CN113238557B - Method for identifying and recovering abnormal drawing, computer readable storage medium and mobile robot - Google Patents
Method for identifying and recovering abnormal drawing, computer readable storage medium and mobile robot Download PDFInfo
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- CN113238557B CN113238557B CN202110531777.0A CN202110531777A CN113238557B CN 113238557 B CN113238557 B CN 113238557B CN 202110531777 A CN202110531777 A CN 202110531777A CN 113238557 B CN113238557 B CN 113238557B
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- 238000000034 method Methods 0.000 title claims abstract description 52
- 230000002159 abnormal effect Effects 0.000 title claims abstract description 20
- 238000013507 mapping Methods 0.000 claims abstract description 33
- 230000005856 abnormality Effects 0.000 claims abstract description 31
- 238000010276 construction Methods 0.000 claims abstract description 19
- 238000011084 recovery Methods 0.000 claims abstract description 4
- 238000004140 cleaning Methods 0.000 claims description 18
- 238000004590 computer program Methods 0.000 claims description 5
- 238000012545 processing Methods 0.000 claims description 3
- 206010033799 Paralysis Diseases 0.000 abstract description 9
- 230000000875 corresponding effect Effects 0.000 description 6
- 238000010408 sweeping Methods 0.000 description 4
- 230000000149 penetrating effect Effects 0.000 description 2
- 230000000739 chaotic effect Effects 0.000 description 1
- 230000002596 correlated effect Effects 0.000 description 1
- 238000012217 deletion Methods 0.000 description 1
- 230000037430 deletion Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0238—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors
- G05D1/024—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors in combination with a laser
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0221—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving a learning process
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0225—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving docking at a fixed facility, e.g. base station or loading bay
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- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Aviation & Aerospace Engineering (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Optics & Photonics (AREA)
- Electromagnetism (AREA)
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
Abstract
The invention discloses a method for identifying and recovering a mapping abnormality, a computer readable storage medium and a mobile robot, wherein the method comprises the following steps: step S1, a mobile robot starts to work and performs repositioning, then a map for repositioning is set as a first map, in the working process, a global map is built in the mobile robot immediately, and after the working is finished, the global map is set as a second map; step S2, based on the comparison of the first map and the second map, the mobile robot judges whether the map construction abnormality occurs, if not, the second map is stored, and if so, the step S3 is entered; and S3, the mobile robot judges whether the first map is a true map, if so, the first map is saved so as to realize recovery of abnormal map construction. The method can effectively identify the map construction abnormality, and can provide a means for recovering the map after the abnormality is found, so as to avoid the functional paralysis of the robot and improve the user experience.
Description
Technical Field
The invention relates to the field of mobile robots, in particular to a method for identifying and recovering abnormal drawing, a computer readable storage medium and a mobile robot.
Background
In the actual use process of the sweeping robot, the drawing is abnormal due to repositioning errors or matching errors, so that the robot runs in a chaotic manner, the phenomena of missing sweeping, virtual wall penetrating or cleaning function paralysis and the like are caused, and the on-off state cannot be recovered to be normal. Reducing repositioning errors or matching errors can reduce the occurrence of mapping anomalies, but cannot recover the correct map after the mapping anomalies occur.
In the disclosure technology of the patent number CN111426312a, a method for updating a positioning map is provided, and the method updates the global map by comparing the difference between a first sub-map acquired in the running process of the robot and a second sub-map at a corresponding position of the global map. The method only can improve the efficiency of updating the map, can not identify whether the map is abnormal or not, and can not recover the map.
Disclosure of Invention
In order to solve the problems, the invention provides a method for identifying and recovering a mapping abnormality, a computer-readable storage medium and a mobile robot, which can effectively identify the mapping abnormality and provide a means for recovering a map after the abnormality is found. The specific technical scheme of the invention is as follows:
A method for identifying and recovering a mapping anomaly, the method comprising: step S1, a mobile robot starts to work and performs repositioning, then a map for repositioning is set as a first map, in the working process, a global map is built in the mobile robot immediately, and after the working is finished, the global map is set as a second map; step S2, based on the comparison of the first map and the second map, the mobile robot judges whether the map construction abnormality occurs, if not, the second map is stored, and if so, the step S3 is entered; and S3, the mobile robot judges whether the first map is a true map, if so, the first map is saved so as to realize recovery of abnormal map construction. Compared with the prior art, the method can effectively identify the abnormal mapping, and can provide a means for recovering the map after the abnormality is found, so that the functional paralysis of the robot is avoided, and the user experience is improved.
Further, in the step S1, the map used for repositioning by the mobile robot is derived from a map saved after the last cleaning by the mobile robot or a map saved after setting a virtual wall.
