CN111694009A - Positioning system, method and device - Google Patents
Positioning system, method and device Download PDFInfo
- Publication number
- CN111694009A CN111694009A CN202010378957.5A CN202010378957A CN111694009A CN 111694009 A CN111694009 A CN 111694009A CN 202010378957 A CN202010378957 A CN 202010378957A CN 111694009 A CN111694009 A CN 111694009A
- Authority
- CN
- China
- Prior art keywords
- data
- robot
- laser radar
- scanner
- global position
- 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
- 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
Landscapes
- Physics & Mathematics (AREA)
- Electromagnetism (AREA)
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
- Optical Radar Systems And Details Thereof (AREA)
Abstract
The invention discloses a positioning method, and belongs to the field of positioning. Acquiring first data of each cell in a specific area through a scanner; the scanner determines the global position of the robot in the specific area according to the first data; acquiring second data of cells in the global position of the first laser radar through the first laser radar; acquiring third data of the cells in the global position of the second laser radar through the second laser radar; and matching the second data with the first data and matching the third data with the first data to determine the specific position of the robot in the global position. The method utilizes the 3D scanner to construct a global map, realizes global positioning of the robot in a large range around the transformer substation, gives the global position of the power inspection robot, and performs primary positioning on the robot; and the local accurate positioning of the robot is realized by using the double laser radars, the large-scale accurate positioning of the robot in a transformer substation can be realized, and the problem of positioning loss caused by blind areas is prevented.
Description
Technical Field
The present invention relates to the field of positioning, and more particularly, to a positioning system, method and apparatus.
Background
In order to meet the requirement of increasing power supply quality, the power inspection robot of the transformer substation is more and more widely applied to the transformer substation. The electric power inspection robot is mainly applied to an outdoor transformer substation, can run to a specified position to execute an instrument recording task under the unattended condition through the autonomous positioning and navigation functions, and can timely find abnormal phenomena such as defects, foreign matter suspension and the like of electric power equipment. When the power inspection robot executes an inspection task, the obstacle avoidance is very important, and the safety of the robot and the normal operation of the whole transformer substation are not only related.
Because the outdoor transformer substation, the environment that the robot patrolled and examined compares indoor comparatively complicacy, thereby has a blind area to produce the location and lose when having other robots of patrolling and examining to pass through around the robot.
Therefore, effective solutions to solve the above problems need to be proposed.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention discloses a positioning system, a method and a device, which solve the problem that the inspection robot is lost in positioning in the prior art.
In order to achieve the purpose, the invention adopts the following technical scheme:
the present invention provides a positioning system comprising: a robot, a scanner, a first lidar, and a second lidar located outdoors;
the scanner and the first laser radar are both arranged at the top of the robot;
acquiring first data of each cell in a specific area through the scanner;
acquiring second data of cells in the global position of the first laser radar through the first laser radar;
acquiring third data of a cell in the global position of the second laser radar through the second laser radar;
the scanner determines the global position of the robot in the specific area according to the first data;
and respectively matching the second data with the first data and the third data with the first data to determine the specific position of the robot in the global position.
The invention also provides a positioning method, which is applicable to the positioning system and comprises the following steps:
acquiring first data of each cell in a specific area through a scanner;
the scanner determines the global position of the robot in the specific area according to the first data;
acquiring second data of a cell in the global position of a first laser radar through the first laser radar;
acquiring third data of a cell in the global position of the second laser radar through the second laser radar;
and matching the second data with the first data and matching the third data with the first data to determine the specific position of the robot in the global position.
Preferably, determining a global position of the robot in the specific area according to the first data comprises:
and the scanner constructs a map of the specific area according to the first data and determines the global position of the robot in the area.
Preferably, matching the second data with the first data and matching the third data with the first data, respectively, to determine a specific position of the robot in the global position includes:
matching the second data with the first data to obtain a first optimal matching probability P (X) so as to obtain a first optimal matching pose P;
matching the third data with the first data to obtain a second optimal matching probability P '(X) so as to obtain a second optimal matching pose P';
determining a specific position of the robot in the global position through a relationship between the P and P'.
