CN110488848B - Unmanned aerial vehicle vision-guided autonomous landing method and system - Google Patents

Unmanned aerial vehicle vision-guided autonomous landing method and system Download PDF

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CN110488848B
CN110488848B CN201910783859.7A CN201910783859A CN110488848B CN 110488848 B CN110488848 B CN 110488848B CN 201910783859 A CN201910783859 A CN 201910783859A CN 110488848 B CN110488848 B CN 110488848B
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aerial vehicle
unmanned aerial
landing point
pattern
height
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王荣阳
孙亚
李威
孙红伟
王经典
郭文骏
崔亮
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China Aeronautical Radio Electronics Research Institute
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    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/04Control of altitude or depth
    • G05D1/06Rate of change of altitude or depth
    • G05D1/0607Rate of change of altitude or depth specially adapted for aircraft
    • G05D1/0653Rate of change of altitude or depth specially adapted for aircraft during a phase of take-off or landing
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Abstract

The invention discloses an unmanned aerial vehicle vision-guided autonomous landing method, which comprises the following steps: step 1: after the unmanned aerial vehicle flies to an effective area above a landing point, a monocular camera shoots a target scene image; wherein: the target scene image comprises an identification pattern, and an internal pattern is arranged in the middle of the identification pattern; step 2: carrying out frame-by-frame processing on the target scene image, identifying the identification pattern, extracting the characteristics, and solving the relative position of the unmanned aerial vehicle relative to the landing point; wherein: when the calculated height of the unmanned aerial vehicle relative to the landing point is larger than the threshold height, measuring the relative position by taking the characteristic size of the whole identification pattern as a reference; and when the height of the unmanned aerial vehicle calculated by the position relative to the landing point is lower than the threshold height, measuring the relative position by taking the characteristic size of the internal pattern in the identification pattern as a reference. And step 3: and controlling the unmanned aerial vehicle to complete centering with the landing point according to the relative position, and descending to the landing point at a constant speed. The unmanned aerial vehicle can be guided to accurately land to a specified place.

Description

Unmanned aerial vehicle vision-guided autonomous landing method and system
Technical Field
The invention relates to the technical field of unmanned aerial vehicle navigation, in particular to a method and a system for unmanned aerial vehicle vision-guided autonomous landing.
Background
With the gradual expansion of the application range of the unmanned aerial vehicle technology in the military and civil fields, the unmanned aerial vehicle with the accurate landing function is more and more concerned, such as accurate landing/carrier landing, fixed-point launching and the like. Conventional guidance techniques include inertial guidance, radar guidance, high-precision satellite guidance, and the like. The position error of inertial navigation is accumulated and increased along with time, and the navigation precision is influenced; the positioning accuracy of the radar is limited, and the equipment is complex; high-precision satellite guidance is easy to interfere by means of satellite signals, and reliability is difficult to guarantee in the final reduction stage. The visual guidance is based on an image processing technology, corresponding processing is carried out on images acquired by the camera, and pose information in the moving process of a target is resolved by combining camera internal parameters, constraint condition information and the like, so that the novel navigation technology for controlling the aircraft to land is widely concerned due to the advantages of high precision, interference resistance, passive imaging, low cost and the like. The vision measurement mainly divide into monocular vision measurement and binocular vision measurement two kinds, and binocular vision measurement needs install two cameras additional on unmanned aerial vehicle, and camera installation accuracy requires highly, realizes complicacy, and the measuring distance requires the baseline more long more far away, installs the difficulty to unmanned aerial vehicle. The monocular vision measurement only needs one camera, and the size information of the target pattern is combined, so that the relative positioning can be realized, the system is simple in structure, the installation requirement is low, and the monocular vision measurement has great advantages for the application scene of the appointed landing point.
Disclosure of Invention
In order to solve the defects of the prior art, the invention aims to provide an unmanned aerial vehicle vision-guided autonomous landing method and an unmanned aerial vehicle vision-guided autonomous landing system, a monocular camera is used for acquiring a target scene image, relative position calculation is realized through image processing, target identification, accurate extraction, state switching control and other technologies, accurate guiding data is provided for the unmanned aerial vehicle landing,
one object of the invention is realized by the following technical scheme:
an unmanned aerial vehicle vision-guided autonomous landing method comprises the following steps:
step 1: after the unmanned aerial vehicle flies to the effective area above the landing point, a monocular camera arranged under the belly of the unmanned aerial vehicle shoots a target scene image; wherein: the target scene image comprises an identification pattern, and an internal pattern is arranged in the middle of the identification pattern;
step 2: carrying out frame-by-frame processing on the target scene image, identifying the identification pattern, extracting the characteristics, and solving the relative position of the unmanned aerial vehicle relative to the landing point; wherein: when the calculated height of the unmanned aerial vehicle relative to the landing point is larger than a threshold height h', measuring a relative position by taking the characteristic size of the whole identification pattern as a reference when identifying the next frame of target scene image; when the height of the unmanned aerial vehicle relative to the landing point calculated by the position solution is lower than a threshold height h', measuring the relative position by taking the characteristic size of an internal pattern in the identification pattern as a reference when identifying the next frame of target scene image;
and 3, step 3: and controlling the unmanned aerial vehicle to complete the centering with the landing point according to the relative position of the unmanned aerial vehicle relative to the landing point, and descending to the landing point at a constant speed.
