CN115166700A

CN115166700A - Ground point cloud filtering method, system, equipment and storage medium for laser radar

Info

Publication number: CN115166700A
Application number: CN202210759747.XA
Authority: CN
Inventors: 谭黎敏; 顾荣琦; 刘俊恺
Original assignee: Shanghai Westwell Information Technology Co Ltd
Current assignee: Shanghai Westwell Information Technology Co Ltd
Priority date: 2022-06-30
Filing date: 2022-06-30
Publication date: 2022-10-11

Abstract

The invention provides a ground point cloud filtering method, a ground point cloud filtering system, ground point cloud filtering equipment and a storage medium for a laser radar, wherein the ground point cloud filtering method comprises the following steps of: mapping each point in a laser radar coordinate system to a stereo coordinate system and coding to obtain a point cloud set, and carrying out structured coding on each point based on the stereo coordinate; filtering the point cloud at least based on a wire harness index, a pitch angle index and a distance index from the center of the laser radar of two leading point information of the current point; inquiring information of upper and lower dominant points of a current point based on the sequence of the horizontal angle indexes, and filtering to distinguish an environment point from a ground point; calibrating to a vehicle body coordinate system, coding the filtered point cloud through a cylindrical coordinate system, and filtering the point cloud again based on the leading point information; and removing the point cloud generated by the vehicle body based on the prior information to obtain the environmental point cloud. The invention can reserve environment points by carrying out structured coding on the point cloud and utilizing conditional query on neighbor points, filter out ground points and noise points in the point cloud and improve the efficiency of the algorithm.

Description

Ground point cloud filtering method, system, equipment and storage medium for laser radar

Technical Field

The invention relates to the technical field of AI vision, in particular to a ground point cloud filtering method, a ground point cloud filtering system, ground point cloud filtering equipment and a storage medium for a laser radar.

Background

Along with the continuous advance of the urban intelligent process, the unmanned technology under each scene gradually rises. The perception algorithm is one of key technologies supporting unmanned driving, and the objective of the perception algorithm is to extract useful environmental information through filtering of obtained sensor information, so that powerful guarantee can be provided for downstream tasks. Nowadays, laser radar has become a general sensor configured in the field of unmanned driving, and how to effectively utilize the point cloud observed by the laser radar to construct useful environmental information and filter out ground and noise is a difficult problem to deal with. If the point cloud information irrelevant to the environment structure is not effectively filtered, the performance of a downstream task is greatly influenced, and therefore the overall performance of the unmanned system is influenced.

Laser Radar (english) is a Radar system that detects characteristic quantities such as a position and a speed of a target by emitting a Laser beam. The working principle is that a detection signal (laser beam) is emitted to a target, then a received signal (target echo) reflected from the target is compared with the emitted signal, and after appropriate processing, relevant information of the target, such as target distance, azimuth, height, speed, attitude, even shape and other parameters, can be obtained, so that the targets of airplanes, missiles and the like are detected, tracked and identified. The laser changes the electric pulse into optical pulse and emits it, and the optical receiver restores the reflected optical pulse from the target into electric pulse and sends it to the display. Although lidar has the advantages of high precision and high resolution, and has the prospect of building a peripheral 3D model, it has the disadvantages of weak detection of stationary objects such as isolation strips and high cost of technical landing. Lidar is widely applicable to ADAS systems such as Adaptive Cruise Control (ACC), front vehicle collision warning (FCW), and Automatic Emergency Braking (AEB).

The current laser radar can directly input the point cloud data into a point cloud identification model to identify the types of obstacles, so that useless calculated amount can be greatly increased, the identification speed and accuracy are reduced, and the driving safety is influenced.

In view of the above, the present invention provides a ground point cloud filtering method, system, device and storage medium for laser radar.

It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the invention and therefore may include information that does not constitute prior art that is already known to a person of ordinary skill in the art.

Disclosure of Invention

The invention aims to provide a ground point cloud filtering method, a ground point cloud filtering system, ground point cloud filtering equipment and a storage medium of a laser radar, overcomes the difficulties in the prior art, and can judge whether a current point is an environmental point needing to be reserved or not by utilizing neighbor point conditional query through point cloud structured coding, so that the ground and noise in an observation point cloud are filtered.

The embodiment of the invention provides a ground point cloud filtering method of a laser radar, which comprises the following steps:

mapping each point of an original observation point cloud in a laser radar coordinate system to a three-dimensional coordinate of a three-dimensional coordinate system, and carrying out structured coding on each point based on the three-dimensional coordinate;

filtering the point cloud at least based on a wire harness index, a pitch angle index and a distance index from the center of the laser radar of two leading point information of a first current point, and removing isolated points;

inquiring information of upper and lower dominating points of a first current point based on the sequence of horizontal angle indexes, and distinguishing an environment point and a ground point in the point cloud when the first current point meets the conditions that the distance indexes of the first current point and the upper dominating point are the same, the heights of the first current point and the upper dominating point are different, and whether the lower dominating point exists;

calibrating the filtered point cloud to a vehicle body coordinate system, coding the filtered point cloud through a cylindrical coordinate system, filtering the point cloud again at least based on the leading point information of the second current point, and removing isolated points;

and removing the point cloud generated by the vehicle body based on the prior information to obtain the environmental point cloud.

Preferably, the mapping each point of the original observation point cloud in the laser radar coordinate system to a three-dimensional coordinate of the three-dimensional coordinate system, and performing structured coding on each point based on the three-dimensional coordinate includes:

mapping each point of an original observation point cloud in a laser radar coordinate system to a three-dimensional coordinate of a three-dimensional coordinate system, wherein an X axis and a Y axis of the three-dimensional coordinate system are respectively parallel to a horizontal plane, and a Z axis is vertical to the horizontal plane;

obtaining the arrangement sequence of the laser beams corresponding to each point in the vertical direction, and carrying out beam index coding on the laser beams of each point in sequence;

acquiring a horizontal-plane-based pitch angle of a connecting line from each point to the center of the laser radar, and sequentially performing pitch angle index coding on each point according to the numerical arrangement sequence of the pitch angles of the horizontal plane;

and obtaining the distance from each point to the center of the laser radar.

