CN117310657A - Noise filtering method and device, autonomous mobile device and storage medium - Google Patents

Abstract

The embodiment of the application provides a noise filtering method and device, an autonomous mobile device and a storage medium, and relates to the technical field of data processing. The larger one of the distance between the current scanning point and the previous scanning point and the distance between the current scanning point and the subsequent scanning point is obtained to be used as a target distance; when the target distance is smaller than or equal to the distance threshold value, acquiring the angle of the current scanning point read by the laser radar, and obtaining the read angle; calculating the angle of the current scanning point according to the previous scanning point and the next scanning point to obtain the calculated angle; when the current scanning point is determined to be the noise point according to the read angle and the calculated angle, the current scanning point is filtered, so that diffraction points and discrete noise points near the real point can be accurately filtered, the filtering precision of laser point cloud noise points is improved, the precision of laser radar point cloud is improved, and the technical problem that the laser radar point cloud precision is lower in the current filtering method based on density is solved.

Description

Noise filtering method and device, autonomous mobile device and storage medium

Technical Field

The present application relates to the field of data processing technologies, and in particular, to a noise filtering method and apparatus, an autonomous mobile apparatus, and a storage medium.

Background

Because laser is not limited by light and interference immunity is strong, point cloud data obtained by laser detection has the characteristics of high precision, strong instantaneity, stable data and the like, and the laser radar is convenient to install, so the laser radar is widely applied to autonomous mobile devices. The autonomous moving apparatus may include, but is not limited to, an autonomous mobile robot (Autonomous Mobile Robot, AMR for short) or an automated guided vehicle (Automated Guided Vehicle, AGV for short).

The imaging quality of lidar is critical to certain fine operations of autonomous mobile devices (e.g., SLAM mapping operations and navigation operations), while lidar imaging relies on point cloud data acquired by the lidar. The higher the accuracy of the lidar point cloud, the higher the imaging quality.

At present, a filtering method based on density is generally adopted to filter noise points, such as outliers, in the laser radar. The filtering method based on the density is used for filtering all laser radar point clouds by adopting the same density, but in practical application, the laser radar point clouds have different densities at positions with different distances, diffraction points at the edge of an object and scattered noise points generated by reflection generally occur near real points, and the diffraction points and the scattered noise points near the real points are difficult to filter by the current filtering method based on the density, so that the accuracy of the laser radar point clouds is lower, and the imaging quality of the laser radar is lower.

Disclosure of Invention

The embodiment of the application provides a noise filtering method and device, an autonomous mobile device and a storage medium, so as to solve the technical problem of low laser radar point cloud precision existing in the current density-based filtering method.

In a first aspect, an embodiment of the present application provides a noise filtering method, where the method includes: acquiring the larger one of the distance between the current scanning point and the previous scanning point and the distance between the current scanning point and the next scanning point as a target distance; when the target distance is smaller than or equal to the distance threshold value, acquiring the angle of the current scanning point read by the laser radar, and obtaining the read angle; calculating the angle of the current scanning point according to the previous scanning point and the next scanning point to obtain the calculated angle; and filtering the current scanning point when the current scanning point is determined to be a noise point according to the read angle and the calculated angle.

In a second aspect, an embodiment of the present application provides a noise filtering apparatus, including: a distance acquisition module for acquiring the larger of the distance between the current scanning point and the previous scanning point and the distance between the current scanning point and the next scanning point as a target distance; the angle reading module is used for acquiring the angle of the current scanning point read by the laser radar when the target distance is smaller than or equal to the distance threshold value, and obtaining the read angle; the angle calculation module is used for calculating the angle of the current scanning point according to the previous scanning point and the next scanning point to obtain the calculated angle; and the noise filtering module is used for filtering the current scanning point when the current scanning point is determined to be the noise point according to the read angle and the calculated angle.

In a third aspect, embodiments of the present application provide an autonomous mobile apparatus, comprising: the system comprises a memory and a processor, wherein an application program is stored in the memory and used for executing the method provided by the embodiment of the application when the application program is called by the processor.

