CN113917934B - Unmanned aerial vehicle accurate landing method based on laser radar - Google Patents
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Abstract
The invention discloses a laser radar-based unmanned aerial vehicle accurate landing method, which comprises the following steps: the unmanned aerial vehicle collects ground information (namely point cloud data) by using a laser radar; extracting characteristic information of the ground mark by processing the point cloud data, and finding out a required outline key point; controlling the unmanned aerial vehicle to reach the upper air of the ground mark center and descend according to the contour key points and the information calculated by the current height of the unmanned aerial vehicle; the unmanned aerial vehicle carries out some necessary inspections when continuously descending, including to unmanned aerial vehicle current altitude, whether ground sign exists, whether unmanned aerial vehicle deviates from the centre of a circle of ground sign and inspects until unmanned aerial vehicle accurately descends to ground sign center. The method can enable the unmanned aerial vehicle to acquire the position information of the landing point in real time, solves the problem of relative pose lag in the descending process, can accurately keep the position to the center of the landmark, and simultaneously meets the requirement that the unmanned aerial vehicle lands at a preset position in the daytime, at night and in light foggy days, and has high landing precision and high reliability.
Description
Technical Field
The invention belongs to the technical field of unmanned aerial vehicle flight control, relates to an unmanned aerial vehicle landing method, and particularly relates to an unmanned aerial vehicle accurate landing method based on a laser radar
Background
Unmanned aerial vehicle landing control is one of the key technologies in unmanned aerial vehicle flight control technical field, unmanned aerial vehicle safe and accurate drops to the assigned position, is unmanned aerial vehicle successful completion task and retrieve the prerequisite. At present, unmanned aerial vehicle autonomous landing technology mainly comprises unmanned aerial vehicle landing by remote control through subjective experience of an operator, unmanned aerial vehicle landing by adopting GPS (Global Positioning System ) and unmanned aerial vehicle landing technology based on vision. The prior art has the following disadvantages:
1. the accuracy and effectiveness of the unmanned aerial vehicle operator to remotely control the unmanned aerial vehicle for landing is severely dependent on the subjective experience of the unmanned aerial vehicle operator.
2. Unmanned aerial vehicle landing mode based on GPS location is limited by GPS precision and GPS signal intensity, loss of GPS signal or too low accuracy of received positioning information can cause irrecoverable loss in unmanned aerial vehicle landing process, and the method can not meet the requirement of unmanned aerial vehicle accurate landing.
3. And (3) placing a visual identifier to a designated landing place in a visual unmanned aerial vehicle landing mode, and realizing visual auxiliary landing by using a camera and an image processing method. The method can improve the landing accuracy of the unmanned aerial vehicle to a certain extent, but has certain limitation.
Firstly, performing complex processing on an image based on a visual method, and then acquiring landmark coordinate information required by an unmanned aerial vehicle controller through an image coordinate system-camera coordinate system-unmanned aerial vehicle body coordinate system change process; the image processing and coordinate transformation processes consume a large amount of hardware resources, the calculation power of the unmanned aerial vehicle onboard computer is limited, the obtained landmark images cannot be processed in real time and are transformed through a series of coordinates, and therefore the landmark position information obtained by the unmanned aerial vehicle has hysteresis (the calculated pose is behind the real-time pose).
Secondly, the imaging of the landmarks obtained by the vision-based method is limited by illumination conditions, so that the vision-based unmanned aerial vehicle landing method has single application scene and cannot adapt to unmanned aerial vehicle landing under complex working conditions (the complex working conditions refer to the conditions that the unmanned aerial vehicle can work in daytime, night and slight foggy days at the same time).
Finally, during the landing of the unmanned aerial vehicle, the size and the image size in the visual field can change along with the change of the body position, which can lead to the loss of the landmark, namely the identification of the landmark can be seriously influenced by the relative position of the ground mark and the unmanned aerial vehicle.
