CN111929657B - Noise filtering method, device and equipment for laser radar - Google Patents
Noise filtering method, device and equipment for laser radar Download PDFInfo
- Publication number
- CN111929657B CN111929657B CN202010872497.1A CN202010872497A CN111929657B CN 111929657 B CN111929657 B CN 111929657B CN 202010872497 A CN202010872497 A CN 202010872497A CN 111929657 B CN111929657 B CN 111929657B
- Authority
- CN
- China
- Prior art keywords
- laser
- point
- segment
- current
- calibration
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
- G01S7/4802—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
Abstract
The embodiment of the invention provides a method, a device and equipment for filtering noise of a laser radar. The method comprises the following steps of 1: segmenting the original laser data to obtain a plurality of laser segments; step 2: setting a granularity threshold value, and executing the step 3; step 3: removing the laser segments smaller than the granularity threshold, and connecting and reorganizing the laser segments with the distance between the starting point and the end point in the rest laser segments smaller than the standard interval with the last laser segment; step 4: and (3) iterating the granularity threshold, and executing the step (3) until the granularity threshold reaches a preset maximum granularity threshold, so as to obtain the laser segment with noise filtered. In this way, the iteration granularity threshold can be dynamic, small-section laser noise points in the granularity range can be filtered, and useful information in laser data can be protected; and carrying out directional filtering on special noise points caused by the reflector lamp with a mechanical structure.
Description
Technical Field
Embodiments of the present invention relate generally to the field of lidar, and more particularly, to a method, apparatus, and device for filtering noise of a lidar.
Background
For some lidars, especially some cheaper lidars, there are often many "dead spots" (points with an output r value of nan being illegal) or noise in the output laser signals, and the noise concentration in such lidars is quite high, when we use larger granularity to filter out laser segments with a length smaller than the granularity, we tend to divide the laser segments into a plurality of points in one laser segment in the process of dividing the laser segments, because the "dead spots" are divided into a plurality of discontinuous small segments, and when the small segments are also smaller than the granularity needed by us, the small segments are also removed by errors, so that the filtered points are quite sparse, and the robot navigation and obstacle avoidance become very difficult.
For laser noise caused by some structures, which does not conform to the mathematical characteristics of the "noise" described above, it is generally difficult to filter the noise by using a general detection method, but the position where the laser appears is generally fixed, and we usually use angle filtering to remove the laser point at a specific angle in the laser scanning profile, so that the method sometimes removes excessive useful information.
Disclosure of Invention
According to the embodiment of the invention, a noise filtering scheme of a laser radar is provided.
In a first aspect of the invention, a method for noise filtering of a lidar is provided. The method comprises the following steps:
step 1: segmenting the original laser data to obtain a plurality of laser segments;
step 2: setting a granularity threshold value, and executing the step 3;
step 3: removing the laser segments smaller than the granularity threshold, and connecting and reorganizing the laser segments with the distance between the starting point and the end point in the rest laser segments smaller than the standard interval with the last laser segment;
step 4: and (3) iterating the granularity threshold, and executing the step (3) until the granularity threshold reaches a preset maximum granularity threshold, so as to obtain the laser segment with noise filtered.
Further, the segmenting the original laser data includes:
step 1.1: starting from the first laser point in the original laser data, executing step 1.2;
step 1.2: calculating a first distance between a next laser point and a current laser point, if the first distance is smaller than a standard interval, updating the end point of a laser section where the current laser point is positioned to the next laser point, and executing step 1.3; if the first distance is not smaller than the standard interval, taking the current laser point as the end point of the laser section where the current laser point is located, taking the next laser point as the starting point of the next laser section, and executing the step 1.3;
step 1.3: judging whether a next laser point exists, and if so, executing the step 1.2; otherwise, ending the current segment.
Further, the connection recombination is to connect the start point of the current laser segment with the end point of the last laser segment, so that the current laser segment and the last laser segment are connected into a recombined laser segment.
Further, the step 4 includes:
step 4.1: adding 1 to the granularity threshold value, and updating the granularity threshold value;
step 4.2: judging whether the current granularity threshold reaches the maximum granularity threshold, if so, ending iteration to obtain a laser segment with noise filtered; otherwise, rejecting the laser segments smaller than the granularity threshold, connecting and recombining the laser segments with the distance between the starting point and the end point in the rest laser segments smaller than the standard interval with the last laser segment, and executing the step 4.1.
Further, the method further comprises the following steps:
calibrating the position of the laser noise clusters to obtain a filtering area;
and filtering the laser points falling into the filtering area.
