阅读说明：本技术 一种应用激光雷达进行最佳着陆点选取方法 (Method for selecting optimal landing point by applying laser radar ) 是由 黄兴 颜晓明 谢立 张元明 荣为君 朱亚明 闫峰 张青青 王良军 于 2020-06-08 设计创作，主要内容包括：本发明一种应用激光雷达进行最佳着陆点选取方法,(1)着陆器上的激光雷达对着陆区域环境进行扫描,生成着陆区域环境三维点云,提取地形水平面后,将着陆区域环境三维点云分割为地形平面子点云与非地形平面子点云。(2)从非地形平面子点云,分割出空间位置独立的物体,每个物体形成单独的子点云,确定每个物体的障碍属性；(3)将着陆区域环境三维点云划分为安全区域子点云以及障碍物子点云,安全区域子点云中的每个点进行邻域搜索,获取每个点的最大安全半径,进行排序,取最大安全半径的最大值,最大安全半径的最大值有一个以上,则从中选择距离着陆器最近的点,作为最佳着陆点,该点对应的最大安全半径为最佳落区半径,实现最佳着陆点选取。(The invention relates to a method for selecting an optimal landing point by applying a laser radar, which comprises the following steps of (1) scanning a landing area environment by the laser radar on a lander to generate a landing area environment three-dimensional point cloud, extracting a terrain horizontal plane, and then dividing the landing area environment three-dimensional point cloud into a terrain plane sub-point cloud and a non-terrain plane sub-point cloud. (2) Segmenting objects with independent space positions from the sub-point clouds of the non-terrain plane, forming an independent sub-point cloud by each object, and determining the barrier attribute of each object; (3) dividing the landing area environment three-dimensional point cloud into a safety area sub-point cloud and an obstacle sub-point cloud, performing neighborhood search on each point in the safety area sub-point cloud, acquiring the maximum safe radius of each point, sequencing, and selecting the point closest to the lander from the maximum safe radius which is more than one, wherein the maximum safe radius corresponding to the point is the optimal landing area radius, and the optimal landing point is selected.)

1. A method for selecting an optimal landing point by using a laser radar is characterized by comprising the following steps:

(1) scanning a landing area environment by a laser radar on the lander to generate a landing area environment three-dimensional point cloud, and extracting a terrain horizontal plane from the landing area environment three-dimensional point cloud; after the terrain horizontal plane is successfully extracted, the landing area environment three-dimensional point cloud is divided into a terrain plane sub-point cloud and a non-terrain plane sub-point cloud;

(2) segmenting objects with independent space positions from the sub-point cloud of the non-terrain plane, wherein each object forms an independent sub-point cloud, extracting the outline of the independent sub-point cloud formed by each object, generating a minimum cuboid surrounding the object, and further determining the overall dimension of the object and the distance from the center of the minimum cuboid to the terrain horizontal plane, so as to determine the obstacle attribute of each object;

(3) dividing the landing area environment three-dimensional point cloud in the step (1) into a safety area sub-point cloud and an obstacle sub-point cloud according to the obstacle attribute of each object determined in the step (2), and performing neighborhood search on each point in the safety area sub-point cloud in the step (1) to obtain the maximum safety radius of each point; and sequencing the maximum safe radiuses of all points in the sub-point cloud of the safe area, taking the maximum value of the maximum safe radiuses, selecting the point closest to the lander from the maximum safe radiuses as the optimal landing point, wherein the maximum safe radius corresponding to the point is the optimal landing area radius.

2. The method for selecting the optimal landing site by using the lidar according to claim 1, wherein: further comprising the step (4): (4) at the end of landing, the aircraft and the area to be landed move relatively slowly, the lander scans the environment of the landing area to form continuous multiframe three-dimensional point clouds of the environment of the landing area, and rigid body transformation relation on the space position is formed between the front frame point cloud and the rear frame point cloud and represented by using a rigid body transformation matrix;

and (3) determining the position of the optimal landing point identified by the previous frame in the current frame according to the optimal landing point obtained in the previous frame and a rigid body transformation matrix, and realizing tracking of the optimal landing point.

3. The method for selecting the optimal landing site by using the lidar according to claim 1, wherein: the lander specifically comprises: an unmanned aerial vehicle performing soft landing missions.

4. The method for selecting the optimal landing site by using the lidar according to claim 1, wherein: the laser radar is a distance measuring instrument, and can continuously scan a space environment to obtain three-dimensional point cloud on the surface of the environment.

5. The method for selecting the optimal landing site by using the lidar according to claim 1, wherein: the end of landing, refers to: and in the landing process of the lander, after passing through the main deceleration section and the approach section, the horizontal speed of the lander is reduced to zero basically, the landing area surface is about hundred meters away, and the lander slowly lands.

6. The method for selecting the optimal landing site by using the lidar according to claim 1, wherein: obstacle attributes for each object, including: protrusions and depressions.