Disclosure of Invention
The invention aims to overcome the defect that the reliability of the existing unmanned aerial vehicle in a manual landing mode is not high; the landing accuracy is too low in a GPS landing mode; the unmanned aerial vehicle accurate landing method based on the laser radar is large in calculated amount, large in occupied hardware resources and difficult to work under complex working conditions.
In order to achieve the above purpose, the invention adopts the following technical scheme:
an unmanned aerial vehicle accurate landing method based on laser radar comprises the following steps:
S1, designing a circular boss type ground mark;
S2, the unmanned aerial vehicle acquires ground information (point cloud data) in real time through a laser radar;
S3, processing laser radar point cloud data, extracting characteristic information of a circular boss type ground mark, and finding out a required outline key point;
S4, controlling the unmanned aerial vehicle to reach the upper air of the center of the round boss type ground mark and start descending according to the contour key points and the information calculated by the current height of the unmanned aerial vehicle;
S5, the unmanned aerial vehicle continuously drops, and some necessary checks are carried out, including checking whether the current height of the unmanned aerial vehicle exists or not and whether the unmanned aerial vehicle deviates from the circle center of the circular boss type ground mark or not until the unmanned aerial vehicle accurately drops to the ground mark center.
Further, the circular boss ground mark in the step S1 is formed by combining two concentric cylinders with the height h and the radius r 1、r2 and a telescopic triangular bracket; wherein the height h of the two cylinders is greater than the minimum resolution of the lidar, and can be distinguished significantly by the lidar; r 1 is larger than the radius of the circumcircle of the unmanned aerial vehicle so as to ensure that the unmanned aerial vehicle has enough landing space and cannot fall down, and the radius of r 2 meets that r 2-r1 is larger than the resolution of the laser radar; the telescopic tripod ensures that the landmark can ensure the level of the boss type ground mark for landing on uneven ground, and ensures that the unmanned aerial vehicle can stably land on the ground mark.
Further, in step S2, the unmanned aerial vehicle-mounted laser radar is installed at the center of the right lower side of the machine body, the 0-angle direction of the laser radar is vertically downward of the machine body, and a vertically downward scattering beam is emitted to obtain ground characteristic information on a projection line (i.e. concave-convex information of the terrain is reflected in the point cloud data); the laser radar adopts a single-line laser radar, the laser radar scans along the direction of a machine head and a machine tail, scattered beams are projected to the ground to form a line, and ground information of the advancing direction of the unmanned aerial vehicle is collected in real time.
Further, in step S3, the specific process of processing Lei Dadian cloud data is:
S301, increasing the data density of point cloud: the multi-frame laser radar point cloud data acquired at the same position of the unmanned aerial vehicle are fused, so that the density of the point cloud data is improved;
s302, filtering the point cloud data with increased density: adopting a straight-through filter to retain point cloud data with the depth of the point cloud data smaller than 6 m;
s303, transforming the point cloud data: the original point cloud data is in a polar coordinate system form with an origin as a laser radar center, and the height difference between the point cloud data can be obtained through triangular calculation, so that the point cloud data in the form of the height difference is obtained; thus obtaining two forms of point cloud data.
Further, in step S3, the extracting the feature information of the circular boss type ground identifier, and finding the specific content of the required contour key point is as follows:
S304, acquiring a characteristic function of the point cloud data by adopting a mobile least square method, namely fitting the point cloud data into a piecewise function; when the point cloud data contains the characteristic information of the boss type ground mark (the characteristic function fitted by the point cloud data accords with the characteristic function of the boss type ground mark), the unmanned aerial vehicle is represented to reach the upper air of the landing position;
S305, extracting outline key points from point cloud data containing boss type ground marks: the outline key points are the intersection points of the laser radar beam surface and the edges of the inner circle and the outer circle of the boss type ground mark; the height difference of the two circular tables in the boss type ground mark is a segment with a slope in the image of the characteristic function, and the end point of the segment is a contour key point to be extracted; contour key points can be extracted according to the geometric relation between each segment in the feature function;
S306, performing feature detection and comparison of contour key point extraction results on two types of point cloud data, so that the correctness of the features and contour key points of the currently detected boss ground marks can be cross-verified; further, it is verified that the unmanned aerial vehicle has reached a predetermined descent position, and the contour key points have been found accurately.
