CN110824498A - Obstacle detection method, device and system - Google Patents
Obstacle detection method, device and system Download PDFInfo
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- CN110824498A CN110824498A CN201810891978.XA CN201810891978A CN110824498A CN 110824498 A CN110824498 A CN 110824498A CN 201810891978 A CN201810891978 A CN 201810891978A CN 110824498 A CN110824498 A CN 110824498A
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- 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
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/89—Lidar systems specially adapted for specific applications for mapping or imaging
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Abstract
The application discloses a method, a device and a system for detecting obstacles, and belongs to the field. The method comprises the following steps: in the running process of the mobile robot, emitting infrared light to the surrounding area of the area where the mobile robot is located; acquiring an image of the surrounding area; when the image contains a target pattern, first position information of an obstacle is obtained, the target pattern is a pattern formed in the image by infrared light reflected by a reflective mark, and the reflective mark is fixedly arranged on the surface of the obstacle. The invention effectively reduces the cost of obstacle detection. The invention is used for obstacle detection of the mobile robot.
Description
Technical Field
The present disclosure relates to the field of robots, and in particular, to a method, an apparatus, and a system for detecting an obstacle.
Background
In the running process of the mobile robot, obstacles existing in the running environment of the mobile robot are detected, and obstacle avoidance is carried out according to the detected obstacles, so that the method is an important measure for ensuring safe running of the mobile robot.
In the related art, when detecting an obstacle, laser light is generally emitted into a traveling environment of a mobile robot, the laser light reflected by the obstacle is received, and then position information of the obstacle is determined by the reflected laser light.
However, the price of a laser emitting apparatus for emitting laser light is generally high, resulting in high cost of the obstacle detection.
Disclosure of Invention
The application provides a method, a device and a system for detecting obstacles, which can solve the problem of higher cost of obstacle detection in the related technology. The technical scheme is as follows:
in a first aspect, there is provided an obstacle detection method, the method comprising:
in the running process of the mobile robot, emitting infrared light to the surrounding area of the area where the mobile robot is located;
acquiring an image of the surrounding area;
when the image contains a target pattern, first position information of an obstacle is obtained, the target pattern is a pattern formed in the image by infrared light reflected by a reflective mark, and the reflective mark is fixedly arranged on the surface of the obstacle.
Optionally, when the image includes a target pattern, acquiring first position information of an obstacle includes:
acquiring second position information of the target pattern in the image based on the image;
and acquiring the first position information based on the second position information.
Optionally, before the obtaining the first location information based on the second location information, the method further includes:
determining a conversion matrix based on the setting position of image acquisition equipment and the setting position of the reflective mark, wherein the image acquisition equipment is used for acquiring the image of the surrounding area, and the conversion matrix is used for carrying out coordinate conversion on a space coordinate system where the reflective mark is located and an image coordinate system where pixel points in the image are located;
the obtaining the first location information based on the second location information includes:
and acquiring the first position information based on the second position information and the conversion matrix.
Optionally, the obtaining second position information of the target pattern in the image based on the image includes:
detecting the pixel value of each pixel point in the image to determine that the target pattern exists in the image;
second position information of the target pattern in the image is acquired.
Optionally, the detecting the pixel value of each pixel point in the image to determine that the target pattern exists in the image includes:
and detecting the pixel value of each pixel point in the image through a connected domain detection algorithm so as to determine that the target pattern exists in the image.
Optionally, the obstacle comprises: a shelf in the warehouse.
In a second aspect, there is provided an obstacle detection apparatus, the apparatus comprising:
the transmitting module is used for transmitting infrared light to the surrounding area of the area where the mobile robot is located in the driving process of the mobile robot;
the acquisition module is used for acquiring the image of the surrounding area;
the first acquisition module is used for acquiring first position information of an obstacle when the image contains a target pattern, wherein the target pattern is a pattern formed in the image by infrared light reflected by a reflective mark, and the reflective mark is fixedly arranged on the surface of the obstacle.
Optionally, the first obtaining module is further configured to:
acquiring second position information of the target pattern in the image based on the image;
and acquiring the first position information based on the second position information.
Optionally, the apparatus further comprises:
a second obtaining module to: determining a conversion matrix based on the setting position of image acquisition equipment and the setting position of the reflective mark, wherein the image acquisition equipment is used for acquiring the image of the surrounding area, and the conversion matrix is used for carrying out coordinate conversion on a space coordinate system where the reflective mark is located and an image coordinate system where pixel points in the image are located;
the first obtaining module is further configured to:
and acquiring the first position information based on the second position information and the conversion matrix. .