Further, in the step S2, the method for determining whether the mapping abnormality occurs by the mobile robot based on the comparison between the first map and the second map includes: step S21, the mobile robot makes a difference between the first map and the second map to obtain a third map; step S22, the mobile robot identifies an obstacle line segment in the third map, then calculates the area of the non-obstacle area of the grid which is located at the corresponding position in the first map and occupied by the obstacle line segment, if the area is smaller than the preset area, no map construction abnormality occurs, otherwise, the map construction abnormality occurs. The logic is simple, and the operand is small.
Further, in the step S21, the method for obtaining the third map by the mobile robot making the difference between the first map and the second map includes: the mobile robot carries out binarization processing and opening operation on the first map and the second map, finds out continuous blocks in the first map and deletes continuous blocks smaller than a preset area, then subtracts the pixel value of the corresponding position on the second map from each pixel value on the first map, and finally carries out opening operation on the subtracted map again and deletes continuous blocks smaller than the preset area to obtain a third map; wherein the consecutive blocks are constituted by a grid of obstacles. Performing an open operation and deleting smaller consecutive blocks can reduce errors in determining a mapping abnormality.
Further, in the step S22, the mobile robot identifies an obstacle line segment in the third map using a hough line identification algorithm. The anti-interference capability is strong, and the required line segment can be accurately extracted.
Further, in the step S3, the method for determining whether the first map is a true map by the mobile robot includes: the mobile robot detects that the first map is a true map after relevant setting is carried out based on the first map, wherein the relevant setting at least comprises any one of setting the first map directly to be the true map, setting the cleaning times based on the first map, setting virtual walls based on the first map, setting a cleaning area based on the first map, or setting a cleaning route based on the first map. According to the technical scheme, whether the first map is set in a correlated mode or not is used for judging the true map, and the reliability is high.
Further, the mobile robot sets the first map as a true map if a command for performing related setting based on the first map is received during operation.
Further, the step S3 further includes: when the first map is not a true map, the mobile robot deletes the first map and the second map. When the mapping abnormality occurs and no true map exists, the first map and the second map are deleted, so that the influence on subsequent work can be avoided.
A computer readable storage medium for storing computer program code which when executed performs the steps of the method for identifying and recovering a mapping anomaly. Compared with the prior art, the computer readable storage medium can enable the mobile robot to effectively identify the mapping abnormality, and provide a means for recovering the map after the abnormality is found, so that the functional paralysis of the robot is avoided, and the user experience is improved.
A mobile robot is provided with a sensor for scanning the environment on the surface of the body of the mobile robot, and the sensor is used for executing the method for identifying and recovering the mapping abnormality. Compared with the prior art, the mobile robot can effectively identify the abnormal mapping, and can provide a means for recovering the map after the abnormal mapping is found, so that the functional paralysis is avoided, and the user experience is improved.
Drawings
FIG. 1 is a flowchart of a method for identifying and recovering a mapping anomaly according to an embodiment of the present invention.
Detailed Description
The following describes the technical solution in the embodiment of the present invention in detail with reference to the drawings in the embodiment of the present invention. It should be understood that the following detailed description is merely illustrative of the invention, and is not intended to limit the invention.
In the actual use process of the existing sweeping robot, the phenomenon of missing sweeping, virtual wall penetrating and the like is caused by disordered construction caused by repositioning errors or matching errors. The reason for this is that most of the functions of robots are very highly dependent on the map. For users using the virtual wall, the influence caused by abnormal drawing is that the virtual wall is not matched with the actual one, the cleaning function is paralyzed, and the on-off operation cannot be recovered to be normal. For users who do not use virtual walls, the drawing abnormality brings about paralysis of the cleaning function, and the startup and shutdown cannot be recovered to be normal.
Therefore, an embodiment of the present invention provides a method for identifying and recovering a mapping exception, where specific implementation steps are shown in fig. 1, including:
Step S1, the mobile robot starts working and performs repositioning, then a map for repositioning is set as a first map, in the working process, a global map is built in the mobile robot immediately, and after the working is finished, the global map is set as a second map.
The map used for repositioning by the mobile robot is derived from a map stored after the last cleaning by the mobile robot or a map stored after the virtual wall is set. If there is no saved map, the mobile robot cannot reposition and needs to execute the first map building and then start to execute the step S1. If the mobile robot fails to reposition, the mobile robot re-builds the map and then starts to execute step S1. In the embodiment of the invention, all the maps are probability grid maps, the grid resolution is 5cm, and the probability value range is 0-255, wherein 0 represents 100% of the probability of no obstacle, and 255 represents 100% of the probability of obstacle.
