CN109141402B - Positioning method based on laser grids and robot autonomous charging method - Google Patents
Positioning method based on laser grids and robot autonomous charging method Download PDFInfo
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- CN109141402B CN109141402B CN201811127273.7A CN201811127273A CN109141402B CN 109141402 B CN109141402 B CN 109141402B CN 201811127273 A CN201811127273 A CN 201811127273A CN 109141402 B CN109141402 B CN 109141402B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/0042—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries characterised by the mechanical construction
- H02J7/0045—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries characterised by the mechanical construction concerning the insertion or the connection of the batteries
Abstract
The invention discloses a positioning method based on a laser grid and an autonomous robot charging method, and belongs to the technical field of intelligent robots. The method comprises the steps of establishing a grid plane at the specified height of the right front part and the wall surfaces at two sides of a room; marking laser grids, namely counting the number of lasers received by each grid, and marking the grids with the number of lasers received by the grids not less than a threshold value; extracting geometric characteristics of the laser grids, namely extracting continuous marked grid sequences vertical to the horizontal direction and the vertical direction respectively on the left side and the right side of a grid plane; obtaining a key point, wherein the key point is an inflection point in the sequence of the grids extracted in the step 3; and determining the coordinates of the robot according to the relative position between the key point and the robot. By adopting the method, the navigation and positioning precision can be high regardless of whether the wall of the charging room is smooth or not.
Description
Technical Field
The invention belongs to the technical field of intelligent robots, and particularly relates to a positioning method based on a laser grid and an autonomous robot charging method.
Background
At present, the autonomous charging of the transformer substation inspection robot mostly adopts a contact type autonomous charging technology. When the inspection robot needs to be charged, the inspection robot can automatically drive to the designated charging area, and the robot charging connection contact is automatically and accurately butted with the power supply contact of the charging base and is charged. After charging is completed, the inspection robot automatically separates from the inspection robot and drives to a working area or a standby area.
How to realize the positioning navigation of the inspection robot is the key for realizing the autonomous charging of the robot. The current common solution is a magnetic track guidance based navigation positioning method. The method is implemented on the premise that the track is laid, so that not only is a large amount of infrastructure construction work brought, but also the defect that the walking route of the robot is inflexible exists. In view of this, the laser navigation positioning technology is increasingly applied to the navigation positioning process of the inspection robot. The laser navigation positioning technology gets rid of the limitation of a track, and the robot can flexibly adjust a walking line while saving cost.
Chinese patent CN201610324865 discloses an autonomous charging method for a substation inspection robot based on laser navigation, which includes performing linear fitting on laser data, then selecting four required linear lines to segment the laser data, and finally obtaining two inflection points corresponding to two corners by using the four linear lines to position the robot.
Chinese patent CN2016112609096 discloses a positioning method and an automatic charging method for an inspection robot, which includes firstly segmenting a continuous laser data set by a fast and efficient secondary point set segmentation algorithm to obtain three edge features with high robustness, then reconstructing a charging room model, and positioning the robot by using a key point corresponding to the reconstructed charging room model. The method has the advantages that the positioning accuracy is guaranteed, meanwhile, the method does not directly depend on the corner inflection point of the charging house, and the dependence on the charging house building process is low.
Both of the above methods have the following problems:
if the left wall and the right wall of the charging house are uneven, deviation of a fitting straight line can be caused, the accuracy of the corner position of the wall of the charging house is affected, the navigation and positioning accuracy of the robot is not ideal, and therefore the phenomenon that the robot charging connection contact and the power supply contact of the charging base are failed to be butted occurs. When the two methods are adopted for navigation positioning and autonomous charging of the robot, the requirement on the flatness of the wall of the charging room is high, and the adaptability of the robot to the environment is poor.
Disclosure of Invention
The invention aims to: aiming at the defects of the prior art, a positioning method based on a laser grid and a robot autonomous charging method based on the positioning method are provided. The method is suitable for autonomous robot charging in trackless navigation positioning, and automation and intellectualization of the whole charging process are realized; the method has the advantage of high navigation and positioning precision regardless of whether the wall of the charging room is flat or not.
The positioning method based on the laser grids comprises the following steps:
establishing a grid plane: establishing a grid plane at the specified height of the right front and the two side wall surfaces of the room;
marking the laser grid: counting the number of the laser received by each grid, and marking the grids with the number of the laser received by the grids not less than a threshold value;
extracting the geometrical characteristics of the laser grids: extracting continuous marked grid sequences in the horizontal direction and the vertical direction from the left side and the right side of the grid plane respectively;
and key point acquisition: acquiring a grid of inflection points in a sequence of the grid extracted in the step of extracting the geometric features of the laser grid, wherein the inflection points in the sequence of the extracted grid are key points;
determining the coordinates of the robot: and determining the coordinates of the robot according to the relative position between the key point and the robot.
