阅读说明：本技术 基于激光雷达的无人机自主识别着陆选址方法 (Unmanned aerial vehicle autonomous landing site selection method based on laser radar ) 是由 罗世彬 胡茂青 于 2020-04-10 设计创作，主要内容包括：本发明提供一种基于激光雷达的无人机自主识别着陆选址方法,包括如下步骤,步骤1：预先在基准图上选好着陆候选区域,并通过机载可见光相机拍摄的实时图像与基准图像匹配；步骤2：机载激光雷达在200米高度,根据高度和视场角推算出选址搜索范围,根据高度和激光雷达距离误差参数,计算出距离误差,还需要识别地面坡度识别结果,进行选址,确定精确的安全降落区域；步骤3：机载激光雷达在100米高度,根据高度和视场角推算出选址搜索范围；根据高度和激光雷达距离误差参数,可以计算出距离误差,确保有效检测地面超过0.1m的障碍物。本发明具有精度高,成本小,适应性强等特点。(The invention provides an unmanned aerial vehicle autonomous landing site selection method based on a laser radar, which comprises the following steps of 1: selecting a landing candidate area on a reference image in advance, and matching a real-time image shot by an airborne visible light camera with the reference image; step 2: the method comprises the steps that when an airborne laser radar is 200 meters in height, a site selection searching range is calculated according to the height and the field angle, a distance error is calculated according to the height and a laser radar distance error parameter, a ground slope identification result needs to be identified, site selection is carried out, and an accurate safe landing area is determined; and step 3: calculating the address selection search range according to the height and the field angle of the airborne laser radar at the height of 100 meters; according to the height and the laser radar distance error parameters, the distance error can be calculated, and the effective detection of the obstacle with the ground exceeding 0.1m is ensured. The invention has the characteristics of high precision, low cost, strong adaptability and the like.)

1. An unmanned aerial vehicle autonomous landing site selection method based on laser radar is characterized by comprising the following steps:

step 1: selecting a landing candidate area on a reference image in advance, and matching a real-time image shot by an airborne visible light camera with the reference image;

step 2, the airborne laser radar images the ground by a 30-degree × 30-degree visual field at the height of 200 meters, a location searching range is calculated according to the height and the visual field angle, a distance error is calculated according to the height and the distance error parameter of the laser radar, a ground slope identification result needs to be identified, the location is selected, and an accurate safe landing area is determined;

and 3, imaging the ground by the airborne laser radar at the height of 100 meters and a 9-degree × 9-degree view field, calculating a site selection search range according to the height and the view field angle, and calculating a distance error according to the height and the distance error parameter of the laser radar so as to ensure that the obstacle of which the ground exceeds 0.1m is effectively detected.

2. The unmanned aerial vehicle autonomous landing site selection method based on laser radar as claimed in claim 1,

the step 1 is specifically that the thickness is previously 1000 × 1000m²Is manually selected to be 150 × 150m on the reference picture²Is a landing candidate area; and at 500 m, matching a real-time image shot by the airborne visible camera with a reference image, and resolving and positioning the position of the aircraft by using PNP.

3. The unmanned aerial vehicle autonomous landing site selection method based on laser radar as claimed in claim 2, wherein in step 1, a plurality of multipoint matching schemes are used during matching, so as to improve positioning accuracy.

4. The unmanned aerial vehicle autonomous landing site selection method based on laser radar as claimed in claim 1,

the step 2 is specifically that the airborne laser radar images the ground in a 30-degree × 30-degree view field at the height of 200 meters;

an address selection search range of about 107 × 107m is calculated according to the height and the field angle²Calculating a Ground Sample Distance (GSD) to be 0.2m according to the laser radar resolution 512 × 512, and calculating a Distance error E to be 0.1m according to the height and the laser radar Distance error parameter;

assuming that the size of a detection target is S, GSD should be controlled below S/3, E (one time) is controlled below S/6, obstacles can be effectively detected, and obstacles with the ground surface exceeding 0.6m can be identified;

in addition, the area with the ground gradient exceeding the range of (-15 degrees and 15 degrees) needs to be identified, and then obstacle detection and gradient identification results are combined for addressing.

5. The unmanned aerial vehicle autonomous landing site selection method based on laser radar as claimed in claim 1,

the step 3 is specifically that the airborne laser radar images the ground in a field of view of 9 degrees × 9 degrees at the height of 100 meters;

according to height and field of viewAngle-deducing address-selecting search range 16 × 16m²Calculating the Ground Sample Distance (GSD) to be 0.3m according to the laser radar resolution 512 × 512;

calculating the distance error E at the moment to be 0.05m according to the height and the laser radar distance error parameters;

assuming that the size of the detection target is S, the GSD is controlled below S/3, and the E is controlled below S/6 (one time), the obstacle can be effectively detected.