Further, step S4 obtains the intersection point (outline key point) of the laser radar beam surface and the edges of the inner circle and the outer circle of the boss type ground mark according to step S3, and triangular calculation is carried out on the outline key point of the outermost circle of the boss type ground mark and the 0-degree direction point (the 0-degree direction point comprises the current height information of the unmanned aerial vehicle) of the laser radar to obtain the secant length of the outline key point of the outer circle and the beam surface, namely one chord length of the outer circle; the chord midpoint can be obtained through calculation of the chord length; the distance between the unmanned aerial vehicle and the midpoint of the chord and the current height of the unmanned aerial vehicle are information needed by us; then the unmanned aerial vehicle moves to a chord midpoint, the laser radar scanning method rotates 90 degrees to obtain another chord length chord midpoint, the chord length at the moment is the diameter of the excircle, and the chord midpoint is the circle center of the excircle; the unmanned aerial vehicle moves to the circle center, namely, the unmanned aerial vehicle reaches the center of the circular boss type ground mark to the air; the drone then begins to descend.
Further, in the step S5, in the real-time descending process of the unmanned aerial vehicle, the operation of the step S4 is performed all the time, the height of the unmanned aerial vehicle is continuously detected, the center coordinates are calculated, when the unmanned aerial vehicle deviates from the center, the unmanned aerial vehicle is corrected to the center position through the step S4, the scanning result does not accord with the characteristics of the boss type ground mark, and the height of the unmanned aerial vehicle is raised and starts from the step S2.
Compared with the prior art, the invention has the following advantages and beneficial effects:
1. the circular boss type ground mark is adopted, so that the characteristics of the ground mark are obviously different from those of the environment, and the circular boss design ensures that the unmanned aerial vehicle can recognize the information of the ground mark in any direction to have unique characteristic information, so that the ground mark can be effectively and uniquely recognized.
2. The invention can detect the current height of the unmanned aerial vehicle and the size and position of the ground mark in real time, and can accurately find the circle center of the position to be landed by adopting a 90-degree crisscross scanning mode in the landing process, and the unmanned aerial vehicle does not depend on manual experience and GPS signals in the landing process, thereby having high reliability and high precision.
3. Compared with a vision-based unmanned aerial vehicle landing method, in the data acquisition process, the vision-based method needs to acquire the same amount of data (p times p data) with the same camera resolution, and only p point cloud data are needed for a single-line laser radar; the camera acquires images with distortion effect, so that the method has high landing precision, can reduce the acquired redundant data quantity and improves the real-time performance of pose feedback.
4. The invention can enable the unmanned aerial vehicle to drop to the preset position in the daytime, at night and in slight fog days, and compared with the existing other unmanned aerial vehicle landing methods, the invention meets the requirement of complex working conditions.
Drawings
FIG. 1 is an overall flow block diagram of a laser radar-based unmanned aerial vehicle accurate landing method of the present invention;
FIG. 2 is a schematic diagram of a boss type ground mark structure used in the present invention;
fig. 3 is a schematic diagram of the ground identification extraction feature of the unmanned aerial vehicle-mounted laser radar;
Fig. 4 is a schematic diagram of a center point of a ground mark found by an unmanned aerial vehicle.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments.
As shown in fig. 1, the invention relates to a laser radar-based unmanned aerial vehicle accurate landing method, which comprises the following specific steps:
step S1: designing a round boss type ground mark.