Preferably, determining the specific position of the robot in the global position by the relationship between P and P' comprises:
when P is larger than P', the probability that the first laser radar is matched with the scanner is larger than the probability that the second laser radar is matched with the scanner, so that the specific position of the robot in the global position is determined to be the position of the first laser radar in the specific area;
when P is smaller than P', the probability that the second laser radar is matched with the scanner is larger than the probability that the first laser radar is matched with the scanner, so that the specific position of the robot in the global position is determined to be the position of the second laser radar in the specific area.
The invention also provides a positioning device, which is suitable for the positioning method and comprises the following steps:
the first acquisition unit is used for acquiring first data of each cell in a specific area through a scanner;
a first determination unit, configured to determine, by the scanner, a global position of the robot in the specific area according to the first data;
the second acquisition unit is used for acquiring second data of the cells in the global position of the first laser radar through the first laser radar;
a third obtaining unit, configured to obtain, by the second lidar, third data of a cell in a global position where the second lidar is located;
and the second determining unit is used for matching the second data with the first data and matching the third data with the first data to determine the specific position of the robot in the global position.
Preferably, the first determining unit is specifically configured to construct a map of the specific area by the scanner according to the first data, and determine a global position of the robot in the area.
Preferably, the second determining unit is specifically configured to match the second data with the first data to obtain a first optimal matching probability P (X) to obtain a first best matching pose P;
matching the third data with the first data to obtain a second optimal matching probability P '(X) so as to obtain a second optimal matching pose P';
determining a specific position of the robot in the global position through a relationship between the P and P'.
Preferably, the second determining unit is further configured to determine that the specific position of the robot in the global position is the position of the first lidar in the specific area, when P is greater than P', the probability that the first lidar is matched with the scanner is greater than the probability that the second lidar is matched with the scanner;
when P is smaller than P', the probability that the second laser radar is matched with the scanner is larger than the probability that the first laser radar is matched with the scanner, so that the specific position of the robot in the global position is determined to be the position of the second laser radar in the specific area.
The invention has the beneficial effects that:
the invention provides a positioning method, which comprises the steps of acquiring first data of each cell in a specific area through a scanner; the scanner determines the global position of the robot in the specific area according to the first data; acquiring second data of cells in the global position of the first laser radar through the first laser radar; acquiring third data of the cells in the global position of the second laser radar through the second laser radar; and matching the second data with the first data and matching the third data with the first data to determine the specific position of the robot in the global position.
The method utilizes the 3D scanner to construct a global map, realizes global positioning of the robot in a large range around the transformer substation, gives the global position of the power inspection robot, and performs primary positioning on the robot; reuse two laser radar and realize the local accurate location of robot, the benefit can possess the advantage that 3D scanner positioning range is big and two laser radar positioning accuracy are high simultaneously, can realize the robot and in the accurate location on a large scale of transformer substation, prevent to produce the problem that the location is lost because of having the blind area.
Drawings
FIG. 1 is a schematic diagram of a positioning system according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of a positioning method according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a positioning device according to an embodiment of the present invention.
In the figure:
101. a first laser radar; 102. a second laser radar; 103. a scanner; 104. a robot.
Detailed Description
The technical scheme of the invention is further explained by the specific implementation mode in combination with the attached drawings.
Fig. 1 is a schematic structural diagram of a positioning system according to an embodiment of the present invention, as shown in fig. 1; fig. 2 is a schematic flow chart of a positioning method according to an embodiment of the present invention, as shown in fig. 2; fig. 3 is a schematic structural diagram of a positioning device according to an embodiment of the present invention, as shown in fig. 3. The target objects in fig. 1 refer to a transformer box, an obstacle, and the like in a transformer station environment, and feature information of these objects is extracted by laser scanning to construct a map. The invention provides a positioning system, comprising: a robot 104, a scanner 103, a first lidar 101, and a second lidar 102 located outdoors; the scanner 103 and the first laser radar 101 are both arranged on the top of the robot; acquiring first data of each cell in a specific area through a scanner 103; acquiring second data of a cell in the global position of the first laser radar 101 through the first laser radar 101; acquiring third data of a cell in the global position of the first laser radar 102 through the first laser radar 102; the scanner 103 determines the global position of the robot in the specific area according to the first data; the second data is matched with the first data and the third data is matched with the first data, respectively, to determine a specific position of the robot 104 in the global position. In specific implementation, the scanner 103 is connected with the top of the bracket through a conductive sliding block, and the bottom of the bracket is fixedly connected with the top of the robot 104; let the robot 104 advance forward, the 3D scanner 103 is installed at an upper position in the middle of the robot 104, the first lidar 101 is installed above the front of the robot 104, and the first lidar 102 is installed above the rear of the robot 104.