6. The unmanned aerial vehicle autonomous landing site selection method based on lidar of claim 5, wherein in step 2, if the lidar range error parameter is doubled, it is not ensured that an obstacle above 0.1m on the ground is effectively detected, and if the lidar range error parameter is tripled, it is ensured that an obstacle above 0.1m on the ground is effectively detected.

Technical Field

The invention relates to the technical field of unmanned aerial vehicle autonomous identification, in particular to an unmanned aerial vehicle autonomous identification landing site selection method based on a laser radar.

Background

The landing of an airplane during approach is an important stage for executing a combat mission and is mainly characterized by low flying speed and altitude, great influence by meteorological conditions, geographic environment and other factors and high requirement on the driving technology of a pilot. Therefore, the number of flight accidents, especially serious flight accidents, occurring at this stage is relatively large. Therefore, drones play an increasingly important role in performing flight missions. The safety problem of the unmanned aerial vehicle is more prominent because no driver is provided in the autonomous landing process. Whether the unmanned aerial vehicle can land safely and accurately is directly related to whether the unmanned aerial vehicle can safely and smoothly recover and whether the flight task can be completed satisfactorily. Aiming at the safety problem of the unmanned aerial vehicle in the landing stage, the autonomous landing technology becomes an important content for research of researchers in various countries.

At present, researchers propose a visual guidance method, a microwave guidance method and the like aiming at the autonomous landing problem of an unmanned aerial vehicle.

① visual guidance method, the visual guidance technique is a new guidance technique for applying computer vision to the autonomous landing mode of unmanned aerial vehicle, it uses various imaging systems (such as camera) to replace visual organs as input sensitive means, obtains the position parameters of unmanned aerial vehicle through image processing, secondly, guides the accurate landing of unmanned aerial vehicle by recognizing the ground obstacle on the picture.

The visual sensor has the advantages of portability, low power consumption, small size and the like. In addition, the working wave band of the visual navigation system is far away from the frequency range of the current electromagnetic countermeasure, and the visual navigation system has the advantages of low cost, strong autonomy, large information quantity, passivity, rich information and the like.

② microwave guidance method, for microwave landing guidance technology, the airborne receiver receives the ground azimuth station and elevation station signals to get the azimuth angle of the plane relative to the center line of the runway and the elevation angle relative to the horizontal plane of the runway, and gets the distance of the plane relative to the phase center of the ranging antenna by the way of inquiry response.

The microwave landing guiding technology has high guiding precision and large proportional coverage area, and can provide various approach routes and all-weather guiding functions.

In the autonomous landing process of the unmanned aerial vehicle, the safety problem is particularly outstanding because no driver is available. However, the unmanned aerial vehicle may turn over during the landing stage due to the topographic relief of the ground surface and the raised obstacles.

The core of the vision-based guided landing technology is a vision sensor, but the vision sensor can cause large difference in imaging due to different application scenes. Especially under the bad weather condition, unmanned aerial vehicle machine carries the sensor and hardly obtains more clear image to influence unmanned aerial vehicle safety and the accuracy of independently landing.

The microwave-based guided landing technology needs to establish a ground base station, and has the defects of high manufacturing cost, high requirements on ground and airborne equipment, high replacement cost and the like, so the development of the technology is limited.

Disclosure of Invention

Aiming at the problems, the invention provides an unmanned aerial vehicle autonomous landing site selection method based on a laser radar.

The technical scheme adopted by the invention is as follows:

the invention provides an unmanned aerial vehicle autonomous landing site selection method based on a laser radar, which comprises the following steps:

step 1: selecting a landing candidate area on a reference image in advance, and matching a real-time image shot by an airborne visible light camera with the reference image;

step 2, the airborne laser radar images the ground by a 30-degree × 30-degree visual field at the height of 200 meters, a location searching range is calculated according to the height and the visual field angle, a distance error is calculated according to the height and the distance error parameter of the laser radar, a ground slope identification result needs to be identified, the location is selected, and an accurate safe landing area is determined;

and 3, imaging the ground by the airborne laser radar at the height of 100 meters and a 9-degree × 9-degree view field, calculating a site selection search range according to the height and the view field angle, and calculating a distance error according to the height and the distance error parameter of the laser radar so as to ensure that the obstacle of which the ground exceeds 0.1m is effectively detected.

Preferably, the step 1 is carried out at 1000 × 1000m in advance²Is manually selected to be 150 × 150m on the reference picture²Is a landing candidate area; at 500 m, pass through the machineThe real-time image shot by the visible light camera is matched with the reference image, and the PNP is used for resolving and positioning the position of the aircraft.

Preferably, in the step 1, a plurality of multi-point matching schemes are used during matching, so as to improve the positioning accuracy.