Further, the marking the position of the laser noise cluster to obtain a filtered area includes:
collecting a frame of laser data, filtering out laser points in the laser data, wherein the polar diameter of the laser points is smaller than the reference range threshold of the laser noise point, and segmenting the rest calibration laser points to obtain a plurality of calibration laser segments;
converting a calibration laser spot in the calibration laser section from a polar coordinate to a coordinate under a Cartesian coordinate system, and respectively finding out an abscissa minimum value, an abscissa maximum value, an ordinate minimum value and an ordinate maximum value;
and establishing a rectangular area by using the abscissa minimum value, the abscissa maximum value, the ordinate minimum value and the ordinate maximum value as filtering areas.
Further, the segmenting the remaining calibration laser points to obtain a plurality of calibration laser points includes:
step 5.1: taking the first calibration laser point which is not 0 in the rest calibration laser points as a starting point, and executing the step 5.2;
step 5.2: calculating a second distance between the current calibration laser point and the starting point, if the second distance is smaller than a maximum distance threshold between the current calibration laser point and the starting point, updating the end point of the calibration laser section where the current calibration laser point is positioned to be the next calibration laser point, and executing the step 5.3; if the second distance is not smaller than the maximum distance threshold between the current calibration laser point and the starting point, taking the current calibration laser point as the end point of the calibration laser section where the current calibration laser point is positioned, taking the next calibration laser point as the starting point of the next calibration laser section, and executing the step 5.3;
step 5.3: judging whether a next calibration laser spot exists, and if so, executing the step 5.2; otherwise, ending the current segment.
In a second aspect of the present invention, a noise filtering apparatus for a lidar is provided. The device comprises:
the segmentation module is used for segmenting the original laser data to obtain a plurality of laser segments;
the setting module is used for setting a granularity threshold value and calling the connection reorganization module;
the connection recombination module is used for eliminating the laser segments smaller than the granularity threshold value, and connecting and recombining the laser segments with the distance between the starting point and the end point in the rest laser segments smaller than the standard interval with the last laser segment;
and the iteration module is used for iterating the granularity threshold value, and returning to the connection recombination module until the granularity threshold value reaches a preset maximum granularity threshold value, so as to obtain the laser segment with noise filtered.
In a third aspect of the invention, an electronic device is provided. The electronic device includes: a memory and a processor, the memory having stored thereon a computer program, the processor implementing the method as described above when executing the program.
In a fourth aspect of the invention, there is provided a computer readable storage medium having stored thereon a computer program which when executed by a processor implements a method as according to the first aspect of the invention.
It should be understood that the description in this summary is not intended to limit the critical or essential features of the embodiments of the invention, nor is it intended to limit the scope of the invention. Other features of the present invention will become apparent from the description that follows.
The invention can dynamically iterate the granularity threshold value, filter small-section laser noise points within the granularity range, and protect useful information in laser data.
Drawings
The above and other features, advantages and aspects of embodiments of the present invention will become more apparent by reference to the following detailed description when taken in conjunction with the accompanying drawings. In the drawings, wherein like or similar reference numerals denote like or similar elements, in which:
FIG. 1 shows a schematic diagram of a laser signal with a dead spot according to an embodiment of the invention;
FIG. 2 shows a flow chart of a method of noise filtering of a lidar according to an embodiment of the invention;
FIG. 3 shows a flow chart for segmenting raw laser data according to an embodiment of the present invention;
FIG. 4 shows a schematic diagram of laser noise due to mechanical structure reflection in accordance with an embodiment of the present invention;
FIG. 5 shows a block diagram of a noise filtering apparatus of a lidar according to an embodiment of the present invention;
fig. 6 shows a block diagram of an exemplary electronic device capable of implementing embodiments of the invention.
In fig. 1, 1 is a laser segment, 2 is a laser segment damaged by a defective pixel, 3 is a defective pixel, 4 is a small segment of a sporadic material that is easily filtered out, 5 is noise, and 6 is a filtering area.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In addition, the term "and/or" herein is merely an association relationship describing an association object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.
In the real laser signal, a lot of bad points often exist, as shown in fig. 1, if according to the existing noise filtering method, small segments of laser points similar to the noise exist in the laser segments damaged by the bad points in fig. 1, as shown by a dotted line box 2 in fig. 1, the small segments are easily regarded as the noise to be wrongly proposed, so that the filtered points are very sparse, and the robot becomes very difficult to navigate and avoid obstacles.
According to the invention, the granularity threshold can be dynamically set, small-section laser noise points in the granularity range are subjected to iterative filtering, and meanwhile, useful information in laser data is protected from being filtered by errors.
Fig. 2 shows a flowchart of a noise filtering method of a lidar according to an embodiment of the present invention.
The method comprises the following steps:
s100, segmenting original laser data to obtain a plurality of laser segments;
the original laser data is a laser radar output signal, and is presented in the form of a polar coordinate point set, namely:
x i ＝[r i ，θ i ]
the length of the point set is recorded as n, r i Is the polar diameter of the laser point in the point concentration under the polar coordinate system; θ i Is the polar angle of the laser point in the polar coordinate system for the point concentration.