Further, the calculation formula of the threshold value is as follows:
wherein a is the side length of the laser grid, theta is the emission angle of the laser equipment, pi is the circumferential ratio, r is the distance from the laser equipment to the wall corner, and N is the total number of lasers in a laser frame projected by the laser equipment.
Further, the step of extracting the geometric features of the laser grid may be preceded by a step of calculating a confidence level, the step of calculating the confidence level may comprise:
step A-1: adjusting the laser projection angle after the step of establishing the grid plane and before the step of marking the laser grid;
step A-2: calculating a confidence level of the marked grid after the step of marking the laser grid; when the confidence coefficient meets the requirement of the confidence coefficient, switching to the step of marking the laser grids; and returning to the step A-1 when the requirements are not met.
Further, the formula for calculating the confidence of the labeled grid is:
where ρ is the confidence, N' is the number of marked grids, and M is the total number of all grids in the grid plane established in the step of marking the laser grid.
Further, the confidence requirement is that 95% or more rho or more is 60% or more.
Further, the method further comprises the step of verifying the characteristic laser grid, namely:
judging whether each characteristic grid positioned in the horizontal direction in the sequence of the two grids extracted in the step of extracting the geometric characteristics of the laser grids is positioned on the same horizontal line; if the feature grids are on the same horizontal line, the feature grids are taken as standard feature grids; and if the laser grids are not on the same horizontal line, waiting for the next frame of laser data to re-extract the geometric features of the laser grids.
Further, the criterion for determining whether the feature grids are on the same horizontal line is whether the grids in the horizontal direction in the sequence of two grids are both within 3 rows.
Further, the key point is an inflection point of two standard feature grids.
Further, the coordinates of the robot are the coordinates of the robot in the global coordinate system and are (-au-x)mcosθ+ymsinθ，av-xmsinθ-ymcosθ)，
Wherein a is the side length of the grid, u is the number of grids contained in the distance from the first key point to the Y axis of the global coordinate system, v is the number of grids contained in the distance from the first key point to the X axis of the global coordinate system, and XmIs the X-axis coordinate, y, of the first key point in the robot coordinate systemmThe Y-axis coordinate of the first key point in the robot coordinate system; theta is the deflection angle of the robot,i.e. the angle of deflection of the Y-axis of the coordinate system with respect to the Y-axis in the global coordinate system.
On the other hand, the invention also provides a method for automatically charging the robot based on the laser grids, which comprises the following steps:
1) obtaining the coordinates and the deflection angle of the robot by using the positioning method based on the laser grids;
2) the robot adjusts the deflection angle to 0 degree;
3) and the robot upper computer sends an instruction to the robot, calculates the distance from the robot to the charging pile, moves to a preset charging position and starts charging.
The invention has the following beneficial effects: the invention relates to a positioning method based on a laser grid and an autonomous robot charging method, which are characterized in that grids are respectively established on a wall surface right in front of a charging room, a left wall surface and a right wall surface by adopting a navigation positioning method based on geometric and quantity characteristics of the laser grid, after laser is projected on the grids, the position information of key points of two wall corners of the charging room is searched by identifying the geometric characteristics of the laser grid, the accurate positioning of a robot is realized by utilizing the two key points, and the concept of confidence coefficient is introduced, so that the positioning precision of the robot is improved, and the requirement on the smoothness of the wall surface of the charging room is lower. Through the test, the positioning accuracy of robot improves greatly, and the error is within the scope of 0.1cm, and under the condition of the wall unevenness, the robot still can accomplish with fill electric pile's accurate positioning.
Drawings
Fig. 1 is a flow chart of a positioning algorithm of an embodiment of the present invention.
Fig. 2 is a schematic diagram of a laser grid according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of a characteristic laser grid of an embodiment of the invention.
Fig. 4 is a schematic diagram of a robot positioning according to an embodiment of the present invention.
Fig. 5 is a robot autonomous charging flowchart of an embodiment of the present invention.
Reference numerals in the drawings: 1-charging house model, 2-robot, 3-laser, 4-charging house right corner, and 5-charging house left corner.
Detailed Description
The present invention will be described in further detail with reference to the following examples and the accompanying drawings.
Example 1:
the invention discloses an autonomous charging method of a transformer substation inspection robot based on laser grid positioning.
The technical terms related to the present embodiment are defined as follows:
grid: a grid array of uniformly sized closely adjacent cells.