Preferably, the step 2 is implemented by imaging the ground by the airborne laser radar with a 30-degree × 30-degree field of view at the height of 200 meters;

an address selection search range of about 107 × 107m is calculated according to the height and the field angle²Calculating a Ground Sample Distance (GSD) to be 0.2m according to the laser radar resolution 512 × 512, and calculating a Distance error E to be 0.1m according to the height and the laser radar Distance error parameter;

assuming that the size of a detection target is S, GSD should be controlled below S/3, E (one time) is controlled below S/6, obstacles can be effectively detected, and obstacles with the ground surface exceeding 0.6m can be identified;

in addition, the area with the ground gradient exceeding the range of (-15 degrees and 15 degrees) needs to be identified, and then obstacle detection and gradient identification results are combined for addressing.

Preferably, the step 3 is to image the ground by the airborne laser radar at the height of 100 meters and with the field of view of 9 degrees × 9 degrees;

calculating an address searching range of 16 × 16m2 according to the height and the field angle, and calculating a Ground Sample Distance (GSD) of 0.3m according to the laser radar resolution of 512 × 512;

calculating the distance error E at the moment to be 0.05m according to the height and the laser radar distance error parameters;

assuming that the size of the detection target is S, the GSD is controlled below S/3, and the E is controlled below S/6 (one time), the obstacle can be effectively detected.

Preferably, in step 2, if the laser radar distance error parameter is one time, it is not possible to ensure that the obstacle whose ground exceeds 0.1m is effectively detected, and if the laser radar distance error parameter is three times, it is possible to ensure that the obstacle whose ground exceeds 0.1m is effectively detected.

The invention has the beneficial effects that:

(1) the invention provides an unmanned aerial vehicle autonomous landing site selection method based on a laser radar, which has the characteristics of high precision, low cost, strong adaptability and the like.

(2) In the embodiment of the invention, the laser radar has the characteristics of high precision and all-weather guiding capability, can be used for guiding the aircraft to land under the complex meteorological conditions of poor visibility and low cloud base, and has low requirement on airborne equipment.

(3) According to the embodiment of the invention, the real-time image shot by the airborne visible light camera is matched with the reference image, and the position of the aircraft is resolved and positioned by using the PNP, so that the aircraft is guided to fly to the designated area. The guiding method based on visual matching has the characteristics of high precision and low cost.

Drawings

Fig. 1 is a flowchart of an autonomous landing and site selection method for an unmanned aerial vehicle based on a laser radar according to an embodiment of the present invention;

FIG. 2 is a schematic diagram of address selection according to an embodiment of the present invention;

Detailed Description

The conception, the specific structure, and the technical effects produced by the present invention will be clearly and completely described in conjunction with the embodiments below, so that the objects, the features, and the effects of the present invention can be fully understood. It is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments, and those skilled in the art can obtain other embodiments without inventive effort based on the embodiments of the present invention, and all embodiments are within the protection scope of the present invention.

The embodiment of the invention provides an unmanned aerial vehicle autonomous landing site selection method based on a laser radar, which roughly comprises the following steps of:

landing site selection is mainly performed in three stages.

The first stage, on a reference map in advance (range 1000 × 1000 m)²) Artificially selected 150 × 150m²Landing candidate area. At 500 meters, a real-time image shot by the airborne visible light camera is matched with the reference image, and the PNP is used for resolving and positioning the position of the aircraft, so that the aircraft is guided to fly to the designated area. Multiple sheets can be used in matchingAnd the multi-point matching scheme is adopted, so that the positioning precision is improved.

And in the second stage, the airborne laser radar images the ground at the height of 200 meters and with the field of view of 30 degrees × 30 degrees and 30 degrees.A site selection schematic diagram is shown in figure 2.A site selection search range of about 107 × 107m is calculated according to the height and the field angle²According to the laser radar resolution 512 × 512, the Ground Sample Distance (GSD) can be calculated to be about 0.2m, according to the height and laser radar Distance error parameters, the Distance error E at the moment can be calculated to be 0.1m, the detection target size is assumed to be S, the GSD is controlled to be below S/3, the E is controlled to be below S/6 (forward downward view angle imaging, Distance direction measurement Ground concave-convex, obstacle detection Distance precision is higher than GSD), obstacles can be effectively detected, so that the obstacles with the Ground surface exceeding 0.6m can be identified in the stage, in addition, the range area with the Ground gradient exceeding (-15 degrees and 15 degrees) is also identified, the area with the size being more than or equal to 20 × 20m and 20m is selected by integrating obstacle detection and gradient identification results, and address selection²The area meeting the landing condition. Then, in a third phase, a more precise safe landing area is searched again in the area.