The segmentation of the original laser data, as shown in fig. 3, includes:
s110, starting from the first laser point in the original laser data, S120 is executed.
As an embodiment of the present invention, the laser points in the original laser data are ordered points, the order of which is sequentially arranged according to the size of the polar angle, and the laser point with the smallest polar angle is marked as the first laser point and is marked as 1.
S120, calculating a first distance between a next laser point and a current laser point, if the first distance is smaller than a standard interval, updating the end point of a laser section where the current laser point is located to the next laser point, and executing S130; if the first distance is not smaller than the standard interval, the current laser point is taken as the end point of the laser section where the current laser point is located, and the next laser point is taken as the start point of the next laser section, and S130 is executed.
As an embodiment of the invention, the distance of the current laser spot to the next laser spot is calculated:
dx＝r i+1 ·cosθ i+1 -r i ·cosθ i
dy＝r i+1 ·sinθ i+1 -r i ·sinθ i
wherein dist i，i+1 Representing the distance between the (i+1) th laser spot and the (i) th laser spot; r is (r) i+1 Representing the polar diameter of the (i+1) th laser spot under the polar coordinate system; r is (r) i Representing the polar diameter of the ith laser spot in the polar coordinate system; θ i+1 Representing the polar angle of the (i+1) th laser spot in the polar coordinate system; θ i Representing the polar angle of the ith laser spot in the polar coordinate system.
In summary, the distance between two laser points is calculated and recorded as the first distance.
A standard interval dist _ max is preset, which represents a conventional distance value between two laser points, which value varies depending on the kind of laser, for example, a standard interval of a general laser is 15cm.
The calculated first distance dist between the two laser points i，i+1 Comparing with a preset standard interval dist_max, if the first distance dist i，i+1 If the distance between the two laser points is smaller than the preset standard interval dist_max, the distance between the two laser points is within the conventional distance, and the two laser points can be regarded as the laser points in the same laser section; i.e., the end point of the laser segment where the i-th laser spot is located is updated to the i+1th laser spot, S130 is executed.
If the first distance dist i，i+1 Not smaller than the preset standard interval dist_max, the distance between the two laser points exceeds the conventional distance, and the two laser points can be regarded as laser points of two different laser segments; i.e. the i-th laser point is taken as the end point of the laser section where the i-th laser point is located, the i+1th laser point is taken as the start point of the next laser section, and the S130 is executed with the i+1th laser point.
S130, judging whether a next laser point exists, and executing S120 if the next laser point exists; otherwise, ending the current segment.
In this embodiment, after the above determination, it is determined whether the (i+2) th laser spot exists, if so, it is indicated that there are any unsegmented laser spots in the original laser data, and the process needs to return to S120 to continue execution; if not, then it is indicated that there is no unsegmented original laser dataThe laser points, at this time, have been segmented to all laser points, resulting in a number of laser segments. The laser segments are represented as segments k ＝{start k ，end k }，start k And end k Indicating the start and end of the laser segment, respectively.
By segmentation, a plurality of discrete laser points in the original laser data are changed into a plurality of laser segments, so that the judgment times in the later filtering process are reduced, and the judgment efficiency is improved.
S200, setting a granularity threshold value, and executing S300;
the granularity threshold value is represented by q and is used for setting a granularity limit of filtering and is used as a judgment basis for filtering a laser segment. The granularity threshold starts at 2 and increases by 1 once with the iterative process, i.e. q=q+1.
And S300, eliminating the laser segments smaller than the granularity threshold, and connecting and recombining the laser segments with the distance between the starting point and the end point in the rest laser segments smaller than the standard interval with the last laser segment.
Here, it is necessary to determine whether or not there is a laser segment smaller than the grain size threshold, i.e., end, among the obtained laser segments k -start k < q, if any, filtering the laser segment; and judging the distance between the starting point of each laser segment and the end point of other laser segments in the laser segments remaining after filteringIf the distance between the two laser segments is smaller than the standard interval dist_max, the distance between the two laser segments is within the standard interval, and the two laser segments can be connected and recombined; the connection reorganization is to connect the start point of the current laser segment and the end point of the last laser segment to connect the current laser segment and the last laser segment into a reorganization laser segment, namely, if->Then segment is to be segment k Starting point and segment of (c) k-1 Is connected at the end of the connection.
And S400, iterating the granularity threshold, and executing S300 until the granularity threshold reaches a preset maximum granularity threshold, so as to obtain the laser segment with noise filtered.
The granularity threshold starts from 2 and increases by 1 at a time with the iterative process, i.e. q=q+1. The iterative process is as follows:
s410, adding 1 to the granularity threshold, and updating the granularity threshold.