Optionally, the first obtaining module is further configured to:
detecting the pixel value of each pixel point in the image to determine that the target pattern exists in the image;
second position information of the target pattern in the image is acquired.
Optionally, the first obtaining module is further configured to:
and detecting the pixel value of each pixel point in the image through a connected domain detection algorithm so as to determine that the target pattern exists in the image.
Optionally, the obstacle comprises: a shelf in the warehouse.
In a third aspect, there is provided an obstacle detection system, the system comprising: the mobile robot comprises a mobile robot and a reflective mark fixedly arranged on the surface of an obstacle, wherein the reflective mark is used for reflecting infrared light emitted to the reflective mark, and the mobile robot is provided with any obstacle detection device in the second aspect.
Optionally, the reflective mark is fixedly arranged at the intersection position of the obstacle and the traveling road surface of the mobile robot.
Optionally, the obstacle detection system is deployed in a warehouse, and the obstacle includes: a shelf in the warehouse.
In a fourth aspect, there is provided a terminal comprising a processor and a memory,
wherein the content of the first and second substances,
the memory is used for storing a computer program;
the processor is configured to execute the program stored in the memory to implement the obstacle detection method according to any one of the first aspect.
In a fifth aspect, a storage medium is provided, in which a computer program is stored, and the computer program realizes the obstacle detection method according to any one of the first aspect when executed by a processor.
The beneficial effect that technical scheme that this application provided brought is:
according to the obstacle detection method, the obstacle detection device and the obstacle detection system, the infrared light is emitted to the surrounding area of the area where the mobile robot is located, the position information of the obstacle is obtained according to the pattern formed by reflecting the infrared light included in the collected image, and therefore the obstacle detection is achieved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic structural diagram of an obstacle detection system according to an embodiment of the present invention;
fig. 2 is a flowchart of an obstacle detection method according to an embodiment of the present invention;
fig. 3 is a flowchart of another obstacle detection method according to an embodiment of the present invention;
FIG. 4 is a flowchart of a method for obtaining second position information of a target pattern in an image according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a target pattern in an image according to an embodiment of the present invention;
fig. 6 is a schematic diagram of a correspondence relationship between a point in an image and a point in a space where a robot is located according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of an obstacle detection device according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of another obstacle detection device according to an embodiment of the present invention.
Detailed Description
To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings.
With the rapid development of science and technology, mobile robots are more and more widely used, for example: storage robots and parking robots. During the operation of the mobile robot, the mobile robot can load the goods shelf to drive the object to be moved (for example, goods in a warehouse or a vehicle to be parked) placed on the goods shelf to move. In addition, in the driving process of the mobile robot, the mobile robot can detect obstacles existing in the driving environment of the mobile robot and avoid the obstacles according to the detected obstacles so as to ensure that the mobile robot can safely drive.
In the related art, the process of detecting an obstacle by a mobile robot is as follows: the method comprises the steps of adopting a laser emitting device arranged on a mobile robot, emitting laser to a surrounding area of an area where the mobile robot is located, collecting an image of the surrounding area through an image collecting device arranged on the mobile robot, and determining the position of an obstacle reflecting the laser by the mobile robot according to the position of the pattern in the image when the collected image comprises the pattern formed by reflecting the laser so as to realize the detection of the obstacle. However, since the price of the laser emitting device is generally high, the cost of the obstacle detection is high.
To this end, an embodiment of the present invention provides an obstacle detection system, as shown in fig. 1, which may include: the robot S is moved. The obstacle detection system may be deployed in a parking lot, a warehouse, or other scenes capable of realizing automatic operation by the mobile robot S, and the obstacles to be detected may include: shelves in parking lots or warehouses, etc.
And, the mobile robot S may include: the mobile robot comprises a mobile robot body, and an infrared light-emitting device and an image acquisition device which are fixedly arranged on the mobile robot body. The infrared light emitting device is used to emit infrared light to the surrounding area of the area where the mobile robot S is located. The image acquisition device is used for acquiring an image of the surrounding area. The mobile robot body is used for loading the goods shelf and driving objects on the goods shelf to move, and the mobile robot body can also perform image processing and image analysis according to images collected by the image collecting equipment so as to obtain the position of the barrier W according to the images.