In the process of executing step S1, when the mobile robot is successfully relocated, the map for relocation is set as the first map, and then the operation is started. In the working process, the mobile robot uses the assembled sensors, such as a visual sensor, a laser sensor or an inertial sensor, and the like to perform instant mapping, so as to construct a global map and set the global map as a second map for subsequent comparison.
Step S2, based on the comparison of the first map and the second map, the mobile robot judges whether the map construction abnormality occurs, if not, the second map is stored, and if so, the step S3 is entered.
In the process of executing the step S2, the method for judging whether the mapping abnormality occurs by the mobile robot based on the comparison of the first map and the second map includes: step S21, the mobile robot makes a difference between the first map and the second map to obtain a third map. The mobile robot makes the difference between the first map and the second map, and the method for obtaining the third map comprises the following steps: the mobile robot carries out binarization processing and opening operation on the first map and the second map, finds out continuous blocks in the first map and deletes continuous blocks smaller than a preset area, then subtracts the pixel value of the corresponding position on the second map from each pixel value on the first map, and finally carries out opening operation on the subtracted map again and deletes continuous blocks smaller than the preset area to obtain a third map; wherein the consecutive blocks are constituted by a grid of obstacles. Performing an open operation and deleting smaller consecutive blocks can reduce errors in determining a mapping abnormality. Specifically, in the binarization process, the probability of all grids with the probability larger than 150 in the first map and the second map is set to 255, and the probability smaller than or equal to 150 is set to 0, so that the binarization operation can extract the obstacle; the preset area is preferably 0.1 square meter in the process of deleting the continuous blocks; in the process of subtracting the two maps, if the difference is not 0, the difference is set to 255.
Step S22, the mobile robot identifies an obstacle line segment in the third map, then calculates the area of the non-obstacle area of the grid which is located at the corresponding position in the first map and occupied by the obstacle line segment, and if the area is smaller than the preset area, no map construction abnormality occurs. Specifically, if the third map obstacle grid (i.e., a grid having a value of 255) falls below 0.5 square meters in total area of the first map non-obstacle grid (i.e., a grid having a value of less than 100), it is considered that no map construction abnormality has occurred. At this point, a second map of the mobile robot build in time is saved, which can be used for the next repositioning. Otherwise, if the area is greater than or equal to 0.5 square meter, the fact that a large difference exists between the first map and the second map indicates that the mobile robot is considered to have abnormal map construction in the last map construction or the current map construction, and at the moment, further judgment is needed. Preferably, the mobile robot identifies the obstacle line segment in the third map using a hough straight line identification algorithm.
And S3, the mobile robot judges whether the first map is a true map, if so, the first map is saved so as to realize recovery of abnormal map construction. Wherein, the true map refers to a map conforming to an actual environment.
In the process of executing step S3, the method for determining whether the first map is a true map by the mobile robot includes: and judging the first map to be a true map when the mobile robot detects that the first map is subjected to relevant setting, wherein the relevant setting at least comprises any one of setting the first map to be the true map directly, setting the cleaning times based on the first map, setting virtual walls based on the first map, setting a cleaning area based on the first map and setting a cleaning route based on the first map. If a map is used to set various parameters, it is indicated that the map has a high probability of conforming to the actual environment, otherwise the map is not used. Therefore, if the mobile robot receives a command to perform related setting based on the first map during operation, the first map is set as a true map. Of course, the command may be a command to directly set the first map as a true map, in addition to the setting parameter.
Optionally, when the mobile robot determines that the first map is a true map, a restoration map flag is set for the first map, otherwise, a deletion map flag is set, and then a corresponding operation is performed according to the flag: if the map mark is recovered, the mobile robot stores the first map, deletes the second map, and then returns to the original point or returns to the charging seat by using the first map; if the map mark is deleted, the mobile robot tries to return to the original point or to the charging seat, but whether the mobile robot returns successfully or not, the first map and the second map are deleted finally so as not to cause unnecessary influence on the next work.
It is noted that the present embodiment also provides an intelligent terminal matched with the mobile robot. The intelligent terminal is used for setting various parameters on a map in the mobile robot, namely, performing relevant setting, wherein the relevant setting at least comprises any one of setting a first map directly as a true map, setting cleaning times based on the first map, setting a virtual wall based on the first map, setting a cleaning area based on the first map, and setting a cleaning route based on the first map.
The embodiment of the invention provides a computer readable storage medium which is used for storing computer program codes and can be arranged in the mobile robot, and the computer program codes realize the steps of the method for identifying and recovering the mapping abnormality when being executed. Compared with the prior art, the computer readable storage medium can enable the mobile robot to effectively identify the mapping abnormality, and provide a means for recovering the map after the abnormality is found, so that the functional paralysis of the robot is avoided, and the user experience is improved.
