CN111929657A - Laser radar noise filtering method, device and equipment - Google Patents
Laser radar noise filtering method, device and equipment Download PDFInfo
- Publication number
- CN111929657A CN111929657A CN202010872497.1A CN202010872497A CN111929657A CN 111929657 A CN111929657 A CN 111929657A CN 202010872497 A CN202010872497 A CN 202010872497A CN 111929657 A CN111929657 A CN 111929657A
- Authority
- CN
- China
- Prior art keywords
- laser
- point
- calibration
- segments
- current
- 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.)
- Granted
Links
Images
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 original laser data to obtain a plurality of laser segments; step 2: setting a granularity threshold value, and executing the step 3; and step 3: removing the laser segments smaller than the granularity threshold, and connecting and recombining the laser segments with the last laser segment, wherein the distance between the starting point and the end point in the rest laser segments is smaller than the standard interval; and 4, 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 section with the noise points filtered. In this way, the granularity threshold can be dynamically iterated, small sections of laser noise points in the granularity range are filtered, and useful information in laser data is protected; the method carries out directional filtering on special noise 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 noise filtering for lidar.
Background
For some laser radars, especially some cheaper laser radars, there are often many "dead spots" (points with output r value of nan illegal value) or noises in the laser signal output by the laser radars, and the concentration of the noises in the laser radars is quite high, when we use a larger granularity to filter out a laser segment with a length smaller than this granularity, we will often divide the laser segment into some points originally supposed to be in a laser segment because the "dead spots" are divided into a plurality of discontinuous segments, and when these segments are also smaller than the granularity that we need, these segments will be mistakenly removed, so that the filtered points are very sparse, and it is very difficult for the robot to navigate and avoid obstacles.
For laser noise caused by some structures, the mathematical characteristics of the noise do not meet the above description, and it is generally difficult to filter the noise by using a general detection method in this case, but the position where the laser appears is generally fixed, and we generally use angle filtering to remove the laser point at a specific angle in the laser scanning profile, and actually this method sometimes removes too much useful information.
Disclosure of Invention
According to the embodiment of the invention, a noise point 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 original laser data to obtain a plurality of laser segments;
step 2: setting a granularity threshold value, and executing the step 3;
and step 3: removing the laser segments smaller than the granularity threshold, and connecting and recombining the laser segments with the last laser segment, wherein the distance between the starting point and the end point in the rest laser segments is smaller than the standard interval;
and 4, 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 section with the noise points filtered.
Further, the segmenting the raw laser data includes:
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 the current laser point, if the first distance is smaller than a standard interval, updating the end point of the laser section where the current laser point is located to the next laser point, and executing the 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, and executing the step 1.3;
step 1.3: judging whether a next laser point exists, if so, executing the step 1.2; otherwise, ending the current segment.
Furthermore, the connection recombination is to connect the starting point of the current laser segment with the end point of the previous laser segment, so that the current laser segment and the previous 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 the iteration to obtain a laser section with noise points 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 remaining laser segments are connected and recombined with the last laser segment, and the step 4.1 is executed.
Further, still include:
calibrating the position of the laser noise cluster to obtain a filtered area;
and filtering the laser points falling into the filtering area.
Further, the step of calibrating the position of the laser noise cluster to obtain a filtered area includes:
collecting a frame of laser data, filtering laser points in the laser data, wherein the polar diameter of the laser points is smaller than a reference range threshold of a laser noise point under a polar coordinate system, and segmenting the remaining calibration laser points to obtain a plurality of calibration laser segments;
converting the polar coordinates of the calibration laser points in the calibration laser section into coordinates 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 a filtering area.
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 value 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 located 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 located, and 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 point exists, if so, executing the step 5.2; otherwise, ending the current segment.
In a second aspect of the invention, a laser radar noise filtering apparatus is provided. The device includes:
the segmentation module is used for segmenting 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 recombination module;
the connection and recombination module is used for removing the laser segments smaller than the granularity threshold value and connecting and recombining the laser segments with the last laser segment, wherein the distance between the starting point and the end point in the rest laser segments is smaller than the standard interval;
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 section with noise points filtered.
In a third aspect of the invention, an electronic device is provided. The electronic device includes: a memory having a computer program stored thereon and a processor implementing the method as described above when executing the program.
In a fourth aspect of the invention, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the method as according to the first aspect of the invention.
It should be understood that the statements herein reciting aspects are not intended to limit the critical or essential features of any embodiment of the invention, nor are they intended to limit the scope of the invention. Other features of the present invention will become apparent from the following description.
The invention can dynamically iterate the granularity threshold value, filter small sections of laser noise points within the granularity range and protect useful information in laser data.
Drawings
The above and other features, advantages and aspects of various embodiments of the present invention will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. In the drawings, like or similar reference characters designate like or similar elements, and wherein:
FIG. 1 shows a laser signal diagram with a dead spot according to an embodiment of the invention;
FIG. 2 shows a flow chart of a method of noise rejection for a lidar in accordance with an embodiment of the invention;
FIG. 3 illustrates a flow diagram for segmenting raw laser data according to an embodiment of the present invention;
FIG. 4 illustrates a schematic diagram of laser noise due to mechanical structure reflections, according to an embodiment of the present invention;
FIG. 5 shows a block diagram of a lidar noise filtering apparatus according to an embodiment of the invention;
FIG. 6 illustrates a block diagram of an exemplary electronic device capable of implementing embodiments of the present invention.
In fig. 1, 1 is a laser segment, 2 is a laser segment destroyed by a dead spot, 3 is a dead spot, 4 is a sporadic segment easy to be filtered, 5 is noise, and 6 is a filtering area.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
In addition, the term "and/or" herein is only one kind of association relationship describing an associated object, and means that there may be three kinds of relationships, for example, a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
A plurality of 'dead spots' often exist in a real laser signal, as shown in fig. 1, if a small segment of laser spots similar to noise spots exist in a laser segment damaged by the dead spots in fig. 1 according to an existing noise spot filtering method, as shown by a dashed line box 2 in fig. 1, the small segment is easily regarded as noise spots to be wrongly proposed, so that the filtered spots are very sparse, and a robot is very difficult to navigate and avoid obstacles.
According to the invention, the granularity threshold can be dynamically set, small sections of laser noise points in the granularity range are filtered in an iterative manner, and meanwhile, useful information in laser data is protected from being filtered by errors.
Fig. 2 is a flowchart illustrating a method for noise filtering 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 laser radar output signals and is presented in a polar coordinate point set mode, namely:
xi＝[ri，θi]
the length of the point set is recorded as n, riThe polar diameter of the laser point with concentrated points under a polar coordinate system; thetaiThe polar angle of the laser point with concentrated point under the polar coordinate system.
The segmenting of the original laser data, as shown in fig. 3, includes:
s110, S120 is performed starting from the first laser spot in the original laser data.
As an embodiment of the present invention, the laser spots in the original laser data are ordered spots, the order of the ordered spots is sequentially arranged according to the size of the polar angle, and the laser spot with the smallest polar angle is denoted as the first laser spot and is denoted as 1.
S120, calculating a first distance between a next laser point and the current laser point, if the first distance is smaller than a standard interval, updating the end point of the laser section where the current laser point is located to the next laser point, and executing S130; if the first distance is not less than the standard interval, the current laser point is taken as the end point of the laser segment where the current laser point is located, and the next laser point is taken as the start point of the next laser segment, and S130 is executed.
As an embodiment of the invention, the distance from the current laser spot to the next laser spot is calculated:
dx＝ri+1·cosθi+1-ri·cosθi
dy＝ri+1·sinθi+1-ri·sinθi
wherein, disti，i+1Representing the distance between the (i + 1) th laser point and the ith laser point; r isi+1The polar diameter of the (i + 1) th laser point under a polar coordinate system is represented; r isiThe polar diameter of the ith laser point in a polar coordinate system is represented; thetai+1Representing the polar angle of the (i + 1) th laser point under a polar coordinate system; thetaiThe polar angle of the ith laser spot in the polar coordinate system is shown.
In summary, the distance between the two laser spots is calculated and is denoted as the first distance.
A standard interval dist _ max is preset, which represents a conventional distance value between two laser spots, and this value varies according to the type of laser, for example, the standard interval of a typical laser is 15 cm.
Calculating the first distance dist between the two laser pointsi，i+1Comparing with a preset standard interval dist _ max if the first distance disti，i+1If 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 laser points in the same laser segment; that is, the end point of the laser segment where the ith laser point is located is updated to the (i + 1) th laser point, and S130 is performed.
If the first distance disti，i+1If the distance between the two laser points is not less 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 sections; that is, the ith laser point is taken as the end point of the laser segment where the ith laser point is located, the (i + 1) th laser point is taken as the start point of the next laser segment, and S130 is executed with the (i + 1) th laser point.
S130, judging whether a next laser point exists or not, and if so, executing S120; otherwise, ending the current segment.
In this embodiment, after the above determination, it is determined whether there is an i +2 th laser point, and if there is an i +2 th laser point, it indicates that there is a laser point that is not segmented in the original laser data, and it needs to return to S120 to continue execution; if the laser segments do not exist, the situation that the unsegmented laser points do not exist in the original laser data at the moment is shown, and the segmentation of all the laser points is completed at the moment, so that a plurality of laser segments are obtained. The plurality of laser segments are represented as segmentsk＝{startk，endk}，startkAnd endkRespectively representing the start and end points of the laser segment.
Through segmentation, a plurality of discrete laser points in original laser data are changed into a plurality of laser segments, 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 is represented by q, and is used for setting a filtered granularity limit as a judgment basis for laser segment filtering. The granularity threshold starts at 2 and increases by 1 as the iterative process progresses once, i.e. q ═ q + 1.
S300, eliminating the laser sections smaller than the granularity threshold, and connecting and recombining the laser sections with the last laser section, wherein the distance between the starting point and the end point in the rest laser sections is smaller than the standard interval.
Here, it is necessary to determine whether there is a laser segment smaller than the granularity threshold, that is, end, in the obtained laser segmentsk-startkIf so, filtering the laser section; and judging the distance between the starting point of each laser segment and the end points of other laser segments in the laser segments left after filtering
Whether the distance is smaller than the standard interval dist _ max or not, if so, the distance between the two laser segments is within the standard interval, and the two laser segments can be connected and recombined; the connection recombination is to connect the starting point of the current laser segment with the end point of the previous laser segment, so that the current laser segment and the previous laser segment are connected into a recombined laser segment, i.e., for example, ifFruit
Segment will bekStarting point and segment ofk-1Are connected.
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 section with noise points filtered.
The granularity threshold starts from 2 and increases by 1 with one iteration, i.e. q ═ q + 1. The iterative process is as follows:
and S410, adding 1 to the granularity threshold value, and updating the granularity threshold value.
As an embodiment of the present invention, if the current granularity threshold is 2, the current granularity threshold is added by 1, that is, the current granularity threshold is updated to 3.
Because the granularity threshold is a continuous positive integer, 1 is added in each iteration, the granularity threshold can be continuously and gradually expanded, no jump-type expansion is carried out, and omission is prevented.
S420, the granularity threshold is not increased without limitation, and a maximum granularity threshold q _ max is preset as required. Judging whether the current granularity threshold reaches the maximum granularity threshold, if so, indicating that all laser sections with the length within the maximum granularity threshold q _ max are filtered, and ending iteration to obtain laser sections with noise points filtered; otherwise, the laser segments smaller than the granularity threshold are removed, and the laser segments with the distance between the starting point and the end point smaller than the standard interval in the remaining laser segments are connected and recombined with the last laser segment, and S410 is executed.
Through the steps S100-S400, small 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 mistakenly removed. 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 methods of S100 to S400, at this time, a region can be calibrated as a designated region, the vertex coordinates of the region are obtained by calibration in advance, and are written into a configuration file, and in the filtering process, by reading the configuration file, the robot determines whether the laser point falls into the region, and filters the laser point falling into the region. The specific implementation method comprises the following steps:
and S510, calibrating the position of the laser noise cluster to obtain a filtered area, wherein the filtering is realized through the following steps 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 reference range threshold of the laser noise points under the polar coordinate system, and segmenting the remaining calibrated laser points to obtain a plurality of calibrated laser segments.
Need mark the position of the laser noise point group of fixed position, place the robot that will install laser radar in spacious position, record a frame laser data, the signal of laser radar output presents with the form of polar coordinate point set, promptly:
xj＝[rj，θj]
the length of the point set is recorded as m, rjThe polar diameter of a point-concentrated calibration laser point under a polar coordinate system; thetajAnd the polar angle of the point-concentrated calibration laser point under the polar coordinate system is obtained.
Because a laser noise point reference range threshold exists in the calibration process, the calibration laser point with the length larger than the laser noise point reference range threshold measured by the laser radar placed in an open place is not taken into consideration for filtering; the laser noise reference range threshold is typically set to 0.8m, i.e., for each rjWhen r isjWhen > 0.8, rj＝0。
Segmenting the remaining calibrated laser points, specifically comprising:
s511-1, taking the first marked laser point which is not 0 in the rest marked laser points as a starting point, and executing S511-2.
First, determine rjWhether the value is 0 or not, if yes, detection is skipped; if r isjIs not 0, with rjThe corresponding calibrated laser spot is used as the starting start of the segment1Each calibration laser point is determined sequentially backward from this point.
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 value 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 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 section where the current calibration laser point is located, and taking the next calibration laser point as the starting point of the next calibration laser section, and executing S511-3.
The distance between the current calibration laser point and the starting point, namely the second distance, is as follows:
wherein, distjThe distance between the current calibration laser point and the starting point is obtained; r isjRepresenting the polar diameter of the current calibration laser point under a polar coordinate system; thetajRepresenting 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 starting point in a polar coordinate system.
The maximum distance threshold beta between the current calibration laser point and the starting point is preset and is generally set to be more than 0.1 and less than 0.2.
Calculating the second distance distjComparing with the maximum distance threshold value beta between the current calibration laser point and the starting point, if distjIf the measured value is less than beta, the end point of the laser section where the jth calibrated laser point is located is updated to be the jth +1 calibrated laser point, and the jth calibrated laser point is added into the segment1S511-3 is performed. If the second distance distjNot less than a maximum distance threshold β, i.e. distjBeta or more, taking the jth calibrated laser point as the end point end of the calibrated laser section where the jth calibrated laser point is positioned1And taking the (i + 1) th calibrated laser point as the starting point start of the next calibrated laser segment2And S511-3 is performed with the j +1 th calibration laser spot.
S511-3, judging whether a next calibration laser point exists or not, and if so, executing S511-2; otherwise, ending the current segment.
In this embodiment, after the above determination, it is determined whether there is a j +2 th calibrated laser point, and if so, it indicates that there is an unsegmented calibrated laser point in the frame of laser data, and it needs to return to S511-2 to continue execution; if the laser segment is not present, the situation that the frame of laser data does not have the unsegmented calibrated laser point is shown, the segmentation of all calibrated laser points is completed at the moment, and a plurality of laser segments are obtained and marked as { segment1，segment2，...，segmentn}。
S512, converting the calibration laser points in the calibration laser section from polar coordinates into coordinates in a Cartesian coordinate system, and setting the abscissa set of all the points as { xjAll ordinate sets are { y }jFinding out the minimum value of the abscissa, the maximum value of the abscissa, the minimum value of the ordinate and the maximum value of the ordinate respectively, namely xmin[J]，xmax[J]，ymin[J]，ymax[J]。
S513, establishing a rectangular area by using the abscissa minimum value, the abscissa maximum value, the ordinate minimum value and the ordinate maximum value as a filtering area.
S520, filtering the laser points falling into the filtering area.
In order to ensure that the calibration is reliable, the calibration can be carried out for multiple times, relatively reasonable data records are taken, the final result is written into a configuration file so as to be called during filtering, and the calibration is finished at the moment.
According to the method, the granularity threshold can be dynamically iterated by the method of S100-S400, small sections of laser noise points in the granularity range are filtered, and meanwhile, useful information in laser data is protected; by the methods of S510 and S520, the special noise caused by the mechanical structure reflector lamp can be directionally filtered.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the invention. Further, those skilled in the art should also appreciate that the embodiments described in the specification are exemplary embodiments and that the acts and modules illustrated are not necessarily required to practice the invention.
The above is a description of method embodiments, and the embodiments of the present invention are further described below by way of apparatus 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 spot in original laser data, and invoke an end point determining module 512;
a first judging module 512, configured to calculate a first distance between a next laser point and a current laser point, update an end point of a laser segment where the current laser point is located to the next laser point if the first distance is smaller than a standard interval, and invoke a second judging module 513; if the first distance is not smaller than the standard interval, the current laser point is taken as the end point of the laser segment where the current laser point is located, the next laser point is taken as the starting point of the next laser segment, and a second judgment module 513 is called;
a second judging module 513, configured to judge whether a next laser point exists, and if so, invoke 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;
a connection and recombination module 530, configured to eliminate the laser segments smaller than the granularity threshold, and perform connection and recombination on the laser segments in which the distance between the starting point and the ending point in the remaining laser segments is smaller than the standard interval and the laser segment above the starting point;
the connection recombination 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.
And the iteration module 540 is configured to iterate the granularity threshold and return to the connection and recombination module until the granularity threshold reaches a preset maximum granularity threshold, so as to obtain a laser segment with noise points filtered.
Further, the iteration module 540 further includes:
an updating module 541, configured to add 1 to the granularity threshold to update the granularity threshold;
a third judging module 542, configured to judge whether the current granularity threshold reaches a maximum granularity threshold, and if so, end the iteration to obtain a laser segment after noise is 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 remaining laser segments are connected and recombined with the last laser segment, and the updating module 541 is called.
The apparatus 500 further comprises:
a calibration module 550, configured to calibrate a position of the laser noise cluster to obtain a filtered region;
and a filtering module 560, configured to filter the laser points falling into the filtering region.
Further, the calibration module 550 further includes:
the second segmentation module 551 is configured to collect a frame of laser data, filter laser points in the laser data, where a polar diameter under a polar coordinate system is smaller than a threshold of a reference range of laser noise points, and segment remaining calibration laser points to obtain a plurality of calibration laser segments;
a coordinate conversion module 552, configured to convert the polar coordinate of the calibration laser point in the calibration laser segment into a coordinate in a cartesian coordinate system, and find out a minimum abscissa value, a maximum abscissa value, a minimum ordinate value, and a maximum ordinate value, respectively;
and the region establishing module 553, 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 the filtering region.
Further, the second segment module 551 further includes:
the second starting module 551-1 is used for taking the first calibrated laser point which is not 0 in the remaining calibrated laser points as a starting point and calling the fourth judging module 551-2;
the fourth judging module 551-2 is configured to calculate a second distance 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 if the second distance is smaller than the maximum distance threshold between the current calibration laser point and the starting point, and call the 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 located, taking the next calibration laser point as the starting point of the next calibration laser section, and calling a fifth judgment module 551-3;
a fifth judging module 551-3, configured to judge whether a next calibrated laser point exists, and if so, execute step 5.2; otherwise, ending the current segment.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the described module may refer to the corresponding process in the foregoing method embodiment, and is not described herein again.
As shown in fig. 6, the electronic device includes a Central Processing Unit (CPU) that can perform various appropriate 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 via 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, including: an input unit such as a keyboard, a mouse, etc.; an output unit such as various types of displays, speakers, and the like; storage units such as magnetic disks, optical disks, and the like; and a communication unit such as a network card, modem, wireless communication transceiver, etc. 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 various methods and processes described above, such as methods S100-S400. For example, in some embodiments, the methods S100-S400 may be implemented as a computer software program tangibly embodied in 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 ROM and/or the communication unit. When the computer program is loaded into RAM and executed by the CPU, one or more of the steps of methods S100-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 way of firmware).
The functions described herein above 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), and the like.
Program code for implementing the methods of the present invention may be written in any combination of one or more programming languages. These program codes 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 codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. 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. A 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.
Further, while 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. Under 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 limitations on 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 disclosed as example forms of implementing the claims.
Claims (10)
1. A method for filtering noise of a laser radar is characterized by comprising the following steps:
step 1: segmenting original laser data to obtain a plurality of laser segments;
step 2: setting a granularity threshold value, and executing the step 3;
and step 3: removing the laser segments smaller than the granularity threshold, and connecting and recombining the laser segments with the last laser segment, wherein the distance between the starting point and the end point in the rest laser segments is smaller than the standard interval;
and 4, 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 section with the noise points filtered.
2. The method of claim 1, wherein segmenting the raw laser data comprises:
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 the current laser point, if the first distance is smaller than a standard interval, updating the end point of the laser section where the current laser point is located to the next laser point, and executing the 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, and executing the step 1.3;
step 1.3: judging whether a next laser point exists, if so, executing the step 1.2; otherwise, ending the current segment.
3. The method of claim 1, wherein the joining recombination is performed by joining a start point of a current laser segment with an end point of a previous laser segment, such that the current laser segment and the previous laser segment are joined into a recombined laser segment.
4. The method of 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 the iteration to obtain a laser section with noise points 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 remaining laser segments are connected and recombined with the last laser segment, and the step 4.1 is executed.
5. The method of claim 1, further comprising:
calibrating the position of the laser noise cluster to obtain a filtered area;
and filtering the laser points falling into the filtering area.
6. The method of claim 5, wherein said locating the laser noise blob to obtain a filtered region comprises:
collecting a frame of laser data, filtering laser points in the laser data, wherein the polar diameter of the laser points is smaller than a reference range threshold of a laser noise point under a polar coordinate system, and segmenting the remaining calibration laser points to obtain a plurality of calibration laser segments;
converting the polar coordinates of the calibration laser points in the calibration laser section into coordinates 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 a filtering area.
7. The method of claim 6, 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 value 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 located 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 located, and 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 point exists, if so, executing the step 5.2; otherwise, ending the current segment.
8. A laser radar noise point filtering device is characterized by comprising:
the segmentation module is used for segmenting 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 recombination module;
the connection and recombination module is used for removing the laser segments smaller than the granularity threshold value and connecting and recombining the laser segments with the last laser segment, wherein the distance between the starting point and the end point in the rest laser segments is smaller than the standard interval;
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 section with noise points filtered.
9. 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 1-7.
10. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, carries out the method according to any one of claims 1 to 7.
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 true CN111929657A (en) | 2020-11-13 |
| CN111929657B 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 (10)
| 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 |
| US20190128998A1 (en) * | 2017-10-30 | 2019-05-02 | Yekutiel Josefsberg | Radar target detection and imaging system for autonomous vehicles with ultra-low phase noise frequency synthesizer |
| 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 |
-
2020
- 2020-08-26 CN CN202010872497.1A patent/CN111929657B/en active Active
Patent Citations (10)
| 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 |
| US20190128998A1 (en) * | 2017-10-30 | 2019-05-02 | Yekutiel Josefsberg | Radar target detection and imaging system for autonomous vehicles with ultra-low phase noise frequency synthesizer |
| 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 |
|---|
| JIXING YAN 等: "A global optimization approach to roof segmentation from airborne lidar point clouds", 《ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING》, pages 183 - 193 * |
| 王晓辉: "汽车模具表面缺陷特征提取关键技术研究", 《中国博士学位论文全文数据库 工程科技Ⅱ辑》, no. 1, pages 035 - 16 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111929657B (en) | 2023-09-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20210063577A1 (en) | Robot relocalization method and apparatus and robot using the same | |
| CN110561423B (en) | Pose transformation method, robot and storage medium | |
| CN109001757B (en) | Parking space intelligent detection method based on 2D laser radar | |
| CN113917912A (en) | Global path planning method, device, terminal and readable storage medium | |
| CN112595323A (en) | Robot and drawing establishing method and device thereof | |
| JP6808787B1 (en) | Building change identification device and program | |
| CN112763993A (en) | Method and device for calibrating radar parameters, electronic equipment and storage medium | |
| US20230205212A1 (en) | Mapping method for mobile robot, mobile robot and computer-readable storage medium | |
| CN113792690A (en) | Lane line detection method and device | |
| CN109635641B (en) | Method, device and equipment for determining road boundary line and storage medium | |
| CN111968102B (en) | Target equipment detection method, system, medium and electronic terminal | |
| CN111929657A (en) | Laser radar noise filtering method, device and equipment | |
| CN108133116B (en) | Method and system for automatically identifying wall thickness of CAD house type graph | |
| CN115457506A (en) | Target detection method, device and storage medium | |
| CN114372689A (en) | Road network operation characteristic variable point identification method based on dynamic planning | |
| CN113435462A (en) | Positioning method, positioning device, electronic equipment and medium | |
| CN115690364A (en) | AR model acquisition method, electronic device and readable storage medium | |
| CN114882461B (en) | Equipment environment recognition method and device, electronic equipment and automatic driving vehicle | |
| CN111523391B (en) | Building identification method, system, electronic device and readable storage medium | |
| CN114694138B (en) | Road surface detection method, device and equipment applied to intelligent driving | |
| CN116563521B (en) | Detection frame processing method and device for target detection and electronic equipment | |
| WO2023231213A1 (en) | Road generation method and apparatus, electronic device, and storage medium | |
| US20240119569A1 (en) | Image processing apparatus and image processing method | |
| CN113377094A (en) | Reference point searching method and device for AGV map, electronic equipment and storage medium | |
| CN116843900A (en) | Infrared dim target detection method, device and storage medium |
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 |