CN113514844A - Mobile robot positioning method and system based on two-dimensional laser reflection intensity - Google Patents
Mobile robot positioning method and system based on two-dimensional laser reflection intensity Download PDFInfo
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- CN113514844A CN113514844A CN202110446961.5A CN202110446961A CN113514844A CN 113514844 A CN113514844 A CN 113514844A CN 202110446961 A CN202110446961 A CN 202110446961A CN 113514844 A CN113514844 A CN 113514844A
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- 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
- G01S17/46—Indirect determination of position data
Abstract
The invention relates to a mobile robot positioning method and system based on two-dimensional laser reflection intensity. The method comprises the following steps: acquiring distance data and laser reflection intensity of the mobile robot and a road sign in the environment where the mobile robot is located; determining the center position of the road sign by adopting a self-adaptive clustering method according to the distance data and the laser reflection intensity; determining a successfully matched road sign according to the center position of the road sign and the position of a preset road sign; the preset position of the road sign is the position of the road sign arranged in the mobile robot; judging whether the number of the successfully matched signposts is greater than or equal to 3; if the pose of the mobile robot is greater than or equal to 3, determining the pose of the mobile robot by adopting a trilateral positioning algorithm and a least square method, and positioning the mobile robot; and if the distance is less than 3, returning to the step of acquiring the distance data between the mobile robot and the road sign in the environment and the laser reflection intensity. The invention improves the positioning accuracy of the mobile robot.
Description
Technical Field
The invention relates to the field of positioning of environments where mobile robots are located, in particular to a mobile robot positioning method and system based on two-dimensional laser reflection intensity.
Background
With the wide application of mobile robot technology in various industries, in an indoor environment, a trilateral positioning method based on two-dimensional laser reflection intensity is also deeply developed, however, the accuracy of data acquisition by a sensor is reduced in an indoor complex environment, and the density of data acquired by a laser sensor is influenced by a measured distance, so that data processing needs to be performed according to an environment adjustment algorithm where the robot is located, and then the trilateral positioning algorithm is used. Namely, the algorithm is complex and the positioning is not accurate enough.
Therefore, how to accurately position the pose of the mobile robot is a technical problem to be solved urgently by technical personnel in the field.
Disclosure of Invention
The invention aims to provide a mobile robot positioning method and system based on two-dimensional laser reflection intensity, and the accuracy of mobile robot positioning is improved.
In order to achieve the purpose, the invention provides the following scheme:
a mobile robot positioning method based on two-dimensional laser reflection intensity comprises the following steps:
acquiring distance data and laser reflection intensity of the mobile robot and a road sign in the environment where the mobile robot is located; the road sign is a reflective column;
determining the center position of the road sign by adopting a self-adaptive clustering method according to the distance data and the laser reflection intensity;
determining a successfully matched road sign according to the center position of the road sign and the position of a preset road sign; the position of the preset road sign is the position of the road sign arranged in the mobile robot;
judging whether the number of the successfully matched signposts is greater than or equal to 3;
if the pose of the mobile robot is greater than or equal to 3, determining the pose of the mobile robot by adopting a trilateral positioning algorithm and a least square method, and positioning the mobile robot;
and if the distance is less than 3, returning to the step of acquiring the distance data between the mobile robot and the road sign in the environment and the laser reflection intensity.
Optionally, the determining the center position of the landmark by using a self-adaptive clustering method according to the distance data and the laser reflection intensity specifically includes:
filtering the distance data by adopting a median filtering method;
converting the filtered distance data into Cartesian coordinate values;
clustering the converted distance data and the laser reflection intensity by adopting a self-adaptive clustering method to determine a road sign data set;
and determining the center position of the landmark according to the landmark data set.
Optionally, if the pose of the mobile robot is greater than or equal to 3, determining the pose of the mobile robot by using a trilateral localization algorithm and a least square method, so as to realize the localization of the mobile robot, specifically including:
using least square method to form formula
Solving to determine the coordinates of the mobile robot;
according to the formula
Determining a global azimuth angle of the mobile robot;
determining the pose of the mobile robot according to the coordinates of the mobile robot and the global azimuth angle of the mobile robot;
wherein (G)x,Gy) In order to move the coordinates of the robot,
the coordinates of the landmark that was successfully matched,
respectively the distance G from the center of the successfully matched road sign to the mobile robotθFor the global azimuth of the mobile robot,
the local azimuth angle formed by the ith preset road sign is n, and the number of the road signs which are successfully matched is n.