Preferably, the obtaining of the pitch angle of the connection line from each point to the center of the laser radar based on the horizontal plane, and sequentially performing pitch angle index coding on each point according to the numerical arrangement order of the pitch angles of the horizontal plane, further includes:

the pitch angle

Preferably, the filtering the point cloud based on at least a line bundle index, a pitch angle index and a distance index to the center of the laser radar of the two leading point information of the first current point, and removing isolated points includes:

traversing the point cloud, based on pitch angle index coding inquiry is located two points on the left and right sides of first current point, judges whether the interval of first current point is less than or equal to predetermined threshold value respectively with the difference between the interval of controlling two points, if, then first current point is the noise point, certainly filter in the point cloud, if not, then based on whether pencil index coding inquiry is located the upper and lower residence point of first current point, judges whether the interval of first current point is equal with the interval of at least one in the upper and lower residence point respectively, if, then first current point is the noise point, certainly filter in the point cloud, if not, then first current point is kept in the point cloud.

Preferably, the querying information of top and bottom dominant points of a first current point based on the order of horizontal angle indexes, when the first current point satisfies that the first current point has the same distance index with the top dominant point, has different height, and has the presence of the bottom dominant point to distinguish the environment point from the ground point in the point cloud, includes:

inquiring information of upper and lower dominating points of the first current point based on the sequence of the horizontal angle indexes;

when the first current point meets the conditions that the distance indexes of the first current point and the upper captivity point are the same, the heights of the first current point and the upper captivity point are different and no lower captivity point exists, the first current point is an environment point;

and when the first current point meets the conditions that the distance indexes of the first current point and the upper dominating point are the same, the heights of the first current point and the upper dominating point are different, and a lower dominating point exists, the first current point is a ground point.

Preferably, the sequentially querying for information of top and bottom dominating points of the first current point based on the horizontal angle index further comprises:

the horizontal angle is h _ angle = (tan) ^-1 (y/x))/pi x 180, and an angle _ index = h _ angle/α, assuming that the horizontal angular resolution is α.

Preferably, the sequentially querying information of top and bottom leading-in points of a first current point based on horizontal angle indexes, calibrating the filtered point cloud to a vehicle body coordinate system after the first current point meets the conditions that the distance indexes of the first current point and the top leading-in point are the same, the heights of the first current point and the top leading-in point are different, and whether the top leading-in point exists or not to distinguish an environmental point and a ground point in the point cloud, encoding the filtered point cloud by a cylindrical coordinate system, filtering the point cloud again at least based on the information of the leading-in points of a second current point, and before removing isolated points, the method includes:

filtering marks of left and right leading points of a first current point retained in the point cloud based on a pitch angle index, and updating the first current point to be a ground point when the left and right leading points are the same in height and are ground points; when the height of the upper and lower captivity points is the same and the captivity points are all ground points, the first current point is updated to be the ground point; and when the left and right leading points are not the environment point and not the ground point, updating the first current point to be the ground point.

Preferably, the left and right dominant points of the first current point retained in the point cloud are filtered based on the pitch angle index, and when the left and right dominant points are the same in height and are all ground points, the first current point is updated to be a ground point; when the heights of the upper and lower captivity points are the same and are all ground points, the first current point is updated to be a ground point; when the right and left leading points are not environment points or ground points, the first current point is updated to be the ground point and then the filtered point cloud is calibrated to the vehicle body coordinate system, the filtered point cloud is encoded through the cylindrical coordinate system, the leading point information at least based on the second current point is used for filtering the point cloud again, and the method comprises the following steps of:

and traversing the point cloud marked as the ground point, inquiring a lower dominating point positioned at a first current point through the wire harness index coding, and if the lower dominating point of the first current point is the ground point and is different from the height of the first current point, updating the first current point into an environment point.

Preferably, the traversal is marked as the ground point the point cloud, through the pencil index coding inquiry is located the lower leading and dwelling point of first current point, if the lower leading and dwelling point of first current point is the ground point and highly different with first current point, then first current point updates after the environmental point, with the point cloud calibration after filtering to the automobile body coordinate system, encode the point cloud after the filtration through the cylinder coordinate system, at least based on the leading and dwelling point information of second current point to filter the point cloud once more, before removing isolated point, include:

and filtering the marked point clouds to remove ground points, and keeping the rest point clouds to be environment points.

Preferably, the calibrating the filtered point cloud to the vehicle body coordinate system, encoding the filtered point cloud through the cylindrical coordinate system, filtering the point cloud again at least based on the leading point information of the second current point, and removing the isolated point includes:

mapping the coordinates of each corresponding laser radar coordinate system in the point cloud to a vehicle body coordinate system based on a pre-calibrated external reference matrix T;

encoding the filtered point cloud by using a horizontal angle index, a radial distance index and a vertical distance index in a cylindrical coordinate system;

respectively inquiring a second current point in the cylindrical coordinate system for the housing points at two sides of the current point through the wire harness index, the radial distance index and the vertical distance index, and if the housing points of the second current point are all environment points, keeping the second current point; and if at least one of the leading points of the second current point is not an environment point, filtering the second current point from the point cloud.

Preferably, the encoding the filtered point cloud by using a horizontal angle index, a radial distance index and a vertical distance index in a cylindrical coordinate system further includes:

encoding with horizontal angular resolution h _ angle _ r, horizontal angular index h _ angle _ index = tan ^-1 (y/x)/h _ angle _ r, the radial angle index calculating the distance of the projection point from the origin point through the projection point of the second current point on the XOY plane in the cylindrical coordinate system, and encoding through the radial distance resolution r _ r, the radial distance index

The vertical distance index is encoded z _ index = z/z _ r by the z-axis coordinate of the second current point and the vertical resolution z _ r.

Preferably, after the point cloud generated by the vehicle body is removed based on the prior information, an environment point cloud is obtained, including:

establishing an interval range of the vehicle body in each axis based on the maximum value and the minimum value of vehicle body point cloud acquired by the prior information laser radar on each axis in a vehicle body coordinate system;

filtering points located in the space range of the vehicle body from the point cloud;

and taking the remaining point clouds as environment point clouds only representing environment points.