According to the optical characteristics of infrared light and the principle of light reflection, when infrared light is emitted to the surface of a common material, the infrared light is scattered, and the infrared light cannot be reflected, so that the obstacle detection system may further include: and a reflective mark F fixedly arranged on the surface of the obstacle W. The reflective mark F is used to reflect the infrared light emitted to the reflective mark F. Due to the arrangement of the reflective mark F, when the reflected infrared light is detected, the position of the reflective mark F which reflects the infrared light can be determined to have an obstacle, and the position of the reflective mark F is the position of the obstacle W, so that the obstacle W can be detected.
Alternatively, the reflective mark F may be a film layer made of a material with a strong light-reflecting ability and coated on the surface of the obstacle W. For example, when the mobile robot S is used in a warehouse, the reflective mark F may be a film layer of retroreflective material applied to a shelf on which goods are placed in the warehouse, or the reflective mark F may be a film layer of retroreflective material applied to a shoe cover worn by a worker in the warehouse.
Further, the reflective flag F may be fixedly disposed at an intersection position of the obstacle W and the traveling road surface of the mobile robot S. When the robot determines the position of the obstacle W, the position of the obstacle W can be obtained according to the corresponding relationship between the points in the plane of the driving road surface of the mobile robot S and the pixel points in the collected image, and when the reflective mark F is arranged at the intersection position of the driving road surface of the obstacle W and the mobile robot S, the reflective mark F has no height difference with the ground, and data conversion is not needed according to the height difference between the reflective mark F and the ground in comparison with the implementation mode that the height difference exists between the reflective mark F and the ground, so that the calculation process for obtaining the position of the obstacle W can be simplified.
As can be seen from the above, the obstacle detection system provided in the embodiment of the present invention can detect an obstacle by emitting infrared light to a surrounding area of an area where the mobile robot is located and acquiring position information of the obstacle according to the acquired image, and compared to the related art, there is no need to use a laser emitting device to emit laser to the surrounding area, and an infrared light emitting device for emitting infrared light is generally low in price, so that the obstacle detection system effectively reduces the cost of obstacle detection.
An embodiment of the present invention further provides an obstacle detection method, where the obstacle detection method may be applied to a mobile robot in the obstacle detection system shown in fig. 1, and as shown in fig. 2, the method may include:
Alternatively, an infrared light emitting device may be fixedly disposed on the mobile robot, and infrared light may be emitted to the surrounding area through the infrared light emitting device during the traveling of the mobile robot.
Optionally, an image capturing device may be fixedly disposed on the mobile robot, and during the driving process of the mobile robot, an image of the surrounding area may be captured by the image capturing device.
And 103, acquiring first position information of the obstacle when the target pattern is included in the image.
The target pattern is formed in an image by infrared light reflected by a reflective mark, the reflective mark is fixedly arranged on the surface of the obstacle, and the position of the obstacle can be reflected by the position of the reflective mark.
For example, the mobile robot may travel in a scene such as a parking lot or a warehouse where an automated job can be realized by the mobile robot S, and the obstacle may include: each shelf in scenes such as parking lots or warehouses can be fixedly provided with a reflective mark, and the reflective mark can be a film layer formed by a retroreflective material coated on the shelf, or the reflective mark can be a film layer formed by a retroreflective material coated on a shoe cover worn by a worker in the warehouse.
When infrared light irradiates the reflective mark, the reflective mark can reflect the infrared light, so that the acquired image can contain the target pattern, at the moment, the position of the reflective mark reflecting the infrared light can be determined to have an obstacle, and then the first position information of the obstacle can be determined according to the position information of the target pattern in the image.
In addition, the position of the obstacle is determined according to the pattern formed by the infrared light in the image, so that the shooting environment can be supplemented by the infrared light when the image of the surrounding area is collected, and compared with the related technology, the method does not need to provide visible light for the shooting environment for supplementing light, so that energy consumed when the visible light is provided for the shooting environment for supplementing light can be saved; on the other hand, when the mobile robot is applied to warehousing, because the warehouse usually has the articles needing to be stored in a dark place, when the visible light is not needed to be provided for the shooting environment for light supplement, the storage conditions of the articles can be ensured.
In summary, according to the obstacle detection method provided in the embodiment of the present invention, the infrared light is emitted to the surrounding area of the area where the mobile robot is located, and the position information of the obstacle is obtained according to the pattern formed by reflecting the infrared light included in the acquired image, so that the obstacle can be detected.