As an embodiment of the present invention, if the current granularity threshold is 2, the current granularity threshold is increased by 1, i.e. the current granularity threshold is updated to 3.
As the granularity threshold is a continuous positive integer, the granularity threshold can be continuously and gradually enlarged without jumping expansion by adding 1 each time of iteration, and omission is prevented.
S420, the granularity threshold is not increased without limitation, and a maximum granularity threshold q_max is preset according to requirements. Judging whether the current granularity threshold reaches the maximum granularity threshold, if so, indicating that all laser segments with the length within the maximum granularity threshold q_max are filtered, ending iteration and obtaining the laser segments with noise filtered; otherwise, rejecting the laser segment smaller than the granularity threshold, and connecting and reorganizing the laser segment with the distance between the starting point and the end point of the rest laser segments smaller than the standard interval with the last laser segment, so as to execute S410.
Through the S100-S400, small sections of laser noise points in the maximum granularity threshold range can be continuously and gradually filtered from small to large, and useful laser data are protected from being wrongly rejected. However, for laser noise caused by some structures, for example, laser noise caused by reflection of a mechanical structure, which does not conform to the mathematical characteristics of the noise described above, as shown in fig. 4, it is difficult to filter by the method of S100 to S400, at this time, the vertex coordinates of an area can be obtained by calibrating an area as a designated area and by calibrating the area in advance, and writing the vertex coordinates into a configuration file, and in the filtering process, the robot judges whether the laser spot falls into the area by reading the configuration file, and filters the laser spot falling into the area. The specific implementation method comprises the following steps:
s510, marking the position of the laser noise cluster, and obtaining a filtering area, wherein the filtering area is realized through the following S511-S514.
S511, collecting a frame of laser data, filtering out laser points in the laser data, wherein the polar diameter of the laser points is smaller than the threshold value of the reference range of the laser noise point, and segmenting the rest calibration laser points to obtain a plurality of calibration laser segments.
The position of the laser noise dot group at the fixed position needs to be calibrated, a robot provided with a laser radar is placed at a clear position, one frame of laser data is recorded, and signals output by the laser radar are presented in the form of a polar coordinate dot set, namely:
x j ＝[r j ，θ j ]
the length of the point set is recorded as m, r j The polar diameter of the calibrated laser point in the point set under the polar coordinate system; θ j The polar angle of the laser spot in the polar coordinate system is calibrated for the point set.
Because a laser noise reference range threshold exists in the calibration process, the calibration laser points with the length larger than the laser noise reference range threshold measured by the laser radar placed at the open place are not taken into consideration, and are filtered; the laser noise reference range threshold is typically set to 0.8m, i.e. for each r j When r is j At > 0.8, r j ＝0。
Segmenting the rest calibration laser points, which specifically comprises:
s511-1, taking the first calibration laser spot which is not 0 in the rest calibration laser spots as a starting point, and executing S511-2.
First, determine r j If 0, skipping detection; if r j Not 0, in r j The corresponding calibrated laser spot is used as the start point of the segment 1 From this point, each calibration laser spot is determined back in turn.
S511-2, calculating a second distance between the current calibration laser point and the starting point, if the second distance is smaller than a maximum distance threshold between the current calibration laser point and the starting point, updating the end point of the calibration laser segment where the current calibration laser point is located to be the next calibration laser point, and executing S511-3; and if the second distance is not smaller than the maximum distance threshold between the current calibration laser point and the starting point, taking the current calibration laser point as the end point of the calibration laser segment where the current calibration laser point is positioned, and taking the next calibration laser point as the starting point of the next calibration laser segment, and executing S511-3.
The distance between the current calibration laser point and the starting point, namely the second distance is:
wherein dist j The distance between the laser point and the starting point is calibrated currently; r is (r) j Representing the polar diameter of the current calibration laser point under a polar coordinate system; θ j Representing the polar angle of the current calibration laser point under a polar coordinate system;representing the polar diameter of the starting point under a polar coordinate system; />Representing the polar angle of the origin in the polar coordinate system.
The maximum distance threshold beta between the current calibration laser spot and the starting point is preset, and is generally set to be 0.1 < beta < 0.2.
The calculated second distance dist j Comparing with the maximum distance threshold beta between the current calibrated laser point and the starting point, if dist j If < beta, updating the end point of the laser segment where the jth calibration laser point is positioned to be the jth+1th calibration laser point, and adding the jth calibration laser point to segment 1 S511-3 is performed. If the second distancedist j Not less than the maximum distance threshold beta, i.e. dist j The j-th calibration laser point is used as the end point end of the calibration laser section where the j-th calibration laser point is positioned 1 And the (i+1) th calibration laser point is used as the starting point of the next calibration laser segment 2 And S511-3 is performed with the j+1th nominal laser spot.
S511-3, judging whether the next calibration laser spot exists, and executing S511-2 if the next calibration laser spot exists; otherwise, ending the current segment.
In this embodiment, after the above determination, it is determined whether the j+2th calibration laser spot exists, if so, it is indicated that there are any non-segmented calibration laser spots in the frame of laser data, and the process needs to be returned to S511-2 for further execution; if not, the frame laser data is indicated to have no unsegmented calibration laser points, and the segmentation of all calibration laser points is completed to obtain a plurality of laser segments, which are marked as { segment } 1 ，segment 2 ，...，segment n }。
S512, converting the calibration laser points in the calibration laser segment from polar coordinates to coordinates in a Cartesian coordinate system, wherein the abscissa set of all points is { x } j All ordinate sets are { y } j Finding out the minimum value, maximum value, minimum value and maximum value of x min [J]，x max [J]，y min [J]，y max [J]。
And S513, establishing a rectangular area with the abscissa minimum value, the abscissa maximum value, the ordinate minimum value and the ordinate maximum value as filtering areas.
S520, filtering the laser points falling into the filtering area.
In order to ensure reliable calibration, multiple calibration can be performed, a corresponding data record is obtained, and a final result is written into a configuration file so as to be called when filtering, and the calibration is finished.
The method of S100-S400 can dynamically iterate the granularity threshold value, filter small-section laser noise points within the granularity range, and protect useful information in laser data; by the method of S510 and S520, the special noise caused by the mechanical reflector lamp can be directionally filtered.
It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present invention is not limited by the order of acts described, as some steps may be performed in other orders or concurrently in accordance with the present invention. Further, those skilled in the art will also appreciate that the embodiments described in the specification are alternative embodiments, and that the acts and modules referred to are not necessarily required for the present invention.
The above description of the method embodiments further describes the solution of the present invention by means of device embodiments.
As shown in fig. 5, the apparatus 500 includes:
the first segmentation module 510 is configured to segment the original laser data to obtain a plurality of laser segments.
Further, the first segmentation module 510 further includes:
a first starting module 511, configured to start from a first laser point in the original laser data, and call the end point judging module 512;
a first judging module 512, configured to calculate a first distance between a next laser point and a current laser point, if the first distance is smaller than a standard interval, update an end point of a laser segment where the current laser point is located to the next laser point, and call a second judging module 513; if the first distance is not smaller than the standard interval, taking the current laser point as the end point of the laser section where the current laser point is located, taking the next laser point as the starting point of the next laser section, and calling a second judging module 513;
a second judging module 513, configured to judge whether a next laser point exists, and if so, call the first judging module 512; otherwise, ending the current segment.
A setting module 520, configured to set a granularity threshold, and invoke a connection reorganization module;
the connection reorganization module 530 is configured to reject the laser segments smaller than the granularity threshold, and perform connection reorganization on the laser segments with the distance between the start point and the end point of the remaining laser segments smaller than the standard interval and the previous laser segment;
the connection recombination is to connect the start point of the current laser segment with the end point of the last laser segment, so that the current laser segment and the last laser segment are connected into a recombined laser segment.
And the iteration module 540 is used for iterating the granularity threshold value and returning to the connection reorganization module until the granularity threshold value reaches a preset maximum granularity threshold value, so as to obtain the laser segment with noise filtered.
Further, the iteration module 540 further includes:
an updating module 541, configured to add 1 to the granularity threshold, and update the granularity threshold;
a third judging module 542, configured to judge whether the current granularity threshold reaches the maximum granularity threshold, and if so, end iteration to obtain a laser segment with noise filtered; otherwise, the laser segments smaller than the granularity threshold are removed, the laser segments with the distance between the starting point and the end point smaller than the standard interval in the rest laser segments are connected and recombined with the last laser segment, and the updating module 541 is invoked.
The apparatus 500 further comprises:
the calibration module 550 is used for calibrating the position of the laser noise cluster to obtain a filtering area;
and the filtering module 560 is configured to filter the laser points that fall within the filtering area.
Further, the calibration module 550 further includes:
the second segmentation module 551 is configured to collect a frame of laser data, filter out laser points in the laser data, where the polar diameter of the laser points in the polar coordinate system is smaller than a threshold value of a reference range of laser noise points, and segment the remaining calibration laser points to obtain a plurality of calibration laser segments;
the coordinate conversion module 552 is configured to convert the polar coordinates of the calibration laser spot in the calibration laser segment into coordinates in a cartesian coordinate system, and find an abscissa minimum value, an abscissa maximum value, an ordinate minimum value, and an ordinate maximum value, respectively;
the region establishing module 553 is configured to establish a rectangular region with the abscissa minimum value, the abscissa maximum value, the ordinate minimum value, and the ordinate maximum value as a filtered region.
Further, the second segmentation module 551 further includes:
the second starting module 551-1 is configured to call the fourth judging module 551-2 by using the first calibration laser point that is not 0 of the remaining calibration laser points as a starting point;
a fourth judging module 551-2, configured to calculate a second distance between the current calibration laser point and the starting point, if the second distance is smaller than a maximum distance threshold between the current calibration laser point and the starting point, update the end point of the calibration laser segment where the current calibration laser point is located to the next calibration laser point, and call a fifth judging module 551-3; if the second distance is not smaller than the maximum distance threshold between the current calibration laser point and the starting point, taking the current calibration laser point as the end point of the calibration laser section where the current calibration laser point is positioned, taking the next calibration laser point as the starting point of the next calibration laser section, and calling a fifth judging module 551-3;
a fifth judging module 551-3, configured to judge whether a next calibration laser spot exists, and if so, execute step 5.2; otherwise, ending the current segment.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the described modules may refer to corresponding procedures in the foregoing method embodiments, which are not described herein again.
As shown in fig. 6, the electronic device includes a Central Processing Unit (CPU) that can perform various suitable actions and processes according to computer program instructions stored in a Read Only Memory (ROM) or computer program instructions loaded from a storage unit into a Random Access Memory (RAM). In the RAM, various programs and data required for the operation of the device can also be stored. The CPU, ROM and RAM are connected to each other by a bus. An input/output (I/O) interface is also connected to the bus.
A plurality of components in an electronic device are connected to an I/O interface, comprising: an input unit such as a keyboard, a mouse, etc.; an output unit such as various types of displays, speakers, and the like; a storage unit such as a magnetic disk, an optical disk, or the like; and communication units such as network cards, modems, wireless communication transceivers, and the like. The communication unit allows the electronic device to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processing unit performs the respective methods and processes described above, for example, the methods S100 to S400. For example, in some embodiments, methods S100-S400 may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as a storage unit. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device via the ROM and/or the communication unit. When the computer program is loaded into RAM and executed by the CPU, one or more steps of the methods S100 to S400 described above may be performed. Alternatively, in other embodiments, the CPU may be configured to perform methods S100-S400 by any other suitable means (e.g., by means of firmware).
The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a load programmable logic device (CPLD), etc.
Program code for carrying out methods of the present invention may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, 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.
Moreover, although operations are depicted in a particular order, this should be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the invention. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single implementation. Conversely, various features that are described in the context of a single implementation can also be implemented in multiple implementations separately or in any suitable subcombination.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are example forms of implementing the claims.
Claims (8)
1. The noise filtering method for the laser radar is characterized by comprising the following steps of:
step 1: segmenting the original laser data to obtain a plurality of laser segments, wherein the segmenting the original laser data comprises the following steps:
step 1.1: starting from the first laser spot in the original laser data, step 1.2 is performed,
step 1.2: calculating a first distance between a next laser point and a current laser point, if the first distance is smaller than a standard interval, updating the end point of a laser section where the current laser point is positioned to the next laser point, and executing step 1.3; if the first distance is not smaller than the standard interval, taking the current laser point as the end point of the laser section where the current laser point is located and taking the next laser point as the starting point of the next laser section, executing the step 1.3,
step 1.3: judging whether a next laser point exists, and if so, executing the step 1.2; otherwise, ending the current segmentation;
step 2: setting a granularity threshold value, and executing the step 3;
step 3: removing the laser segments smaller than the granularity threshold, and connecting and recombining the laser segments with the distance between the starting point and the end point in the rest laser segments smaller than the standard interval with the last laser segment, wherein the connecting and recombining is to connect the starting point of the current laser segment with the end point of the last laser segment, so that the current laser segment and the last laser segment are connected into a recombined laser segment;
step 4: and (3) iterating the granularity threshold, and executing the step (3) until the granularity threshold reaches a preset maximum granularity threshold, so as to obtain the laser segment with noise filtered.
2. The method according to claim 1, wherein the step 4 comprises:
step 4.1: adding 1 to the granularity threshold value, and updating the granularity threshold value;
step 4.2: judging whether the current granularity threshold reaches the maximum granularity threshold, if so, ending iteration to obtain a laser segment with noise filtered; otherwise, rejecting the laser segments smaller than the granularity threshold, connecting and recombining the laser segments with the distance between the starting point and the end point in the rest laser segments smaller than the standard interval with the last laser segment, and executing the step 4.1.
3. The method as recited in claim 1, further comprising:
calibrating the position of the laser noise clusters to obtain a filtering area;
and filtering the laser points falling into the filtering area.