The embodiment of the invention also provides a ground point cloud filtering system of a laser radar, which is used for realizing the ground point cloud filtering method of the laser radar, and the ground point cloud filtering system of the laser radar comprises:

the structured coding module is used for mapping each point of an original observation point cloud in a laser radar coordinate system to a three-dimensional coordinate of a three-dimensional coordinate system and carrying out structured coding on each point based on the three-dimensional coordinate;

the isolated point removing module is used for filtering the point cloud at least based on the wire harness index, the pitch angle index and the distance index from the laser radar center of the two leading point information of the first current point to remove the isolated point;

the point cloud classification module is used for inquiring information of upper and lower dominating points of a first current point based on the sequence of horizontal angle indexes, and distinguishing an environment point and a ground point in the point cloud when the first current point meets the conditions that the distance indexes of the first current point and the upper dominating point are the same, the heights of the first current point and the upper dominating point are different, and whether the lower dominating point exists or not;

the first filtering module is used for calibrating the filtered point cloud to a vehicle body coordinate system, coding the filtered point cloud through a cylindrical coordinate system, filtering the point cloud again at least based on the leading point information of the second current point, and removing isolated points;

and the environment point cloud module is used for removing the point cloud generated by the vehicle body based on the prior information to obtain the environment point cloud.

The embodiment of the invention also provides ground point cloud filtering equipment of the laser radar, which comprises:

a processor;

a memory having stored therein executable instructions of the processor;

wherein the processor is configured to perform the steps of the above-described ground point cloud filtering method for lidar via execution of executable instructions.

The embodiment of the invention also provides a computer readable storage medium for storing a program, and the program realizes the steps of the ground point cloud filtering method of the laser radar when being executed.

According to the ground point cloud filtering method, the ground point cloud filtering system, the ground point cloud filtering equipment and the storage medium of the laser radar, whether the current point is an environmental point needing to be reserved or not can be judged through point cloud structured coding and neighbor point conditional query, so that ground and noise in the observed point cloud are filtered.

Drawings

Other features, objects and advantages of the present invention will become more apparent upon reading of the detailed description of non-limiting embodiments thereof, with reference to the following drawings.

FIG. 1 is a flow chart of a ground point cloud filtering method of a lidar according to the present invention.

Fig. 2 to 13 are schematic views of an implementation process of the ground point cloud filtering method for laser radar of the present invention.

FIG. 14 is a schematic diagram of the ground point cloud filtering system of the lidar of the present invention.

Fig. 15 is a schematic structural diagram of the ground point cloud filtering apparatus of the lidar of the present invention. And

fig. 16 is a schematic structural diagram of a computer-readable storage medium according to an embodiment of the present invention.

Detailed Description

The following embodiments of the present application are described by specific examples, and other advantages and effects of the present application will be readily apparent to those skilled in the art from the disclosure herein. The present application is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present application. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.

Embodiments of the present application will be described in detail below with reference to the accompanying drawings so that those skilled in the art to which the present application pertains can easily carry out the present application. The present application may be embodied in many different forms and is not limited to the embodiments described herein.

Reference throughout this specification to "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," or the like, means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. Furthermore, the particular features, structures, materials, or characteristics shown may be combined in any suitable manner in any one or more embodiments or examples. Moreover, various embodiments or examples and features of different embodiments or examples presented in this application can be combined and combined by those skilled in the art without contradiction.

Furthermore, the terms "first", "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the feature. In the expressions of this application, "plurality" means two or more unless explicitly defined otherwise.

In order to clearly explain the present application, components that are not related to the description are omitted, and the same reference numerals are given to the same or similar components throughout the specification.

Throughout the specification, when a device is referred to as being "connected" to another device, this includes not only the case of being "directly connected" but also the case of being "indirectly connected" with another element interposed therebetween. In addition, when a device "includes" a certain component, unless otherwise stated, the device does not exclude other components, but may include other components.

When a device is said to be "on" another device, this may be directly on the other device, but may also be accompanied by other devices in between. When a device is said to be "directly on" another device, there are no other devices in between.

Although the terms first, second, etc. may be used herein to describe various elements in some instances, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, the first interface and the second interface are represented. Furthermore, as used in this application, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes" and/or "including," when used in this specification, specify the presence of stated features, steps, operations, elements, components, items, species, and/or groups, but do not preclude the presence, or addition of one or more other features, steps, operations, elements, components, items, species, and/or groups thereof. The terms "or" and/or "as used herein are to be construed as inclusive or meaning any one or any combination. Thus, "a, B or C" or "a, B and/or C" means "any of the following: a; b; c; a and B; a and C; b and C; A. b and C ". An exception to this definition will occur only when a combination of elements, functions, steps or operations are inherently mutually exclusive in some way.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, the singular forms "a", "an" and "the" include plural forms as long as the words do not expressly indicate a contrary meaning. The term "comprises/comprising" when used in this specification is taken to specify the presence of stated features, regions, integers, steps, operations, elements, and/or components, but does not exclude the presence or addition of other features, regions, integers, steps, operations, elements, and/or components.

Although not defined differently, including technical and scientific terms used herein, all terms have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terms defined in commonly used dictionaries are to be interpreted as having meanings consistent with those of the related art documents and the present prompts, and must not be excessively interpreted as having ideal or very formulaic meanings unless defined otherwise.

FIG. 1 is a flow chart of a ground point cloud filtering method of a lidar according to the present invention. As shown in fig. 1, an embodiment of the present invention provides a ground point cloud filtering method for a laser radar, including the following steps:

s110, mapping each point of an original observation point cloud in a laser radar coordinate system to a three-dimensional coordinate of a three-dimensional coordinate system, and carrying out structured coding on each point based on the three-dimensional coordinate;

s120, filtering the point cloud based on at least a wire harness index, a pitch angle index and a distance index from the center of the laser radar of the two leading point information of the first current point, and removing isolated points;

s130, inquiring information of upper and lower dominant points of the first current point based on the sequence of the horizontal angle indexes, and distinguishing an environment point and a ground point in the point cloud when the first current point meets the conditions that the distance indexes of the first current point and the upper dominant point are the same, the heights of the first current point and the upper dominant point are different and whether the lower dominant point exists or not;

s170, calibrating the filtered point cloud to a vehicle body coordinate system, coding the filtered point cloud through a cylindrical coordinate system, filtering the point cloud again at least based on the leading point information of the second current point, and removing isolated points;

and S180, removing the point cloud generated by the vehicle body based on the prior information to obtain the environmental point cloud.