Fig. 3 is a flowchart of another obstacle detection method according to an embodiment of the present invention, where the obstacle detection method is applicable to a mobile robot in the obstacle detection system shown in fig. 1, and as shown in fig. 3, the method may include:
step 201, determining a transformation matrix based on the setting position of the image acquisition device and the setting position of the reflective sign.
Wherein, the image acquisition equipment is used for gathering the image of surrounding area, and this image acquisition equipment can set up on mobile robot. The image capturing device may be a Charge Coupled Device (CCD) camera or the like.
The transformation matrix is used for carrying out coordinate transformation on a space coordinate system where the reflective mark is located and an image coordinate system where pixel points in the image collected by the image collecting equipment are located. For example, the transformation matrix may be a homography matrix, and coordinate transformation may be performed on the spatial coordinate system and the image coordinate system through the homography matrix, so as to implement mapping between a point in a spatial plane and a pixel point in an image. That is, the homography matrix may determine the position information of the point in the spatial plane according to the position information of the point in the image, or may determine the position information of the point in the image according to the position information of the point in the spatial plane.
In general, the transformation matrix may be a3 × 3 matrix, and the coordinates a of a point in the image, the coordinates B of a point in space, and the transformation matrix P satisfy a mapping relationship: b ═ a × P. Accordingly, the implementation process of step 201 may include: after the image acquisition equipment is installed on the mobile robot, the image acquisition equipment is used for acquiring images of four preset markers arranged at different positions in the same space plane, and according to the setting positions of the preset markers and the positions of the preset markers in the images, and the mapping relation among the coordinates of points in the images, the coordinates of the points in the space and the conversion matrix, each element of the conversion matrix is solved, so that the conversion matrix corresponding to the points in the space plane and the pixel points in the images is obtained.
It should be noted that, for the same image acquisition device, the process of determining the transformation matrix may be understood as: and determining the corresponding relation between the position information of the pixel points in the image and the position information of the spatial plane internal points according to external parameters such as the installation position of the image acquisition equipment on the premise of defaulting the internal parameters. And when the positions of the planes for setting the preset markers are different when the conversion matrix is determined, the values of the elements in the determined conversion matrix are different. Therefore, in this step 201, the preset markers may be disposed in the disposition plane of the reflective markers, for example: all the reflective signs in the warehouse can be arranged at the intersection position (namely on the ground) of the corresponding barrier and the driving road surface of the mobile robot, at the moment, the preset signs can be also arranged on the ground, and the corresponding conversion matrix is determined.
Step 202, in the running process of the mobile robot, infrared light is emitted to the surrounding area of the area where the mobile robot is located.
Optionally, when the mobile robot travels in the target field, an infrared light emitting device fixedly disposed on the mobile robot body may be used to emit infrared light to a surrounding area of an area where the mobile robot is located. For example, when the mobile robot travels in a warehouse, the infrared light emitting device may be employed to emit infrared light to the front of the mobile robot.
Step 203, collecting images of surrounding areas.
The image capturing device may capture an image of the surrounding area in real time during the traveling of the mobile robot, or the image of the surrounding area may be captured periodically. For example, as a mobile robot travels in a warehouse, an image acquisition device may be employed to acquire images in an area in front of the mobile robot.
Optionally, the image capturing device may further be provided with an infrared filter, where the infrared filter is configured to filter a visible light component in the ambient light to reduce interference of the visible light component on the infrared light, so that the image captured by the image capturing device only includes a target pattern formed in the image by the infrared light reflected by the reflective marker as much as possible, and then the contrast of the target pattern in the image is improved, so as to improve accuracy of determining the position of the obstacle according to the target pattern.
In addition, when the image of the surrounding area is collected, the shooting environment can be supplemented with light through the infrared light, and compared with the related technology, the method does not need to provide visible light for the shooting environment for supplementing light, so that on one hand, energy consumed when the visible light is provided for the shooting environment for supplementing light can be saved; on the other hand, when the mobile robot is applied to warehousing, because the warehouse usually has the articles needing to be stored in a dark place, when the visible light is not needed to be provided for the shooting environment for light supplement, the storage conditions of the articles can be ensured.
And step 204, when the target pattern is contained in the image, acquiring second position information of the target pattern in the image based on the image.