7. A system for selecting an optimal landing point by using a laser radar is characterized in that: the system comprises a three-dimensional point cloud processing module, an obstacle attribute determining module and an optimal landing point determining module;

the three-dimensional point cloud processing module scans a landing area environment to generate a landing area environment three-dimensional point cloud by facing a laser radar on a lander, and extracts a terrain horizontal plane; after the terrain horizontal plane is successfully extracted, the landing area environment three-dimensional point cloud is divided into a terrain plane sub-point cloud and a non-terrain plane sub-point cloud;

the obstacle attribute determining module is used for segmenting objects with independent space positions from the sub-point cloud of the non-terrain plane, wherein each object forms an independent sub-point cloud, extracting the outline of the independent sub-point cloud formed by each object, generating a minimum cuboid surrounding the object, and further determining the overall dimension of the object and the distance from the center of the minimum cuboid to the terrain plane, so that the obstacle attribute of each object is determined;

the optimal landing point determining module is used for dividing the landing area environment three-dimensional point cloud in the three-dimensional point cloud processing module into a safety area sub-point cloud and an obstacle sub-point cloud according to the obstacle attribute of each object determined by the obstacle attribute determining module, and performing neighborhood search on each point in the safety area sub-point cloud in the three-dimensional point cloud processing module to obtain the maximum safety radius of each point; and sequencing the maximum safe radiuses of all points in the sub-point cloud of the safe area, taking the maximum value of the maximum safe radiuses, selecting the point closest to the lander from the maximum safe radiuses as the optimal landing point, wherein the maximum safe radius corresponding to the point is the optimal landing area radius.

8. The system of claim 7, wherein the system further comprises: the system also comprises an optimal landing point tracking module, wherein the optimal landing point tracking module has the following functions:

at the end of landing, the aircraft and the area to be landed move relatively slowly, the lander scans the environment of the landing area to form continuous multiframe three-dimensional point clouds of the environment of the landing area, and rigid body transformation relation on the space position is formed between the front frame point cloud and the rear frame point cloud and represented by using a rigid body transformation matrix;

and determining the position of the optimal landing point in the current frame by the previous frame according to the optimal landing point obtained by the three-dimensional point cloud processing module, the obstacle attribute determining module and the optimal landing point determining module, and realizing the tracking of the optimal landing point.

9. The system of claim 7, wherein the system further comprises: the lander specifically comprises: an unmanned aerial vehicle performing soft landing missions.

10. The system of claim 7, wherein the system further comprises: the laser radar is a distance measuring instrument, and can continuously scan a space environment to obtain three-dimensional point cloud on the surface of the environment.

Technical Field

The invention relates to a method for selecting an optimal landing point by using a laser radar, and belongs to the technical field of autonomous navigation of an aircraft at the landing tail section.

Background

In recent years, extraterrestrial celestial body inspection tour detection and unmanned aerial vehicle field development are rapid, the optimal landing point selection and tracking of the detector and the unmanned aerial vehicle at the landing end section are taken as one key technology, the method is an effective means for improving landing safety and landing environment adaptability, and the method is also a basis and prerequisite for establishing a navigation resolving coordinate system and providing a target point for a detector and an unmanned aerial vehicle navigation system. The traditional methods mainly have two types: 1. based on star catalogue remote sensing observation prior knowledge, artificially reserving a landing point/landing area; 2. and (3) automatically identifying the landing area and the landing point in real time by adopting an image processing technology, and tracking the landing point by methods such as projecting beacons or characteristic point identification and the like. The two methods have certain defects respectively, the first method has poor autonomy and insufficient real-time adaptability to the environment, and relies on prior remote sensing detection information, so that failure of a landing point predetermined strategy can be caused if the detection information is wrong or the information accuracy is insufficient. The second method is mainly susceptible to illumination, requires a certain illumination condition in practical implementation, and has high algorithm complexity.

Disclosure of Invention

The technical problem solved by the invention is as follows: the method can effectively overcome the defect that real-time and autonomous navigation cannot be carried out in the landing process only by the artificial preset landing point method, and can avoid the adverse effect of illumination.

The technical scheme of the invention is as follows: a method for selecting an optimal landing point by using a laser radar comprises the following steps:

(1) scanning a landing area environment by a laser radar on the lander to generate a landing area environment three-dimensional point cloud, and extracting a terrain horizontal plane from the landing area environment three-dimensional point cloud; and after the terrain horizontal plane is successfully extracted, the landing area environment three-dimensional point cloud is divided into a terrain plane sub-point cloud and a non-terrain plane sub-point cloud.

(2) Segmenting objects with independent space positions from the sub-point cloud of the non-terrain plane, wherein each object forms an independent sub-point cloud, extracting the outline of the independent sub-point cloud formed by each object, generating a minimum cuboid surrounding the object, and further determining the overall dimension of the object and the distance from the center of the minimum cuboid to the terrain horizontal plane, so as to determine the obstacle attribute of each object;

(3) dividing the landing area environment three-dimensional point cloud in the step (1) into a safety area sub-point cloud and an obstacle sub-point cloud according to the obstacle attribute of each object determined in the step (2), and performing neighborhood search on each point in the safety area sub-point cloud in the step (1) to obtain the maximum safety radius of each point; and sequencing the maximum safe radiuses of all points in the sub-point cloud of the safe area, taking the maximum value of the maximum safe radiuses, selecting the point closest to the lander from the maximum safe radiuses as the optimal landing point, wherein the maximum safe radius corresponding to the point is the optimal landing area radius.