In a fourth aspect, embodiments of the present application provide a computer readable storage medium having stored thereon program code for causing a processor to perform the method provided by the embodiments of the present application when invoked by the processor.

The noise filtering method and device, the autonomous mobile device and the storage medium provided by the embodiment of the application acquire the larger one of the distance between the current scanning point and the previous scanning point and the distance between the current scanning point and the next scanning point as the target distance; when the target distance is smaller than or equal to the distance threshold value, acquiring the angle of the current scanning point read by the laser radar, and obtaining the read angle; calculating the angle of the current scanning point according to the previous scanning point and the next scanning point to obtain the calculated angle; when the current scanning point is determined to be the noise point according to the read angle and the calculated angle, the current scanning point is filtered, diffraction points and discrete noise points near the real point can be accurately filtered, the filtering precision of laser point cloud noise points is improved, the precision of laser radar point cloud is improved, and the technical problem that the laser radar point cloud precision is lower in the current filtering method based on density is solved.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings that are required for the description of the embodiments will be briefly introduced below, and it is apparent that the drawings in the following description are only some embodiments of the present application, but not all embodiments. All other embodiments and figures obtained by persons of ordinary skill in the art based on the embodiments of the present application without inventive effort are within the scope of the present application.

Fig. 1 is a schematic flow chart of a noise filtering method according to an embodiment of the present application;

FIG. 2 illustrates a gray scale map of a point cloud image provided in an exemplary embodiment of the present application;

FIG. 3 is a schematic diagram of three scan points continuously acquired by a lidar according to an exemplary embodiment of the present application;

FIG. 4 is a schematic view of two adjacent rays of light impinging on two planes according to an exemplary embodiment of the present application;

FIG. 5 illustrates a gray scale map of an original point cloud image provided in an exemplary embodiment of the present application;

FIG. 6 is a gray scale view of a point cloud image formed after filtering the noise in FIG. 5 according to an exemplary embodiment of the present application;

fig. 7 shows a block diagram of a noise filtering device according to an embodiment of the present application;

fig. 8 shows a block diagram of an autonomous mobile apparatus provided in an embodiment of the present application.

Detailed Description

In order to enable those skilled in the art to better understand the present application, the following description will make clear and complete descriptions of the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application.

Referring to fig. 1, fig. 1 is a flow chart illustrating a noise filtering method according to an embodiment of the present application. The noise filtering method may be applied to a noise filtering device or an autonomous mobile device, or other laser radar equipped devices (e.g., vehicles). The noise filtering method may include the following steps S110 to S140.

Step S110, the larger of the distance between the current scanning point and the previous scanning point and the distance between the current scanning point and the subsequent scanning point is acquired as the target distance.

Lidar (Lidar) is a radar system that detects characteristic amounts such as a position, a speed, and the like of a target with an emitted laser beam. The main working principle is to emit single-line/multi-line laser beams to a target, then compare a reflected signal with an emitted signal, analyze the Time of Flight (TOF) or frequency difference (Doppler shift) of the signal, obtain relevant parameters such as the target distance, and even derive information such as the target gesture, shape, and the like secondarily. The line number is one of the most important parameters of the laser radar type of the conventional vision detection system, and the laser radar can be classified into a single-line laser radar and a multi-line laser radar according to the line number (the number of transmitter/receiver groups). The single-line laser radar can only complete plane scanning, is mainly used for avoiding obstacles, has high scanning speed, high resolution and high reliability, and is mainly applied to scenes with low requirements on height information, such as service robots. The multi-line laser radar can identify the height information (which can be understood as integration in the vertical direction) of an object, and is mainly 4-128 lines, has high manufacturing cost and is mainly used in the fields of automatic driving and the like. In the embodiment of the application, the laser radar may comprise a single-line laser radar or a multi-line laser radar.