4. A method according to claim 3, wherein the calibrating the location of the laser noise cluster to obtain the filtered region comprises:
collecting a frame of laser data, filtering out laser points in the laser data, wherein the polar diameter of the laser points is smaller than the reference range threshold of the laser noise point, and segmenting the rest calibration laser points to obtain a plurality of calibration laser segments;
converting a calibration laser spot in the calibration laser section from a polar coordinate to a coordinate under a Cartesian coordinate system, and respectively finding out an abscissa minimum value, an abscissa maximum value, an ordinate minimum value and an ordinate maximum value;
and establishing a rectangular area by using the abscissa minimum value, the abscissa maximum value, the ordinate minimum value and the ordinate maximum value as filtering areas.
5. The method of claim 4, wherein the segmenting the remaining calibration laser points to obtain a plurality of calibration laser segments comprises:
step 5.1: taking the first calibration laser point which is not 0 in the rest calibration laser points as a starting point, and executing the step 5.2;
step 5.2: calculating a second distance between the current calibration laser point and the starting point, if the second distance is smaller than a maximum distance threshold between the current calibration laser point and the starting point, updating the end point of the calibration laser section where the current calibration laser point is positioned to be the next calibration laser point, and executing the step 5.3; if the second distance is not smaller than the maximum distance threshold between the current calibration laser point and the starting point, taking the current calibration laser point as the end point of the calibration laser section where the current calibration laser point is positioned, taking the next calibration laser point as the starting point of the next calibration laser section, and executing the step 5.3;
step 5.3: judging whether a next calibration laser spot exists, and if so, executing the step 5.2; otherwise, ending the current segment.
6. A noise filtering device for a laser radar, comprising:
the segmentation module is used for segmenting the original laser data to obtain a plurality of laser segments, wherein the segmentation of the original laser data comprises the following steps:
step 1.1: starting from the first laser spot in the original laser data, step 1.2 is performed,
step 1.2: calculating a first distance between a next laser point and a current laser point, if the first distance is smaller than a standard interval, updating the end point of a laser section where the current laser point is positioned to the next laser point, and executing step 1.3; if the first distance is not smaller than the standard interval, taking the current laser point as the end point of the laser section where the current laser point is located and taking the next laser point as the starting point of the next laser section, executing the step 1.3,
step 1.3: judging whether a next laser point exists, and if so, executing the step 1.2; otherwise, ending the current segmentation;
the setting module is used for setting a granularity threshold value and calling the connection reorganization module;
the connection recombination module is used for eliminating the laser segments smaller than the granularity threshold, and connecting and recombining the laser segments with the starting point and the end point of the rest laser segments, wherein the distance between the starting point and the end point of the laser segments is smaller than the standard interval, with the last laser segment, and the connection recombination is that the starting point of the current laser segment is connected with the end point of the last laser segment, so that the current laser segment and the last laser segment are connected into a recombined laser segment;
and the iteration module is used for iterating the granularity threshold value, and returning to the connection recombination module until the granularity threshold value reaches a preset maximum granularity threshold value, so as to obtain the laser segment with noise filtered.
7. An electronic device comprising a memory and a processor, the memory having stored thereon a computer program, wherein the processor, when executing the program, implements the method of any of claims 1-5.
8. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method according to any one of claims 1-5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010872497.1A CN111929657B (en) | 2020-08-26 | 2020-08-26 | Noise filtering method, device and equipment for laser radar |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010872497.1A CN111929657B (en) | 2020-08-26 | 2020-08-26 | Noise filtering method, device and equipment for laser radar |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111929657A CN111929657A (en) | 2020-11-13 |
| CN111929657B true CN111929657B (en) | 2023-09-19 |
Family
ID=73305861
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010872497.1A Active CN111929657B (en) | 2020-08-26 | 2020-08-26 | Noise filtering method, device and equipment for laser radar |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111929657B (en) |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104240251A (en) * | 2014-09-17 | 2014-12-24 | 中国测绘科学研究院 | Multi-scale point cloud noise detection method based on density analysis |