Preferably, the effective area is an inverted round table, and the range of the effective area is as follows:
Figure GDA0003501866240000021
Figure GDA0003501866240000022
h 1 =r 1 /tan(θ/2)
h 2 =r 2 /tan(θ/2)
wherein the height of the upper bottom of the circular truncated cone from the descending point is h 1 The height of the lower bottom of the circular truncated cone from the descending point is h 2 The radius of the upper bottom of the circular truncated cone is r 1 The radius of the lower bottom of the circular truncated cone is r 2 The field angle of the camera is theta, the vertical resolution of the camera is D, and the side length of the complete identification pattern is w 1 Side length of the inner pattern is w 2 The minimum resolution of the marking pattern required for correct visual measurement is P min
Preferably, the interior pattern is provided with features to resist shadow occlusion.
Preferably, the extracting the feature means extracting an edge feature of the complete identification pattern or the internal pattern by an image processing technology, and using an actual size of the edge feature as a measurement parameter.
Preferably, the threshold height h' is:
Figure GDA0003501866240000031
the other purpose of the invention is realized by the following technical scheme:
the utility model provides an unmanned aerial vehicle vision guide is from system of falling, is including installing the monocular camera, installing at the inside embedded vision processor of unmanned aerial vehicle and the flight control computer in unmanned aerial vehicle ventral bottom, its characterized in that:
when the unmanned aerial vehicle flies to an effective area above a landing point, the monocular camera shoots a target scene image and transmits the target scene image to the embedded visual processor frame by frame; the target scene image comprises an identification pattern, and an internal pattern is arranged in the middle of the identification pattern;
the embedded vision processor is used for processing the target scene image frame by frame, identifying the identification pattern, extracting the characteristics, solving the relative position of the unmanned aerial vehicle relative to the landing point, and sending the relative position data of the unmanned aerial vehicle and the landing point to the flight control computer according to a certain protocol format;
and the flight control computer controls the unmanned aerial vehicle to complete centering with the landing point according to the relative position of the unmanned aerial vehicle relative to the landing point and descend to the landing point at a constant speed.
Preferably, the flight control computer is further configured to control the lighting device to illuminate the identification pattern in the event of insufficient light.
The unmanned aerial vehicle landing method has the advantages that after the unmanned aerial vehicle flies above the landing point and enters an effective range, the relative position between the unmanned aerial vehicle and the landing point is accurately calculated through a monocular vision guiding means and is sent to a flight control computer of the unmanned aerial vehicle, and the unmanned aerial vehicle can be guided to land at an appointed place accurately in a whole period of time by adopting a mode of lighting identification patterns under the condition of insufficient light.
Drawings
Fig. 1 is a schematic flowchart of a method for autonomous landing guided by vision of an unmanned aerial vehicle according to an embodiment.
Fig. 2 is a schematic diagram of the active area above the landing point.
Fig. 3 is a schematic diagram of a layout of a logo.
Fig. 4 is a high precision satellite/vision measurement data plot for altitude Z.
Fig. 5 is a graph of X-direction high precision satellite/vision measurement data.
Fig. 6 is a Y-direction high precision satellite/vision measurement data plot.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples.
Example one
The embodiment provides an unmanned aerial vehicle vision-guided autonomous landing method, which comprises the following steps:
step 1: after the unmanned aerial vehicle flies to the effective area above the landing point, a monocular camera installed under the belly of the unmanned aerial vehicle shoots a target scene image.
Referring to fig. 2, the effective area is an inverted circular truncated cone, and the height of the upper bottom of the circular truncated cone from the descending point is h 1 The height of the lower bottom of the circular truncated cone from the descending point is h 2 The radius of the upper bottom of the circular truncated cone is r 1 The radius of the lower bottom of the circular truncated cone is r 2 The visual angle of the camera is theta, the vertical resolution of the camera is D, and the side length of the complete identification pattern is w 1 Side length of the internal pattern is w 2 Minimum resolution P of the marking pattern required for correct visual measurement min In relation, the range of the effective area is:
Figure GDA0003501866240000041
Figure GDA0003501866240000042
h 1 =r 1 /tan(θ/2)
h 2 =r 2 /tan(θ/2)
when the unmanned aerial vehicle enters the effective area, the identification pattern arranged on the landing point is inevitably contained in the target scene image shot by the camera fixed at the bottom of the belly. Referring to fig. 3, the logo is a square image, an internal pattern is arranged in the middle of the logo, and the internal pattern can be added with a shadow blocking resistant feature, so that the proper identification and measurement can be still performed when the shadow of the object is projected on the pattern.