The angular resolution of a lidar refers to the ability of the lidar to differentially distinguish between the smallest spacings of two adjacent objects, and may be represented by the angular dimension of the lidar between two smallest distinguishable objects. The image output by the laser radar is called a point cloud image, and the included angle between two adjacent points is the angular resolution, that is, the angular interval of laser scanning of the laser radar is the angular resolution of the laser radar. As an example, for a single-line lidar, where the single-line lidar collects data once every interval Δθ, the angular resolution of the single-line lidar is Δθ. The angular resolution of a lidar is related to the actual type of lidar, and in general the angular resolution of a lidar is inversely proportional to the laser wavelength and proportional to the diameter of the antenna (or called the aperture), i.e. the longer the laser wavelength the lower the angular resolution and the larger the aperture the higher the angular resolution.

One point cloud image (shown in fig. 2) output by the laser radar represents one frame of laser radar data, and the laser radar finishes scanning corresponding to one rotation of the motor in the laser radar, that is, the laser radar finishes 360-degree looking around scanning once scanning. The laser radar performs a laser scan to obtain a point cloud including a plurality of point clouds, each of which may include, but is not limited to, three-dimensional coordinates of a scan point, laser reflection intensity at the scan point, and a distance between the scan point and the laser radar, wherein the laser point cloud refers to a data set of a spatial point (referred to herein as a scan point) scanned by the laser radar device, and the laser reflection intensity is related to a surface texture and roughness of a target irradiated by laser, a laser incidence angle, a laser wavelength, and an energy density of the laser radar.

As an example, assuming that one 360-degree looking around laser scans at an angular interval of 45 degrees (angular resolution), one 360-degree looking around scan is completed, distances between the laser radar and scanning points at each of 0 degrees, 45 degrees, 90 degrees, 135 degrees, 180 degrees, 225 degrees, 270 degrees, and 315 degrees, and the laser emission intensity can be acquired, respectively.

Referring to fig. 2, fig. 2 shows a gray scale of a point cloud image according to an exemplary embodiment of the present application. As shown in fig. 2, when the laser beam emitted by the lidar irradiates the edge of the object, diffraction occurs, and diffraction points in the class I frame and discrete noise points in the class II frame shown in fig. 2 are generated. In the embodiment of the present application, in order to remove diffraction points and discrete noise points, step S110 to step S140 may be performed for each collected point cloud, so as to determine whether each point cloud is a noise point, thereby effectively filtering noise points in the point cloud output by the laser radar.

In the embodiment of the application, the point clouds output by the laser radar can be obtained, and for each point cloud, the current scanning point in the current point cloud and the distance between the current scanning point and the laser radar can be obtained.

The distance (absolute value) between the current scanning point and the previous scanning point may be calculated as a first distance, the distance (absolute value) between the current scanning point and the next scanning point may be calculated as a second distance, the magnitudes of the first distance and the second distance may be compared, and if the first distance is greater than or equal to the second distance, the first distance may be taken as the target distance. And if the first distance is smaller than the second distance, taking the second distance as the target distance.

As an example, as shown in fig. 3, assuming that the current scanning point is point B, a distance |ba| between point B and point a and a distance |bc| between point B and point C may be calculated, with the larger of |ba| and |bc| as the target distance L according to the following expression (1) _B 。

L _B ＝max(|BA|，|BC|) (1)

Referring to FIG. 4, a first light beam emitted from a point O reaches a first plane S1 to form a point C1, and a second light beam emitted from a point O reaches a second plane S2 to form a point C2, wherein the first light beam and the second light beam are adjacent light beams, i.e. the emission interval of the first light beam and the second light beam is a scan interval delta _θ . Based on fig. 4, an approximate relationship between adjacent rays as shown in expressions (2) and (3) can be obtained.

BC 1L (minimum resolution size) (2)

|BC1|≈|BC2|*cos(∠C2BC1) (3)

Where |bc1| represents the distance between point B and point C1, |bc2| represents the distance between points B and C2.

Based on the approximate relationships (5) and (6) between adjacent rays derived in fig. 4, in the embodiment of the present application, a filtering method of neighbor distance constraint may be adopted, and according to the minimum resolution size and the target distance, it is determined whether the current scanning point is a noise point. Specifically, the minimum resolution size of the laser radar at the current scanning point can be obtained, the minimum resolution size is the minimum distance from which the laser radar can distinguish two objects in distance, a distance threshold is determined according to the minimum resolution size and a preset first angle, and the distance threshold is adopted to filter out discrete noise points with a larger distance from the true point.