Preferably, at the end of landing, the aircraft and the area to be landed move relatively slowly, the lander scans the landing area environment to form continuous multi-frame landing area environment three-dimensional point clouds, a rigid body transformation relation on a space position is formed between the front frame point cloud and the rear frame point cloud, and a rigid body transformation matrix is used for representation;

and (4) taking the optimal landing point obtained in the steps (1) to (3) as the optimal landing point obtained in the previous frame, and determining the position of the optimal landing point identified in the previous frame in the current frame according to the optimal landing point obtained in the previous frame and the rigid body transformation matrix so as to realize the tracking of the optimal landing point.

Preferably, the lander is specifically: an unmanned aerial vehicle performing soft landing missions.

Preferably, the laser radar, in particular to a distance measuring instrument, can continuously scan the space environment to obtain the three-dimensional point cloud on the surface of the environment.

Preferably, the landing end means: and in the landing process of the lander, after passing through the main deceleration section and the approach section, the horizontal speed of the lander is reduced to zero basically, the landing area surface is about hundred meters away, and the lander slowly lands.

Preferably, the obstacle attribute of each object includes: protrusions and depressions.

A system for selecting an optimal landing point by using a laser radar comprises a three-dimensional point cloud processing module, an obstacle attribute determining module and an optimal landing point determining module;

the three-dimensional point cloud processing module scans a landing area environment to generate a landing area environment three-dimensional point cloud by facing a laser radar on a lander, and extracts a terrain horizontal plane; after the terrain horizontal plane is successfully extracted, the landing area environment three-dimensional point cloud is divided into a terrain plane sub-point cloud and a non-terrain plane sub-point cloud;

the obstacle attribute determining module is used for segmenting objects with independent space positions from the sub-point cloud of the non-terrain plane, wherein each object forms an independent sub-point cloud, extracting the outline of the independent sub-point cloud formed by each object, generating a minimum cuboid surrounding the object, and further determining the overall dimension of the object and the distance from the center of the minimum cuboid to the terrain plane, so that the obstacle attribute of each object is determined;

the optimal landing point determining module is used for dividing the landing area environment three-dimensional point cloud in the three-dimensional point cloud processing module into a safety area sub-point cloud and an obstacle sub-point cloud according to the obstacle attribute of each object determined by the obstacle attribute determining module, and performing neighborhood search on each point in the safety area sub-point cloud in the three-dimensional point cloud processing module to obtain the maximum safety radius of each point; and sequencing the maximum safe radiuses of all points in the sub-point cloud of the safe area, taking the maximum value of the maximum safe radiuses, selecting the point closest to the lander from the maximum safe radiuses as the optimal landing point, wherein the maximum safe radius corresponding to the point is the optimal landing area radius.

Preferably, the system further comprises an optimal landing point tracking module, and the optimal landing point tracking module functions as follows:

at the end of landing, the aircraft and the area to be landed move relatively slowly, the lander scans the environment of the landing area to form continuous multiframe three-dimensional point clouds of the environment of the landing area, and rigid body transformation relation on the space position is formed between the front frame point cloud and the rear frame point cloud and represented by using a rigid body transformation matrix;

and determining the position of the optimal landing point in the current frame by the previous frame according to the optimal landing point obtained by the three-dimensional point cloud processing module, the obstacle attribute determining module and the optimal landing point determining module, and realizing the tracking of the optimal landing point.

Preferably, the lander is specifically: an unmanned aerial vehicle performing soft landing missions.

Preferably, the laser radar, in particular to a distance measuring instrument, can continuously scan the space environment to obtain the three-dimensional point cloud on the surface of the environment.

Compared with the prior art, the invention has the advantages that:

(1) the invention can realize the identification of obstacles in the environment and the selection and tracking of safe landing points on the premise of independently using the point cloud data of the laser radar.

(2) The method provided by the invention can effectively play a role in adverse illumination conditions, and avoids the influence of illumination on landing precision.

(3) The invention relates to a real-time autonomous navigation obstacle avoidance method, which can select a safe and proper landing point according to a real-time terrain environment at the final stage of landing.

(4) According to the method, after the optimal landing point is obtained in a certain frame, the optimal landing point is not required to be repeatedly calculated every time, the optimal landing point of a frame after the certain frame can be further obtained according to the rigid body transformation matrix, and the like, so that the tracking of the optimal landing point is realized.