The invention provides a robust ground point cloud and noise data filtering method, which can obtain point coordinates by obtaining coordinate points in original observation point cloud and by carrying out structured coding on the point cloud. Firstly, carrying out isolated point filtering on point cloud, judging whether a left neighbor and a right neighbor which are close to each other or an upper neighbor and a lower neighbor which belong to the same surface exist in a current point through inquiry (because a fine and high environmental characteristic can be scanned, the left neighbor and the right neighbor of the current point are far from each other but are environmental characteristics which still need to be reserved), and if not, filtering the current point. And then adding a vertical direction height index (by using a preset vertical direction distance range and vertical coding fine granularity) to the filtered point cloud, and horizontally calibrating the point cloud to a vehicle body coordinate system through a calibrated external reference matrix T. And finally, judging whether the point cloud after calibration belongs to the ground point needing to be filtered, traversing all points, if the current point does not exist in an upper neighbor point and a lower neighbor point at the same time, determining whether all left and right neighbor points currently used as environment points are ground points, if so, determining that errors need to be filtered, then determining all lower neighbor points used as ground points, if the lower neighbor points and the current point belong to the same object surface but have different vertical heights, determining that the errors exist, and if not, mistakenly determining the current point as the ground point to be reserved, thereby completing the observation data of the uppermost laser beam which is used as the ground point to be filtered because the upper neighbor point does not exist.

In order to further ensure that the retained environment points have no ground points which are misjudged, all the environment points need to be traversed, and the judgment state (environment points or ground points) of the neighbor points is traversed and inquired in a preset effective range (within a certain horizontal angle, a certain vertical height and a certain distance range from the current point), if the neighbor points are the ground, the state of the current point is modified into the ground points. And filtering the point cloud generated by the vehicle body according to the size of the vehicle body to obtain the final environmental point cloud required to be reserved.

In a preferred embodiment, S110 includes:

s111, mapping each point of an original observation point cloud in a laser radar coordinate system to a three-dimensional coordinate of a three-dimensional coordinate system, wherein an X axis and a Y axis of the three-dimensional coordinate system are respectively parallel to a horizontal plane, and a Z axis of the three-dimensional coordinate system is vertical to the horizontal plane;

s112, obtaining the arrangement sequence of the laser beams corresponding to each point in the vertical direction, and sequentially carrying out beam index coding on the laser beams of each point;

s113, acquiring a horizontal-plane-based pitch angle of a connecting line from each point to the center of the laser radar, and sequentially performing pitch angle index coding on each point according to the numerical arrangement sequence of the pitch angles of the horizontal plane;

and S114, obtaining the distance from each point to the center of the laser radar.

In a preferred embodiment, S113 further includes: pitch angle of the wing

In a preferred embodiment, S120 includes:

s121, traversing the point cloud, inquiring a left point and a right point which are positioned at a first current point based on the pitch angle index code, judging whether the difference value between the distance of the first current point and the distance between the left point and the right point is less than or equal to a preset threshold value, if so, executing a step S124, and if not, executing a step S122;

s122, inquiring upper and lower dominating points at the first current point based on the wire harness index codes, judging whether the distance between the first current point and at least one of the upper and lower dominating points is equal, if so, executing a step S124, and if not, executing a step S123;

s123, the first current point is reserved in a point cloud;

s124, the first current point is a noise point and is filtered from the point cloud.

In a preferred embodiment, S130 includes:

s131, sequentially inquiring information of upper and lower dominating points of a first current point based on horizontal angle indexes;

s132, when the first current point meets the conditions that the distance indexes of the first current point and the upper dominating point are the same, the heights are different and no lower dominating point exists, the first current point is an environment point;

and S133, when the first current point meets the conditions that the distance indexes of the first current point and the upper dominating point are the same, the heights of the first current point and the upper dominating point are different, and the lower dominating point exists, the first current point is a ground point.

In a preferred embodiment, S131 further comprises: horizontal angle h _ angle = (tan) ^-1 (y/x))/pi x 180, and with horizontal angular resolution of α, angle _ index = h _ angle/α.

In a preferred embodiment, after S130 and before S170, the method includes:

s140, filtering marks of left and right leading points of a first current point retained in the point cloud based on the pitch angle index, and updating the first current point to be a ground point when the left and right leading points are the same in height and are ground points; when the height of the upper and lower captivity points is the same and the upper and lower captivity points are all ground points, the first current point is updated to be the ground point; and when the left and right leading points are not the environment point and not the ground point, updating the first current point to be the ground point.

In a preferred embodiment, after S140 and before S170, the method includes:

s150, traversing the point cloud marked as the ground point, inquiring a lower dominating point positioned at the first current point through the wire harness index coding, and if the lower dominating point of the first current point is the ground point and is different from the first current point in height, updating the first current point into an environment point.

In a preferred embodiment, after S150 and before S170, the method includes:

and S160, filtering the marked point clouds to obtain ground points, and keeping the rest point clouds to be environment points.

In a preferred embodiment, S170 includes:

s171, mapping the coordinates of each laser radar coordinate system corresponding to the point cloud to a vehicle body coordinate system based on a pre-calibrated external reference matrix T;

s172, encoding the filtered point cloud by using a horizontal angle index, a radial distance index and a vertical distance index in a cylindrical coordinate system;

s173, respectively inquiring the second current point in the cylindrical coordinate system for the domination points at two sides of the current point through the wire harness index, the radial distance index and the vertical distance index, and if the domination points of the second current point are all environment points, keeping the second current point; and if at least one leading point of the second current point is not the environment point, filtering the second current point from the cloud point.

In a preferred embodiment, step S172 further comprises:

encoding with a horizontal angular resolution h _ angle _ r, horizontal angular index h _ angle _ index = tan ^-1 (y/x)/h _ angle _ r, the radial angle index calculating the distance of the projection point from the origin point through the projection point of the second current point on the XOY plane in the cylindrical coordinate system, and encoding through the radial distance resolution r _ r, the radial distance index

The vertical distance index encodes z _ index = z/z _ r by the z-axis coordinate of the second current point and the vertical resolution z _ r.