In some embodiments, the angular resolution of the lidar may be determined based on the actual type of lidar. In other embodiments, the angular resolution of the lidar may be determined based on the angular separation between two adjacent scan points. As an example, two adjacent scanning points may be arbitrarily acquired, and an angular interval of the two scanning points is calculated as the angular resolution. As another example, the angular interval between all adjacent scan points may be calculated, taking the average of all the angular intervals as the angular resolution.

When the distance between the current scanning point and the laser radar and the angular resolution of the laser radar are obtained, the minimum resolution size can be calculated according to the distance between the current scanning point and the laser radar and the angular resolution. As an example, the mean value of the distance and angular resolution of the current scanning point from the lidar may be calculated, with the resulting radian value being the minimum resolution size.

As an example, let the angular resolution of the lidar be Δ _θ The initial angle of scanning is theta _s The data for each point location is noted asThe number of points in one complete scan is denoted as N, and the data D acquired in one scan may be denoted as:

θ _i ＝θ _s +i*Δ _θ ,i＝0,1,2,…,N (4)

as shown in FIG. 3, the X-O-Y coordinate system in FIG. 3 is a laser radar coordinate system, and points A, B and C are respectively at intervals of delta _θ Three points continuously collected, point A is marked as r _A,θ Point B is noted asPoint C is marked->Let the distance between the point B and the laser radar be r _B The minimum resolution size L can be calculated according to the following expression (6).

L＝r _B *Δ _θ (6)

After determining the minimum resolution size, the distance threshold may be determined according to the minimum resolution size and a preset first angle. If the target distance is greater than the distance threshold, the current scanning point can be determined as the noise point, and the current scanning point is filtered to filter out the discrete noise point far from the true point. If the target distance is less than or equal to the distance threshold, in order to filter out diffraction points that are very close to the true point but look like straight lines, a slope-based noise filtering method needs to be further adopted to determine whether the current scan point is a noise point, i.e., steps S120 to S140 are performed.

The first angle can be preset according to the actual requirement on noise filtering precision. In some embodiments, the first angle may be preset to 80 degrees, and when the first angle takes 80 degrees, the effect of removing the noise point in the laser radar point cloud is better, and the denoising precision is higher.

In some embodiments, a ratio between the minimum resolution size and the cosine value of the first angle may be determined as the distance threshold.

For example, let the minimum resolution be L, the first angle be k, and the target distance be L _B The filtering method of the neighbor distance constraint can be as shown in the tableThe expression (7) is shown, wherein,is a distance threshold.

And step S120, when the target distance is smaller than or equal to the distance threshold value, acquiring the angle of the current scanning point read by the laser radar, and obtaining the read angle.

When the laser radar obtains the current scanning point B, the laser moves along a line segment OB formed by the origin O of the laser radar coordinate system and the current scanning point B, and at the moment, the actual angle of the included angle between the line segment OB and the X axis of the laser radar coordinate system can be directly read as theta+delta by the laser radar _θ 。

Step S130, calculating the angle of the current scanning point according to the previous scanning point and the next scanning point to obtain the calculated angle.

The slope of the current scanning point can be calculated according to the previous scanning point (A) and the next scanning point (C), the arc tangent calculation can be carried out on the slope, and the vector formed by the next scanning point (C) and the previous scanning point (A) can be calculatedConverting the arctangent calculation result to a specified interval (e.g., [ -. Pi.,. Pi]) The calculated angle is obtained. In particular, it is possible to follow the vector +.>Positive and negative of x and y, will calculate the angle K _B The value of (2) is converted into [ -pi, pi]。

As an example, assume that the current scan point is point B, and the previous scan point is point a (a _x ，A _y ) The latter scan point is point C (C _x ，C _y ) The slope of the current scan point is K, and the calculated angle K can be calculated according to the following expression (8) _B 。

Wherein, the atan (x) function is the arctangent (tan-1) of each element returned to x in radians. The atan (x) function accepts real and complex inputs simultaneously. For the real value of x, the atan (x) function returns values in the interval [ -pi/2, pi/2 ].