Optionally, if the pose of the mobile robot is greater than or equal to 3, determining the pose of the mobile robot by using a trilateral localization algorithm and a least square method to realize the localization of the mobile robot, and then further including:
and updating the mobile robot according to the pose of the mobile robot, and returning to the step of acquiring the distance data between the mobile robot and the road sign in the environment and the laser reflection intensity for continuous positioning.
A mobile robot positioning system based on two-dimensional laser reflection intensity, comprising:
the mobile data acquisition module is used for acquiring distance data between the mobile robot and a road sign in the environment and the laser reflection intensity; the road sign is a reflective column;
the center position determining module of the road sign is used for determining the center position of the road sign by adopting a self-adaptive clustering method according to the distance data and the laser reflection intensity;
the successfully matched landmark determining module is used for determining a successfully matched landmark according to the center position of the landmark and the position of a preset landmark; the position of the preset road sign is the position of the road sign arranged in the mobile robot;
the judging module is used for judging whether the number of the successfully matched signposts is more than or equal to 3;
the pose determining module of the mobile robot is used for determining the pose of the mobile robot by adopting a trilateral positioning algorithm and a least square method if the pose is greater than or equal to 3, so that the mobile robot is positioned;
and the road sign data updating module is used for returning to the step of acquiring the distance data between the mobile robot and the road sign in the environment and the laser reflection intensity if the distance data is less than 3.
Optionally, the module for determining the center position of the landmark specifically includes:
the filtering unit is used for filtering the distance data by adopting a median filtering method;
the data conversion unit is used for converting the filtered distance data into Cartesian coordinate values;
a road sign data set determining unit, configured to cluster the converted distance data and the laser reflection intensity by using a self-adaptive clustering method, and determine a road sign data set;
and the landmark center position determining unit is used for determining the landmark center position according to the landmark data set.
Optionally, the pose determination module of the mobile robot specifically includes:
coordinate determination unit of mobile robot for fitting formula by least square method
Solving to determine the coordinates of the mobile robot;
a global azimuth angle determining unit of the mobile robot for determining the global azimuth angle according to a formula
Determining a global azimuth angle of the mobile robot;
the mobile robot position and orientation determining unit is used for determining the position and orientation of the mobile robot according to the coordinates of the mobile robot and the global azimuth angle of the mobile robot;
wherein (G)x,Gy) In order to move the coordinates of the robot,
the coordinates of the landmark that was successfully matched,
respectively the distance G from the center of the successfully matched road sign to the mobile robotθFor the global azimuth of the mobile robot,
the local azimuth angle formed by the ith preset road sign is n, and the number of the road signs which are successfully matched is n.
Optionally, the method further comprises:
and the continuous positioning module is used for updating the mobile robot according to the pose of the mobile robot and returning to the step of acquiring the distance data between the mobile robot and the road sign in the environment and the laser reflection intensity for continuous positioning.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides a mobile robot positioning method and system based on two-dimensional laser reflection intensity, which are used for acquiring distance data between a mobile robot and a road sign in the environment and the laser reflection intensity, performing clustering identification on a light reflection column by combining a self-adaptive clustering method to determine the central position of the road sign, and solving the pose of the mobile robot in the global environment according to a trilateral positioning algorithm. The guideposts in the invention can be flexibly arranged in an unstructured environment, and the calculation amount of the global pose is small, so that the positioning accuracy of the mobile robot can be ensured, and the high reliability can be ensured.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
Fig. 1 is a schematic flow chart of a mobile robot positioning method based on two-dimensional laser reflection intensity according to the present invention;
FIG. 2 is a coordinate system depiction of a mobile robot;
FIG. 3 is an adaptive threshold δ geometry;
FIG. 4 is a schematic diagram of center position extraction of a landmark;
FIG. 5 is a schematic diagram of a landmark under a coordinate system of the mobile robot;
FIG. 6 is a schematic diagram of a trilateration algorithm;
fig. 7 is a schematic structural diagram of a mobile robot positioning system based on two-dimensional laser reflection intensity provided by the present invention.
