerial vehicle runs for a long time in an area without GPS signals, the calculated position and attitude information can have accumulated errors, and a loop detection function can be added to reduce the accumulated errors of pose estimation.
Optionally, the flight control module 10 includes a first control unit 11 and a second control unit 12, the first control unit 11 is configured to determine whether the signal strength of the GPS module 30 is greater than a threshold value, and correct the navigation data of the inertial navigation module 20 using the GPS data when the signal strength of the GPS module 30 is greater than the threshold value; the second control unit 12 is used for correcting the navigation data of the inertial navigation module 20 through the visual image data when the signal intensity of the GPS module is less than or equal to the threshold value.
The first control unit 11 is electrically connected to the second control unit 12. The first control unit 11 is a main control unit, and is configured to determine whether the signal strength of the GPS module 30 is greater than a threshold, and control the GPS module 30 to assist the inertial navigation module 20 in navigating the unmanned aerial vehicle when the signal strength of the GPS module 30 is greater than the threshold; and when the signal intensity of the GPS module is less than or equal to the threshold value, the visual navigation module 40 is controlled by controlling the second control unit 12 to assist the inertial navigation module 20 in navigating the unmanned aerial vehicle.
Optionally, the first control unit 11 is an STM control chip, and the second control unit 12 is an industrial personal computer.
Wherein, when GPS signal intensity is greater than the threshold value (when the signal is good promptly), through GPS module 30 and inertial navigation module 20 control unmanned aerial vehicle's navigation, because GPS data and inertial navigation module's navigation data is digital signal, for the guarantee real-time, adopt ordinary STM32 control chip can. When GPS signals are poor, navigation of the unmanned aerial vehicle is controlled through the visual navigation module 40 and the inertial navigation module 20, a large amount of image data need to be processed, the data volume is large, and the real-time performance of the common STM32 single chip microcomputer cannot be guaranteed, so that the industrial personal computer is adopted for processing. Illustratively, the first control unit 11 may be an STM32F407VGT6 processor.
In addition, this unmanned aerial vehicle's inertial navigation system still includes data transmission module, data transmission module respectively with flight control module and user side communication connection for realize the communication transmission between user side and the unmanned aerial vehicle.
EXAMPLE III
The embodiment of the invention also provides the unmanned aerial vehicle, which comprises the inertial navigation system of the unmanned aerial vehicle in any embodiment of the invention.
Wherein, this unmanned aerial vehicle can be used for circuit tower to patrol and examine operation, farmland and spray, forestry inspection operation, patrol, flight and shoot etc.. This unmanned aerial vehicle's inertial navigation system can effectively reduce the preparation work that the flying robot operation of patrolling and examining need be done, reduce and patrol and examine artifical rate of utilization of process and participation rate, can switch over each other between two kinds of combination navigation according to the power of GPS signal, reduced and patrolled and examined flying robot navigation data's error rate to can effectively reduce flying robot and patrol and examine the input of operation in-process staff, improve the intellectuality of patrolling and examining the operation, improved unmanned aerial vehicle and fallen to the ground the accuracy.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. An inertial navigation system of an unmanned aerial vehicle is characterized by comprising a flight control module, an inertial navigation module, a GPS module and a visual navigation module; the flight control module is in communication connection with the inertial navigation module, the GPS module and the visual navigation module;
the GPS module is used for acquiring GPS data in flight;
the visual navigation module is used for acquiring visual image data in flight;
the flight control module is used for judging whether the signal intensity of the GPS module is greater than a threshold value or not, and correcting the navigation data of the inertial navigation module by using the GPS data when the signal intensity of the GPS module is greater than the threshold value; correcting navigation data of the inertial navigation module through the visual image data when the signal intensity of the GPS module is less than or equal to the threshold value;
and the inertial navigation module is used for controlling the navigation flight of the unmanned aerial vehicle according to the corrected navigation data.
2. The inertial navigation system of a drone of claim 1, further comprising a predictor for delay compensation of GPS data to generate GPS prediction data, the correcting navigation data of the inertial navigation module using the GPS data comprising:
and correcting the navigation data of the inertial navigation module by using the GPS data after the time delay compensation.
3. The inertial navigation system of a drone of claim 2, wherein the inertial navigation module includes an accelerometer, a gyroscope, and a barometer; wherein, the accelerometer is used for calculating unmanned aerial vehicle's acceleration, the gyroscope is used for calculating unmanned aerial vehicle's angular velocity, the barometer is used for calculating unmanned aerial vehicle's height.
4. The inertial navigation system of an unmanned aerial vehicle of claim 3, further comprising a fault diagnosis determination module, wherein the fault diagnosis determination module is configured to perform fault diagnosis on the measured data and the GPS predicted data when the signal strength of the GPS module is greater than the threshold value, and to shield the faulty GPS predicted data according to a fault diagnosis result.