An absolute value of the difference between the calculated angle and the read angle may be determined. If the absolute value is smaller than the second angle, the current scanning point is determined to be the noise point, and the current scanning point is filtered, that is, step S140 is performed. And if the absolute value is greater than or equal to the second angle, determining the current scanning point as a real point. The second angle is smaller than the first angle, and for a diffraction point, the error between the slope of the diffraction point and the slope value of the diffraction point read by the laser radar is small, so that the diffraction point can be filtered by selecting the smaller second angle. In some embodiments, the second angle may be 3 degrees, and when the second angle is 3 degrees, the effect of removing the noise point in the laser radar point cloud is better, and the denoising precision is higher.

As an example, let the calculated angle be K _B The read angle is θ+Δ _θ An embodiment of determining whether the current scan point is a noise point using a slope-based noise point filtering method with the second angle being t may be as shown in the following expression (9).

When the slope-based noise filtering method determines that the current scanning point is a noise point, the current scanning point is filtered, that is, step S140 is performed. And when the current scanning point is determined to be a real point by the slope-based noise point filtering method, the current scanning point is reserved.

Step S140, filtering the current scanning point when determining the current scanning point as a noise point according to the read angle and the calculated angle.

The noise filtering method provided by the embodiment of the application can acquire the larger one of the distance between the current scanning point and the previous scanning point and the distance between the current scanning point and the next scanning point as the target distance; when the target distance is smaller than or equal to the distance threshold value, acquiring the angle of the current scanning point read by the laser radar, and obtaining the read angle; calculating the angle of the current scanning point according to the previous scanning point and the next scanning point to obtain the calculated angle; when the current scanning point is determined to be the noise point according to the read angle and the calculated angle, the current scanning point is filtered, diffraction points and discrete noise points near the real point can be accurately filtered, the filtering precision of laser point cloud noise points is improved, the precision of laser radar point cloud is improved, and the technical problem that the laser radar point cloud precision is lower in the current filtering method based on density is solved.

Referring to fig. 5 and 6, fig. 5 shows a gray scale of an original point cloud image according to an exemplary embodiment of the present application, and fig. 6 shows a gray scale of a point cloud image formed by filtering noise points in fig. 5 according to an exemplary embodiment of the present application. The points in the class I box in fig. 5 are diffraction points, and the points in the class II box are discrete noise points. Fig. 6 is a point cloud image obtained after performing noise filtering on fig. 5 by using the noise filtering method provided in the embodiment of the present application. As is evident from comparing fig. 5 and 6, both the diffraction points in the class I box and the discrete noise points in the class II box in fig. 5 are filtered out, and the point cloud image shown in fig. 6 has no diffraction points and discrete noise points. Therefore, the diffraction points and discrete noise points in the laser point cloud can be effectively filtered by adopting the noise filtering method provided by the embodiment of the application, and the accuracy of the laser radar point cloud is improved.

Referring to fig. 7, fig. 7 shows a block diagram of a noise filtering apparatus according to an embodiment of the present application. The noise filtering apparatus 100 may be applied to an autonomous mobile apparatus, or other apparatus equipped with a lidar (e.g., a vehicle). The noise filtering apparatus 100 includes a distance acquisition module 110, an angle reading module 120, an angle calculating module 130, and a noise filtering module 140.

The distance acquisition module 110 is configured to acquire, as the target distance, the larger one of the distance between the current scanning point and the previous scanning point and the distance between the current scanning point and the subsequent scanning point.

The angle reading module 120 is configured to obtain a minimum resolution size of the lidar at the current scanning point, where the minimum resolution size is a minimum distance at which the lidar can distinguish two objects over a distance.

The angle calculating module 130 is configured to calculate an angle of the current scanning point according to the previous scanning point and the next scanning point, and obtain the calculated angle.

The noise filtering module 140 is configured to filter the current scanning point when determining that the current scanning point is a noise point according to the read angle and the calculated angle.