Embodiments of the present invention provide a mobile robot whose body surface is equipped with a sensor for scanning an environment, such as a vision sensor, a laser sensor, or an inertial sensor, which is commonly used for a device for constructing a map. Compared with the prior art, the mobile robot can effectively identify the abnormal mapping, and can provide a means for recovering the map after the abnormal mapping is found, so that the functional paralysis is avoided, and the user experience is improved.
It is obvious that the above-mentioned embodiments are only some embodiments of the present invention, but not all embodiments, and that the technical solutions of the embodiments may be combined with each other. Furthermore, if terms such as "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. are used in the embodiments, the indicated orientation or positional relationship is based on that shown in the drawings, only for convenience in describing the present invention and simplifying the description, and does not indicate or imply that the indicated apparatus or element must have a specific orientation or be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention. If the terms "first," "second," "third," etc. are used in an embodiment to facilitate distinguishing between related features, they are not to be construed as indicating or implying a relative importance, order, or number of technical features.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the method embodiments described above may be performed by hardware associated with program instructions. These programs may be stored in a computer readable storage medium (such as ROM, RAM, magnetic or optical disk, etc. various media that can store program codes). The program, when executed, performs steps including the method embodiments described above.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.
Claims (9)
1. The method for identifying and recovering the mapping abnormality is characterized by comprising the following steps:
Step S1, a mobile robot starts to work and performs repositioning, then a map for repositioning is set as a first map, in the working process, a global map is built in the mobile robot immediately, and after the working is finished, the global map is set as a second map;
Step S2, based on the comparison of the first map and the second map, the mobile robot judges whether the map construction abnormality occurs, if not, the second map is stored, and if so, the step S3 is entered;
step S3, the mobile robot judges whether the first map is a true map or not, if so, the first map is saved so as to realize recovery of abnormal map construction;
The method for judging whether the mapping abnormality occurs by the mobile robot based on the comparison of the first map and the second map comprises the following steps:
step S21, the mobile robot makes a difference between the first map and the second map to obtain a third map;
Step S22, the mobile robot identifies an obstacle line segment in the third map, then calculates the area of the non-obstacle area of the grid which is located at the corresponding position in the first map and occupied by the obstacle line segment, if the area is smaller than the preset area, no map construction abnormality occurs, otherwise, the map construction abnormality occurs.
2. The method for identifying and recovering abnormal mapping according to claim 1, wherein in the step S1, the map for repositioning by the mobile robot is derived from a map saved after the last cleaning by the mobile robot or a map saved after the virtual wall is set.
3. The method for identifying and recovering abnormal mapping according to claim 1, wherein in the step S21, the mobile robot makes the difference between the first map and the second map to obtain the third map, the method comprising:
The mobile robot carries out binarization processing and opening operation on the first map and the second map, finds out continuous blocks in the first map and deletes continuous blocks smaller than a preset area, then subtracts the pixel value of the corresponding position on the second map from each pixel value on the first map, and finally carries out opening operation on the subtracted map again and deletes continuous blocks smaller than the preset area to obtain a third map; wherein the consecutive blocks are constituted by a grid of obstacles.
4. The method for identifying and recovering abnormal mapping according to claim 1, wherein in the step S22, the mobile robot uses hough line identification algorithm to identify the obstacle line segment in the third map.
5. The method for identifying and recovering abnormal mapping according to claim 1, wherein in the step S3, the method for determining whether the first map is a true map by the mobile robot includes:
the mobile robot detects that the relevant setting is performed based on the first map, the first map is a true map,
Wherein the related settings include at least any one of the first map being directly set as a true map, or the number of times of cleaning being set based on the first map, or the virtual wall being set based on the first map, or the cleaning area being set based on the first map, or the cleaning route being set based on the first map.
6. The method according to claim 1, wherein the mobile robot sets the first map as a true map if it receives a command for performing related setting based on the first map during operation.
7. The method for identifying and recovering a mapping anomaly according to claim 1, wherein the step S3 further comprises:
when the first map is not a true map, the mobile robot deletes the first map and the second map.
8. A computer readable storage medium storing computer program code, wherein the computer program code when executed performs the steps of the method for identifying and recovering a mapping anomaly of any one of claims 1 to 7.
9. A mobile robot, the body surface of which is equipped with a sensor for scanning the environment, characterized in that the computer-readable storage medium of claim 8 is provided inside the mobile robot for executing the method for identifying and recovering a mapping anomaly of any one of claims 1 to 7.
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