Laser grid: there is a grid illuminated by a laser.
Gray grid: a laser grid that meets confidence requirements.
Grid plane: and grids are built on the wall surface right in front of the charging house, the left wall surface and the right wall surface at the same height to form a grid plane.
Continuous grid: a grid of closely connected cells.
Characteristic grids: the grids that make up the L-shaped gray grid sequence.
Standard feature grid: the feature grids are located at right angles to the feature grid sequence and on the same line in the horizontal direction in the grid plane.
Inflection point of standard feature grid: points located at right angles to the standard feature grid, see fig. 4.
The key points are as follows: two corners of the grid plane on the wall right in front of the charging room are represented by the inflection points of the standard characteristic grid in the algorithm.
The key point coordinates are as follows: and coordinates of the key points in a global coordinate system corresponding to the charging room model.
Referring to fig. 1, the robot autonomous charging scheme is described in detail as follows: the method comprises the following steps: the site worker has entered the position of filling electric pile in the room that charges into the industrial computer of robot. When the robot needs to supplement electric power, the robot automatically drives to the charging room through the positioning navigation technology, the robot upper computer sends an instruction to the electric cabinet of the charging room, the electric cabinet opens the door of the charging room after receiving the instruction, and the robot backs up to enter the charging room. The robot is internally provided with an electric quantity detection module, and when the total electric quantity is lower than a certain value (for example, 10%), the robot is judged to need to be charged. After entering a charging room, the coordinate information and the deflection angle information of the robot are obtained by using the positioning method based on the laser grids.
The overall process of the positioning method based on the laser grid is shown in fig. 2, and the specific implementation steps are as follows:
1. and establishing the grid.
As shown in fig. 3, a grid with a side length of a is established on a same height of the wall surface right in front of the charging room, the left wall surface and the right wall surface, so as to form a grid plane. The length of the side length a satisfies a epsilon [1cm, 2cm ].
2. The laser grid is marked. And counting the number n of the laser received by each grid, and marking the grid as grey when the condition of formula (1) is met so as to distinguish the grid which does not meet the condition. The number of gray grids N' is counted.
n≥threshod (1)
Where n is the number of lasers received by a single grid, threshod is a threshold, and the calculation formula is shown in formula (2).
Wherein a is the side length of the laser grid, θ is the emission angle of the laser device, π is the circumferential ratio, r is the distance from the laser device to the wall corner, and N is the total number of laser beams in a laser frame projected by the laser device, which is a fixed value, generally about 1141.
3. And extracting the geometrical characteristics of the laser grids.
On the left and right sides of the grid plane, continuous gray grids are extracted, which are perpendicular to each other in the horizontal direction and the vertical direction, respectively, and represent two corners of the charging room (see 4, 5 in fig. 3). The grid satisfying the requirement is shown in fig. 4, the height h (referring to the distance from the grid to the origin of the global coordinate system in the vertical direction) of the gray grid on the grid plane should be not less than one half of the depth of the charging room, and the width W (referring to the distance from the grid to the origin of the global coordinate system in the horizontal direction) should be not less than one half of the difference between the width of the charging room and the width of the gate, i.e. h is not more than L/2, and W is not more than W/2, wherein L is the depth of the charging room, and W is the difference between the width of the charging room and the width of.
(optional) calculating confidence. The reliability and the precision of the algorithm can be improved by introducing confidence calculation, and the confidence calculation can be omitted under the conditions that the data configuration of a charging room model and the like is correct and excessive noise does not occur to laser.
A-1) adjusting the laser projection angle. The robot adjusts the steering of the robot, further adjusts the laser projection angle, the adjustment range is +/-20 degrees, and the adjustment step length is 1 degree each time.
A-2) calculating the confidence p of the laser grid, and the calculation formula is shown in formula (3). When p does not meet the confidence requirement, for example, is lower than 60%, particularly lower than 85%, returning to step 2-1); and when the rho meets the confidence requirement, such as 95% ≧ rho ≧ 60%, especially rho ≧ 85%, returning to step 2.
Where N' is the number of gray grids and M is the total number of all grids established in step 1.
(optional) verification of laser grid characteristics. It is verified whether the respective feature grids in the horizontal direction in the two L-shaped gray grid sequences extracted in step 2 (see 4 and 5 in fig. 3) are on the same horizontal line. I.e. when the horizontal gray grids in both L-shaped gray grid sequences are within 3 rows, in particular in the same row of grids. The judgment within a specific few rows as being on the same horizontal line depends on the size of the grid, i.e. the resolution of the laser. If the condition is met, the standard feature grid is obtained. And when the condition is not met, waiting for the next frame of laser data and returning to the step 2.
4. And acquiring key points.
The inflection points (4 and 5 in fig. 3) of the two standard feature grids are two key points of the charged corner of the house. The coordinates of the two key points can be determined through the method in the step 4-1), namely the grid number of the inflection point to the x axis and the y axis respectively is counted, and the coordinates of the inflection point on the x axis and the y axis can be obtained by multiplying the grid number and the grid side length as the grid side length is known.
5. And (4) positioning the robot (determining the coordinates of the robot according to the relative position between the key point and the robot).
The positioning principle of the robot is shown in fig. 5, wherein a coordinate system XOY is a global coordinate system adopted by the charging room model; the coordinate system X 'O' Y 'is the robot coordinate system, and O' corresponds to the position of the robot. M, N corresponds to the keypoints obtained in step 4 (see fig. 4). And (4) determining the coordinates of the robot in the global coordinate system XOY by using the relative positions of the two key points and the robot obtained in the step (4).
5-1) in the coordinate system XOY, the coordinates of the two keypoints are obtained M, N. Counting the distances from the point M to the Y axis (i.e., the number u of grids in the horizontal direction), and the distances from the point M to the X axis (i.e., the number v of grids in the vertical direction), the coordinate of the available point M in the coordinate system XOY is M (-au, av). Since the points M and N are symmetrically distributed about the Y axis in the global coordinate system, the coordinates of the point N in the coordinate system XOY are N (au, av).
5-2) determining the coordinates of the robot in the global coordinate system XOY. In the coordinate system X ' O ' Y ', the coordinates of M, N are M (X) respectivelym，ym)、N(xn，yn). Making a perpendicular line of the straight line MN through the O' point, wherein the vertical foot is P; making a perpendicular line of a Y' axis through the M point, wherein the foot is Q; the intersection of the line MN and the Y' axis is R. Then, the coordinates of the robot in the global coordinate system XOY can be calculated by only calculating | MP | and | O' P |. The specific process of calculating | MP | and | O' P | is as follows:
let | MQ | ═ Xm，|O’Q|＝ym. A parallel line passing through the point N as the axis X 'intersects with Y' at a point L, and if the angle MNL is equal to theta, then
Therefore, the temperature of the molten metal is controlled,
∠QMN＝θ。
|MR|＝-xm/cosθ，|QR|＝-xmtanθ
therefore, | MP | + | MR | + | PR | - | ymsinθ-xmcosθ，|O′P|＝|O′R|cosθ＝ymcosθ+xmsin θ. Thus, the robot has coordinates (-au-x) in the global coordinate systemmcosθ+ymsinθ，av-xmsinθ-ymcos θ) and the deflection angle θ.
After the coordinates and the deflection angle of the robot are obtained, the robot adjusts the deflection angle of the robot to enable the two sides of the robot to be parallel to the center line of the left key point and the center line of the right key point, namely the deflection angle theta of the robot is adjusted to be 0 degree. And then, the robot upper computer sends an instruction to the robot, and the distance from the robot to the charging pile is calculated. If the robot does not reach the preset position (the position in the charging state), the robot slowly moves back until the preset position is reached. The location of the charging post is known. After the robot upper computer determines that the robot is located at the correct position, an instruction is sent to the robot, and the robot stretches out of the charging arm and is inserted into the charging pile. When the robot detects that the charging arm is well connected with the charging pile, the robot starts to charge; otherwise, the robot upper computer sends an instruction to the robot, the charging arm is retracted, and the position and angle information of the robot is adjusted again according to the steps.
The invention discloses a transformer substation inspection robot autonomous charging method based on laser grid positioning, which is characterized in that grids are respectively established on a wall surface right in front of a charging room, a left wall surface and a right wall surface by adopting a navigation positioning method based on geometric and quantity characteristics of laser grids, after laser is projected onto the grids, the position information of key points of two wall corners of the charging room is searched by identifying the geometric characteristics of the laser grids, the accurate positioning of a robot is realized by utilizing the two key points, and the concept of confidence coefficient is introduced, so that the positioning precision of the robot is improved, and the requirement on the smoothness of the wall surface of the charging room is lower. Through the test, the positioning accuracy of robot improves greatly, and the error is within the scope of 0.1cm, and under the condition of the wall unevenness, the robot still can accomplish with fill electric pile's accurate positioning.
Although the present invention has been described in terms of the preferred embodiment, it is not intended that the invention be limited to the embodiment. Any equivalent changes or modifications made without departing from the spirit and scope of the present invention also belong to the protection scope of the present invention. The scope of the invention should therefore be determined with reference to the appended claims.
Claims (9)
1. A positioning method based on a laser grid is characterized by comprising the following steps:
establishing a grid plane: establishing a grid plane at the specified height of the right front and the two side wall surfaces of the room;
marking the laser grid: counting the number of the laser received by each grid, and marking the grids with the number of the laser received by the grids not less than a threshold value; the calculation formula of the threshold is as follows:
wherein a is the side length of the laser grid, theta is the emission angle of the laser equipment, pi is the circumferential ratio, r is the distance from the laser equipment to a wall corner, and N is the total number of lasers in a laser frame projected by the laser equipment;
extracting the geometrical characteristics of the laser grids: extracting continuous marked grid sequences in the horizontal direction and the vertical direction from the left side and the right side of the grid plane respectively;
and key point acquisition: acquiring a grid of inflection points in a sequence of the grid extracted in the step of extracting the geometric features of the laser grid, wherein the inflection points in the sequence of the extracted grid are key points;
determining the coordinates of the robot: and determining the coordinates of the robot according to the relative position between the key point and the robot.
2. The laser grid-based positioning method of claim 1, wherein the step of extracting geometrical features of the laser grid is preceded by a step of calculating a confidence level, the step of calculating the confidence level comprising the following processes:
step A-1: adjusting the laser projection angle after the step of establishing the grid plane and before the step of marking the laser grid;
step A-2: calculating a confidence level of the marked grid after the step of marking the laser grid; when the confidence coefficient meets the requirement of the confidence coefficient, switching to the step of marking the laser grids; and returning to the step A-1 when the requirements are not met.
3. The laser grid based positioning method of claim 2, wherein the formula for calculating the confidence of the marked grid is:
where ρ is the confidence, N' is the number of marked grids, and M is the total number of all grids in the grid plane established in the step of marking the laser grid.
4. The laser grid based positioning method of claim 3, wherein the confidence requirement is 95% ≧ ρ ≧ 60%.
5. The laser grid based positioning method of claim 1, further comprising the step of verifying the characteristic laser grid by:
judging whether each characteristic grid positioned in the horizontal direction in the sequence of the two grids extracted in the step of extracting the geometric characteristics of the laser grids is positioned on the same horizontal line; if the feature grids are on the same horizontal line, the feature grids are taken as standard feature grids; and if the laser grids are not on the same horizontal line, waiting for the next frame of laser data to re-extract the geometric features of the laser grids.
6. The laser grid-based positioning method of claim 5, wherein the criterion for determining whether the feature grids are on the same horizontal line is whether the grids in the horizontal direction in the sequence of two grids are within 3 rows.
7. The laser grid-based positioning method of claim 5, wherein the key point is an inflection point of two standard feature grids.
8. The laser grid-based positioning method of claim 1, wherein the coordinates of the robot are the coordinates of the robot in a global coordinate system, and are (-au-x)m cosθ+ym sinθ，av-xm sinθ-ym cosθ)，
Wherein a is the side length of the grid, u is the number of grids contained in the distance from the first key point to the Y axis of the global coordinate system, v is the number of grids contained in the distance from the first key point to the X axis of the global coordinate system, and XmIs the X-axis coordinate, y, of the first key point in the robot coordinate systemmThe Y-axis coordinate of the first key point in the robot coordinate system; theta is the deflection angle of the robot, i.e. the deflection angle of the Y-axis of the coordinate system relative to the Y-axis in the global coordinate system.
9. A robot autonomous charging method based on laser grids is characterized by comprising the following steps:
1) obtaining the coordinates and deflection angle of the robot by using the positioning method based on the laser grids according to any one of claims 1 to 8;
2) the robot adjusts the deflection angle to 0 degree;
3) and the robot upper computer sends an instruction to the robot, calculates the distance from the robot to the charging pile, moves to a preset charging position and starts charging.
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| CN109991980B (en) * | 2019-04-01 | 2022-07-08 | 珠海一微半导体股份有限公司 | Method for forming signal quantization distribution diagram of charging seat |
| CN112214011B (en) * | 2019-07-11 | 2022-05-10 | 珠海一微半导体股份有限公司 | System and method for positioning charging seat of self-moving robot |
| CN110647148B (en) * | 2019-09-19 | 2022-11-11 | 北京小狗吸尘器集团股份有限公司 | Wall position determining method and device, computer equipment and storage medium |
| CN111324121B (en) * | 2020-02-27 | 2023-07-18 | 四川阿泰因机器人智能装备有限公司 | Automatic mobile robot charging method based on laser radar |
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