Drawings

FIG. 1 is a flow chart of the present invention;

FIG. 2(a) is a schematic diagram of a landing area environment three-dimensional point cloud;

FIG. 2(b) a schematic diagram of a topographic planar sub-point cloud;

FIG. 2(c) a schematic diagram of a non-terrain-plane sub-point cloud;

FIG. 3 is a schematic diagram of optimal landing site selection based on r-radius neighborhood search.

Detailed Description

The invention is described in further detail below with reference to the figures and specific embodiments.

The invention relates to a method for selecting an optimal landing point by applying a laser radar, which comprises the following steps that (1) the laser radar on a lander scans the landing area environment to generate a landing area environment three-dimensional point cloud, and a terrain horizontal plane is successfully extracted from the landing area environment three-dimensional point cloud; and after the terrain horizontal plane is successfully extracted, the landing area environment three-dimensional point cloud is divided into a terrain plane sub-point cloud and a non-terrain plane sub-point cloud. (2) Segmenting objects with independent space positions from the sub-point cloud of the non-terrain plane, wherein each object forms an independent sub-point cloud, extracting the outline of the independent sub-point cloud formed by each object, generating a minimum cuboid surrounding the object, and further determining the overall dimension of the object and the distance from the center of the minimum cuboid to the terrain horizontal plane, so as to determine the obstacle attribute of each object; (3) dividing the landing area environment three-dimensional point cloud in the step (1) into a safety area sub-point cloud and an obstacle sub-point cloud according to the obstacle attribute of each object determined in the step (2), and performing neighborhood search on each point in the safety area sub-point cloud in the step (1) to obtain the maximum safety radius of each point; and sequencing the maximum safe radiuses of all points in the sub-point cloud of the safe area, taking the maximum value of the maximum safe radiuses, selecting the point closest to the lander from the maximum safe radiuses as the optimal landing point, wherein the maximum safe radius corresponding to the point is the optimal landing area radius.

Aiming at the problem that in the planet detection soft landing task, under the condition that the illumination condition of a landing area is unfavorable, an optical image is difficult to play a role, the method can solve the key problem that the detector autonomously selects a safe landing point at the tail stage of landing and provides support for subsequent autonomous navigation.

As shown in fig. 1, the optimal landing site selection method using laser radar according to the present invention includes the following steps:

(1) scanning a landing area environment by a laser radar on the lander to generate a landing area environment three-dimensional point cloud, and successfully extracting a terrain horizontal plane from the landing area environment three-dimensional point cloud; and after the terrain horizontal plane is successfully extracted, the landing area environment three-dimensional point cloud is divided into a terrain plane sub-point cloud and a non-terrain plane sub-point cloud.

The lander of the present invention is preferably an unmanned aerial vehicle that performs soft landing tasks. The laser radar is a distance measuring instrument, and the interior of the laser radar is composed of a plurality of laser transceivers and corresponding processing circuits; laser transceiver transmits laser to environmental surface one point, and the receipt reverberation, calculates the distance of laser irradiation point to laser transceiver through the time difference of sending and receiving, and these laser transceivers regular spread on laser radar's rotation axis direction, can rotate around the rotation axis to the realization is to the distance measurement of certain regional internal environment surface, because laser transceiver array angle and processing time, therefore laser radar has certain level, vertical angular resolution. The laser radar is installed at the bottom of the lander and used for scanning the landing area environment below the lander to form three-dimensional point cloud of the landing area environment.

The space environment in a certain range below the lander determined by the view angle range of the laser radar is a landing area. At the end of landing, the landing device slowly descends in a posture perpendicular to the terrain plane of the landing area, the laser radar installed at the bottom of the landing device continuously scans and measures the landing area, a measurement point set of the surface of the landing area is formed in each scanning and measuring, and a coordinate point set under a laser radar three-dimensional rectangular coordinate system obtained through calculation is called as a three-dimensional point cloud, as shown in fig. 2 (a).

Successfully extracting a terrain horizontal plane from the three-dimensional point cloud of the landing area environment, wherein the preferable scheme comprises the following steps:

1. positioning the three-dimensional point cloud formed by each scanning as X_i；

2. Extraction of X_iIn (1) a terrain plane sub-point cloud Xp_iThe method comprises the following steps:

a) random selection of X_iDetermining a plane by using any 3 non-collinear points;

b) calculating X_iIs less than a threshold Th_pIs an interior point, otherwise is an exterior point, forming an interior point set XL_iWith an outlier set XO_iCounting the number C of inner points_i；

c) Repeating a) and b) until the maximum number of iterations k is reached, selecting C_i～C_kMaximum value of C_tCorresponding XL_tI.e. the determined terrain plane sub-point cloud Xp_iAs shown in fig. 2 (b).