In a preferred embodiment, S180 includes:

s181, establishing an interval range of the vehicle body in each axis based on the maximum value and the minimum value of the vehicle body point cloud acquired by the prior information laser radar on each axis in the vehicle body coordinate system;

s182, filtering out points in the space range of the vehicle body from the point cloud;

and S183, taking the residual point cloud as the environment point cloud only representing the environment point.

According to the invention, through point cloud structured coding, neighbor point conditional query is utilized to judge whether the current point is an environmental point which needs to be reserved, so that the ground and noise in the observation point cloud are filtered.

Fig. 2 to 13 are schematic views of an implementation process of the ground point cloud filtering method for the laser radar of the present invention. As shown in fig. 2, in the present embodiment, isolated point noise is mainly filtered by structurally encoding a point cloud; the method comprises the steps of filtering ground points by utilizing a neighbor point information construction condition, encoding filtered point clouds by utilizing a cylindrical coordinate system, filtering noise in reserved environment points by utilizing the neighbor point information construction condition, and finally filtering the point clouds generated by a vehicle body in the environment points according to prior information of the vehicle body size. The specific process steps are described step by step below.

Assuming that the vehicle body is provided with N laser radars, in order to determine which radar the current observation point belongs to specifically, the number of the laser radars arranged on the vehicle body is uniformly coded, and the index of each radar is recorded as i (, N)>＝i>= 1), wherein the number of the line bundles of each multi-line laser radar is M, in order to conveniently determine which line bundle of which radar the current observation point belongs to, and obtain the feedback through scanning, globally and uniformly encoding the laser line bundles, that is, the index of each line is marked as [ line _ index ]](M*N>line_index>= 0), the radar at the current moment in total getsThe number of point cloud observations is K, the number of observation point clouds per lidar is K (1, 2.. N), K = K ₁ +k ₂ +...+k _N Because each point in the point cloud is subjected to the same filtering treatment, a point to be processed in the current observation point cloud is recorded as P, and the coordinate of P in the Cartesian coordinate system is recorded as P _x,y,z The sequential storage location of the observation point cloud obtained by P at the current time is denoted as j, the point cloud needs to be structured and encoded in order to quickly query the left, right, top and bottom neighbors of each point in the unordered point cloud in space, the line _ index of the current point needs to be known in order to query the top and bottom neighbors of the current point, the angle _ index of the current point needs to be known in order to query the left and right neighbors of the current point, and the dis _ index needs to be known in order to know the distance between the current point and the vehicle body, that is, the original point coordinate P (x, y, z) is mapped to P (line _ index, angle _ index, dis _ index) through encoding. As shown in fig. 3 and 4, in this embodiment,

laser radars

11 and 12 are installed on two sides of the lower portion of the vehicle head of the container truck 1,

laser radars

13 and 14 are installed on the top portion of the rear portion of the vehicle head, a coordinate center of the laser radars is defined as a central point O of a connecting line of the

laser radars

13 and 14, and the point cloud 2 is obtained by scanning the front of the

laser radars

11, 12, 13 and 14 through laser. The subsequent vehicle body coordinate system also uses O as an origin, the Y axis as a vehicle head foreground direction, the X axis as a vehicle body width direction, and the Z axis as a vehicle body height direction, but not limited thereto

Calculating line _ index of P, and judging which laser radar the current point to be processed belongs to according to j and k (1, 2.. N), namely if j is>＝(k ₁ +k ₂ +...+k _L ) The j point belongs to the Lth laser radar, that is, the current point to be processed lidar _ id = L, and the distance from the projection of the current point to be processed P on the XOY plane to the radar center is

P pitch angle from the center of the radar of angle = tan ^-1 (z, dis2 center)/π x 180. Since each laser has some line bundle observation angles below the origin, the calculated angle is negative, and for the convenience of coding, the lowest laser line bundle is uniformly compensated for all observation anglesThe angle α between each laser line, i.e. angle = tan, with respect to 0 degrees up to an offset β ^-1 (z,dis2center)/π*180+β，line_index＝angle/α+lidar_id*M。

Calculate the angle _ index of P, since each laser line is scanned at 360 degrees, calculate the horizontal angle h _ angle = (tan) of the projection of P point onto XOY plane ^-1 (y/x))/pi x 180, with horizontal angular resolution α, angle _ index = h _ angle/α.

Calculating dis _ index of P, calculating the distance of P point from the origin in Cartesian coordinate system as

Fine granularity of distance coding is γ, dis _ index = dis2center — 3d/γ.

As shown in FIG. 5, first, traverse the point cloud, filter out the isolated points, and query the current point P using angle _ index _b And its left and right neighbors P _a 、P _c If the distance between the current point and the dis _ index of the left and right neighbor points is less than the set threshold, the current point P is retained _b Because of the current point P _b And neighbor point P _a 、P _c Nearer is not an isolated noise point. As shown in FIG. 6, if the distance to the left and right neighbors is large, the current point P is queried using the line _ index _b And its upper and lower neighbor points P _d 、P _e Dis _ index if the upper neighbor P _d Or lower neighbor P _e The dis _ index of a point is equal to the dis _ index of the current point, and the point P is reserved _b Since this indicates the point P _b And the upper and lower neighbor points are not isolated noise points on the surface of the same object, otherwise, the points should be filtered.

When the grid index of the point cloud of each laser radar is generated according to the horizontal angle, the laser line beam number and the distance relative to the radar coordinate system is marked as P (line _ index, angle _ index, dis _ index), the point cloud is observed in a traversing way, the line _ index can be used for finding the upper and lower neighbor points of the current point, P _ up = P (line _ index-1) and P _ down = P (line _ index + 1), if the P _ up and P distances are the same but the heights are different, whether the lower neighbor point P _ down exists is further judged, if the point P exists, the point P is an environment point, and if the point P exists, the point P is a ground point, the point P is shown in figure 8. (see FIGS. 7, 8, and 9, P is the current point to be processed, and P is an environmental point when there is a neighbor point in both the upper and lower wire bundles, and P is a ground point when there is a neighbor)

And if the left adjacent point or the right adjacent point is consistent with the height of the P and is a ground point, modifying the current point to be a ground point. If the left and right neighbors are not the environment point or the ground point, the left and right neighbors of the P point are the noise to be removed, and therefore the current point is modified to be the ground point.