Because the reflective mark is fixedly arranged on the surface of the obstacle, when the obstacle exists in the shooting range of the image acquisition equipment, the reflective mark on the surface of the obstacle can reflect the infrared light irradiated to the reflective mark, and when the image acquisition equipment acquires the image, the infrared light reflected by the reflective mark can form a target pattern in the image, namely the acquired image can contain the target pattern. When no obstacle exists in the shooting range of the image acquisition equipment, the target pattern is not contained in the image acquired by the image acquisition equipment. Therefore, when the obstacle detection is performed according to the image, if the image does not contain the target pattern, it can be determined that no obstacle exists in the shooting range of the image acquisition device, and at the moment, the mobile robot does not need to avoid the obstacle. If the image contains the target pattern, it can be determined that an obstacle exists in the shooting range of the image acquisition device, and at this time, the position of the obstacle needs to be determined, so that the mobile robot can avoid the obstacle according to the position of the obstacle.
Accordingly, referring to fig. 4, the implementation of step 204 may include:
Optionally, a connected domain detection algorithm may be adopted to detect the pixel value of each pixel point in the image. When a connected region satisfying a preset condition is detected in the image, it may be determined that a target pattern exists in the image. Because the pixel value of the pixel point corresponding to the target pattern is usually greater than the pixel values of other pixel points in the image except the target pattern, that is, the target pattern is represented as a bright spot in the image, the preset condition may be: and if the pixel value of the pixel point is larger than the preset threshold value, determining that the target pattern exists in the image when the pixel mean value of the pixel point in the communication area is larger than the preset threshold value.
The detection process of the connected domain detection algorithm is as follows: traversing pixel points in the image, marking the pixel points meeting the conditions in the traversing process, and determining an area formed by the pixel points with a communication relation as a communication area in all the marked pixel points. Wherein, the fact that the pixel points have the communication relation means that the pixel points are adjacent or indirectly adjacent. For example: referring to fig. 5, a pixel a1 is adjacent to a pixel a2, a pixel a2 is adjacent to a pixel A3, and a pixel a1 is not adjacent to a pixel A3, but a pixel a1 is indirectly adjacent to a pixel A3 through a pixel a2, and at this time, it can be said that a pixel a1, a pixel a2, and a pixel A3 have a communication relationship.
For example, please refer to fig. 5 again, each square in fig. 5 represents a pixel, the pixels with filling patterns in the square are marked pixels, among all the marked pixels, a pixel a1, a pixel a2, a pixel A3, a pixel a4, a pixel a5 and a pixel A6 have a connected relationship, and a pixel B has no connected relationship with other marked pixels, so that a region composed of the pixel a1, the pixel a2, the pixel A3, the pixel a4, the pixel a5 and the pixel A6 can be determined as a connected region, and it is determined that a target pattern exists in the image.
It should be noted that before detecting the pixel values of the pixel points in the image, the image may be subjected to image preprocessing, for example: and carrying out filtering processing and binarization processing on the image. By preprocessing the image, the interference in the image can be removed, correspondingly, the calculated amount in the detection process can be reduced, and the accuracy of the determined position of the obstacle can be improved when the position of the obstacle is determined according to the preprocessed image.
After the target pattern is determined to exist in the image, the position of the pixel point corresponding to the target pattern in the image can be obtained, and the position information of the pixel point corresponding to the target pattern in the image is determined as the second position information.
For example, please refer to fig. 5, the pixel points corresponding to the target pattern are: the image processing method comprises the following steps of A1, A2, A3, A4, A5 and A6, wherein the position information of the six pixels in the image is as follows: (3, 4), (3, 5), (3, 6), (4, 4), (4, 5) and (4, 6), the position information of the six pixel points in the image can be determined as the second position information. The position information (x, y) represents that the pixel point is positioned in the x-th row and the y-th column in the image.
Step 205, acquiring the first position information based on the second position information and the transformation matrix.
The transformation matrix may be the transformation matrix determined in step 201. Since the mapping relationship is satisfied between the coordinates a of the points in the image, the coordinates B of the points in space, and the transformation matrix P: in this step 205, the position information of the reflective marker in the space may be determined according to the second position information of the target pattern in the image and the mapping relationship. And because the reflective mark is fixedly arranged on the surface of the obstacle, and the position of the reflective mark is the position of the obstacle, the position information of the reflective mark can be determined as the first position information.