And in the third stage, the airborne laser radar images the ground at the height of 100 meters and by using a 9-degree × 9-degree field of view to image the ground, and the address searching range is calculated to be about 16 × 16m according to the height and the field angle²According to the laser radar resolution 512 × 512, the Ground Sample Distance (GSD) can be calculated to be about 0.3m, according to the height and the laser radar Distance error parameter, the Distance error E at the moment can be calculated to be 0.05m, the GSD is supposed to be controlled below S/3, the E is supposed to be controlled below S/6 (one time), and the obstacle can be effectively detected, so according to the conclusion, if the laser radar Distance error parameter is one time, the obstacle exceeding 0.1m on the Ground can not be effectively detected, and if the laser radar Distance error parameter is three times, the obstacle exceeding 0.1m on the Ground can be effectively detected.

According to the scheme, the airborne Flash laser radar images the ground for 2 times at the stages of 200 meters and 100 meters, and imaging data is input to a landing obstacle detection and addressing algorithm to obtain the following output results: the system comprises a Terrain slope analysis Map (TSM), a Terrain Roughness analysis Map (TRM) and an addressing suggestion Map (Hazardcost Map, HCM), wherein the TSM describes the ground slope condition in a form of thermodynamic diagram, the TRM describes the ground Roughness in a form of thermodynamic diagram, and the HCM describes the addressing confidence in a form of thermodynamic diagram.

Elevation Map (EM) estimation

EM estimation is largely divided into three steps, first transferring the lidar point cloud from the lidar coordinate system (L idrarframe) to the ground coordinate system (ground frame) and then projecting the height of each point onto the EM.

TSM estimation

The gradient estimation algorithm is mainly divided into 3 steps

(1) Using 5 x 5m²The window slides over the search area.

(2) The plane P is estimated using a Median least squares estimate (L east Median Square, L MedSq).

(3) The normal vector of the plane P is estimated, resulting in the plane slope. And then returning to the step (1). By repeating the above steps, the gradient can be estimated for all 5 × 5 regions in the search region, so as to obtain a Smooth Surface Map (SSM) and a TSM. Obviously, the step (2) is key to the algorithm, and the basic principle is that a plane can be estimated by using three points:

three non-collinear points (X) on a given plane_a,X_b,X_c) The plane normal and intercept (n, d) are estimated as follows:

n＝(X_b-X_a)×(X_c-X_a)(1)

d＝-n·X_a(2)

if more than 3 points are available, the overdetermined solution can be solved by using the least square method. And the sum of the distances from the plane to each point obtained by least square estimation is minimum.

The plane can be estimated by using median least squares or RANSAC least squares, the plane can be correctly estimated under the condition that the outlier rate is less than 50 percent, the RANSAC least squares can correctly estimate the plane under the condition that the outlier rate is 90 percent, but the time consumption and the iteration number of the RANSAC least squares are obviously higher than L MedSq.

TRM estimation

TRM is the difference between EM and SSM, TRM | EM-SSM |.

HCM estimation

Obtaining TRM and TSM, HCM can be calculated according to the following formula

Wherein (x, y) is the coordinates of HCM, R_tRepresenting a gradient threshold (tolerable maximum gradient), S_tA threshold value representing the ground protrusion distance (maximum protrusion tolerable).

Safe landing site selection

According to the safe landing requirements, sliding calculation and evaluation are performed in the search area by using 5-by-5 windows:

(1) the location within the window containing HCM (x, y) ═ 1 is the unsafe landing area.

(2) And the position with the minimum HCM mean value in the window is the recommended landing position.

It should be noted that, in the embodiment of the present invention,

and (3) autonomous landing: the landing flight process is that the airborne automatic flight system completely controls the aircraft to land and fly.

A visual sensor: instruments that acquire image information of the external environment using optical elements and imaging devices typically use image resolution to describe the performance of the vision sensor.

PNP: the PNP problem is how to calculate the pose of the camera based on the real coordinates of N spatial points in a known world coordinate system and the projection of the spatial points on the image.

RANSAC algorithm: it can iteratively estimate the parameters of the mathematical model from a set of observed data sets comprising "outliers".

L MedSq algorithm is also an algorithm for estimating parameters of a mathematical model, but its outlier point should be less than 50%.

The principles and embodiments of the present invention are explained herein using specific examples, which are presented only to assist in understanding the method and its core concepts of the present invention. It should be noted that there are no more than infinite trial-and-error modes objectively due to the limited character expressions, and it will be apparent to those skilled in the art that various modifications, decorations, or changes may be made without departing from the spirit of the invention or the technical features described above may be combined in a suitable manner; such modifications, variations, combinations, or adaptations of the invention using its spirit and scope, as defined by the claims, may be directed to other uses and embodiments.