3.Xp_iThe complementary set is the sub-point cloud Xm of the non-terrain plane_iAs shown in FIG. 2(c), Xp_iAnd Xm_iThe relationship of (a) is as follows:

X_i＝Xp_iUXm_i；

(2) segmenting objects with independent space positions from the sub-point cloud of the non-terrain plane, wherein each object forms an independent sub-point cloud, extracting the outline of the independent sub-point cloud formed by each object, generating a minimum cuboid surrounding the object, and further determining the overall dimension of the object and the distance from the center of the minimum cuboid to the terrain horizontal plane, so as to determine the obstacle attribute of each object; the preferred scheme is as follows:

1. the method for segmenting the object with independent position from the sub-point cloud of the non-terrain plane comprises the following steps:

1.1 determining the non-terrain plane sub-point cloud Xm for the (1) th_iBuilding a three-dimensional k-d Tree T_r；

1.2 pairs of Xm_iAt any point p in_jAt T_rThe Euclidean distance between the medium search and the medium search is less than a threshold value r₀Forming a neighborhood point set N;

1.3 at any point in the point set N, at T_rThe Euclidean distance between the medium search and the medium search is less than a threshold value r₀Adding the point to a point set N until no new point is added in the point set N, and recording the point N as an independent sub-point cloud;

1.4 calculation of N at Xm_iRepeating the steps 2 and 3 for each point in M to form a plurality of independent sub-point clouds until M is empty, and defining c independent sub-point clouds N₁～N_c。

2. To N₁～N_cRespectively calculating outlines of the independent sub-point clouds, analyzing distribution spans of the outline points on an X, Y, Z axis as a, b and h, and obtaining the size of a minimum cuboid surrounding the sub-point clouds;

3. for each independent sub-point cloud N_i(N_i∈[N₁,…N_c]) Calculating the mean value of three coordinate vectors of all points contained in the point cloud to obtain the barycentric coordinate of the point cloud, and taking the barycentric as the center, wherein a, b and h are three side lengths of a cuboid, so that the minimum cuboid surrounding the independent sub-point cloud can be obtained;

4. according to the relation between the barycentric coordinates of each independent sub-point cloud and the terrain horizontal plane, protrusions are arranged above the terrain horizontal plane, and pits are arranged below the terrain horizontal plane;

5. according to the volume of the minimum cuboid surrounding each independent sub-point cloud, the minimum cuboid is larger than the barrier threshold value O_DJudging as an obstacle, otherwise, judging as a non-obstacle.

(3) Dividing the landing area environment three-dimensional point cloud in the step (1) into a safety area sub-point cloud and an obstacle sub-point cloud according to the obstacle attribute of each object determined in the step (2), and performing neighborhood search on each point in the safety area sub-point cloud in the step (1) to obtain the maximum safety radius of each point; and sequencing the maximum safe radiuses of all points in the sub-point cloud of the safe area, taking the maximum value of the maximum safe radiuses, and selecting the point closest to the lander from the maximum safe radiuses as the optimal landing point when more than one maximum safe radiuses exist, wherein the maximum safe radius corresponding to the point is the optimal landing area radius. The preferred scheme is as follows:

1. the independent sub-point cloud N determined in the step (2)₁～N_cIn (1), the combination determined as the obstacle is the obstacle sub-point cloud Xo_i；

2. Obstacle sub-point cloud Xo_iAt X_iThe complement in (1) is a safe region sub-point cloud Xs_i；

3. Sequencing the maximum safe radius of all points in the sub-point cloud of the safe area, taking the maximum value of the maximum safe radius, and selecting the point closest to the lander from the maximum safe radius as the optimal landing point when the maximum value of the maximum safe radius is more than one, wherein the specific steps are as follows:

3.1 extraction of Xs_iEdge of, traverse Xs_iEach point p in_j；

3.2 search by r radius neighborhood, r ═ Gr × n, G_rThe grid size of the point cloud is used for defining the spatial resolution during point cloud processing so as to improve the processing efficiency, n is a self-increasing integer used for increasing the value of a search radius r, and p is extracted by using a k-d tree_jR radius neighborhood point index of pointsCloud index Xo with obstacle points_iPerforming intersection operation with the intersection result Xc_j；

3.3 such as Xc_jIf not, adding 1 to the value of n, then assigning n, and continuing for 3.2 steps;

3.4 if not, exiting, and recording the safety radius of the current point as r;

4. obtaining Xs_iSecurity of all pointsSelecting a point with the largest safe radius as an optimal landing point, and if the maximum safe radius has repeated conditions, selecting a point closest to the origin of the laser radar rectangular coordinate system as an optimal landing point xp_iAs shown in fig. 3, the light color circular area is a selected safe landing area, the center of the circle is the optimal landing point, and the radius is the maximum safe radius.

The further scheme is as follows: further comprising the step (4): (4) at the end of landing, the aircraft and the area to be landed move relatively slowly, the lander scans the environment of the landing area to form continuous multiframe three-dimensional point clouds of the environment of the landing area, and rigid body transformation relation on the space position is formed between the front frame point cloud and the rear frame point cloud and represented by using a rigid body transformation matrix;

and (4) taking the optimal landing point obtained in the steps (1) to (3) as the optimal landing point obtained in the previous frame, and determining the position of the optimal landing point identified in the previous frame in the current frame according to the optimal landing point obtained in the previous frame and the rigid body transformation matrix so as to realize the tracking of the optimal landing point. The preferred scheme is as follows:

1. defining the three-dimensional point clouds of the front and the back frames as X respectively_i-1、X_iTo X_i-1Adopting the optimal landing point xp obtained in the steps (1) to (3)_i-1；

2. To X_i-1、X_iRespectively carrying out down-sampling to reduce the density of the point clouds, and respectively recording the point clouds after the down-sampling as X_i-1 ^{^}、X_i ^{^}；

3. Due to the strong relevance of the front and rear point cloud frames, a rigid body transformation matrix of the front and rear point cloud frames is calculated by adopting a closest point iterative algorithm (ICP), and the method specifically comprises the following steps:

3.1 optional selection of X_i-1 ^{^}M points { p¹:p¹ ₁,...,p¹ _mIs p¹Each point in X_i ^{^}The point closest to the selected point forms a point set { p²:p² ₁,...,p² _m}；

3.2 define matrix a ═ p¹ ₁,...,p¹ _mI, matrixB＝|p² ₁,...,p² _mI, matrix H

H_4×4＝A×B^T

Wherein B is^TIs a transposed matrix of the matrix B;

3.3 singular value decomposition of H

H＝UΣV

Wherein sigma is a diagonal matrix; u represents a square matrix, and V represents a square matrix;

3.4 then the transformation matrix T can be solved by:

T＝V×U^T

4. the best landing point xp in the current frame_iThe solution can be solved by:

xp_i＝T×xp_i-1

in the formula, xp_i-1Is the best landing point in the previous frame of the current frame.

The method can realize the tracking of the optimal landing point in the continuous point cloud frame sequence and the continuous tracking of the optimal landing point in the maneuvering process of the lander, which is important for the subsequent establishment of relative navigation between the lander and the optimal landing point.

The method uses the laser radar as a navigation sensor, continuously scans the landing area at the tail stage of landing to form the three-dimensional point cloud of the landing area environment, processes the three-dimensional point cloud of the landing area environment in real time, accurately identifies various obstacles in the landing environment, and selects and tracks the optimal landing point according to the obstacle. The method is independent of the illumination condition of the landing area, has high laser ranging precision, and has better adaptability to the safe and autonomous landing of the lander under the condition of unknown illumination.

The invention relates to a system for selecting an optimal landing point by applying a laser radar, which comprises a three-dimensional point cloud processing module, an obstacle attribute determining module and an optimal landing point determining module;

the three-dimensional point cloud processing module scans a landing area environment to generate a landing area environment three-dimensional point cloud by facing a laser radar on a lander, and extracts a terrain horizontal plane; after the terrain horizontal plane is successfully extracted, the landing area environment three-dimensional point cloud is divided into a terrain plane sub-point cloud and a non-terrain plane sub-point cloud;

the obstacle attribute determining module is used for segmenting objects with independent space positions from the sub-point cloud of the non-terrain plane, wherein each object forms an independent sub-point cloud, extracting the outline of the independent sub-point cloud formed by each object, generating a minimum cuboid surrounding the object, and further determining the overall dimension of the object and the distance from the center of the minimum cuboid to the terrain plane, so that the obstacle attribute of each object is determined;

the optimal landing point determining module is used for dividing the landing area environment three-dimensional point cloud in the three-dimensional point cloud processing module into a safety area sub-point cloud and an obstacle sub-point cloud according to the obstacle attribute of each object determined by the obstacle attribute determining module, and performing neighborhood search on each point in the safety area sub-point cloud in the three-dimensional point cloud processing module to obtain the maximum safety radius of each point; and sequencing the maximum safe radiuses of all points in the sub-point cloud of the safe area, taking the maximum value of the maximum safe radiuses, selecting the point closest to the lander from the maximum safe radiuses as the optimal landing point, wherein the maximum safe radius corresponding to the point is the optimal landing area radius.

Preferably, the system further comprises an optimal landing point tracking module, and the optimal landing point tracking module functions as follows: at the end of landing, the aircraft and the area to be landed move relatively slowly, the lander scans the landing area environment to form continuous multiframe landing area environment three-dimensional point clouds, rigid body transformation relation on the space position is formed between the front frame point cloud and the rear frame point cloud, and a rigid body transformation matrix is used for representation;

and determining the position of the optimal landing point in the current frame by the previous frame according to the optimal landing point obtained by the three-dimensional point cloud processing module, the obstacle attribute determining module and the optimal landing point determining module, and realizing the tracking of the optimal landing point.

The lander specifically comprises: an unmanned aerial vehicle performing soft landing missions.

The laser radar is a distance measuring instrument, and can continuously scan a space environment to obtain three-dimensional point cloud on the surface of the environment.