In some embodiments, the distance acquisition module 110 is further configured to acquire a minimum resolution size of the lidar at the current scanning point, where the minimum resolution size is a minimum distance over which the lidar can distinguish between two objects; and determining a distance threshold according to the minimum resolution size and a preset first angle.

In some embodiments, the distance acquisition module 110 is further configured to determine a ratio between the minimum resolution size and the cosine value of the first angle as the distance threshold.

In some embodiments, the distance acquisition module 110 is further configured to acquire a distance between the current scanning point and the laser radar and an angular resolution of the laser radar, where the angular resolution is a minimum angle at which the laser radar can distinguish two objects; and calculating the minimum resolution size according to the distance between the current scanning point and the laser radar and the angular resolution.

In some embodiments, the noise filtering module 140 is further configured to determine an absolute value of a difference between the calculated angle and the read angle; and when the absolute value is smaller than a preset second angle, determining the current scanning point as a noise point, wherein the second angle is smaller than the first angle.

In some embodiments, the noise filtering module 140 is further configured to determine the current scanning point as a real point and reserve the current scanning point when the absolute value is greater than or equal to the second angle.

In some embodiments, the angle calculating module 130 is further configured to calculate a slope of the current scan point according to the previous scan point and the next scan point; performing arctangent calculation on the slope; and converting the arc tangent calculation result into a designated interval according to the direction of a vector formed by the last scanning point and the previous scanning point to obtain the calculated angle.

In some embodiments, the noise filtering module 140 is further configured to filter the current scan point when the target distance is greater than the distance threshold.

It is clear to a person skilled in the art that the above device provided in the embodiments of the present application can implement the method provided in the embodiments of the present application. The specific working process of the above-described device and module may refer to a process corresponding to the method in the embodiment of the present application, which is not described herein again.

In the embodiments provided in this application, the modules shown or discussed are coupled, directly coupled, or communicatively coupled to each other, and may be indirectly coupled or communicatively coupled via some interfaces, devices, or modules, which may be electrical, mechanical or otherwise.

In addition, each functional module in the embodiments of the present application may be integrated into one processing module, or each module may exist alone physically, or two or more modules may be integrated into one module. The integrated modules may be implemented in hardware or in software as functional modules.

Referring to fig. 8, fig. 8 is a block diagram illustrating a configuration of an autonomous mobile apparatus according to an embodiment of the present application. Autonomous mobile device 200 may include a memory 210 and a processor 220, the memory 210 having stored therein an application configured to perform methods provided by embodiments of the present application when invoked by processor 220.

Processor 220 may include one or more processing cores. The processor 220 utilizes various interfaces and lines to connect various portions of the overall autonomous mobile apparatus 200 for executing or executing instructions, programs, code sets, or instruction sets stored in the memory 210, and invoking execution or execution of data stored in the memory 210, performing various functions of the autonomous mobile apparatus 200 and processing the data.

The processor 220 may be implemented in hardware in at least one of digital signal processing (Digital Signal Processing, DSP for short), field programmable gate array (Field-Programmable Gate Array, FPGA for short), and programmable logic array (Programmable Logic Array, PLA for short).

The processor 220 may integrate one or a combination of several of a central processing unit (Central Processing Unit, CPU for short), an image processor (Graphics Processing Unit, GPU for short) and a modem. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for being responsible for rendering and drawing of display content; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 220 and may be implemented solely by a single communication chip.

The Memory 210 may include a random access Memory (Random Access Memory, abbreviated as RAM) or a Read-Only Memory (abbreviated as ROM). Memory 210 may be used to store instructions, programs, code sets, or instruction sets. The memory 210 may include a stored program area and a stored data area. The storage program area may store instructions for implementing an operating system, instructions for implementing at least one function, instructions for implementing the various method embodiments described above, and the like. The storage data area may store data created by the autonomous mobile apparatus 200 in use, etc.

The present embodiments also provide a computer readable storage medium having program code stored thereon, the program code being configured to perform the methods provided by the embodiments of the present application when invoked by a processor. The computer readable storage medium may be an electronic Memory such as a flash Memory, an Electrically erasable programmable read-Only Memory (EEPROM), an erasable programmable read-Only Memory (EPROM), a hard disk, or a ROM.