The invention also provides a positioning method, which is suitable for the positioning system and comprises the following steps:
s101: acquiring first data of each cell in a specific area through a scanner;
s102: the scanner determines the global position of the robot in the specific area according to the first data;
s103: acquiring second data of cells in the global position of the first laser radar through the first laser radar;
s104: acquiring third data of the cells in the global position of the second laser radar through the second laser radar;
s105: and matching the second data with the first data and matching the third data with the first data to determine the specific position of the robot in the global position.
The main function of the invention is to determine the global position of the robot by the scanning of the scanner; and respectively matching the point cloud information scanned by the first laser radar with the point cloud information scanned by the scanner and the point cloud information scanned by the second laser radar with the point cloud information scanned by the scanner, and selecting the position with the highest probability as the actual position of the robot, namely the specific position of the robot in the global position.
In S101, acquiring first data of each cell in a specific area through a scanner; and in S102, the scanner determines the global position of the robot in the specific area according to the first data; specifically, the 3D scanner obtains 3D point cloud data through 360-degree rotation scanning, the 3D scanner constructs a map of a current specific area according to the 3D point cloud data, the global positioning of the current specific area is achieved, and the global position of the power inspection robot is determined. Wherein each cell is divided in a specific area in advance; the specific area is the whole environment around the outdoor transformer substation, and specifically can be the environment within several meters around the outdoor transformer substation, such as 3 meters, 5 meters and the like; the scanner is a 3D scanner; the first data is 3-dimensional point cloud data; the robot adopts the electric power inspection robot. The 3D scanner can rotate for 360 degrees to scan, and more abundant 3-dimensional point cloud information can be obtained. The 3D scanner scans and acquires 3D point cloud data by 360 ° rotation, and in the implementation, the 3D point cloud data may be acquired by calculation of a scanning algorithm, and the scanning frequency may be determined according to the implementation, for example, the scanning frequency may be set to 20 frames/S.
In S103, second data of cells in the global position where the first laser radar is located are obtained through the first laser radar; specifically, the first laser radar constructs and acquires a map of cells in the global position where the first laser radar is located through scanning, and acquires second data of the cells in the global position where the first laser radar is located. Wherein the first laser radar is a 2D laser radar; the second data is 2-dimensional point cloud information; in a specific implementation, the scanning angle of the first laser radar is 120 degrees, and the scanning radius is R1。
In S104, acquiring third data of the cells in the global position where the second laser radar is located through the second laser radar; specifically, the second laser radar constructs and acquires a map of cells in the global position where the second laser radar is located through scanning, and acquires a third map of cells in the global position where the second laser radar is locatedData; in specific implementation, the scanning angle of the second laser radar is 360 degrees, and the scanning radius is R2. Wherein R is1Greater than R2. Likewise, wherein the second lidar is a 2D lidar; the third data is 2-dimensional point cloud information.
The method utilizes the 3D scanner to construct a global map, realizes global positioning of the robot in a large range around the transformer substation, gives the global position of the power inspection robot, and performs primary positioning on the robot; reuse two laser radar and realize the local accurate location of robot, the benefit can possess the advantage that 3D scanner positioning range is big and two laser radar positioning accuracy are high simultaneously, can realize the robot and in the accurate location on a large scale of transformer substation, prevent to produce the problem that the location is lost because of having the blind area. In addition, the laser radar has the excellent characteristics of being not influenced by conditions such as weather, illumination and the like, not depending on lines and colors for distinguishing, not being sensitive to shadow noise and the like. The scanning frequency is high during the measurement of the laser radar, the data volume is rich, and the returned distance value is convenient for quick processing. Therefore, the laser radar is adopted to sense the environmental information around the inspection robot, so that the method has good adaptability and rapidity, but the working range of a single laser radar is relatively limited.
Preferably, from the first data, a global position of the robot in the specific area is determined, including; the scanner constructs a map of the specific area according to the first data, and determines the global position of the robot in the area.