For example, referring to fig. 6, it is assumed that the second position information of the target pattern is represented by position information of a pixel a1, a pixel a2, a pixel A3, a pixel a4, a pixel a5, and a pixel a6, and the position information of the six pixels in the image is: (3, 4), (3, 5), (3, 6), (4, 4), (4, 5) and (4, 6), according to the position information of each pixel and the transformation matrix determined in step 201, the corresponding points of the six pixels in space can be determined to be point a11, point a12, point a13, point a14, point a15 and point a16, and the position information of the six pixels, that is, the positions defined by the six pixels can be determined to be the positions of the obstacles, so the position information of the six pixels can be determined to be the first position information.
In summary, according to the obstacle detection method provided in the embodiment of the present invention, the infrared light is emitted to the surrounding area of the area where the mobile robot is located, and the position information of the obstacle is obtained according to the pattern formed by reflecting the infrared light included in the acquired image, so that the obstacle can be detected.
It should be noted that, the sequence of the steps of the obstacle detection method provided in the embodiment of the present invention may be appropriately adjusted, and the steps may also be increased or decreased according to the circumstances, and any method that can be easily conceived by those skilled in the art within the technical scope of the present invention should be included in the protection scope of the present invention, and therefore, the details are not described again.
Fig. 7 is a schematic structural diagram of an obstacle detection apparatus according to an embodiment of the present invention, and as shown in fig. 7, the obstacle detection apparatus 700 may include:
the emitting module 701 is configured to emit infrared light to a surrounding area of an area where the mobile robot is located during a driving process of the mobile robot.
An acquisition module 702 is configured to acquire an image of a surrounding area.
The first obtaining module 703 is configured to obtain first position information of the obstacle when the image includes a target pattern, where the target pattern is a pattern formed in the image by infrared light reflected by a reflective marker, and the reflective marker is fixedly disposed on a surface of the obstacle.
In summary, according to the obstacle detection apparatus provided in the embodiment of the present invention, the emitting module emits the infrared light to the surrounding area of the area where the mobile robot is located, and the first obtaining module obtains the position information of the obstacle according to the pattern formed by reflecting the infrared light included in the collected image, so as to achieve the detection of the obstacle.
Optionally, the first obtaining module 703 is further configured to:
based on the image, second position information of the target pattern in the image is acquired.
Based on the second position information, first position information is acquired.
Optionally, as shown in fig. 8, the apparatus 700 may further include:
a second obtaining module 704, configured to: determining a conversion matrix based on the setting position of the image acquisition equipment and the setting position of the reflective mark, wherein the image acquisition equipment is used for acquiring images of surrounding areas, and the conversion matrix is used for carrying out coordinate conversion on a space coordinate system where the reflective mark is located and an image coordinate system where pixel points in the images are located;
the first obtaining module 703 is further configured to: and acquiring the first position information based on the second position information and the conversion matrix.
Optionally, the first obtaining module 703 is further configured to:
and detecting the pixel value of each pixel point in the image to determine that the target pattern exists in the image.
Second position information of the target pattern in the image is acquired.
Optionally, the first obtaining module 703 is further configured to: and detecting the pixel value of each pixel point in the image through a connected domain detection algorithm so as to determine that the target pattern exists in the image.
Optionally, the obstacle detection device provided by the embodiment of the invention may be deployed on a mobile robot. The obstacle may include: shelves in parking lots or warehouses, etc.
In summary, according to the obstacle detection apparatus provided in the embodiment of the present invention, the emitting module emits the infrared light to the surrounding area of the area where the mobile robot is located, and the first obtaining module obtains the position information of the obstacle according to the pattern formed by reflecting the infrared light included in the collected image, so as to detect the obstacle.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and modules may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
An embodiment of the present invention further provides a mobile robot, where the mobile robot may include: the obstacle detection device provided by the embodiment is provided. The mobile robot may be, for example, a parking robot or a warehousing robot.
Optionally, the mobile robot may further include: the mobile robot comprises a mobile robot body, and an infrared light-emitting device and an image acquisition device which are fixedly arranged on the mobile robot body.
Embodiments of the present invention also provide a terminal, which may be deployed on the mobile robot, and which may include a processor and a memory,
wherein the content of the first and second substances,
a memory for storing a computer program.
And a processor for executing the program stored in the memory to implement the obstacle detection method provided by the above embodiment.
Optionally, the processor may include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor may be implemented in at least one hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), and a PLA (Programmable Logic Array). The processor may also include a main processor and a coprocessor, where the main processor is a processor for Processing data in an awake state, and is also called a Central Processing Unit (CPU); a coprocessor is a low power processor for processing data in a standby state. In some embodiments, the processor may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content that the display screen needs to display. In some embodiments, the processor may further include an AI (artificial intelligence) processor for processing computing operations related to machine learning.