Referring to fig. 9, since there is a misjudgment in the filtering of the grid index, that is, the uppermost laser beam of each radar does not have an upper neighbor point, which cannot represent that the observed value is a ground point at this time, it is necessary to complement the environment point misjudged as the ground. And traversing all the point clouds determined as ground points, inquiring a lower neighbor point of the current point through the line _ index, and if the lower neighbor point is determined as the ground and has different height from the current point, correcting the current point to be an environment point. And eliminating the point cloud marked as the ground according to the state bit of each point, and keeping the rest point cloud as the environment point.

And correcting each laser radar coordinate system to a vehicle body coordinate system according to the calibrated external reference matrix T level.

The environment point cloud after ground filtering is encoded by using a cylindrical coordinate system (as shown in fig. 10), the cylindrical coordinate system encodes the environment point cloud through a horizontal angle h _ angle, a radial distance index r _ index and a vertical distance index z _ index, the current environment point to be processed is regarded as PE, and the environment point coordinate [ PE ] (x, y, z) is mapped into [ PE ] (h _ angle _ index, r _ index, z _ index) through encoding.

The horizontal angular index is the rotation angle of the projection point calculated by the projection of the PE on the XOY plane and is encoded by the horizontal angular resolution h _ angle _ r, h _ angle _ index = tan ^-1 (y/x)/h _ angle _ r. The radial angle index calculates the distance of the projected point from the origin, from the projected point of the PE on the XOY plane, and is encoded by the radial distance resolution r _ r,

the vertical distance index is encoded by z _ index = z/z _ r by the z-axis coordinate of the PE and the vertical resolution z _ r.

Fig. 10, 11, and 12 show that an ellipse represents a projected XOY horizontal plane, a point filled with oblique lines represents a point that has been determined as a ground point, P is a current point to be processed, if left and right neighbors of the current point are ground points, the current point to be processed P is a ground point (see fig. 10), if one of the points is a ground point, it is determined whether P is consistent with the height thereof (see fig. 11 and 12), if so, it is determined that the current point to be processed P is a ground point, otherwise, the current point to be processed P is not a ground point.

And inquiring two adjacent neighbor points according to the indexes of the current point PE in the horizontal angle, the radial distance and the vertical distance direction, if the neighbor points are all environment points, skipping the current point, and otherwise, modifying the state of the current point into noise point removal.

In order to further avoid point cloud information generated by laser radar points reflected by a vehicle body, according to prior information of vehicle body sizes (scanning of the

laser radars

11, 12, 13 and 14 on the vehicle body in advance), the minimum value and the maximum value of point clouds generated by scanning the vehicle body to the radar in the space on each axis are set, so that a point cloud interval of the vehicle body is obtained and converted into a vehicle body coordinate system, and the space range of the vehicle body in the vehicle body coordinate system is obtained, so that the point clouds on the part are filtered. Or, when the reserved environment point cloud coordinate is in the set self point cloud interval of the vehicle body, the reserved environment point cloud coordinate belongs to the vehicle body instead of the real environment point, and therefore filtering is needed.

And finally, the filtered points are reserved as the environment information of the finally filtered ground, the ground information, the early point information and the vehicle body information of the point cloud data are filtered, and the accuracy can be greatly improved when the subsequent obstacle judgment is carried out on the basis of the point cloud of the part, so that the unnecessary calculated amount is reduced, the calculation speed of road surface identification is improved, and the driving safety is improved.

FIG. 14 is a schematic diagram of the ground point cloud filtering system of the lidar of the present invention. As shown in fig. 14, the ground point cloud filtering system 5 of the laser radar of the present invention includes:

the structured coding module 51 is used for mapping each point of the original observation point cloud in the laser radar coordinate system to a three-dimensional coordinate of the three-dimensional coordinate system and carrying out structured coding on each point based on the three-dimensional coordinate;

the isolated point removing module 52 is used for filtering the point cloud at least based on the wire harness index, the pitch angle index and the distance index from the center of the laser radar of the two pieces of housing point information of the first current point, and removing the isolated points;

the point cloud classification module 53 is used for inquiring the information of the upper and lower dominating points of the first current point based on the sequence of the horizontal angle indexes, and distinguishing the environment point and the ground point in the point cloud when the first current point meets the conditions that the distance indexes of the first current point and the upper dominating point are the same, the heights of the first current point and the upper dominating point are different, and whether the lower dominating point exists or not;

the first filtering module 57 is used for calibrating the filtered point cloud to the vehicle body coordinate system, coding the filtered point cloud through the cylindrical coordinate system, and filtering the point cloud again at least based on the leading and residing point information of the second current point to remove isolated points;

and the environment point cloud module 58 is used for removing the point cloud generated by the vehicle body based on the prior information to obtain the environment point cloud.

In a preferred embodiment, the structured coding module 51 is configured to map each point of the original observation point cloud in the lidar coordinate system to a stereo coordinate of a stereo coordinate system, wherein an X axis and a Y axis of the stereo coordinate system are respectively parallel to a horizontal plane, and a Z axis is perpendicular to the horizontal plane; obtaining the arrangement sequence of the laser beams corresponding to each point in the vertical direction, and sequentially carrying out beam index coding on the laser beams of each point; acquiring a horizontal plane-based pitch angle of a connecting line from each point to the center of the laser radar, and sequentially performing pitch angle index coding on each point according to the numerical arrangement sequence of the pitch angles of the horizontal plane; and obtaining the distance from each point to the center of the laser radar.

In a preferred embodiment, pitch angle in the structured coding module 51

In a preferred embodiment, the isolated point removing module 52 is configured to traverse the point cloud, query two left and right points located at the first current point based on the pitch angle index coding, determine whether a difference between a distance between the first current point and a distance between the two left and right points is less than or equal to a preset threshold, if yes, perform the steps that the first current point is a noise point and is filtered from the point cloud, if no, query upper and lower dominant points located at the first current point based on the harness index coding, determine whether the distance between the first current point and at least one of the upper and lower dominant points is equal, if yes, the first current point is a noise point and is filtered from the point cloud, and if no, the first current point is retained in the point cloud.