5. The inertial navigation system of a drone of claim 4, wherein the inertial navigation module is further configured to input the time-delay compensated timestamp and the fault diagnosis result into an extended Kalman filter to predict position and speed information of the drone.
6. The inertial navigation system of a drone of claim 1, wherein the GPS module includes a magnetometer and a GPS, the magnetometer and the GPS being connected.
7. The inertial navigation system of a drone of claim 1, wherein the visual navigation module is a visual camera.
8. The inertial navigation system of a drone of claim 1, wherein the flight control module includes a first control unit and a second control unit, the first control unit being configured to determine whether the signal strength of the GPS module is greater than the threshold value, and to modify the navigation data of the inertial navigation module using the GPS data when the signal strength of the GPS module is greater than the threshold value; the second control unit is used for correcting the navigation data of the inertial navigation module through the visual image data when the signal intensity of the GPS module is smaller than or equal to the threshold value.
9. The inertial navigation system of unmanned aerial vehicle of claim 8, wherein the first control unit is an STM control chip and the second control unit is an industrial personal computer.
10. A drone, characterized in that it comprises an inertial navigation system of a drone according to any one of claims 1 to 9.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110859460.XA CN113447028B (en) | 2021-07-28 | 2021-07-28 | Unmanned aerial vehicle's inertial navigation system and unmanned aerial vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110859460.XA CN113447028B (en) | 2021-07-28 | 2021-07-28 | Unmanned aerial vehicle's inertial navigation system and unmanned aerial vehicle |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113447028A true CN113447028A (en) | 2021-09-28 |
| CN113447028B CN113447028B (en) | 2024-08-27 |
Family
ID=77817502
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110859460.XA Active CN113447028B (en) | 2021-07-28 | 2021-07-28 | Unmanned aerial vehicle's inertial navigation system and unmanned aerial vehicle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113447028B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20220043102A1 (en) * | 2010-11-12 | 2022-02-10 | Position Imaging, Inc. | Position tracking system and method using radio signals and inertial sensing |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050203677A1 (en) * | 2004-03-08 | 2005-09-15 | Jean-Laurent Auger | Method for guiding in real time a landborne vehicle provided with an off-board navigation system |
| CN101598557A (en) * | 2009-07-15 | 2009-12-09 | 北京航空航天大学 | A kind of integrated navigation system that is applied to unmanned spacecraft |
| US20100274481A1 (en) * | 2009-04-22 | 2010-10-28 | Honeywell International Inc. | System and method for collaborative navigation |
| CN102680996A (en) * | 2011-03-08 | 2012-09-19 | 精工爱普生株式会社 | Positioning apparatus and positioning method |
| CN105096642A (en) * | 2015-09-02 | 2015-11-25 | 重庆大学 | Real-time bus arrival time prediction method in consideration of GPS data delay effect |
| US20150369923A1 (en) * | 2014-06-19 | 2015-12-24 | Novatel Inc. | Method for using partially occluded images for navigation and positioning |
| US20170328716A1 (en) * | 2016-05-16 | 2017-11-16 | Northrop Grumman Systems Corporation | Vision-aided aerial navigation |
| CN108121003A (en) * | 2017-12-26 | 2018-06-05 | 湖南迈克森伟电子科技有限公司 | Integrated navigation precise positioning system |
| KR20190001832A (en) * | 2017-06-28 | 2019-01-07 | 국방과학연구소 | Inertial navigation system with adaptive time delay compensation and rapid initial alignment method thereof |
| CN110657800A (en) * | 2018-06-29 | 2020-01-07 | 北京自动化控制设备研究所 | Time synchronization method of position measurement integrated navigation system |
| CN112304304A (en) * | 2020-10-23 | 2021-02-02 | 国网智能科技股份有限公司 | Patrol unmanned aerial vehicle, system and method suitable for transformer substation |
-
2021
- 2021-07-28 CN CN202110859460.XA patent/CN113447028B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050203677A1 (en) * | 2004-03-08 | 2005-09-15 | Jean-Laurent Auger | Method for guiding in real time a landborne vehicle provided with an off-board navigation system |
| US20100274481A1 (en) * | 2009-04-22 | 2010-10-28 | Honeywell International Inc. | System and method for collaborative navigation |
| CN101598557A (en) * | 2009-07-15 | 2009-12-09 | 北京航空航天大学 | A kind of integrated navigation system that is applied to unmanned spacecraft |
