CN116449379A - AGV positioning method and device based on special shape recognition - Google Patents

AGV positioning method and device based on special shape recognition Download PDF

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Publication number
CN116449379A
CN116449379A CN202310228675.0A CN202310228675A CN116449379A CN 116449379 A CN116449379 A CN 116449379A CN 202310228675 A CN202310228675 A CN 202310228675A CN 116449379 A CN116449379 A CN 116449379A
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shape
characteristic information
special
positioning
agv
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钟火炎
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Suzhou Century Electronics Co ltd
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Suzhou Century Electronics Co ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
    • G06V10/75—Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries
    • G06V10/757—Matching configurations of points or features
    • 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
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/006—Theoretical aspects
    • 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
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
    • G01S17/06—Systems determining position data of a target
    • 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
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/60—Electric or hybrid propulsion means for production processes

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Remote Sensing (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Electromagnetism (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
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  • General Health & Medical Sciences (AREA)
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  • Health & Medical Sciences (AREA)
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Abstract

The invention discloses an improved AGV positioning method based on special shape recognition, which comprises the following steps: acquiring laser data of an actual environment according to the actual working environment of the AGV, and setting a target object in the actual working environment as a special object shape to be identified; preprocessing the shape of a special object, extracting characteristic information of the shape, and carrying out coding sequencing again based on the characteristic information to form a unique variable of the shape of the special object; preprocessing laser data, extracting characteristic information of the laser data, calculating the matching accuracy through a characteristic matching model based on a unique variable, and selecting the highest accuracy obtained by calculation as a final positioning result. According to the invention, the matching accuracy is calculated, so that the intelligent transfer robot AGV can realize precision positioning by identifying the object with a special shape under the complex and frequent change scene, any hardware and site deployment work are not required to be added, the cost is low, and the positioning precision is improved.

Description

AGV positioning method and device based on special shape recognition
Technical Field
The invention relates to the technical field of intelligent mobile robots, in particular to an improved AGV positioning method and device based on special shape recognition.
Background
The laser radar technology is widely applied to the fields of intelligent transfer robots (Automated Guided Vehicle) AGVs, unmanned and the like, and the AGVs based on the laser radar technology are widely applied to the fields of cargo transportation, express transportation and the like by virtue of the characteristics of high stability, high positioning precision and small dependence on scenes. The laser radar is mainly applied to self-positioning of an AGV, and the currently mainstream positioning mode is a triangular positioning algorithm based on a reflecting plate. However, the algorithm has natural limitations, requires a stricter layout of the reflecting plate, and cannot ensure accurate positioning of the AGV in complex and frequent changing scenes, so that the positioning of the AGV is inaccurate.
Disclosure of Invention
This section is intended to outline some aspects of embodiments of the invention and to briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section as well as in the description summary and in the title of the application, to avoid obscuring the purpose of this section, the description summary and the title of the invention, which should not be used to limit the scope of the invention.
The present invention has been made in view of the above-described problems occurring in the prior art.
Therefore, the invention provides an improved AGV positioning method and device based on special shape recognition, which solve the problem that the existing laser positioning technology cannot ensure accurate positioning of the AGV in complex and variable frequent scenes.
In order to solve the technical problems, the invention provides the following technical scheme:
in a first aspect, an embodiment of the present invention provides a method for improving an AGV positioning based on special shape recognition, including:
acquiring laser data of an actual working environment according to the actual working environment of an AGV, and setting a target object in the actual working environment as a special object shape to be identified;
preprocessing the special object shape, extracting characteristic information of the shape, and carrying out coding sequencing again based on the characteristic information to form a unique variable of the special object shape;
preprocessing the laser data, extracting characteristic information of the laser data, calculating the matching accuracy through a characteristic matching model based on the unique variable, and selecting the highest accuracy obtained by calculation as a final positioning result.
As a preferred embodiment of the method for improving the positioning of an AGV based on special shape recognition according to the present invention, the following is adopted: preprocessing the special object shape, including:
performing error detection on the input special object shape;
and dividing the composition of the special object shape into a straight line L class and an arc C class based on the actual shape of the target object, and respectively extracting the characteristic information of the class.
As a preferred embodiment of the method for improving the positioning of an AGV based on special shape recognition according to the present invention, the following is adopted: extracting feature information of the shape, including:
the straight line L-shaped characteristic information F L Expressed as:
A*x+B*y+C＝0
wherein A is a first coefficient, B is a second coefficient, A and B are not 0 at the same time, x is a first variable, and y is a second variable;
the arc C type characteristic information F C Expressed as:
(x-a) 2 +(y-b) 2 ＝r 2
wherein, (a, b) is the center of a circle, r is the radius of the circle, x is a first variable, and y is a second variable.
As a preferred embodiment of the method for improving the positioning of an AGV based on special shape recognition according to the present invention, the following is adopted: the characteristic information is subjected to coding sequencing again to form a unique variable of the shape of the special object, and the method comprises the following steps:
sorting according to the shape characteristics of the actual object to obtain a unique variable, wherein the unique variable is expressed as:
T＝{F L1 ,F C2 ,F L2 ,F C1 }
wherein F is L1 For the first straight line characteristic information, F L2 For the second straight line characteristic information, F C1 F is the first arc characteristic information C2 And the second arc characteristic information.
As a preferred embodiment of the method for improving the positioning of an AGV based on special shape recognition according to the present invention, the following is adopted: removing noise points in the laser data;
the removing of the noise data is based on the original data of the laser radar, and the denoising is completed by using a noise removing processing function.
As a preferred embodiment of the method for improving the positioning of an AGV based on special shape recognition according to the present invention, the following is adopted: extracting straight line and circular arc characteristics in laser data, comprising:
extracting data describing a straight line in a laser point cloud by utilizing a findLine function based on the processed laser data;
and extracting data describing the circular arc in the laser point cloud by utilizing the findCURVE function.
As a preferred embodiment of the method for improving the positioning of an AGV based on special shape recognition according to the present invention, the following is adopted: calculating accuracy through the feature matching model, including:
calculating matching accuracy based on an actual matching Model through the unique variable and the linear characteristic information and the circular arc characteristic information;
based on the matching sequence mode of the laser data and the unique variable, sequencing the accuracy according to the arrangement and combination result;
when the combination accuracy is highest, the combination is selected as a final matching result, and the final high-precision positioning result is obtained by calculating the final matching positioning precision.
In a second aspect, embodiments of the present invention provide an improved AGV positioning device based on special shape recognition, comprising,
the data acquisition setting module is used for acquiring laser data of an actual environment according to the actual working environment of the AGV, and setting a target environment in the actual working environment as a special object shape to be identified;
the shape analysis module is used for preprocessing the shape of the special object, extracting the characteristic information of the shape, and carrying out coding sequencing again based on the characteristic information to form a unique variable of the shape of the special object;
the shape recognition module is used for preprocessing the laser data, extracting the characteristic information of the laser data, calculating the matching accuracy through a characteristic matching model based on the unique variable, and selecting the highest accuracy obtained by calculation as a final positioning result.
In a third aspect, embodiments of the present invention provide a computing device comprising:
a memory and a processor;
the memory is configured to store computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to implement an improved AGV positioning method based on special shape recognition according to any of the embodiments of the present invention.
In a fourth aspect, embodiments of the present invention provide a computer readable storage medium storing computer executable instructions that when executed by a processor implement the improved AGV positioning method based on special shape recognition.
Compared with the prior art, the invention has the beneficial effects that: according to the invention, the matching accuracy is calculated, so that the intelligent transfer robot AGV can realize precision positioning by identifying the object with a special shape under the complex and frequent change scene, any hardware and site deployment work are not required to be added, the cost is low, and the positioning precision is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. Wherein:
FIG. 1 is a general flow chart of a method and apparatus for improving AGV positioning based on special shape recognition in accordance with one embodiment of the present invention;
FIG. 2 is a flow chart of a shape analysis module for an improved AGV positioning method and apparatus based on special shape recognition in accordance with one embodiment of the present invention;
FIG. 3 is a flow chart of a shape recognition module for improving AGV positioning method and apparatus based on special shape recognition in accordance with one embodiment of the present invention;
FIG. 4 is a diagram of an exemplary special shape for an improved AGV positioning method and apparatus based on special shape recognition in accordance with one embodiment of the present invention;
FIG. 5 is a data diagram of an improved AGV positioning method and apparatus for matching accuracy based on special shape recognition in accordance with one embodiment of the present invention;
FIG. 6 is a graph showing a comparison of the positioning accuracy of an improved AGV positioning method and apparatus based on special shape recognition according to one embodiment of the present invention.
Detailed Description
So that the manner in which the above recited objects, features and advantages of the present invention can be understood in detail, a more particular description of the invention, briefly summarized above, may be had by reference to the embodiments, some of which are illustrated in the appended drawings. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present invention is not limited to the specific embodiments disclosed below.
Further, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic can be included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
While the embodiments of the present invention have been illustrated and described in detail in the drawings, the cross-sectional view of the device structure is not to scale in the general sense for ease of illustration, and the drawings are merely exemplary and should not be construed as limiting the scope of the invention. In addition, the three-dimensional dimensions of length, width and depth should be included in actual fabrication.
Also in the description of the present invention, it should be noted that the orientation or positional relationship indicated by the terms "upper, lower, inner and outer", etc. are based on the orientation or positional relationship shown in the drawings, are merely for convenience of describing the present invention and simplifying the description, and do not indicate or imply that the apparatus or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first, second, or third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
The terms "mounted, connected, and coupled" should be construed broadly in this disclosure unless otherwise specifically indicated and defined, such as: can be fixed connection, detachable connection or integral connection; it may also be a mechanical connection, an electrical connection, or a direct connection, or may be indirectly connected through an intermediate medium, or may be a communication between two elements. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.
Example 1
1-4, an embodiment of the present invention provides an improved AGV positioning method based on special shape recognition, comprising:
s1, acquiring laser data of an actual environment according to the actual working environment of an AGV, and setting a target object in the actual working environment as a special object shape to be identified;
s2, preprocessing the shape of the special object, extracting characteristic information of the shape, and carrying out coding sequencing again based on the characteristic information to form a unique variable of the shape of the special object;
still further, pre-processing a particular object shape, including:
performing error detection on the input special object shape;
the composition of the shape of the special object is divided into a straight line L class and an arc C class based on the actual shape of the target object, and the characteristic information of the classes is respectively extracted.
It should be noted that error detection is to overlap and smooth the shape of a specific object to be identified and detect other objects that do not meet the identification criteria.
Further, extracting feature information of the shape includes:
straight line L type characteristic information F L Expressed as:
A*x+B*y+C＝0
wherein A is a first coefficient, B is a second coefficient, A and B are not 0 at the same time, x is a first variable, and y is a second variable;
arc C type characteristic information F C Expressed as:
(x-a) 2 +(y-b) 2 ＝r 2
wherein, (a, b) is the center of a circle, r is the radius of the circle, x is a first variable, and y is a second variable.
Specifically, the feature information is reordered to form a unique variable of the shape of the special object, including:
sorting according to the shape characteristics of the actual object to obtain a unique variable, wherein the unique variable is expressed as:
T＝{F L1 ,F C2 ,F L2 ,F C1 }
wherein F is L1 For the first straight line characteristic information, F L2 For the second straight line characteristic information, F C1 F is the first arc characteristic information C2 And the second arc characteristic information.
S3, preprocessing laser data, extracting characteristic information of the laser data, calculating the matching accuracy through a characteristic matching model based on a unique variable, and selecting the highest accuracy obtained by calculation as a final positioning result;
still further, preprocessing the laser data includes: removing noise points in the laser data;
the removing of the noise data is based on the original data of the laser radar, and the denoising is completed by using a noise removing processing function.
Further, extracting straight line and arc features in the laser data includes:
extracting data describing a straight line in the laser point cloud by utilizing a findLine function based on the processed laser data;
and extracting data describing the circular arc in the laser point cloud by utilizing the findCURVE function.
Further, calculating the accuracy through the feature matching model includes:
calculating the matching accuracy based on an actual matching Model through the unique variable and the linear characteristic information and the circular arc characteristic information;
based on a matching sequence mode of the laser data and the unique variable, sequencing the accuracy according to the arrangement and combination result;
when the combination accuracy is highest, selecting the combination as a final matching result, and calculating the positioning accuracy of the final matching to obtain a final high-accuracy positioning result.
The foregoing is an illustrative version of the present embodiment for improving the AGV positioning method based on special shape recognition. It should be noted that, the technical solution of the improved AGV positioning device based on the special shape recognition and the technical solution of the improved AGV positioning method based on the special shape recognition described above belong to the same concept, and details of the technical solution of the improved AGV positioning device based on the special shape recognition in this embodiment, which are not described in detail, can be referred to the description of the technical solution of the improved AGV positioning method based on the special shape recognition described above.
The AGV positioning device is improved based on special shape recognition in the embodiment, and comprises:
the data acquisition setting module is used for acquiring laser data of an actual environment according to the actual working environment of the AGV, and setting a target environment in the actual working environment as a special object shape to be identified;
the shape analysis module is used for preprocessing the shape of the special object, extracting the characteristic information of the shape, and carrying out coding sequencing again based on the characteristic information to form a unique variable of the shape of the special object;
the shape recognition module is used for preprocessing the laser data and extracting the characteristic information of the laser data, calculating the matching accuracy through the characteristic matching model based on the unique variable, and selecting the highest accuracy obtained by calculation as a final positioning result.
In an alternative embodiment, the shape analysis module extracts the characteristic information of the shape of the selected special object, and uploads the characteristic information to the shape recognition module, the shape recognition module receives the information and combines the laser point cloud data, calculates the accuracy of a plurality of groups of matching models, and selects one with the highest numerical value as a final high-precision positioning result.
The embodiment also provides a computing device adapted to improve the AGV positioning method based on special shape recognition, including:
a memory and a processor; the memory is used for storing computer executable instructions, and the processor is used for executing the computer executable instructions to realize the AGV positioning method based on special shape recognition improvement as proposed by the embodiment.
The computer device may be a terminal comprising a processor, a memory, a communication interface, a display screen and input means connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
The present embodiment also provides a storage medium having a computer program stored thereon, which when executed by a processor, implements an improved AGV positioning method based on special shape recognition as set forth in the above embodiments.
The storage medium according to the present embodiment belongs to the same inventive concept as the data storage method according to the above embodiment, and technical details not described in detail in the present embodiment can be seen in the above embodiment, and the present embodiment has the same advantageous effects as the above embodiment.
Example 2
Referring to fig. 1 to 6, for one embodiment of the present invention, scientific verification was performed through a comparative experiment.
From the actual working environment of the AGV, the shape of an object is selected as a special shape, and the shape analysis module extracts the characteristic information of the selected special shape, as shown in FIG. 4, and the selected shape is formed by the characteristic information F L ,F C Composition, respectively F L1 ，F L2 ，F C1 ，F C2 According to the order of the shape characteristics, T= { F L1 ,F C2 ,F L2 ,F C1 }。
The shape recognition module firstly preprocesses the laser data, removes noise points in the laser radar data,
LaserData＝remove_outliers(raw_data),
wherein raw_data is the original data of the laser radar, including noise data, remove_outliers is the noise removal processing function, and LaserData is the laser data after processing.
Then, searching straight line and circular arc characteristics in the laser data:
Data_line＝findLine(LaserData)，
where data_line represents Data describing a straight line in the laser point cloud.
Data_curve＝findCurve(LaserData)，
Where data_cut represents the Data describing an arc in the laser point cloud.
Building a matching model, and calculating the accuracy:
precision_rate＝Model(T,Data_line,Data_curve,loc_accuracy)，
wherein T is the variable capable of uniquely describing the actual shape, data_line is the straight line feature Data, data_curve is the circular arc feature Data, loc_accuracy represents the calculated positioning accuracy, and Model is the actual matching Model.
The laser data and the shape variable T are brought into a model, and the matching accuracy is calculated; as shown in fig. 5, multiple sets of data are calculated in the actual scene, a set with a better result is selected as a final result, the accuracy is ranked, the highest combination is selected as the final result, and the ranking result is as follows:
precision_rate1＝Model(T,Data_line1,Data_curve1,loc_accuracy1),
precision_rate2＝Model(T,Data_line2,Data_curve2,loc_accuracy2),
precision_rate3＝Model(T,Data_line3,Data_curve3,loc_accuracy3),
...
p_rate_final＝sort(precision_rate1,precision_rate2,precision_rate3,...)
the p_rate_final accuracy is highest, and the corresponding positioning precision is used as a final high-precision positioning result.
As can be seen from the combination of FIG. 6, compared with the conventional method, the AGV of the invention can improve the positioning accuracy by identifying the object with a special shape in the complex and frequent change scene, and the positioning accuracy is far higher than that of the conventional method. Preprocessing, extracting features and recoding the shape of an object in the environment through a shape analysis module, establishing a matching model by a shape recognition module, bringing a recoding result and laser data into the matching model, and calculating the matching accuracy; the method has the advantages that multiple groups of data are brought into the matching model to obtain multiple accuracy rates, the multiple groups of data are ordered, and the group with high accuracy is selected as a final result.
It should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention may be modified or substituted without departing from the spirit and scope of the technical solution of the present invention, which is intended to be covered in the scope of the claims of the present invention.

Claims (10)

1. An improved AGV positioning method based on special shape recognition, comprising:
acquiring laser data of an actual working environment according to the actual working environment of an AGV, and setting a target object in the actual working environment as a special object shape to be identified;
preprocessing the special object shape, extracting characteristic information of the shape, and carrying out coding sequencing again based on the characteristic information to form a unique variable of the special object shape;
preprocessing the laser data, extracting characteristic information of the laser data, calculating the matching accuracy through a characteristic matching model based on the unique variable, and selecting the highest accuracy obtained by calculation as a final positioning result.
2. The method of improving AGV positioning based on special shape recognition according to claim 1 wherein preprocessing the special object shape comprises:
performing error detection on the input special object shape;
and dividing the composition of the special object shape into a straight line L class and an arc C class based on the actual shape of the target object, and respectively extracting the characteristic information of the class.
3. The method of improving AGV positioning based on special shape recognition as set forth in claim 2, wherein extracting characteristic information of the shape comprises:
the straight line L-shaped characteristic information F L Expressed as:
A*x+B*y+C＝0
wherein A is a first coefficient, B is a second coefficient, A and B are not 0 at the same time, x is a first variable, and y is a second variable;
the arc C type characteristic information F C Expressed as:
(x-a) 2 +(y-b) 2 ＝r 2
wherein, (a, b) is the center of a circle, r is the radius of the circle, x is a first variable, and y is a second variable.
4. The improved AGV positioning method based on special shape recognition as set forth in claim 3, wherein said feature information reorders the code ordering to form a unique variable for the special object shape comprising:
sorting according to the shape characteristics of the actual object to obtain a unique variable, wherein the unique variable is expressed as:
T＝{F L1 ,F C2 ,F L2 ,F C1 }
wherein F is L1 For the first straight line characteristic information, F L2 For the second straight line characteristic information, F C1 F is the first arc characteristic information C2 And the second arc characteristic information.
5. The method of improving AGV positioning based on special shape recognition according to claim 4 wherein preprocessing the laser data comprises: removing noise points in the laser data;
the removing of the noise data is based on the original data of the laser radar, and the denoising is completed by using a noise removing processing function.
6. The method of improving AGV positioning based on special shape recognition according to claim 5 wherein extracting straight line and arc features from laser data comprises:
extracting data describing a straight line in a laser point cloud by utilizing a findLine function based on the processed laser data;
and extracting data describing the circular arc in the laser point cloud by utilizing the findCURVE function.
7. The method of improving AGV positioning based on special shape recognition according to claim 6 wherein calculating accuracy by a feature matching model comprises:
calculating matching accuracy based on an actual matching Model through the unique variable and the linear characteristic information and the circular arc characteristic information;
based on the matching sequence mode of the laser data and the unique variable, sequencing the accuracy according to the arrangement and combination result;
when the combination accuracy is highest, the combination is selected as a final matching result, and the final high-precision positioning result is obtained by calculating the final matching positioning precision.
8. An improved AGV positioning device based on special shape recognition, comprising,
the data acquisition setting module is used for acquiring laser data of an actual environment according to the actual working environment of the AGV, and setting a target environment in the actual working environment as a special object shape to be identified;
the shape analysis module is used for preprocessing the shape of the special object, extracting the characteristic information of the shape, and carrying out coding sequencing again based on the characteristic information to form a unique variable of the shape of the special object;
the shape recognition module is used for preprocessing the laser data, extracting the characteristic information of the laser data, calculating the matching accuracy through a characteristic matching model based on the unique variable, and selecting the highest accuracy obtained by calculation as a final positioning result.
9. A computing device, comprising:
a memory and a processor;
the memory is configured to store computer executable instructions that when executed by the processor perform the steps of the improved AGV positioning method based on special shape recognition as defined in any one of claims 1 to 7.
10. A computer readable storage medium storing computer executable instructions which when executed by a processor perform the steps of the improved AGV positioning method based on special shape recognition of any one of claims 1 to 7.
CN202310228675.0A 2023-03-10 2023-03-10 AGV positioning method and device based on special shape recognition Pending CN116449379A (en)

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