In a preferred embodiment, the point cloud classification module 53 is configured to query the information of the top and bottom dominant points of the first current point based on the order of the horizontal angular index; when the first current point meets the conditions that the distance indexes of the first current point and the upper captivity point are the same, the heights of the first current point and the upper captivity point are different and no lower captivity point exists, the first current point is an environment point; and when the first current point meets the conditions that the distance indexes of the first current point and the upper captivity point are the same, the heights of the first current point and the upper captivity point are different, and the lower captivity point exists, the first current point is the ground point.

In a preferred embodiment, the horizontal angle in the point cloud classification module 53 is h _ angle = (tan) ^-1 (y/x))/pi x 180, and with horizontal angular resolution of α, angle _ index = h _ angle/α.

In a preferred embodiment, further comprising: a second filtering module 54 configured to filter the labels of the left and right dominant points of the first current point retained in the point cloud based on the pitch angle index, and when the heights of the left and right dominant points are the same and are all ground points, the first current point is updated to be a ground point; when the height of the upper and lower captivity points is the same and the upper and lower captivity points are all ground points, the first current point is updated to be the ground point; and when the left and right leading points are not the environment point and not the ground point, updating the first current point to be the ground point.

In a preferred embodiment, further comprising: and a third filtering module 55 configured to traverse the point cloud marked as the ground point, query the lower dominant point located at the first current point through the line bundle index coding, and update the first current point to the environment point if the lower dominant point of the first current point is the ground point and is different from the height of the first current point.

In a preferred embodiment, further comprising: and a fourth filtering module 56 configured to filter out the point clouds marked as ground points, and keep the rest point clouds as environment points.

In a preferred embodiment, the first filtering module 57 is configured to map the coordinates of each corresponding lidar coordinate system in the point cloud to the vehicle body coordinate system based on a pre-calibrated external reference matrix T; encoding the filtered point cloud by using a horizontal angle index, a radial distance index and a vertical distance index in a cylindrical coordinate system; respectively inquiring the second current point in the cylindrical coordinate system for the colonization points on the two sides of the current point through the wire harness index, the radial distance index and the vertical distance index, and if the colonization points of the second current point are all environment points, keeping the second current point; and if at least one leading point of the second current point is not the environment point, filtering the second current point from the cloud point.

In a preferred embodiment, the first filtering module 57 encodes with a horizontal angular resolution h _ angle _ r, the horizontal angular index h _ angle _ index = tan ^-1 (y/x)/h _ angle _ r, the radial angle index calculating the distance of the projection point from the origin point through the projection point of the second current point on the XOY plane in the cylindrical coordinate system, and encoding through the radial distance resolution r _ r, the radial distance index

In a preferred embodiment, the environment point cloud module 58 is configured to establish an interval range of the vehicle body in each axis based on the maximum value and the minimum value of the vehicle body point cloud acquired by the prior information laser radar in each axis in the vehicle body coordinate system; filtering points in the space range of the vehicle body from the point cloud; and taking the residual point cloud as an environment point cloud only representing the environment point.

According to the ground point cloud filtering system of the laser radar, whether the current point is an environmental point needing to be reserved or not can be judged through point cloud structured coding and neighbor point conditional query, so that ground and noise in the observation point cloud are filtered.

The embodiment of the invention also provides ground point cloud filtering equipment of the laser radar, which comprises a processor. A memory having stored therein executable instructions of the processor. Wherein the processor is configured to perform the steps of the ground point cloud filtering method of lidar via execution of executable instructions.

As described above, the ground point cloud filtering device of the laser radar of the present invention can determine whether the current point is an environmental point that needs to be retained by using neighbor point conditional query through structured coding of the point cloud, thereby filtering ground and noise in the observation point cloud.

As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or program product. Accordingly, various aspects of the present invention may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" platform.

Fig. 15 is a schematic structural diagram of the ground point cloud filtering apparatus of the lidar of the present invention. An electronic device 600 according to this embodiment of the invention is described below with reference to fig. 15. The electronic device 600 shown in fig. 15 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.

As shown in fig. 15, the electronic device 600 is embodied in the form of a general purpose computing device. The components of the electronic device 600 may include, but are not limited to: at least one processing unit 610, at least one memory unit 620, a bus 630 connecting the different platform components (including the memory unit 620 and the processing unit 610), a display unit 640, etc.

Wherein the storage unit stores program code executable by the processing unit 610 to cause the processing unit 610 to perform steps according to various exemplary embodiments of the present invention described in the above-mentioned electronic prescription flow processing method section of the present specification. For example, processing unit 610 may perform the steps as shown in fig. 1.

The storage unit 620 may include readable media in the form of volatile storage units, such as a random access memory unit (RAM) 6201 and/or a cache storage unit 6202, and may further include a read-only memory unit (ROM) 6203.

The memory unit 620 may also include a program/utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.

Bus 630 may be one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

The electronic device 600 may also communicate with one or more external devices 700 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 600, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 600 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interface 650. Also, the electronic device 600 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via the network adapter 660. The network adapter 660 may communicate with other modules of the electronic device 600 via the bus 630. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms, to name a few.

The embodiment of the invention also provides a computer readable storage medium for storing a program, and the program realizes the steps of the ground point cloud filtering method of the laser radar when being executed. In some possible embodiments, the various aspects of the invention may also be implemented in the form of a program product comprising program code for causing a terminal device to perform the steps according to various exemplary embodiments of the invention described in the above-mentioned electronic prescription flow processing method section of this specification, when the program product is run on the terminal device.

As shown above, when the program of the computer-readable storage medium of this embodiment is executed, it is able to determine whether the current point is an environmental point that needs to be retained by using neighbor point conditional query through structured coding of the point cloud, so as to filter the ground and noise in the observation point cloud.

Fig. 16 is a schematic structural diagram of a computer-readable storage medium of the present invention. Referring to fig. 16, a program product 800 for implementing the above method according to an embodiment of the present invention is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited in this respect, and in this document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

A computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In situations involving remote computing devices, the remote computing devices may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to external computing devices (e.g., through the internet using an internet service provider).