| CN102680996A (en) * | 2011-03-08 | 2012-09-19 | 精工爱普生株式会社 | Positioning apparatus and positioning method |
| US20150369923A1 (en) * | 2014-06-19 | 2015-12-24 | Novatel Inc. | Method for using partially occluded images for navigation and positioning |
| CN105096642A (en) * | 2015-09-02 | 2015-11-25 | 重庆大学 | Real-time bus arrival time prediction method in consideration of GPS data delay effect |
| US20170328716A1 (en) * | 2016-05-16 | 2017-11-16 | Northrop Grumman Systems Corporation | Vision-aided aerial navigation |
| KR20190001832A (en) * | 2017-06-28 | 2019-01-07 | 국방과학연구소 | Inertial navigation system with adaptive time delay compensation and rapid initial alignment method thereof |
| CN108121003A (en) * | 2017-12-26 | 2018-06-05 | 湖南迈克森伟电子科技有限公司 | Integrated navigation precise positioning system |
| CN110657800A (en) * | 2018-06-29 | 2020-01-07 | 北京自动化控制设备研究所 | Time synchronization method of position measurement integrated navigation system |
| CN112304304A (en) * | 2020-10-23 | 2021-02-02 | 国网智能科技股份有限公司 | Patrol unmanned aerial vehicle, system and method suitable for transformer substation |
Non-Patent Citations (4)
| Title |
|---|
| 姜鑫;周广涛;石惠文;程正生;: "重力辅助惯性导航中延时误差补偿算法研究", 压电与声光, no. 01, 28 February 2015 (2015-02-28), pages 114 - 116 * |
| 朱晓飞;张连环;: "飞行中惯导定位误差的修正方法研究", 电子世界, no. 23, 31 December 2012 (2012-12-31), pages 92 - 93 * |
| 杨淑媛;: "小型无人机SINS/GPS/视觉组合导航研究", 山东工业技术, no. 22, 30 November 2016 (2016-11-30), pages 296 - 298 * |
| 黄建;胡越黎;杨文荣;冉峰;: "组合导航系统在四旋翼无人机上的实现", 电子技术应用, vol. 41, no. 05, 31 May 2015 (2015-05-31), pages 167 - 170 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20220043102A1 (en) * | 2010-11-12 | 2022-02-10 | Position Imaging, Inc. | Position tracking system and method using radio signals and inertial sensing |
| US12066561B2 (en) * | 2010-11-12 | 2024-08-20 | Position Imaging, Inc. | Position tracking system and method using radio signals and inertial sensing |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113447028B (en) | 2024-08-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106873627B (en) | Multi-rotor unmanned aerial vehicle and method for automatically inspecting power transmission line | |
| CN108303081B (en) | Bionic polarization/inertia/atmospheric data combined navigation system | |
| CN113124856B (en) | Visual inertia tight coupling odometer based on UWB (ultra wide band) online anchor point and metering method | |
| CN110487267B (en) | Unmanned aerial vehicle navigation system and method based on VIO & UWB loose combination | |
| CN112130579A (en) | Tunnel unmanned aerial vehicle inspection method and system | |
| US20180022472A1 (en) | Autonomous system for taking moving images from a drone, with target tracking and improved target location | |
| CN110926460A (en) | Uwb positioning abnormal value processing method based on IMU | |
| CN111045454A (en) | Unmanned aerial vehicle self-driving instrument based on bionic autonomous navigation | |
| CN111077907A (en) | Autonomous positioning method of outdoor unmanned aerial vehicle | |
| CN113447028A (en) | Unmanned aerial vehicle's inertial navigation system and unmanned aerial vehicle | |
| CN111141286A (en) | Unmanned aerial vehicle flight control multi-sensor attitude confidence resolving method | |
| CN118259697A (en) | Method and system for realizing tethered unmanned aerial vehicle following by utilizing speed synchronization and attitude | |
| CN211012986U (en) | Unmanned autonomous cruise vehicle navigation system based on inertial navigation technology | |
| CN115727842B (en) | Unmanned aerial vehicle rapid alignment method, unmanned aerial vehicle rapid alignment system, computer equipment and storage medium | |
| CN208188678U (en) | Unmanned machine positioning device and unmanned plane | |
| Liu et al. | The altitude hold algorithm of UAV based on millimeter wave radar sensors | |
| CN111610800B (en) | Loosely-coupled unmanned aerial vehicle control system | |
| CN113206951B (en) | Real-time electronic image stabilization method based on flapping wing flight system | |
| CN112285756A (en) | High-precision positioning system and method based on IMU and Beidou system | |
| Zang et al. | Event-triggered Extended Kalman Filter for UAV Monitoring System | |
| WO2020107473A1 (en) | Parameter optimization method and apparatus for mobile platform, and control device and aerial vehicle | |
| CN111207741A (en) | Unmanned aerial vehicle navigation positioning method based on indoor vision vicon system | |
| CN114964238B (en) | Aircraft positioning method and system | |
| CN213748481U (en) | Co-organization multi-robot cooperation system | |
| CN115145294B (en) | Combined navigation system and method for autonomous air refueling docking |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |