Floor identification method, device, equipment and storage medium

Abstract

The present application provides a floor recognition method, device, equipment and storage medium, which relate to the field of robots. The floor recognition method includes: obtaining environmental feature information of the current floor where the robot is currently located; obtaining first environmental information in a map corresponding to a target floor; determining a first matching score between the environmental feature information and the first environmental information based on the environmental feature information and the first environmental information; judging whether the current floor is the target floor based on the first matching score. The technical solution of the present application can effectively identify whether the floor where the robot is currently located is the target floor.

Description

Technical Field

[0001] The present application relates to the field of robotics technology, and in particular to a floor recognition method, device, equipment and storage medium. Background Art

[0002] At present, when a robot takes an elevator, it needs to rely on the recognition module inside the robot to identify the floor the elevator is on. For example, the robot relies on the inertial measurement unit (IMU) inside the robot to determine the distance the robot moves up and down, and determines the floor information based on the distance the robot moves up and down. This recognition method has cumulative errors, and the higher the floors, the greater the cumulative error, making the robot's recognition accuracy of the elevator floor not high.

[0003] When the robot misidentifies the floor in the elevator, it may cause the robot to get off the elevator at a non-target floor. However, on non-target floors, the robot will not be able to complete the task normally, and there may even be certain safety hazards. In addition, existing robots cannot identify whether the current floor is the target floor, which will lead to the failure of subsequent task execution.

[0004] Therefore, a method is needed in the prior art to accurately identify whether the floor where the robot is located is the target floor. Summary of the invention

[0005] The embodiments of the present application provide a floor recognition method, device, equipment and storage medium to solve the problem in the prior art that it is impossible to accurately identify whether the current floor of the robot is the target floor.

[0006] In a first aspect, the present application provides a floor recognition method, comprising:

[0007] Get the environmental feature information of the current floor where the robot is currently located;

[0008] Obtaining first environment information in a map corresponding to a target floor;

[0009] Determining a first matching score between the environmental feature information and the first environmental information according to the environmental feature information and the first environmental information;

[0010] According to the first matching score, it is determined whether the current floor is the target floor.

[0011] In an optional implementation, judging whether the current floor is the target floor according to the first matching score includes:

[0012] If the first matching score is greater than or equal to a preset score, determining that the current floor is the target floor;

[0013] If the first matching score is less than the preset score, obtaining second environment information in the map corresponding to at least one other floor, wherein the other floor is a floor other than the current floor;

[0014] respectively determining a second matching score between the environmental feature information and each of the second environmental information;

[0015] If there is a matching score greater than or equal to the first matching score among the at least one of the second matching scores, determining that the current floor is not the target floor;

[0016] If none of the at least one second matching score has a matching score greater than or equal to the first matching score, it is determined that the current floor is the target floor.

[0017] In an optional implementation, the acquiring the first environment information in the map corresponding to the target floor includes:

[0018] Acquire a first environment map corresponding to the target floor;

[0019] Obtaining current position information of the robot on the current floor;

[0020] Projecting the current posture information onto the first environment map to obtain the first posture information of the robot in the first environment map;

[0021] The first environment information is determined according to the first posture information and the first environment map.

[0022] In an optional implementation, the obtaining of second environment information in a map corresponding to at least one other floor includes:

[0023] Acquire a second environment map corresponding to at least one of the other floors;

[0024] Obtaining current position information of the robot on the current floor;

[0025] Projecting the current posture information onto each of the second environment maps to obtain second posture information of the robot in each of the second environment maps;

[0026] Determine the at least one second environment information according to the at least one second posture information and the at least one second environment map.

[0027] In an optional implementation, if the first matching score is greater than or equal to a preset score, the current floor is the target floor, including:

[0028] If the first matching score is greater than or equal to the preset score, detecting whether there is a preset target object on the current floor;

[0029] If the preset target object is detected, the current floor is determined to be the target floor.

[0030] In an optional implementation, the preset target object is a charging pile; if the preset target object is detected, after determining that the current floor is the target floor,

[0031] The method further comprises:

[0032] If the robot meets the preset charging conditions, it is charged on the current floor according to the position and direction of the charging pile.

[0033] In an optional implementation, the step of obtaining environmental feature information of a current floor where the robot is currently located includes:

[0034] Performing laser scanning on the current floor to obtain point cloud information of the environmental feature information; and / or

[0035] An image scan is performed on the current floor to obtain image information of the environmental feature information.

[0036] In a second aspect, the present application provides a floor identification device, comprising:

[0037] The first acquisition module is used to obtain the environmental feature information of the current floor where the robot is currently located;

[0038] A second acquisition module is used to acquire first environmental information in a map corresponding to a target floor;

[0039] a determination module, configured to determine a first matching score between the environmental feature information and the first environmental information according to the environmental feature information and the first environmental information;

[0040] A judgment module is used to judge whether the current floor is the target floor according to the first matching score.