In summary, the ground point cloud filtering method, system, device and storage medium for the laser radar can judge whether the current point is an environmental point which needs to be reserved or not by virtue of the point cloud structured coding and the neighbor point conditional query, so as to filter the ground and noise in the observation point cloud.

The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, numerous simple deductions or substitutions may be made without departing from the spirit of the invention, which shall be deemed to belong to the scope of the invention.

Claims

1. A ground point cloud filtering method of a laser radar is characterized by comprising the following steps:

filtering the point cloud based on at least a wire harness index, a pitch angle index and a distance index from the laser radar center of two leading point information of a first current point, and removing isolated points;

2. The method for filtering ground point cloud of laser radar according to claim 1, wherein the step of mapping each point of the original observed point cloud in the laser radar coordinate system to a stereo coordinate of a stereo coordinate system and performing structured coding on each point based on the stereo coordinate comprises:

obtaining the arrangement sequence of the laser beams corresponding to each point in the vertical direction, and sequentially carrying out beam index coding on the laser beams of each point;

and obtaining the distance from each point to the center of the laser radar.

3. The method of claim 1, wherein the obtaining of the pitch angle of the line connecting the points to the center of the lidar is based on a horizontal plane, and the pitch angle index coding is sequentially performed on the points according to a numerical permutation order of the pitch angles of the horizontal plane, further comprising:

the pitch angle

4. The method of claim 1, wherein the filtering the point cloud based on at least a line bundle index, a pitch angle index and a distance index to the center of the lidar of the two leading point information of the first current point to remove isolated points comprises:

5. The ground point cloud filtering method for lidar according to claim 4, wherein the querying for information of top and bottom dominating points of a first current point based on the order of horizontal angle indexes, when the first current point satisfies that the first current point has the same distance index as the top dominating point, has a different height, and has a bottom dominating point to distinguish an environment point from a ground point in the point cloud, comprises:

6. The method of claim 5, wherein the step of sequentially querying information of top and bottom dominating points of the first current point based on the horizontal angle index further comprises:

the horizontal angle is h _ angle = (tan) ^-1 (y/x))/pi x 180, with a horizontal angular resolution ofα，angle_index＝h_angle/α。

7. The method of claim 3, wherein the step of querying information of upper and lower dominant points of a first current point based on the order of horizontal angle indexes comprises, after the first current point satisfies the condition that the first current point has the same distance index as the upper dominant point, has a different height, and has a lower dominant point to distinguish an environmental point from a ground point in the point cloud, the step of calibrating the filtered point cloud to the vehicle body coordinate system, encoding the filtered point cloud by the cylindrical coordinate system, and filtering the point cloud again based on at least information of the dominant point of a second current point, before removing isolated points, the method comprises:

filtering marks of left and right leading points of a first current point retained in the point cloud based on a pitch angle index, and updating the first current point to be a ground point when the left and right leading points are the same in height and are ground points; when the height of the upper and lower captivity points is the same and the captivity points are all ground points, the first current point is updated to be the ground point; and when the left and right dominant points are not environment points or ground points, updating the first current point to be a ground point.

8. The method of claim 5, wherein the filtering is performed on the left and right leading points of the first current point retained in the point cloud based on the pitch index, and when the left and right leading points are the same height and are all ground points, the first current point is updated to be a ground point; when the heights of the upper and lower captivity points are the same and are all ground points, the first current point is updated to be a ground point; when the right and left leading points are not environment points or ground points, the first current point is updated to be the ground point and then the filtered point cloud is calibrated to the vehicle body coordinate system, the filtered point cloud is encoded through the cylindrical coordinate system, the leading point information at least based on the second current point is used for filtering the point cloud again, and the method comprises the following steps of:

and traversing the point cloud marked as the ground point, inquiring a lower inhabitation point positioned at a first current point through the wiring harness index coding, and if the lower inhabitation point of the first current point is the ground point and is different from the height of the first current point, updating the first current point into an environment point.

9. The method of claim 5, wherein traversing the point cloud marked as a ground point, querying a lower dominating point at a first current point by the wire harness index code, calibrating the filtered point cloud to a vehicle body coordinate system after the first current point is updated to an environmental point if the lower dominating point of the first current point is the ground point and is different in height from the first current point, coding the filtered point cloud by a cylindrical coordinate system, and filtering the point cloud again based on at least dominating point information of a second current point, before removing a isolated point, the method comprises:

10. The method of claim 1, wherein the calibrating the filtered point cloud to the vehicle coordinate system, encoding the filtered point cloud by a cylindrical coordinate system, and filtering the point cloud again based on at least the leading point information of the second current point to remove outliers comprises:

respectively querying the second current point in the cylindrical coordinate system for the housing points on two sides of the current point through the wire harness index, the radial distance index and the vertical distance index, and if the housing points of the second current point are all environment points, reserving the second current point; and if at least one of the leading points of the second current point is not an environment point, filtering the second current point from the point cloud.

11. The method of claim 10, wherein the encoding the filtered point cloud using the horizontal angle index, the radial distance index and the vertical distance index in the cylindrical coordinate system, further comprises:

12. The ground point cloud filtering method for the laser radar as recited in claim 1, wherein after removing the point cloud generated by the vehicle body based on the prior information, obtaining an environment point cloud comprises:

filtering points in the space range of the vehicle body from the point cloud;

13. A lidar ground point cloud filtering system, comprising:

the point cloud classification module is used for inquiring the information of upper and lower dominating points of a first current point based on the sequence of horizontal angle indexes, and distinguishing an environment point and a ground point in the point cloud when the first current point meets the conditions that the distance indexes of the first current point and the upper dominating point are the same, the heights of the first current point and the upper dominating point are different and whether the lower dominating point exists or not;

14. A ground point cloud filtering device of a laser radar, comprising:

a processor;

a memory having stored therein executable instructions of the processor;

wherein the processor is configured to perform the steps of the lidar ground point cloud filtering method of any of claims 1-12 via execution of the executable instructions.

15. A computer readable storage medium storing a program, wherein the program when executed implements the steps of the ground point cloud filtering method for lidar according to any one of claims 1 to 12.