In some embodiments, the computer readable storage medium comprises a Non-volatile computer readable medium (Non-Transitory Computer-Readable Storage Medium, referred to as Non-TCRSM). The computer readable storage medium has storage space for program code to perform any of the method steps described above. The program code can be read from or written to one or more computer program products. The program code may be compressed in a suitable form.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and are not limiting thereof; although the present application has been described in detail with reference to the foregoing embodiments, one of ordinary skill in the art will appreciate that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not drive the essence of the corresponding technical solutions to depart from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims (11)

1. The noise filtering method is characterized by comprising the following steps of:

acquiring the larger one of the distance between the current scanning point and the previous scanning point and the distance between the current scanning point and the next scanning point as a target distance;

when the target distance is smaller than or equal to the distance threshold value, acquiring the angle of the current scanning point read by the laser radar, and obtaining the read angle;

calculating the angle of the current scanning point according to the previous scanning point and the next scanning point to obtain the calculated angle;

and filtering the current scanning point when the current scanning point is determined to be a noise point according to the read angle and the calculated angle.

2. The method of claim 1, wherein, when the target distance is greater than the distance threshold, the method further comprises, before the step of obtaining the read angle, obtaining the angle of the current scanning point read by the laser radar:

acquiring the minimum resolution size of the laser radar at the current scanning point, wherein the minimum resolution size is the minimum distance from which the laser radar can distinguish two objects in distance;

and determining a distance threshold according to the minimum resolution size and a preset first angle.

3. The method of claim 2, wherein the step of determining a distance threshold based on the minimum resolution size and a predetermined first angle comprises:

and determining the ratio between the minimum resolution size and the cosine value of the first angle as a distance threshold.

4. The method of claim 2, wherein the step of obtaining a minimum resolved dimension of the lidar at the current scan point comprises:

acquiring the distance between the current scanning point and the laser radar and the angular resolution of the laser radar, wherein the angular resolution is the minimum angle at which the laser radar can distinguish two objects;

and calculating the minimum resolution size according to the distance between the current scanning point and the laser radar and the angular resolution.

5. The method of claim 1, wherein the step of determining the current scan point as a noise point based on the read angle and the calculated angle comprises:

determining an absolute value of a difference between the calculated angle and the read angle;

and when the absolute value is smaller than a preset second angle, determining the current scanning point as a noise point, wherein the second angle is smaller than the first angle.

6. The method of claim 5, wherein the method further comprises:

and when the absolute value is larger than or equal to the second angle, determining the current scanning point as a real point, and reserving the current scanning point.

7. The method of claim 1, wherein the step of calculating the angle of the current scan point from the previous scan point and the next scan point, the calculated angle comprising:

calculating the slope of the current scanning point according to the previous scanning point and the next scanning point;

performing arctangent calculation on the slope;

and converting the arc tangent calculation result into a designated interval according to the direction of a vector formed by the last scanning point and the previous scanning point to obtain the calculated angle.

8. The method according to claim 1, wherein the method further comprises:

and filtering the current scanning point when the target distance is greater than the distance threshold.

9. A noise filtering apparatus, comprising:

a distance acquisition module for acquiring the larger of the distance between the current scanning point and the previous scanning point and the distance between the current scanning point and the next scanning point as a target distance;

the angle reading module is used for acquiring the angle of the current scanning point read by the laser radar when the target distance is smaller than or equal to the distance threshold value, and obtaining the read angle;

the angle calculation module is used for calculating the angle of the current scanning point according to the previous scanning point and the next scanning point to obtain the calculated angle;

and the noise filtering module is used for filtering the current scanning point when the current scanning point is determined to be the noise point according to the read angle and the calculated angle.

10. An autonomous mobile apparatus, comprising:

a memory and a processor, the memory having stored therein an application for performing the method of any of claims 1-8 when invoked by the processor.

11. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a program code for performing the method according to any of claims 1-8 when called by a processor.