The invention relates to a round boss ground mark for unmanned plane landing, which is formed by combining two concentric cylinders with the height of h and the radius of r 1、r2 and a telescopic triangular bracket, and is particularly shown in figure 2. Wherein the height h of the two cylinders is larger than the minimum resolution res of the laser radar, and can be distinguished by the laser radar obviously; r 1 is larger than the radius of the circumcircle of the unmanned aerial vehicle so as to ensure that the unmanned aerial vehicle has enough landing space and cannot fall down, and the radius of r 2 meets that r 2-r1 is larger than the resolution of the laser radar; the telescopic tripod ensures that the landmark can ensure the level of the boss type ground mark for landing on uneven ground, and ensures that the unmanned aerial vehicle can stably land on the ground mark.
Step S2: the unmanned aerial vehicle collects ground information (point cloud data) in real time through a laser radar arranged right below the carrying machine body, and particularly collects the point cloud data of the ground mark of the circular boss in the step S1.
In specific implementation, the unmanned aerial vehicle-mounted laser radar is installed at the center under the machine body, the 0-angle direction of the laser radar is vertical downwards to the unmanned aerial vehicle body, and the vertical downwards scattering beam is emitted to acquire the characteristic information on the projection line, as shown in fig. 3, wherein the included angle between the laser beam and the 0-angle direction is (theta i). In order to reduce the calculated amount and improve the real-time performance of data, the laser radar adopts a single-line laser radar, the laser radar scans along the direction of a machine head and a machine tail, scattered beams are projected to the ground to form a line, and ground information of the advancing direction of the unmanned aerial vehicle is collected in real time.
Step S3: and (3) processing the laser radar point cloud data obtained in the step (S2), extracting ground identification features, and finding out required contour key points.
In specific implementation, as shown in fig. 4, the unmanned aerial vehicle flies to the s point first in the landing process, and then ground information is collected; the specific method comprises the following steps:
Step S301: and when data are acquired, multi-frame laser radar data acquired at the same position of the unmanned aerial vehicle are fused, so that the point cloud density is improved.
Step S302: filtering the point cloud data with the increased density in the step S301, and adopting a straight-through filter to retain the point cloud data with the depth of less than 6 m;
Step S303: transforming the point cloud data subjected to S302 filtering, wherein the original point cloud data is in a polar coordinate system form with an origin as a laser radar center, and the height difference between the point cloud data can be obtained through triangular calculation, so that the point cloud data in a height difference form is obtained; thus obtaining two forms of point cloud data.
The two forms of point cloud data processed in step S303 are then subjected to the following steps S304 and S305.
Step S304: acquiring a characteristic function of the point cloud data by adopting a mobile least square method, namely fitting the point cloud data into a piecewise function; when the point cloud data contains the characteristic information of the boss type ground mark (the characteristic function fitted by the point cloud data accords with the characteristic function of the boss type ground mark), the unmanned aerial vehicle is represented to reach the upper air of the landing position;
step S305: extracting outline key points from point cloud data containing boss type ground marks: the outline key points are the intersection points of the laser radar beam surface and the edges of the inner circle and the outer circle of the boss type ground mark; the height difference of the two circular tables in the boss type ground mark is a segment with a slope in the image of the characteristic function, and the end point of the segment is a contour key point to be extracted; contour key points can be extracted according to the geometric relation between each segment in the feature function;
Step S306: through the steps 304 and 305, we obtain the feature detection result and the contour key point in the polar coordinate form, and the feature detection result and the contour key point in the relative height difference form; the correctness of the characteristics and the outline key points of the currently detected boss ground marks can be cross-verified by comparing the characteristic detection results and the outline key points under the two forms; further, it is verified that the drone has reached the vicinity of the descent location and has accurately found the contour keypoints.