Detailed Description
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 only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a mobile robot positioning method and system based on two-dimensional laser reflection intensity, and the accuracy of mobile robot positioning is improved.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Fig. 1 is a schematic flow chart of a mobile robot positioning method based on two-dimensional laser reflection intensity provided by the present invention, and as shown in fig. 1, the mobile robot positioning method based on two-dimensional laser reflection intensity provided by the present invention includes:
s101, obtaining distance data between the mobile robot and a road sign in the environment and laser reflection intensity; the road sign is a reflective column. A coordinate system description of the mobile robot is shown in fig. 2.
In a specific embodiment, the distance information D is acquired by an onboard laser sensor on the mobile roboti(i ═ 1, …, n) and energy value (laser reflection intensity) Ei(i＝1，…，n)。
And S102, determining the center position of the road sign by adopting a self-adaptive clustering method according to the distance data and the laser reflection intensity.
S102 specifically comprises the following steps:
filtering the distance data by adopting a median filtering method to obtain filtered distance data
Converting the filtered distance data into Cartesian coordinate values, i.e. using a formula
Converting to obtain converted distance data
And clustering the converted distance data and the laser reflection intensity by adopting a self-adaptive clustering method to determine a road sign data set.
The adaptive threshold δ geometry is shown in fig. 3, and an adaptive clustering method is used, when the distance between adjacent points is smaller than the adaptive threshold δ, the adjacent points are considered to belong to the same class of objects, and the formula is as follows:
δ＝||Rh-Pi-1||+3σr；
identifying a reflective column data set, and setting an energy threshold lambdaδAnd the diameter interval of the reflecting column [ D ]min，Dmax]As a limiting condition, the formula is:
wherein D ismin，DmaxAnd λδDetermined from the actual situation, λmaxRepresenting the maximum surface energy value in a certain retroreflective sheeting data set, and d represents the observed retroreflective sheeting diameter.
A series of reflective column data sets can be obtained according to the previous step
The center position of the landmark is determined from the landmark data set and is shown in fig. 4.
Obtaining the center of the reflecting column according to a formula
Comprises the following steps:
s103, determining a road sign successfully matched according to the center position of the road sign and the position of a preset road sign; the position of the preset landmark is the position of the landmark set in the mobile robot, as shown in fig. 5.
Combining the reflective columns in a group of 3, and correspondingly matching a landmark list under a global (in the environment) coordinate system with a landmark list scanned by a sensor at the current moment under a robot coordinate system.
Can convert any triangle information
The summary is as follows:
triangle information in a current environment
With triangle information in a global environment
And if the minimum value of all the difference values meets the following conditions, the matching is considered to be successful:
and S104, judging whether the number of the successfully matched signposts is more than or equal to 3.
And S105, if the pose of the mobile robot is greater than or equal to 3, determining the pose of the mobile robot by adopting a trilateral positioning algorithm and a least square method, and positioning the mobile robot.
And if the distance is less than 3, returning to the step of acquiring the distance data between the mobile robot and the road sign in the environment and the laser reflection intensity.
If the pose of the mobile robot is greater than or equal to 3, determining the pose of the mobile robot by adopting a trilateral positioning algorithm and a least square method to realize the positioning of the mobile robot, and specifically comprising the following steps:
using least square method to form formula
And solving to determine the coordinates of the mobile robot. A schematic diagram of the trilateration algorithm is shown in fig. 6.
The least square method is (Gx，Gy)T＝(ATA)-1ATb。
Wherein:
according to the formula
A global azimuth of the mobile robot is determined.
Wherein, the local azimuth angle of the ith preset road sign of the mobile robot
Comprises the following steps:
determining the pose of the mobile robot according to the coordinates of the mobile robot and the global azimuth angle of the mobile robotGR＝[Gx，Gy，Gθ]。
Wherein (G)x，Gy) In order to move the coordinates of the robot,
the coordinates of the landmark that was successfully matched,
respectively the distance G from the center of the successfully matched road sign to the mobile robotθFor the global azimuth of the mobile robot,
the local azimuth angle formed by the ith preset road sign is n, and the number of the road signs which are successfully matched is n.
If the pose of the mobile robot is greater than or equal to 3, determining the pose of the mobile robot by adopting a trilateral positioning algorithm and a least square method to realize the positioning of the mobile robot, and then further comprising the following steps:
and updating the mobile robot according to the pose of the mobile robot, and returning to the step of acquiring the distance data between the mobile robot and the road sign in the environment and the laser reflection intensity for continuous positioning.
Namely, the laser sensor observes the road signs in the environment in real time, thereby realizing the continuous positioning of the mobile construction robot.
Fig. 7 is a schematic structural diagram of a mobile robot positioning system based on two-dimensional laser reflection intensity, as shown in fig. 7, the mobile robot positioning system based on two-dimensional laser reflection intensity provided by the present invention includes:
a mobile data acquisition module 701, configured to acquire distance data between the mobile robot and a road sign in an environment where the mobile robot is located, and laser reflection intensity; the road sign is a reflective column.
And a landmark center position determining module 702, configured to determine the landmark center position by using a self-adaptive clustering method according to the distance data and the laser reflection intensity.
A successfully matched landmark determining module 703, configured to determine a successfully matched landmark according to the center position of the landmark and a position of a preset landmark; the preset position of the road sign is the position of the road sign arranged in the mobile robot.
And a judging module 704, configured to judge whether the number of the successfully matched signposts is greater than or equal to 3.
And a pose determining module 705 of the mobile robot, configured to determine the pose of the mobile robot by using a trilateral localization algorithm and a least square method if the pose is greater than or equal to 3, so as to implement localization of the mobile robot.
And the landmark data updating module 706 is configured to return to the step of acquiring the distance data between the mobile robot and the landmark in the environment and the laser reflection intensity if the distance data is less than 3.
The landmark center position determining module 702 specifically includes:
and the filtering unit is used for filtering the distance data by adopting a median filtering method.
And the data conversion unit is used for converting the filtered distance data into Cartesian coordinate values.
And the road sign data set determining unit is used for clustering the converted distance data and the laser reflection intensity by adopting a self-adaptive clustering method to determine a road sign data set.
And the landmark center position determining unit is used for determining the landmark center position according to the landmark data set.
The pose determination module 705 of the mobile robot specifically includes:
coordinate determination unit of mobile robot for fitting formula by least square method
And solving to determine the coordinates of the mobile robot.
A global azimuth angle determining unit of the mobile robot for determining the global azimuth angle according to a formula
A global azimuth of the mobile robot is determined.
And the pose determining unit of the mobile robot is used for determining the pose of the mobile robot according to the coordinates of the mobile robot and the global azimuth angle of the mobile robot.
Wherein (G)x,Gy) In order to move the coordinates of the robot,
the coordinates of the landmark that was successfully matched,
respectively the distance G from the center of the successfully matched road sign to the mobile robotθFor the global azimuth of the mobile robot,
the local azimuth angle formed by the ith preset road sign is n, and the number of the road signs which are successfully matched is n.
The invention provides a mobile robot positioning system based on two-dimensional laser reflection intensity, which further comprises:
and the continuous positioning module is used for updating the mobile robot according to the pose of the mobile robot and returning to the step of acquiring the distance data between the mobile robot and the road sign in the environment and the laser reflection intensity for continuous positioning.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (8)
1. A mobile robot positioning method based on two-dimensional laser reflection intensity is characterized by comprising the following steps:
acquiring distance data and laser reflection intensity of the mobile robot and a road sign in the environment where the mobile robot is located; the road sign is a reflective column;
determining the center position of the road sign by adopting a self-adaptive clustering method according to the distance data and the laser reflection intensity;
determining a successfully matched road sign according to the center position of the road sign and the position of a preset road sign; the position of the preset road sign is the position of the road sign arranged in the mobile robot;
judging whether the number of the successfully matched signposts is greater than or equal to 3;
if the pose of the mobile robot is greater than or equal to 3, determining the pose of the mobile robot by adopting a trilateral positioning algorithm and a least square method, and positioning the mobile robot;
and if the distance is less than 3, returning to the step of acquiring the distance data between the mobile robot and the road sign in the environment and the laser reflection intensity.
2. The method according to claim 1, wherein the determining the center position of the landmark by using an adaptive clustering method according to the distance data and the laser reflection intensity specifically comprises:
filtering the distance data by adopting a median filtering method;
converting the filtered distance data into Cartesian coordinate values;
clustering the converted distance data and the laser reflection intensity by adopting a self-adaptive clustering method to determine a road sign data set;
and determining the center position of the landmark according to the landmark data set.
3. The method according to claim 1, wherein if the two-dimensional laser reflection intensity is greater than or equal to 3, determining the pose of the mobile robot by using a trilateral positioning algorithm and a least square method to realize the positioning of the mobile robot, specifically comprising:
using least square method to form formula
Solving to determine the coordinates of the mobile robot;
according to the formula
Determining a global azimuth angle of the mobile robot;
determining the pose of the mobile robot according to the coordinates of the mobile robot and the global azimuth angle of the mobile robot;
wherein (G)x,Gy) In order to move the coordinates of the robot,
the coordinates of the landmark that was successfully matched,
respectively the distance G from the center of the successfully matched road sign to the mobile robotθFor the global azimuth of the mobile robot,
is equal to the ith preset wayAnd the local azimuth angle formed by the target, wherein n is the number of the successfully matched signposts.
4. The method for positioning a mobile robot based on two-dimensional laser reflection intensity according to claim 1, wherein if the laser reflection intensity is greater than or equal to 3, determining the pose of the mobile robot by using a trilateral positioning algorithm and a least square method to realize positioning of the mobile robot, and then further comprising:
and updating the mobile robot according to the pose of the mobile robot, and returning to the step of acquiring the distance data between the mobile robot and the road sign in the environment and the laser reflection intensity for continuous positioning.
5. A mobile robot positioning system based on two-dimensional laser reflection intensity, comprising:
the mobile data acquisition module is used for acquiring distance data between the mobile robot and a road sign in the environment and the laser reflection intensity; the road sign is a reflective column;
the center position determining module of the road sign is used for determining the center position of the road sign by adopting a self-adaptive clustering method according to the distance data and the laser reflection intensity;
the successfully matched landmark determining module is used for determining a successfully matched landmark according to the center position of the landmark and the position of a preset landmark; the position of the preset road sign is the position of the road sign arranged in the mobile robot;
the judging module is used for judging whether the number of the successfully matched signposts is more than or equal to 3;
the pose determining module of the mobile robot is used for determining the pose of the mobile robot by adopting a trilateral positioning algorithm and a least square method if the pose is greater than or equal to 3, so that the mobile robot is positioned;
and the road sign data updating module is used for returning to the step of acquiring the distance data between the mobile robot and the road sign in the environment and the laser reflection intensity if the distance data is less than 3.
6. The two-dimensional laser reflection intensity-based mobile robot positioning system according to claim 5, wherein the landmark center position determining module specifically comprises:
the filtering unit is used for filtering the distance data by adopting a median filtering method;
the data conversion unit is used for converting the filtered distance data into Cartesian coordinate values;
a road sign data set determining unit, configured to cluster the converted distance data and the laser reflection intensity by using a self-adaptive clustering method, and determine a road sign data set;
and the landmark center position determining unit is used for determining the landmark center position according to the landmark data set.
7. The two-dimensional laser reflection intensity-based mobile robot positioning system according to claim 5, wherein the pose determination module of the mobile robot specifically comprises:
coordinate determination unit of mobile robot for fitting formula by least square method
Solving to determine the coordinates of the mobile robot;
a global azimuth angle determining unit of the mobile robot for determining the global azimuth angle according to a formula
Determining a global azimuth angle of the mobile robot;
the mobile robot position and orientation determining unit is used for determining the position and orientation of the mobile robot according to the coordinates of the mobile robot and the global azimuth angle of the mobile robot;
wherein (G)x,Gy) In order to move the coordinates of the robot,
the coordinates of the landmark that was successfully matched,
respectively the distance G from the center of the successfully matched road sign to the mobile robotθFor the global azimuth of the mobile robot,
the local azimuth angle formed by the ith preset road sign is n, and the number of the road signs which are successfully matched is n.
8. The two-dimensional laser reflection intensity-based mobile robot positioning system according to claim 5, further comprising:
and the continuous positioning module is used for updating the mobile robot according to the pose of the mobile robot and returning to the step of acquiring the distance data between the mobile robot and the road sign in the environment and the laser reflection intensity for continuous positioning.
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Application publication date: 20211019 |