Preferably, the matching the second data with the first data and the matching the third data with the first data respectively to determine the specific position of the robot in the global position includes:
matching the second data with the first data to obtain a first optimal matching probability P (X) so as to obtain a first optimal matching pose P;
matching the third data with the first data to obtain a second optimal matching probability P '(X) so as to obtain a second optimal matching pose P';
and determining the specific position of the robot in the global position through the relation between the P and the P'.
In the above implementation, the first optimal matching probability and the second optimal matching probability are calculated by the following formula (1);
wherein the content of the first and second substances,
mu is the mean value, ∑ is the variance,
representing all the scanning points in one cell.
In a specific implementation, an industrial personal computer is also mounted in the positioning system and is used for realizing a data processing function. The industrial personal computer adopts an SLAM algorithm which is an NDT algorithm, and the algorithm has the idea that a map of a unit cell in the global position of the first laser radar is matched with a map of a current specific area constructed by the 3D scanner according to the 3-dimensional point cloud data, and a map of a unit cell in the global position of the second laser radar is matched with the map of the current specific area constructed by the 3D scanner according to the 3-dimensional point cloud data. The two-dimensional plane is first decomposed into a series of fixed-size cells, the probability density function of which is calculated based on the points of the cells. The conversion can directly scan the matched analytical expressions everywhere without considering the correspondence between points or characteristics, can quickly and accurately complete map matching, and effectively solves the problems of local position tracking and global positioning of the robot in the outdoor environment of the transformer substation.
Preferably, determining the specific position of the robot in the global position by the relationship between P and P' comprises:
when P is larger than P', the probability of matching the first laser radar with the scanner is larger than that of matching the second laser radar with the scanner, so that the specific position of the robot in the global position is determined to be the position of the first laser radar in the specific area;
when P is smaller than P', the probability that the second laser radar is matched with the scanner is larger than that of the first laser radar, so that the specific position of the robot in the global position is determined to be the position of the second laser radar in the specific area.
In order to further clarify the process of matching the point cloud information acquired by the first laser radar and the 3D scanner and the process of matching the point cloud information acquired by the second laser radar and the 3D scanner, the following description mainly describes the matching of the point cloud information acquired by the first laser radar and the 3D scanner:
(1) a normal distribution transformation for the 3D scanner scan is created.
(2) Initializing coordinate transformation parameters by using the odometer reading;
(3) for each sample scanned by the first laser radar, mapping the sample into a first scanning coordinate system according to the coordinate transformation parameters;
(4) determining a corresponding normal distribution for each mapping point;
(5) evaluating the sum of the probability distribution of each mapping point as a fraction value of each coordinate transformation parameter;
(6) optimizing the fraction values by using a Hessian matrix method, and calculating a new parameter estimation value;
(7) returning to step 3, continuing the loop until the convergence requirement is met, the fractional values of the coordinate transformation parameters p are expressed as:
where i is a mapping point of coordinate transformation.
U hereiThe same as the above μ, and no additional explanation is made.
Here, as part of the scan matching algorithm, the error function-score (p) must be minimized, i.e., maximized, to ensure that the coordinate transformation according to parameter p is optimal.
The first laser is arrangedOptimizing data of the reach and 3D scanner through a Hessian matrix, and calculating optimal probability distribution of sensor reading obtained when the current position and the map of the robot are given
Similarly, the optimal matching probability P '(X) of the second lidar may also be obtained, which is not described herein again, and finally, the maximum value of P (X) and P' (X) is selected as the optimal matching pose P of the current position*。
The invention also provides a positioning device, which is suitable for the positioning method and comprises the following steps:
201: the first acquisition unit is used for acquiring first data of each cell in a specific area through a scanner;
202: the first determination unit is used for determining the global position of the robot in the specific area according to the first data by the scanner;
203: the second acquisition unit is used for acquiring second data of the cells in the global position where the first laser radar is located through the first laser radar;
204: the third acquisition unit is used for acquiring third data of the cells in the global position where the second laser radar is located through the second laser radar;
205: and the second determining unit is used for matching the second data with the first data, matching the third data with the first data and determining the specific position of the robot in the global position.
Preferably, the first determining unit is specifically configured to construct a map of the specific area and determine the global position of the robot in the area according to the first data.
Preferably, the second determining unit is specifically configured to match the second data with the first data to obtain a first optimal matching probability P (X) to obtain a first best matching pose P;
matching the third data with the first data to obtain a second optimal matching probability P '(X) so as to obtain a second optimal matching pose P';
and determining the specific position of the robot in the global position through the relation between the P and the P'.
Preferably, the second determining unit is further configured to determine that the specific position of the robot in the global position is the position of the first lidar in the specific area, when P is greater than P';
when P is smaller than P', the probability that the second laser radar is matched with the scanner is larger than that of the first laser radar, so that the specific position of the robot in the global position is determined to be the position of the second laser radar in the specific area.
While the invention has been described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the spirit and scope of the invention. The present invention is not to be limited by the specific embodiments disclosed herein, and other embodiments that fall within the scope of the claims of the present application are intended to be within the scope of the present invention.
Claims (9)
1. A positioning system, comprising:
a robot, a scanner, a first lidar, and a second lidar located outdoors;
the scanner and the first laser radar are both arranged at the top of the robot;
acquiring first data of each cell in a specific area through the scanner;
acquiring second data of cells in the global position of the first laser radar through the first laser radar;
acquiring third data of a cell in the global position of the second laser radar through the second laser radar;
the scanner determines the global position of the robot in the specific area according to the first data;
and respectively matching the second data with the first data and the third data with the first data to determine the specific position of the robot in the global position.
2. A positioning method applied to the positioning system of claim 1, comprising:
acquiring first data of each cell in a specific area through a scanner;
the scanner determines the global position of the robot in the specific area according to the first data;
acquiring second data of a cell in the global position of a first laser radar through the first laser radar;
acquiring third data of a cell in the global position of the second laser radar through the second laser radar;
and matching the second data with the first data and matching the third data with the first data to determine the specific position of the robot in the global position.
3. The positioning method of claim 2,
determining a global position of the robot in the specific area according to the first data, comprising:
and the scanner constructs a map of the specific area according to the first data and determines the global position of the robot in the area.
4. The positioning method of claim 2,
respectively matching the second data with the first data and the third data with the first data, and determining a specific position of the robot in the global position, including:
matching the second data with the first data to obtain a first optimal matching probability P (X) so as to obtain a first optimal matching pose P;
matching the third data with the first data to obtain a second optimal matching probability P '(X) so as to obtain a second optimal matching pose P';
determining a specific position of the robot in the global position through a relationship between the P and P'.
5. The positioning method of claim 4,
determining a specific position of the robot in the global position by the relationship between P and P', including:
when P is larger than P', the probability that the first laser radar is matched with the scanner is larger than the probability that the second laser radar is matched with the scanner, so that the specific position of the robot in the global position is determined to be the position of the first laser radar in the specific area;
when P is smaller than P', the probability that the second laser radar is matched with the scanner is larger than the probability that the first laser radar is matched with the scanner, so that the specific position of the robot in the global position is determined to be the position of the second laser radar in the specific area.
6. A positioning apparatus adapted to the positioning method according to any one of claims 2 to 5, comprising:
the first acquisition unit is used for acquiring first data of each cell in a specific area through a scanner;
a first determination unit, configured to determine, by the scanner, a global position of the robot in the specific area according to the first data;
the second acquisition unit is used for acquiring second data of the cells in the global position of the first laser radar through the first laser radar;
a third obtaining unit, configured to obtain, by the second lidar, third data of a cell in a global position where the second lidar is located;
and the second determining unit is used for matching the second data with the first data and matching the third data with the first data to determine the specific position of the robot in the global position.
7. The positioning method of claim 6,
the first determining unit is specifically configured to construct a map of the specific area according to the first data by the scanner, and determine a global position of the robot in the area.
8. The positioning method of claim 6,
the second determining unit is specifically configured to match the second data with the first data to obtain a first optimal matching probability P (X) so as to obtain a first best matching pose P;
matching the third data with the first data to obtain a second optimal matching probability P '(X) so as to obtain a second optimal matching pose P';
determining a specific position of the robot in the global position through a relationship between the P and P'.
9. The positioning method of claim 8,
the second determining unit is further specifically configured to determine that the specific position of the robot in the global position is the position of the first lidar in the specific area, when P is greater than P', the probability that the first lidar is matched with the scanner is greater than the probability that the second lidar is matched with the scanner;
when P is smaller than P', the probability that the second laser radar is matched with the scanner is larger than the probability that the first laser radar is matched with the scanner, so that the specific position of the robot in the global position is determined to be the position of the second laser radar in the specific area.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010378957.5A CN111694009B (en) | 2020-05-07 | 2020-05-07 | Positioning system, method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010378957.5A CN111694009B (en) | 2020-05-07 | 2020-05-07 | Positioning system, method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111694009A true CN111694009A (en) | 2020-09-22 |
| CN111694009B CN111694009B (en) | 2023-07-11 |
Family
ID=72476619
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010378957.5A Active CN111694009B (en) | 2020-05-07 | 2020-05-07 | Positioning system, method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111694009B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113341431A (en) * | 2021-04-22 | 2021-09-03 | 国网浙江省电力有限公司嘉兴供电公司 | Transformer substation robot indoor navigation positioning method based on double-path laser |
| CN113778109A (en) * | 2021-11-05 | 2021-12-10 | 深圳市普渡科技有限公司 | Forbidden path setting method and device for robot, robot and storage medium |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA1234419A (en) * | 1984-11-09 | 1988-03-22 | Robert J. Mongeon | Dual mode scanner/tracker |
| US20080033645A1 (en) * | 2006-08-03 | 2008-02-07 | Jesse Sol Levinson | Pobabilistic methods for mapping and localization in arbitrary outdoor environments |
| CN103941264A (en) * | 2014-03-26 | 2014-07-23 | 南京航空航天大学 | Positioning method using laser radar in indoor unknown environment |
| CN104848851A (en) * | 2015-05-29 | 2015-08-19 | 山东鲁能智能技术有限公司 | Transformer substation patrol robot based on multi-sensor data fusion picture composition and method thereof |
| CN105607071A (en) * | 2015-12-24 | 2016-05-25 | 百度在线网络技术（北京）有限公司 | Indoor positioning method and device |
| CN105758408A (en) * | 2016-01-05 | 2016-07-13 | 福州华鹰重工机械有限公司 | Method and device for building local maps |
| US20160378111A1 (en) * | 2005-12-30 | 2016-12-29 | Irobot Corporation | Method and System for Controlling a Remote Vehicle |
| US20170031004A1 (en) * | 2007-08-31 | 2017-02-02 | Raymarine Uk Limited | Digital ranging systems and methods |
| CN106584451A (en) * | 2015-10-14 | 2017-04-26 | 山东鲁能智能技术有限公司 | Visual navigation based transformer substation automatic composition robot and method |
| CN107505940A (en) * | 2017-08-08 | 2017-12-22 | 速感科技（北京）有限公司 | Double laser radar control method, system and localization method on automated guided vehicle |
| CN108507580A (en) * | 2018-06-19 | 2018-09-07 | 南昌大学 | A kind of mobile robot platform self aligning system and method for self-locating |
| CN108932736A (en) * | 2018-05-30 | 2018-12-04 | 南昌大学 | Two-dimensional laser radar Processing Method of Point-clouds and dynamic robot pose calibration method |
| CN110967011A (en) * | 2019-12-25 | 2020-04-07 | 苏州智加科技有限公司 | Positioning method, device, equipment and storage medium |
-
2020
- 2020-05-07 CN CN202010378957.5A patent/CN111694009B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA1234419A (en) * | 1984-11-09 | 1988-03-22 | Robert J. Mongeon | Dual mode scanner/tracker |
| US20160378111A1 (en) * | 2005-12-30 | 2016-12-29 | Irobot Corporation | Method and System for Controlling a Remote Vehicle |
| US20080033645A1 (en) * | 2006-08-03 | 2008-02-07 | Jesse Sol Levinson | Pobabilistic methods for mapping and localization in arbitrary outdoor environments |
| US20170031004A1 (en) * | 2007-08-31 | 2017-02-02 | Raymarine Uk Limited | Digital ranging systems and methods |
| CN103941264A (en) * | 2014-03-26 | 2014-07-23 | 南京航空航天大学 | Positioning method using laser radar in indoor unknown environment |
| CN104848851A (en) * | 2015-05-29 | 2015-08-19 | 山东鲁能智能技术有限公司 | Transformer substation patrol robot based on multi-sensor data fusion picture composition and method thereof |
| CN106584451A (en) * | 2015-10-14 | 2017-04-26 | 山东鲁能智能技术有限公司 | Visual navigation based transformer substation automatic composition robot and method |
| CN105607071A (en) * | 2015-12-24 | 2016-05-25 | 百度在线网络技术（北京）有限公司 | Indoor positioning method and device |
| CN105758408A (en) * | 2016-01-05 | 2016-07-13 | 福州华鹰重工机械有限公司 | Method and device for building local maps |
| CN107505940A (en) * | 2017-08-08 | 2017-12-22 | 速感科技（北京）有限公司 | Double laser radar control method, system and localization method on automated guided vehicle |
| CN108932736A (en) * | 2018-05-30 | 2018-12-04 | 南昌大学 | Two-dimensional laser radar Processing Method of Point-clouds and dynamic robot pose calibration method |
| CN108507580A (en) * | 2018-06-19 | 2018-09-07 | 南昌大学 | A kind of mobile robot platform self aligning system and method for self-locating |
| CN110967011A (en) * | 2019-12-25 | 2020-04-07 | 苏州智加科技有限公司 | Positioning method, device, equipment and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 韩同辉: ""大型运载车平台自主定位关键技术研究"", 《中国优秀硕士学位论文全文数据库工程科技辑||辑》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113341431A (en) * | 2021-04-22 | 2021-09-03 | 国网浙江省电力有限公司嘉兴供电公司 | Transformer substation robot indoor navigation positioning method based on double-path laser |
| CN113341431B (en) * | 2021-04-22 | 2022-04-15 | 国网浙江省电力有限公司嘉兴供电公司 | Transformer substation robot indoor navigation positioning method based on double-path laser |
| CN113778109A (en) * | 2021-11-05 | 2021-12-10 | 深圳市普渡科技有限公司 | Forbidden path setting method and device for robot, robot and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111694009B (en) | 2023-07-11 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109001711B (en) | Multi-line laser radar calibration method | |
| CN113359097B (en) | Millimeter wave radar and camera combined calibration method | |
| CN110443836A (en) | A kind of point cloud data autoegistration method and device based on plane characteristic | |
| CN111435163B (en) | Ground point cloud data filtering method, device, detection system and storage medium | |
| CN109085838A (en) | A kind of dynamic barrier rejecting algorithm based on laser positioning | |
| CN110208771B (en) | Point cloud intensity correction method of mobile two-dimensional laser radar | |
| CN110568433A (en) | High-altitude parabolic detection method based on millimeter wave radar | |
| CN111694009B (en) | Positioning system, method and device | |
| JP6756889B1 (en) | Vortex detector, vortex detection method, program and trained model | |
| CN112305559A (en) | Power transmission line distance measuring method, device and system based on ground fixed-point laser radar scanning and electronic equipment | |
| CN114488099A (en) | Laser radar coefficient calibration method and device, electronic equipment and storage medium | |
| CN109407112B (en) | LiDAR point cloud data-based fruit tree crown volume measuring and calculating method and system | |
| CN111532260A (en) | Parking space detection performance evaluation method and electronic equipment | |
| CN113534110A (en) | Static calibration method for multi-laser radar system | |
| CN115953604B (en) | Real estate geographic information mapping data acquisition method | |
| CN117055014A (en) | Automatic calibration method for full-freedom pose of single-axis laser radar turntable without targets | |
| Song et al. | Registration for 3D LiDAR Datasets using Pyramid Reference Object | |
| CN116381726A (en) | Unmanned aerial vehicle laser point cloud precision self-evaluation method based on data | |
| WO2023000540A1 (en) | Method and terminal device for measuring burden surface profile of blast furnace, and storage medium | |
| CN115343698A (en) | Millimeter wave distance measurement optimization method and system | |
| CN115201794A (en) | Robot positioning error evaluation method and device based on two-dimensional laser | |
| CN115018983A (en) | Phase-shifting transformer site selection method, device, electronic equipment and storage medium | |
| CN115267756A (en) | Monocular real-time distance measurement method based on deep learning target detection | |
| Lindzey et al. | Extrinsic calibration between an optical camera and an imaging sonar | |
| CN113848825B (en) | AGV state monitoring system and method for flexible production workshop |
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 |