The memory may include one or more computer-readable storage media, which may be non-transitory. The memory may also include high speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In some embodiments, a non-transitory computer readable storage medium in a memory is used to store at least one instruction for execution by a processor to implement the obstacle detection method provided by method embodiments herein.
An embodiment of the present invention further provides a storage medium, where the storage medium may be a non-volatile computer-readable storage medium, and a computer program is stored in the storage medium, and when being executed by a processor, the computer program implements the obstacle detection method provided in the foregoing embodiment.
Embodiments of the present invention also provide a computer program product containing instructions, which when run on a computer, cause the computer to execute the obstacle detection method provided by the above embodiments.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The above description is only exemplary of the present application and should not be taken as limiting, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (15)
1. An obstacle detection method, characterized in that the method comprises:
in the running process of the mobile robot, emitting infrared light to the surrounding area of the area where the mobile robot is located;
acquiring an image of the surrounding area;
when the image contains a target pattern, first position information of an obstacle is obtained, the target pattern is a pattern formed in the image by infrared light reflected by a reflective mark, and the reflective mark is fixedly arranged on the surface of the obstacle.
2. The method of claim 1, wherein obtaining first position information of an obstacle when a target pattern is included in the image comprises:
acquiring second position information of the target pattern in the image based on the image;
and acquiring the first position information based on the second position information.
3. The method of claim 2, wherein prior to said obtaining the first location information based on the second location information, the method further comprises:
determining a conversion matrix based on the setting position of image acquisition equipment and the setting position of the reflective mark, wherein the image acquisition equipment is used for acquiring the image of the surrounding area, and the conversion matrix is used for carrying out coordinate conversion on a space coordinate system where the reflective mark is located and an image coordinate system where pixel points in the image are located;
the obtaining the first location information based on the second location information includes:
and acquiring the first position information based on the second position information and the conversion matrix.
4. The method according to claim 2 or 3, wherein the obtaining second position information of the target pattern in the image based on the image comprises:
detecting the pixel value of each pixel point in the image to determine that the target pattern exists in the image;
second position information of the target pattern in the image is acquired.
5. The method of claim 4, wherein the detecting pixel values of the pixels in the image to determine that the target pattern exists in the image comprises:
and detecting the pixel value of each pixel point in the image through a connected domain detection algorithm so as to determine that the target pattern exists in the image.
6. The method of any of claims 1 to 3, wherein the obstacle comprises: shelves in the warehouse.
7. An obstacle detection apparatus, characterized in that the apparatus comprises:
the transmitting module is used for transmitting infrared light to the surrounding area of the area where the mobile robot is located in the driving process of the mobile robot;
the acquisition module is used for acquiring the image of the surrounding area;
the first acquisition module is used for acquiring first position information of an obstacle when the image contains a target pattern, wherein the target pattern is a pattern formed in the image by infrared light reflected by a reflective mark, and the reflective mark is fixedly arranged on the surface of the obstacle.
8. The apparatus of claim 7, wherein the first obtaining module is further configured to:
acquiring second position information of the target pattern in the image based on the image;
and acquiring the first position information based on the second position information.
9. The apparatus of claim 8, further comprising:
a second obtaining module to: determining a conversion matrix based on the setting position of image acquisition equipment and the setting position of the reflective mark, wherein the image acquisition equipment is used for acquiring the image of the surrounding area, and the conversion matrix is used for carrying out coordinate conversion on a space coordinate system where the reflective mark is located and an image coordinate system where pixel points in the image are located;
the first obtaining module is further configured to:
and acquiring the first position information based on the second position information and the conversion matrix.
10. The apparatus of claim 8 or 9, wherein the first obtaining module is further configured to:
detecting the pixel value of each pixel point in the image to determine that the target pattern exists in the image;
second position information of the target pattern in the image is acquired.
11. The apparatus of claim 10, wherein the first obtaining module is further configured to:
and detecting the pixel value of each pixel point in the image through a connected domain detection algorithm so as to determine that the target pattern exists in the image.
12. The apparatus of any of claims 7 to 9, wherein the obstacle comprises: shelves in the warehouse.
13. An obstacle detection system, characterized in that the system comprises: the mobile robot and a reflective mark fixedly arranged on the surface of the obstacle, wherein the reflective mark is used for reflecting infrared light emitted to the reflective mark, and the obstacle detection device of any one of claims 7 to 12 is deployed on the mobile robot.