The lander is an unmanned aerial vehicle for executing a soft landing task. The laser radar is preferably a range finder, and the interior of the range finder consists of a plurality of laser transceivers and corresponding processing circuits; laser transceiver transmits laser to environmental surface one point, and the receipt reverberation, calculates the distance of laser irradiation point to laser transceiver through the time difference of sending and receiving, and these laser transceivers regular spread on laser radar's rotation axis direction, can rotate around the rotation axis to the realization is to the distance measurement of certain regional internal environment surface, because laser transceiver array angle and processing time, therefore laser radar has certain level, vertical angular resolution. The laser radar is installed at the bottom of the lander and used for scanning the landing area environment below the lander to form three-dimensional point cloud of the landing area environment.

The space environment in a certain range below the lander determined by the view angle range of the laser radar is a landing area. At the end of landing, the landing device slowly descends in a posture perpendicular to the terrain plane of the landing area, the laser radar installed at the bottom of the landing device continuously scans and measures the landing area, a measurement point set of the surface of the landing area is formed in each scanning and measuring, and a coordinate point set under a laser radar three-dimensional rectangular coordinate system obtained through calculation is called as a three-dimensional point cloud, as shown in fig. 2 (a).

The three-dimensional point cloud processing module successfully extracts a terrain horizontal plane from the three-dimensional point cloud of the landing area environment, and the optimal scheme comprises the following steps:

1. positioning the three-dimensional point cloud formed by each scanning as X_i；

2. Extraction of X_iIn (1) a terrain plane sub-point cloud Xp_iThe method comprises the following steps:

a) random selection of X_iDetermining a plane by using any 3 non-collinear points;

b) calculating X_iIs less than a threshold Th_pIs an interior point, otherwise is an exterior point, forming an interior point set XL_iTo the exterior pointSet XO_iCounting the number C of inner points_i；

c) Repeating a) and b) until the maximum number of iterations k is reached, selecting C_i～C_kMaximum value of C_tCorresponding XL_tI.e. the determined terrain plane sub-point cloud Xp_iAs shown in fig. 2 (b).

3.Xp_iThe complementary set is the sub-point cloud Xm of the non-terrain plane_iAs shown in FIG. 2(c), Xp_iAnd Xm_iThe relationship of (a) is as follows:

X_i＝Xp_iUXm_i；

the obstacle attribute determining module is used for segmenting objects with independent space positions from the sub-point clouds of the non-terrain plane, wherein each object forms an independent sub-point cloud, extracting the outline of the independent sub-point cloud formed by each object, generating a minimum cuboid surrounding the object, and further determining the overall dimension of the object and the distance from the center of the minimum cuboid to the terrain plane, so that the obstacle attribute of each object is determined;

the preferred scheme is as follows:

1. the method for segmenting the object with independent position from the sub-point cloud of the non-terrain plane comprises the following steps:

1.1 pairs of non-terrain plane sub-point clouds Xm_iBuilding a three-dimensional k-d Tree T_r；

1.2 pairs of Xm_iAt any point p in_jAt T_rThe Euclidean distance between the medium search and the medium search is less than a threshold value r₀Forming a neighborhood point set N;

1.3 at any point in the point set N, at T_rThe Euclidean distance between the medium search and the medium search is less than a threshold value r₀Adding the point to a point set N until no new point is added in the point set N, and recording the point N as an independent sub-point cloud;

1.4 calculation of N at Xm_iRepeating the steps 1.2 and 1.3 (traversing all the points in M) for each point in M to form a plurality of independent sub-point clouds until M is empty, and defining c independent sub-point clouds N₁～N_c。

2. To N₁～N_cIndependent sub-point cloud separationRespectively solving the contour, and analyzing the distribution span of contour points on an X, Y, Z axis as a, b and h, namely the size of the minimum cuboid surrounding the sub-point cloud;

3. for each independent sub-point cloud N_i(N_i∈[N₁,…N_c]) Calculating the mean value of three coordinate vectors of all points contained in the point cloud to obtain the barycentric coordinate of the point cloud, and taking the barycentric as the center, wherein a, b and h are three side lengths of a cuboid, so that the minimum cuboid surrounding the independent sub-point cloud can be obtained;

4. according to the relation between the barycentric coordinates of each independent sub-point cloud and the terrain horizontal plane, protrusions are arranged above the terrain horizontal plane, and pits are arranged below the terrain horizontal plane;

5. according to the volume of the minimum cuboid surrounding each independent sub-point cloud, the minimum cuboid is larger than the barrier threshold value O_DJudging as an obstacle, otherwise, judging as a non-obstacle.