Step S4: acquiring the intersection point (contour key point) of the laser radar beam surface and the edges of the inner circle and the outer circle of the boss type ground mark according to the step S3, performing triangular calculation on the contour key point a (R a,θa)、b(Rb,θb) of the outermost circle of the boss type ground mark and the 0-degree direction point (R s, 0) of the laser radar (the 0-degree direction point comprises the current height information of the unmanned aerial vehicle) to obtain the secant length of the contour key point of the outer circle and the beam surface, namely one chord length l of the outer circle; the distance d between the chord midpoint and the distance chord midpoint of the unmanned aerial vehicle can be calculated through the chord length;
The specific way of solving the chord lengths l and d is as follows:
The distance between the unmanned aerial vehicle and the midpoint of the chord and the current height of the unmanned aerial vehicle are information needed by us; then the unmanned aerial vehicle moves to a chord midpoint, the laser radar scanning method rotates 90 degrees to obtain another chord length chord midpoint, the chord length at the moment is the diameter of the excircle, and the chord midpoint is the circle center of the excircle; the unmanned aerial vehicle moves to the center of the circle and begins to descend.
Step S5: the drone continues to land and performs the necessary checks. Considering that the unmanned aerial vehicle has external disturbance in the landing process, whether the characteristic information of the boss type ground mark is contained in the current laser radar point cloud is verified again every time the unmanned aerial vehicle lands at a certain height, and if the characteristic information of the boss type ground mark is lost, the unmanned aerial vehicle ascends at a certain height to search the characteristic information of the boss type ground mark. In the descending process of the unmanned aerial vehicle, the unmanned aerial vehicle deviates from the circle center due to external disturbance, so that the airborne laser radar can perform 90-degree cross scanning again when the unmanned aerial vehicle descends to a certain height, and the circle center of a descending point is found until the unmanned aerial vehicle precisely descends to a boss type ground identification center appointed by people.
The above embodiments are merely examples, but the present invention is not limited to the above embodiments. Even if various changes are made to the present invention, it is within the scope of the appended claims and their equivalents to fall within the scope of the invention.
Claims (6)
1. An unmanned aerial vehicle accurate landing method based on a laser radar is characterized by comprising the following steps:
S1, designing a circular boss type ground mark;
s2, the unmanned aerial vehicle acquires ground information, namely point cloud data, in real time through a laser radar;
S3, processing laser radar point cloud data, extracting characteristic information of a circular boss type ground mark, and finding out a required outline key point;
S4, controlling the unmanned aerial vehicle to reach the upper air of the center of the round boss type ground mark and start descending according to the contour key points and the information calculated by the current height of the unmanned aerial vehicle;
S5, continuously landing the unmanned aerial vehicle, and carrying out necessary checks, wherein the check comprises that whether the ground mark exists at the current height of the unmanned aerial vehicle or not, and whether the unmanned aerial vehicle deviates from the circle center of the circular boss type ground mark or not until the unmanned aerial vehicle accurately lands at the center of the ground mark;
Step S1, the circular boss type ground mark is formed by combining two concentric cylinders with the height of h and the radius of r 1、r2 and a telescopic triangular bracket; the height h of the two cylinders is larger than the minimum resolution of the laser radar, and can be obviously distinguished by the laser radar; r 1 is larger than the radius of the circumcircle of the unmanned aerial vehicle, so that the unmanned aerial vehicle is guaranteed to have enough landing space and cannot fall down, and the radius of r 2 meets that r 2-r1 is larger than the laser radar resolution; the telescopic triangular bracket can ensure that the landmark can ensure the level of the boss type ground mark for landing on uneven ground, and ensure that the unmanned aerial vehicle can stably land on the ground mark.
2. The unmanned aerial vehicle accurate landing method based on the laser radar according to claim 1, wherein in the step S2, the laser radar is installed at the center under the unmanned aerial vehicle body, the 0-angle direction of the laser radar is vertical downwards to the unmanned aerial vehicle body, and the vertical downwards scattering beam is emitted to obtain ground characteristic information on a projection line, namely, the concave-convex information of the terrain is reflected in the point cloud data; the laser radar adopts a single-line laser radar, the laser radar scans along the direction of the head and the tail of the unmanned aerial vehicle, scattered beams are projected on the ground to form a line, and ground information of the advancing direction of the unmanned aerial vehicle is collected in real time.