Step 2: and carrying out frame-by-frame processing on the target scene image, identifying the identification pattern, extracting the characteristics, and solving the relative position of the unmanned aerial vehicle relative to the landing point.
When the calculated height of the unmanned aerial vehicle relative to the landing point is larger than a threshold height h', measuring a relative position by taking the characteristic size of the whole identification pattern as a reference when a next frame of target scene image is identified; when the height of the unmanned aerial vehicle relative to the landing point calculated by the position is lower than the threshold height h', the relative position is measured by taking the characteristic size of the internal pattern in the identification pattern as a reference when the next frame of target scene image is identified.
Extracting the feature refers to extracting the edge feature of the complete identification pattern or the internal pattern through an image processing technology, and using the actual size of the edge feature as a measurement parameter.
The threshold height h' is set in advance to be switched to the height for identifying the internal pattern in order to avoid that the whole identification pattern exceeds the field range of the camera when the height is reduced, and the calculation method comprises the following steps:
Figure GDA0003501866240000051
and step 3: and controlling the unmanned aerial vehicle to complete the centering with the landing point according to the relative position of the unmanned aerial vehicle relative to the landing point, and descending to the landing point at a constant speed.
Example two
The embodiment provides an unmanned aerial vehicle vision guide is system of independently falling, including installing the monocular camera in unmanned aerial vehicle ventral bottom, installing at the inside embedded vision processor of unmanned aerial vehicle and flying to control the computer. The embedded vision processor is connected with the monocular camera through a video interface (such as USB and DVI) and connected with the flight control computer through a data interface (such as a network port and a serial port).
The focal length of the monocular camera is adjusted to certain specific values, and the internal parameters are calibrated in advance under the conditions of the focal lengths. The camera angle of view theta is known, or the camera angle of view theta can be measured in real time through mechanical devices such as a holder and fed back to the unmanned aerial vehicle flight control equipment. When the unmanned aerial vehicle flies to an effective area above a landing point, the monocular camera shoots a target scene image and transmits the target scene image to the embedded visual processor frame by frame. The target scene image includes a mark pattern, and the effective region and the mark pattern are the same as those described in the first embodiment, and are not repeated here.
The embedded vision processor is used for processing the target scene image frame by frame, identifying the identification pattern, extracting the characteristics, solving the relative position of the unmanned aerial vehicle relative to the landing point, and sending the relative position data of the unmanned aerial vehicle and the landing point to the flight control computer according to a certain protocol format.
When the calculated height of the unmanned aerial vehicle relative to the landing point is larger than a threshold height h', measuring the relative position by taking the characteristic size of the whole identification pattern as a reference when identifying the next frame of target scene image; when the height of the unmanned aerial vehicle relative to the landing point calculated by the position is lower than the threshold height h', the relative position is measured by taking the characteristic size of the internal pattern in the identification pattern as a reference when the next frame of target scene image is identified.
Extracting the feature refers to extracting the edge feature of the complete identification pattern or the internal pattern through an image processing technology, and using the actual size of the edge feature as a measurement parameter.
The threshold height h' is set in advance to be switched to the height for recognizing the internal pattern in order to avoid that the whole mark pattern exceeds the field range of the camera when the height is reduced, and the calculation method comprises the following steps:
Figure GDA0003501866240000061
and the flight control computer controls the unmanned aerial vehicle to complete centering with the landing point according to the relative position of the unmanned aerial vehicle relative to the landing point and descend to the landing point at a constant speed.
Under the not enough condition of light, the flight control computer can also control lighting apparatus and throw light on to the identification pattern, guarantees to use under night, the dark surrounds.
In the whole landing process, the high-precision satellite measurement data is taken as the reference, the vision measurement data is converted by a coordinate system to obtain the position coordinates (X, Y, Z) of the mass center of the airplane relative to the landing point, and the position coordinates are shown in fig. 4-6, wherein fig. 4 is a high-precision satellite/vision measurement data curve of the height Z, fig. 5 is a high-precision satellite/vision measurement data curve of the X direction, fig. 6 is a high-precision satellite/vision measurement data curve of the Y direction, and the centering precision (X, Y direction) is in centimeter level and the height Z precision is in decimeter level.
In conclusion, the invention provides a simple, reliable and high-precision visual guidance means for autonomous landing of the rotor unmanned aerial vehicle, and can provide guarantee for day and night accurate landing of the unmanned aerial vehicle.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made to the present invention by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (5)

1. An unmanned aerial vehicle vision-guided autonomous landing method comprises the following steps:
step 1: after the unmanned aerial vehicle flies to an effective area above a landing point, a monocular camera arranged under the belly of the unmanned aerial vehicle shoots a target scene image; wherein: the target scene image comprises an identification pattern, and an internal pattern is arranged in the middle of the identification pattern; the effective area is an inverted round table, and the height of the upper bottom of the round table from a landing point is h 1 The height of the lower bottom of the circular truncated cone from the descending point is h 2 The radius of the upper bottom of the circular truncated cone is r 1 The radius of the lower bottom of the circular truncated cone is r 2 The visual angle of the camera is theta, the vertical resolution of the camera is D, and the side length of the complete identification pattern is w 1 Side length of the internal pattern is w 2 The minimum resolution of the marking pattern required for correct visual measurement is P min The range of the effective area is:
Figure FDA0003501866230000011
Figure FDA0003501866230000012
h 1 =r 1 /tan(θ/2)
h 2 =r 2 /tan(θ/2);
step 2: carrying out frame-by-frame processing on the target scene image, identifying the identification pattern, extracting the characteristics, and solving the relative position of the unmanned aerial vehicle relative to the landing point; wherein: the threshold height h' is:
Figure FDA0003501866230000013
when the calculated height of the unmanned aerial vehicle relative to the landing point is larger than a threshold height h', measuring a relative position by taking the characteristic size of the whole identification pattern as a reference when identifying the next frame of target scene image; when the height of the unmanned aerial vehicle calculated by the position relative to the landing point is lower than a threshold height h', measuring the relative position by taking the characteristic size of an internal pattern in the identification pattern as a reference when identifying the next frame of target scene image;
and step 3: and controlling the unmanned aerial vehicle to complete the centering with the landing point according to the relative position of the unmanned aerial vehicle relative to the landing point, and descending to the landing point at a constant speed.
2. The unmanned aerial vehicle vision-guided autonomous landing method of claim 1, wherein the inner pattern is provided with a shadow blocking resistant feature.
3. The unmanned aerial vehicle vision-guided autonomous landing method according to claim 1, wherein the feature extraction is to extract an edge feature of a complete identification pattern or an internal pattern by an image processing technology, and use an actual size of the edge feature as a measurement parameter.
4. The utility model provides an unmanned aerial vehicle vision guide is from system of falling, is including installing the monocular camera, installing at the inside embedded vision processor of unmanned aerial vehicle and the flight control computer in unmanned aerial vehicle ventral bottom, its characterized in that:
when the unmanned aerial vehicle flies to an effective area above a landing point, the monocular camera shoots a target scene image and transmits the target scene image to the embedded visual processor frame by frame; the target scene image comprises a mark pattern, and an internal pattern is arranged in the middle of the mark pattern; the effective area is an inverted round table, and the height of the upper bottom of the round table from a landing point is h 1 The height of the lower bottom of the circular truncated cone from the descending point is h 2 The radius of the upper bottom of the circular truncated cone is r 1 The radius of the lower bottom of the circular truncated cone is r 2 The visual angle of the camera is theta, the vertical resolution of the camera is D, and the side length of the complete identification pattern is w 1 Side length of the internal pattern is w 2 The minimum resolution of the marking pattern required for correct visual measurement is P min The range of the effective area is:
Figure FDA0003501866230000021
Figure FDA0003501866230000022
h 1 =r 1 /tan(θ/2)
h 2 =r 2 /tan(θ/2);
the embedded vision processor is used for processing the target scene image frame by frame, identifying the identification pattern, extracting the characteristics, solving the relative position of the unmanned aerial vehicle relative to the landing point, and sending the relative position data of the unmanned aerial vehicle and the landing point to the flight control computer according to a certain protocol format; wherein: the threshold height h' is:
Figure FDA0003501866230000023
when the calculated height of the unmanned aerial vehicle relative to the landing point is larger than a threshold height h', measuring a relative position by taking the characteristic size of the whole identification pattern as a reference when identifying the next frame of target scene image; when the height of the unmanned aerial vehicle calculated by the position relative to the landing point is lower than a threshold height h', measuring the relative position by taking the characteristic size of an internal pattern in the identification pattern as a reference when identifying the next frame of target scene image; and the flight control computer controls the unmanned aerial vehicle to complete the centering with the landing point according to the relative position of the unmanned aerial vehicle relative to the landing point, and the unmanned aerial vehicle descends to the landing point at a constant speed.
5. The system of claim 4, wherein the flight control computer is further configured to control the illumination device to illuminate the identification pattern in the event of insufficient lighting.
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