The optimal landing point determining module is used for dividing the landing area environment three-dimensional point cloud in the three-dimensional point cloud processing module into a safe area sub-point cloud and an obstacle sub-point cloud according to the determined obstacle attribute of each object, and performing neighborhood search on each point in the safe area sub-point cloud obtained in the step (1) to obtain the maximum safe radius of each point; and sequencing the maximum safe radiuses of all points in the sub-point cloud of the safe area, taking the maximum value of the maximum safe radiuses, and selecting the point closest to the lander from the maximum safe radiuses as the optimal landing point when more than one maximum safe radiuses exist, wherein the maximum safe radius corresponding to the point is the optimal landing area radius. The preferred scheme is as follows:

1. independent sub-point cloud N determined by obstacle attribute determination module₁～N_cIn (1), the combination determined as the obstacle is the obstacle sub-point cloud Xo_i；

2. Obstacle sub-point cloud Xo_iAt X_iThe complement in (1) is a safe region sub-point cloud Xs_i；

3. Sequencing the maximum safe radius of all points in the sub-point cloud of the safe area, taking the maximum value of the maximum safe radius, and selecting the point closest to the lander from the maximum safe radius as the optimal landing point when the maximum value of the maximum safe radius is more than one, wherein the specific steps are as follows:

3.1 extraction of Xs_iEdge of, traverse Xs_iEach point p in_j；

3.2 search by r radius neighborhood, r ═ Gr × n, G_rThe grid size of the point cloud is used for defining the spatial resolution during point cloud processing so as to improve the processing efficiency, n is a self-increasing integer used for increasing the value of a search radius r, and p is extracted by using a k-d tree_jR radius neighborhood point index of points

Cloud index Xo with obstacle points_iPerforming intersection operation with the intersection result Xc_j；

3.3 such as Xc_jIf not, adding 1 to the value of n, then assigning n, and continuing for 3.2 steps;

3.4 if not, exiting, and recording the safety radius of the current point as r;

4. obtaining Xs_iSelecting a point with the largest safe radius as an optimal landing point from the safe radius sequences of all the points, and if the largest safe radius is repeated, selecting a point closest to the origin of the rectangular coordinate system of the laser radar as the optimal landing point xp_iAs shown in fig. 3, the light color circular area is a selected safe landing area, the center of the circle is the optimal landing point, and the radius is the maximum safe radius.

The further scheme is as follows: the system also comprises an optimal landing point tracking module, wherein the optimal landing point tracking module has the following functions:

at the end of landing, the aircraft and the area to be landed move relatively slowly, the lander scans the environment of the landing area to form continuous multiframe three-dimensional point clouds of the environment of the landing area, and rigid body transformation relation on the space position is formed between the front frame point cloud and the rear frame point cloud and represented by using a rigid body transformation matrix;

and determining the position of the optimal landing point identified by the previous frame in the current frame according to the optimal landing point obtained by the previous frame and the rigid body transformation matrix, so as to realize the tracking of the optimal landing point. The preferred scheme is as follows:

1. defining the three-dimensional point clouds of the front and the back frames as X respectively_i-1、X_iTo X_i-1Obtaining an optimal landing point xp by a three-dimensional point cloud processing module, an obstacle attribute determining module and an optimal landing point determining module_i-1；

2. To X_i-1、X_iRespectively carrying out down-sampling to reduce the density of the point clouds, and respectively recording the point clouds after the down-sampling as X_i-1 ^{^}、X_i ^{^}；

3. Due to the strong relevance of the front and rear point cloud frames, a rigid body transformation matrix of the front and rear point cloud frames is calculated by adopting a closest point iterative algorithm (ICP), and the method specifically comprises the following steps:

3.1 optional selection of X_i-1 ^{^}M points { p¹:p¹ ₁,...,p¹ _mIs p¹Each point in X_i ^{^}The point closest to the selected point forms a point set { p²:p² ₁,...,p² _m}；

3.2 define matrix a ═ p¹ ₁,...,p¹ _mI, matrix B ═ p² ₁,...,p² _mI, matrix H

H_4×4＝A×B^T

Wherein B is^TIs a transposed matrix of the matrix B;

3.3 singular value decomposition of H to form a form of square matrix multiplied by diagonal matrix, preferably the formula is as follows

H＝UΣV

Wherein, U represents a square matrix, Sigma represents a diagonal matrix, and V represents a square matrix;

3.4 then the transformation matrix T can be solved by:

T＝V×U^T

4. then it is currentOptimal landing point xp in a frame_iIt may be preferred to solve by:

xp_i＝T×xp_i-1

in the formula, xp_i-1Is the best landing point in the previous frame of the current frame.

The method can realize the tracking of the optimal landing point in the continuous point cloud frame sequence and the continuous tracking of the optimal landing point in the maneuvering process of the lander, which is important for the subsequent establishment of relative navigation between the lander and the optimal landing point.

The scheme further improves the landing point selection efficiency and the operation efficiency.

The further preferable scheme of the invention is as follows: local feature extraction of front and back point cloud frames is added, closest point iteration is carried out by using feature points, the accuracy of associated point pairs is improved, the number of the associated point pairs is reduced, the calculation amount of an algorithm is reduced, and the tracking effect is further improved.

On the premise of independently using the point cloud data of the laser radar, the invention can realize the identification of obstacles in the environment and the selection and tracking of safe landing points, and can effectively play a role in the condition of unfavorable illumination, thereby avoiding the influence of the illumination on the landing precision;

the invention relates to a real-time autonomous navigation obstacle avoidance method, which can select a safe and proper landing point according to a real-time terrain environment at the final stage of landing.