14. The obstacle detection system according to claim 13, wherein the light-reflecting sign is fixedly provided at an intersection position of the obstacle and a travel surface of the mobile robot.
15. The obstacle detection system according to claim 13 or 14, wherein the obstacle detection system is deployed in a warehouse, the obstacle comprising: a shelf in the warehouse.
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| CN201810891978.XA CN110824498A (en) | 2018-08-07 | 2018-08-07 | Obstacle detection method, device and system |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112394690A (en) * | 2020-10-30 | 2021-02-23 | 北京旷视机器人技术有限公司 | Warehouse management method, device and system and electronic equipment |
| CN112506189A (en) * | 2020-11-19 | 2021-03-16 | 深圳优地科技有限公司 | Method for controlling robot to move |
| CN112804447A (en) * | 2020-12-30 | 2021-05-14 | 北京石头世纪科技股份有限公司 | Method, device, medium and electronic equipment for detecting near-field object |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202702247U (en) * | 2012-07-31 | 2013-01-30 | 山东大学 | Rapid and accurate positioning system used for indoor mobile robot |
| CN103492228A (en) * | 2011-04-22 | 2014-01-01 | 株式会社小糸制作所 | Obstacle detection device |
| CN105539404A (en) * | 2015-12-31 | 2016-05-04 | 清华大学苏州汽车研究院（吴江） | Target detection prewarning and auxiliary braking system for parking |
| CN106289232A (en) * | 2016-07-24 | 2017-01-04 | 广东大仓机器人科技有限公司 | A kind of Obstacle Avoidance based on depth transducer |
| CN106326930A (en) * | 2016-08-24 | 2017-01-11 | 王忠民 | Method for determining position of tracked object in virtual reality and device and system thereof |
| US20170121910A1 (en) * | 2011-02-23 | 2017-05-04 | Crane & Co., Inc. | Security sheet or document having one or more enhanced watermarks |
| CN107291080A (en) * | 2017-06-27 | 2017-10-24 | 深圳普思英察科技有限公司 | A kind of sweeping robot and barrier-avoiding method, readable storage medium storing program for executing |
| CN107689061A (en) * | 2017-07-11 | 2018-02-13 | 西北工业大学 | Rule schema shape code and localization method for indoor mobile robot positioning |
-
2018
- 2018-08-07 CN CN201810891978.XA patent/CN110824498A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170121910A1 (en) * | 2011-02-23 | 2017-05-04 | Crane & Co., Inc. | Security sheet or document having one or more enhanced watermarks |
| CN103492228A (en) * | 2011-04-22 | 2014-01-01 | 株式会社小糸制作所 | Obstacle detection device |
| CN202702247U (en) * | 2012-07-31 | 2013-01-30 | 山东大学 | Rapid and accurate positioning system used for indoor mobile robot |
| CN105539404A (en) * | 2015-12-31 | 2016-05-04 | 清华大学苏州汽车研究院（吴江） | Target detection prewarning and auxiliary braking system for parking |
| CN106289232A (en) * | 2016-07-24 | 2017-01-04 | 广东大仓机器人科技有限公司 | A kind of Obstacle Avoidance based on depth transducer |
| CN106326930A (en) * | 2016-08-24 | 2017-01-11 | 王忠民 | Method for determining position of tracked object in virtual reality and device and system thereof |
| CN107291080A (en) * | 2017-06-27 | 2017-10-24 | 深圳普思英察科技有限公司 | A kind of sweeping robot and barrier-avoiding method, readable storage medium storing program for executing |
| CN107689061A (en) * | 2017-07-11 | 2018-02-13 | 西北工业大学 | Rule schema shape code and localization method for indoor mobile robot positioning |
Non-Patent Citations (2)
| Title |
|---|
| 刘晓龙: "基于被动式红外路标的移动机器人室内定位技术研究与嵌入式实现", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
| 杨磊: "《数字媒体技术概论》", 30 September 2017 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112394690A (en) * | 2020-10-30 | 2021-02-23 | 北京旷视机器人技术有限公司 | Warehouse management method, device and system and electronic equipment |
| CN112506189A (en) * | 2020-11-19 | 2021-03-16 | 深圳优地科技有限公司 | Method for controlling robot to move |
| CN112804447A (en) * | 2020-12-30 | 2021-05-14 | 北京石头世纪科技股份有限公司 | Method, device, medium and electronic equipment for detecting near-field object |
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