| CN105547305A (en) * | 2015-12-04 | 2016-05-04 | 北京布科思科技有限公司 | Pose solving method based on wireless positioning and laser map matching |
| CN109272524A (en) * | 2018-08-27 | 2019-01-25 | 大连理工大学 | A kind of small scale point cloud noise denoising method based on Threshold segmentation |
| JP2019126035A (en) * | 2018-01-15 | 2019-07-25 | キヤノン株式会社 | Image processing system, image processing method and program |
| CN110298795A (en) * | 2019-05-22 | 2019-10-01 | 中交第二航务工程局有限公司 | Tunnel three-dimensional laser aggregation of data denoising method |
| CN110969624A (en) * | 2019-11-07 | 2020-04-07 | 哈尔滨工程大学 | Laser radar three-dimensional point cloud segmentation method |
| CN111080536A (en) * | 2019-11-13 | 2020-04-28 | 武汉华中天经通视科技有限公司 | Self-adaptive filtering method for airborne laser radar point cloud |
| CN210822527U (en) * | 2019-07-31 | 2020-06-23 | 深圳布科思科技有限公司 | Double-laser setting structure for unmanned carrying vehicle |
| CN111462275A (en) * | 2019-01-22 | 2020-07-28 | 北京京东尚科信息技术有限公司 | Map production method and device based on laser point cloud |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10598764B2 (en) * | 2017-10-30 | 2020-03-24 | Yekutiel Josefsberg | Radar target detection and imaging system for autonomous vehicles with ultra-low phase noise frequency synthesizer |
-
2020
- 2020-08-26 CN CN202010872497.1A patent/CN111929657B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104240251A (en) * | 2014-09-17 | 2014-12-24 | 中国测绘科学研究院 | Multi-scale point cloud noise detection method based on density analysis |
| CN105547305A (en) * | 2015-12-04 | 2016-05-04 | 北京布科思科技有限公司 | Pose solving method based on wireless positioning and laser map matching |
| JP2019126035A (en) * | 2018-01-15 | 2019-07-25 | キヤノン株式会社 | Image processing system, image processing method and program |
| CN109272524A (en) * | 2018-08-27 | 2019-01-25 | 大连理工大学 | A kind of small scale point cloud noise denoising method based on Threshold segmentation |
| CN111462275A (en) * | 2019-01-22 | 2020-07-28 | 北京京东尚科信息技术有限公司 | Map production method and device based on laser point cloud |
| CN110298795A (en) * | 2019-05-22 | 2019-10-01 | 中交第二航务工程局有限公司 | Tunnel three-dimensional laser aggregation of data denoising method |
| CN210822527U (en) * | 2019-07-31 | 2020-06-23 | 深圳布科思科技有限公司 | Double-laser setting structure for unmanned carrying vehicle |
| CN110969624A (en) * | 2019-11-07 | 2020-04-07 | 哈尔滨工程大学 | Laser radar three-dimensional point cloud segmentation method |
| CN111080536A (en) * | 2019-11-13 | 2020-04-28 | 武汉华中天经通视科技有限公司 | Self-adaptive filtering method for airborne laser radar point cloud |
Non-Patent Citations (2)
| Title |
|---|
| A global optimization approach to roof segmentation from airborne lidar point clouds;Jixing Yan 等;《ISPRS Journal of Photogrammetry and Remote Sensing》;183-193 * |
| 汽车模具表面缺陷特征提取关键技术研究;王晓辉;《中国博士学位论文全文数据库 工程科技Ⅱ辑》(第1期);C035-16 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111929657A (en) | 2020-11-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109001757B (en) | Parking space intelligent detection method based on 2D laser radar | |
| CN115810133B (en) | Welding control method based on image processing and point cloud processing and related equipment | |
| CN112462758A (en) | Drawing establishing method and device, computer readable storage medium and robot | |
| CN113762003A (en) | Target object detection method, device, equipment and storage medium | |
| CN115239772A (en) | Ship curved plate three-dimensional point cloud registration method, system, storage medium and terminal | |
| CN111929657B (en) | Noise filtering method, device and equipment for laser radar | |
| CN114708400A (en) | Three-dimensional laser noise reduction method and device, medium and robot | |
| CN108960246B (en) | Binarization processing device and method for image recognition | |
| CN112465908B (en) | Object positioning method, device, terminal equipment and storage medium | |
| CN112097772B (en) | Robot and map construction method and device thereof | |
| CN111968102B (en) | Target equipment detection method, system, medium and electronic terminal | |
| CN116385415A (en) | Edge defect detection method, device, equipment and storage medium | |
| CN115457506A (en) | Target detection method, device and storage medium | |
| CN113362227B (en) | Image processing method, device, electronic equipment and storage medium | |
| CN115222939A (en) | Image recognition method, device, equipment and storage medium | |
| CN113805157A (en) | Height measuring method, device and equipment based on target | |
| CN111507287A (en) | Method and system for extracting road zebra crossing corner points in aerial image | |
| CN112052777B (en) | Method and device for extracting water-crossing bridge based on high-resolution remote sensing image | |
| CN114882461B (en) | Equipment environment recognition method and device, electronic equipment and automatic driving vehicle | |
| CN115512147B (en) | Semantic information based clustering method and device, electronic equipment and storage medium | |
| CN116051564B (en) | Chip packaging defect detection method and system | |
| CN113139975B (en) | Road feature-based pavement segmentation method and device | |
| CN114970700A (en) | Information classification method and device based on KNN algorithm of area buffer | |
| CN113139454B (en) | Road width extraction method and device based on single image | |
| US20240119569A1 (en) | Image processing apparatus and image processing method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |