CN115183778A - Image building method, device, equipment and medium based on pier stone pier - Google Patents
Image building method, device, equipment and medium based on pier stone pier Download PDFInfo
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- 239000004575 stone Substances 0.000 title claims abstract description 109
- 238000000034 method Methods 0.000 title claims abstract description 20
- 238000005457 optimization Methods 0.000 claims abstract description 14
- 238000013507 mapping Methods 0.000 claims description 15
- 238000004364 calculation method Methods 0.000 claims description 4
- 108010014173 Factor X Proteins 0.000 claims description 3
- 238000010276 construction Methods 0.000 claims description 3
- 238000013075 data extraction Methods 0.000 claims description 3
- 238000010586 diagram Methods 0.000 abstract description 2
- 238000000605 extraction Methods 0.000 abstract 1
- 238000013135 deep learning Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
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- 230000009286 beneficial effect Effects 0.000 description 1
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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
- G01C21/20—Instruments for performing navigational calculations
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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
- G01C21/005—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 with correlation of navigation data from several sources, e.g. map or contour matching
Abstract
The invention relates to a diagram building method based on a wharf stone pier, comprising the following steps of 1, initializing a stone pier map M and a factor graph G; step 2, calculating the pose of the current vehicle; step 3, acquiring laser radar observation data and extracting stone pier data; step 4, corresponding each stone pier data to a stone pier map M, and establishing data association; step 5, adding related factors in the factor graph G according to the vehicle pose estimation value and each stone pier position value; step 6, carrying out nonlinear optimization solution on the factor graph G to obtain the positions of all the stone piers, and updating a stone pier map M; 7, repeating the steps 3-6 after new laser radar observation data exist; if not, ending the flow; and 8, after the flow is finished, the final stone pier map M is the result. The invention uses a factor graph to carry out optimization solution, and the factors are divided into two types, namely, estimation of the pose of the vehicle is used as a prior pose factor of the vehicle, and data obtained by observation and extraction of the stone mounds is used as an observation position factor of the stone mounds.
Description
Technical Field
The invention relates to the technical field of automatic driving, in particular to a method, a device, equipment and a medium for constructing a diagram based on a pier stone pier.
Background
With the development of unmanned technology, automated dock transport is becoming possible. During transportation, higher requirements are put on the positioning technology of the vehicle. The conventional solution is a GPS (global positioning system) based solution, which directly acquires positioning information. In addition, there are existing map-based positioning schemes, which typically use vision and laser sensors to pre-map the field and then use existing maps and real-time observations for position estimation during operation.
GPS-based solutions require good communication with satellites, and in some building shelters, the positioning results are significantly affected. In addition, the positioning accuracy of the current civil GPS is generally in the meter level, and the high-accuracy positioning requirement cannot be met. In the positioning scheme based on the existing map, the accuracy and stability of the laser sensor are superior to those of the visual sensor, so that the laser sensor is the current mainstream scheme. However, the calculation is also complicated and the real-time performance is low. Especially for multiline lidar, the computation is more time consuming because of the large amount of data.
Disclosure of Invention
The invention aims to provide a wharf stone pier-based mapping method, a wharf stone pier-based mapping device, equipment and a medium, which can map the wharf stone pier efficiently in real time so as to facilitate subsequent navigation control.
In order to achieve the purpose, the invention provides the following technical scheme:
a construction method based on wharf stone piers is characterized by comprising the steps of 1, initializing a stone pier map M and a factor graph G; step 2, calculating the pose of the current vehicle; step 3, acquiring laser radar observation data and extracting stone pier data; step 4, corresponding each stone pier data to a stone pier map M, and establishing data association; step 5, adding related factors into the factor graph G according to the estimated value of the vehicle pose and the position value of each stone pier; step 6, carrying out nonlinear optimization solution on the factor graph G to obtain the position of each stone pillar, and updating the stone pillar map M; 7, after new laser radar observation data exist, repeatedly executing the steps 3-6; if not, ending the flow; and 8, after the flow is finished, the final stone pier map M is the required result.
The invention further sets that in the initial state, the stone pier map M is empty, and the factor map G is empty.
The invention is further arranged that when the pose of the current vehicle is calculated, the pose of the vehicle under the global map is calculated to be R at the time t according to the GPS and the IMU data of the vehicle t 。
The invention is further provided with a device which is provided with a plurality of guide rails, the position of each stone pier is S = { S = { (S) } 1 ，s 2 ，...，s k In which the position of the stone mounds is determined by the vehicle coordinate system.
The invention is further configured such that for each pier s i If a pier M within H meters of the pier map M is found j Then, it is called si and m j Data association occurs. If not found, inserting si into the stone pier map M, and setting the newly inserted stone pier as M u Then call s i And m u A data association is generated.
The invention further provides that, when adding relevant factors in the factor graph G, the factor graph is inserted with prior factor X = (X) t ，R t ) And a set of observation factors associated with the stone pillar: l = { (X) t ，L U(i) ，S i ) I =1,2,3,. So, k }, where U (i) denotes M and s i The data association stone pier number occurs.
The invention also provides a device for constructing the image based on the pier stone pier, which comprises:
the mapping module initializes a stone pier map M and a factor map G, updates the stone pier map M and forms a final stone pier map;
the calculation module is used for calculating the pose of the current vehicle according to the GPS and the IMU data of the vehicle and calculating the pose of the vehicle under the global map to be R t ；
The laser radar observation module is used for acquiring observation data;
the data extraction module is used for acquiring observation data in the laser radar observation module, extracting stone pier data and combining the observation data with the stone pier dataThe position of each stone pier is marked as S = { S = } 1 ,s 2 ,...,s k }；
The data association module is used for corresponding each stone pier data to a stone pier map M and establishing data association; the factor adding module is used for adding relevant factors in a factor graph G according to the estimated value of the vehicle pose and the position value of each stone pier;
a data optimization module; and carrying out nonlinear optimization solution on the factor graph G to obtain the position of each stone pillar, and updating the stone pillar map M.
The present invention also provides an electronic device, comprising: a processor, and a memory communicatively coupled to the processor; the memory stores computer execution instructions; the processor executes computer-executable instructions stored by the memory to implement a mapping method.
The invention also provides a computer-readable storage medium, which is characterized in that the computer-readable storage medium stores computer-executable instructions, and when the instructions are executed, the instructions cause a computer to perform the mapping method.
The invention has the beneficial effects that: the algorithm uses a factor graph to carry out optimization solution, wherein the factors are divided into two types, one type is that the pose estimation of the vehicle is used as a prior pose factor of the vehicle, and the other type is that data obtained by observing and extracting the stone pier is used as an observation position factor of the stone pier, and then the factor graph is optimized and solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a flow chart of an embodiment of the present invention.
FIG. 2 is an example of the structure of the factor graph of the present invention.
Detailed Description
Embodiments of the present application will be described in detail with reference to the drawings and examples, so that how to implement technical means to solve technical problems and achieve technical effects of the present application can be fully understood and implemented.
And identifying the position of each stone pier in each frame of laser observation by deep learning, and then integrating the stone pier position data of all the laser frames to establish a stone pier map of the whole wharf.
A mound map M is maintained throughout the process, which records the position of each mound under the global map. In addition, we also maintain a factor graph G, specifically a nonlinear factor graph instance of the gtsam library, to solve. The overall steps are as follows, and the flowchart can refer to fig. 1:
1. at the initial moment, the stone pier map M is empty, and the factor graph G is empty.
2. And calculating the pose of the current vehicle according to data such as the GPS and the IMU of the vehicle. We note as: at the moment t, the pose of the vehicle under the global map is calculated to be R t 。
3. And acquiring observation data of the laser radar, and extracting data of each stone pillar from the observation data of the radar. We note as: the position of each stone pillar is s = { s = { s 1 ，s 2 ，...，s k -wherein the position of the stone mounds is relative to the vehicle coordinate system.
4. And corresponding each stone pier data to a stone pier map M, and establishing data association. The method comprises the following specific steps: for each stone pier s i If a stone pillar M within H meters of the stone pillar map M is found j Then is called s i And m j Data association occurs. If not found, then s is i Inserting into the stone pier map M, and setting the newly inserted stone pier as M u Then is called s i And m u A data association is generated.
5. And adding relevant factors in the factor graph G according to the presumed value of the vehicle pose in the step 2 and the position value of each stone pillar in the step 3. The method comprises the following specific steps: we insert the prior factor X = (X) on the factor graph t ，R t ) And a set of observation factors associated with the stone pillar: l = { (X) t ，L U(i) ，s i ) I =1,2, 3.., k }, where U (i) represents M and s i The data association stone pier number occurs.
6. And carrying out nonlinear optimization solution on the factor graph G to obtain the position of each stone pier so as to update the stone pier map M.
7. And after new laser observation data exist, repeating the steps of 3-6, otherwise, ending the process.
8. And after the flow is finished, the final stone pier map M is the required result.
The invention also provides a device for constructing the image based on the pier stone pier, which comprises:
the mapping module initializes a stone pier map M and a factor graph G, updates the stone pier map M and forms a final stone pier map;
the calculation module is used for calculating the pose of the current vehicle according to the GPS and the IMU data of the vehicle and calculating that the pose of the vehicle under the global map is R t ；
The laser radar observation module is used for acquiring observation data;
the data extraction module is used for acquiring observation data in the laser radar observation module, extracting stone pier data and recording the position of each stone pier as S = { S = 1 ，s 2 ，...，s k }；
The data association module is used for corresponding each stone pier data to the stone pier map M and establishing data association; the factor adding module is used for adding relevant factors in a factor graph G according to the estimated value of the vehicle pose and the position value of each stone pier;
a data optimization module; and carrying out nonlinear optimization solution on the factor graph G to obtain the position of each stone pier so as to update the stone pier map M.
The present invention also provides an electronic device, comprising: a processor, and a memory communicatively coupled to the processor; the memory stores computer execution instructions; the processor executes computer-executable instructions stored by the memory to implement a mapping method.
The invention also provides a computer-readable storage medium, which stores computer-executable instructions, and when the instructions are executed, the computer-readable storage medium causes the mapping method to be executed by a computer.
The invention uses a factor graph to carry out optimization solution, wherein the factors are divided into two types, one type is the estimation of the pose of the vehicle as the prior pose factor of the vehicle, and the other type is the data obtained by observing and extracting the stone pier as the observation position factor of the stone pier. Then, optimizing and solving the factor graph, wherein the current common library of the factor graph is gtsam, and certain optimization libraries such as ceres can also be used for autonomous realization; when data management is performed, the position is used as a judgment standard, and other schemes such as triangle matching and the like can also be used. Identifying the stone mounds is not limited to some deep learning algorithm.
As used in the specification and in the claims, certain terms are used to refer to particular components. As one skilled in the art will appreciate, manufacturers may refer to a component by different names. This specification and claims do not intend to distinguish between components that differ in name but not function. In the following description and in the claims, the terms "include" and "comprise" are used in an open-ended fashion, and thus should be interpreted to mean "include, but not limited to. "substantially" means within an acceptable error range, that a person skilled in the art can solve the technical problem within a certain error range to substantially achieve the technical effect.
It is noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a good or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such good or system. Without further limitation, an element defined by the phrases "comprising one of \8230;" does not exclude the presence of additional like elements in an article or system comprising the element.
The foregoing description shows and describes several preferred embodiments of the invention, but as aforementioned, it is to be understood that the invention is not limited to the forms disclosed herein, but is not to be construed as excluding other embodiments and is capable of use in various other combinations, modifications, and environments and is capable of changes within the scope of the inventive concept as expressed herein, commensurate with the above teachings, or the skill or knowledge of the relevant art. And that modifications and variations may be effected by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (9)
1. A construction method based on wharf stone piers is characterized by comprising the steps of 1, initializing a stone pier map M and a factor graph G; step 2, calculating the pose of the current vehicle; step 3, acquiring laser radar observation data and extracting stone pier data; step 4, corresponding each stone pier data to a stone pier map M, and establishing data association; step 5, adding related factors into the factor graph G according to the estimated value of the vehicle pose and the position value of each stone pier; step 6, carrying out nonlinear optimization solution on the factor graph G to obtain the position of each stone pillar, and updating the stone pillar map M; 7, after new laser radar observation data exist, repeatedly executing the steps 3-6; if not, ending the flow; and 8, after the flow is finished, the final stone pier map M is the result.
2. The pier-based mapping method of claim 1, wherein in an initial state, a pier map M is empty, and a factor map G is empty.
3. The pier-based mapping method of claim 2, wherein the pose of the current vehicle is estimated according to GPS and IMU data of the vehicle, and at time t, the pose of the vehicle under the global map is estimated to be R t 。
4. The dock pier-based mapping method of claim 3, wherein the position of each pier is S = { S = 1 ,s 2 ,...,s k And (6) determining the positions of the stone piers through a vehicle coordinate system.
5. The dock pier-based construction method of claim 4, wherein the method is characterized in thatCharacterised by, for each stone pillar s i If a stone pillar M within H meters of the stone pillar map M is found j Then call s i And m j Data association occurs. If not found, then s is i Inserting into the stone pier map M, and setting the newly inserted stone pier as M u Then call s i And m u A data association is generated.
6. The pier-based mapping method of claim 5, wherein when a relevant factor is added to the factor graph G, the factor graph is inserted with a priori factor X = (X) t ，R t ) And a set of observation factors associated with the stone pillar: l = { (X) t ，L U(i) ，s i ) I =1,2,3, \8230;, k }, where U (i) denotes M and s i The data association stone pier number occurs.
7. A build picture device based on pier stone pillar, its characterized in that includes:
the mapping module initializes a stone pier map M and a factor map G, updates the stone pier map M and forms a final stone pier map;
the calculation module is used for calculating the pose of the current vehicle according to the GPS and the IMU data of the vehicle and calculating the pose of the vehicle under the global map to be R t ；
The laser radar observation module is used for acquiring observation data;
the data extraction module is used for acquiring observation data in the laser radar observation module, extracting stone pier data and recording the position of each stone pier as S = { S = 1 ,s 2 ,...,s k }；
The data association module is used for corresponding each stone pier data to the stone pier map M and establishing data association;
the factor adding module is used for adding relevant factors in a factor graph G according to the estimated value of the vehicle pose and the position value of each stone pier;
a data optimization module; and carrying out nonlinear optimization solution on the factor graph G to obtain the position of each stone pier so as to update the stone pier map M.
8. An electronic device, comprising: a processor, and a memory communicatively coupled to the processor; the memory stores computer-executable instructions; the processor executes computer-executable instructions stored by the memory to implement the mapping method of any of claims 1-6.
9. A computer-readable storage medium having computer-executable instructions stored therein that, when executed, cause a computer to perform the mapping method of any one of claims 1-6.
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