3. The unmanned aerial vehicle accurate landing method based on the laser radar according to claim 1, wherein in the step S3, the specific content and method steps for processing the laser radar point cloud data include:
(1) Increasing the point cloud data density: the multi-frame laser radar point cloud data acquired at the same position of the unmanned aerial vehicle are fused, so that the density of the point cloud data is improved;
(2) Filtering the point cloud data with increased density: adopting a straight-through filter to retain point cloud data with the depth of the point cloud data smaller than 6 m;
(3) Transforming the point cloud data: the original point cloud data is in a polar coordinate system form with an origin as a laser radar center, and the height difference between the point cloud data is obtained through triangular solution to obtain the point cloud data in a height difference form; two forms of point cloud data are obtained.
4. The unmanned aerial vehicle accurate landing method based on the laser radar according to claim 3, wherein in step S3, the feature information of the circular boss type ground mark is extracted, and the two types of point cloud data according to claim 3 are simultaneously subjected to the following operations for finding the required outline key points:
(1) Acquiring a characteristic function of the point cloud data by adopting a mobile least square method, and fitting the point cloud data into a piecewise function; when the point cloud data contains the characteristic information of the boss type ground mark, namely, the characteristic function fitted by the point cloud data accords with the characteristic function of the boss type ground mark, the unmanned aerial vehicle is represented to reach the upper air of the landing position;
(2) Extracting outline key points from point cloud data containing boss type ground marks: the outline key points are the intersection points of the laser radar beam surface and the edges of the inner circle and the outer circle of the boss type ground mark; the height difference of the two circular tables in the boss type ground mark is a segment with a slope in the image of the characteristic function, and the end point of the segment is a contour key point to be extracted; according to the geometric relation between each segment in the feature function, the outline key points can be extracted;
(3) By comparing the feature detection and the contour key point extraction results of the two types of point cloud data, the correctness of the feature and the contour key point of the currently detected boss ground mark can be cross-verified; further, it is verified that the unmanned aerial vehicle has reached the vicinity of the predetermined descent position, and the contour key points have been found accurately.
5. The method for accurately landing the unmanned aerial vehicle based on the laser radar according to claim 1, wherein in the step S4, the specific flow for controlling the unmanned aerial vehicle to reach the upper air of the circular boss type ground mark center and start descending according to the contour key points and the information calculated by the current height of the unmanned aerial vehicle is as follows:
(1) The contour key point of the outermost circle of the boss type ground mark and the 0-degree direction point of the laser radar, namely, the 0-degree direction point comprises the current height information of the unmanned aerial vehicle, triangular calculation is carried out to obtain the secant length of the contour key point of the outer circle and the beam surface, namely, one chord length of the outer circle; obtaining a chord midpoint through chord length calculation; the distance between the unmanned aerial vehicle and the midpoint of the chord and the current height of the unmanned aerial vehicle are required information;
(2) The unmanned aerial vehicle moves to a chord midpoint, the laser radar scanning method rotates 90 degrees to obtain another chord length and the chord midpoint, the chord length at the moment is the diameter of the excircle, and the chord midpoint is the center of the excircle; the unmanned aerial vehicle moves to the circle center, namely, the unmanned aerial vehicle reaches the center of the circular boss type ground mark to the air; the drone then begins to descend.
6. The laser radar-based unmanned aerial vehicle accurate landing method according to claim 1, wherein in the continuous descending process of the unmanned aerial vehicle in the step S5, the unmanned aerial vehicle height is continuously detected through the laser radar, the center coordinates of the boss type ground mark are calculated, when the deviation from the center occurs, the unmanned aerial vehicle is corrected to the center position through the step S4, and when the feature extraction result does not accord with the feature of the boss type ground mark, the unmanned aerial vehicle height is raised and the step S2 starts.
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