[0041] In an optional implementation, the judgment module is also used to: if the first matching score is greater than or equal to a preset score, determine that the current floor is the target floor; if the first matching score is less than the preset score, obtain the second environmental information in the map corresponding to at least one other floor, wherein the other floor is a floor other than the current floor; respectively determine the second matching scores between the environmental feature information and each of the second environmental information; if there is a matching score greater than or equal to the first matching score among the at least one of the second matching scores, determine that the current floor is not the target floor; if there is no matching score greater than or equal to the first matching score among the at least one of the second matching scores, determine that the current floor is the target floor.

[0042] In an optional implementation, the second acquisition module is also used to: obtain the first environment map corresponding to the target floor; obtain the current posture information of the robot on the current floor; project the current posture information onto the first environment map to obtain the first posture information of the robot in the first environment map; determine the first environment information based on the first posture information and the first environment map.

[0043] In an optional implementation, the judgment module is also used to: obtain a second environment map corresponding to at least one of the other floors; obtain current posture information of the robot on the current floor; project the current posture information on each of the second environment maps to respectively obtain the second posture information of the robot in each of the second environment maps; determine the at least one second environment information based on the at least one second posture information and the at least one second environment map.

[0044] In an optional implementation, the judgment module is further used to: if the first matching score is greater than or equal to the preset score, detect whether there is a preset target object on the current floor; if the preset target object is detected, determine that the current floor is the target floor.

[0045] In an optional implementation, the preset target object is a charging pile; and the floor recognition device further includes:

[0046] The charging module is used to charge the robot on the current floor according to the position and direction of the charging pile if the robot meets the preset charging conditions.

[0047] In an optional implementation, the first acquisition module is specifically configured to:

[0048] Performing laser scanning on the current floor to obtain point cloud information of the environmental characteristic information; and / or performing image scanning on the current floor to obtain image information of the environmental characteristic information.

[0049] In a third aspect, the present application provides a floor identification device, comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method described in the first aspect or any optional method of the first aspect is implemented.

[0050] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in the first aspect or any optional method of the first aspect is implemented.

[0051] In a fifth aspect, an embodiment of the present application provides a computer program product. When the computer program product is run on a floor identification device, the floor identification device executes the steps of the floor identification method described in the first aspect above.

[0052] Compared with the prior art, the beneficial effect of the technical solution of the present application is that the floor identification method provided by the present application can effectively identify whether the current floor of the robot is the target floor, thereby avoiding the robot from performing tasks on non-target floors.

[0053] It can be understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0055] Figure 1 This is a schematic diagram of an application scenario of a floor recognition method provided by an embodiment of the present application;

[0056] Figure 2 is a schematic flow chart of a floor identification method provided in an embodiment of the present application;

[0057] Figure 3 yes Figure 2 Specific implementation flow chart of step S202;

[0058] Figure 4 yes Figure 1Specific implementation flow chart of step S204;

[0059] Figure 5 is a schematic diagram of a floor identification device provided in an embodiment of the present application;

[0060] Figure 6 It is a schematic diagram of a floor identification device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0061] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0062] It should be understood that in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and should not be understood as indicating or implying relative importance.

[0063] It should also be understood that references to "one embodiment" or "some embodiments" described in the specification of the present application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. The terms "include", "comprises", "has" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0064] Before describing the floor recognition method provided by the present application, first Figure 1 The application scenario of the floor recognition method proposed in this application is exemplified.

[0065] Figure 1 Schematic diagram of an application scenario of a floor recognition method provided by an embodiment of the present application. Figure 1 It can be seen that the embodiment of the present application is aimed at the situation that when the robot 101 is riding in the elevator 102, if there is an error in judging the elevator floor, the robot will get off the elevator at a non-target floor (not the preset target floor for the robot to get off the elevator). Figure 1As shown, in this example, it is assumed that the preset target floor 103 of the robot 102 getting off the elevator is the 4th floor, and the robot 102 gets off the elevator at the non-target floor 104 (2nd floor). It can be understood that the non-target floor 104 can be any other floor except the target floor 103. In this embodiment, only one non-target floor 104 is shown for exemplary description. If the robot 101 cannot identify that the current floor is the non-target floor 104, it will affect the subsequent execution of tasks by the robot 101. Therefore, a method is needed for a robot to identify whether the floor it is on is the target floor, so as to help the robot return to the elevator in time and perform subsequent tasks when it is on the non-target floor.

[0066] In this application, a technical solution is introduced to match the environmental feature information of the current floor with the first environmental information of the target floor, and determine whether the current floor of the robot is the target floor by matching the score. The floor recognition method provided by this application is exemplarily described below through specific embodiments.

[0067] See also Figure 2 , Figure 2 is a schematic flow chart of a floor identification method provided in an embodiment of the present application. The floor identification method in this embodiment is performed by a floor identification device, including but not limited to a smart phone, tablet computer, wearable device, computer, server, etc. that can communicate with a robot, and can also be a robot or mobile service robot in various application scenarios. For ease of explanation, in this embodiment of the present application, a robot is used as the execution subject for explanation, such as Figure 2 The floor identification method shown may include the following steps S201-S204:

[0068] Step S201, obtaining environmental feature information of the current floor where the robot is currently located.

[0069] In an optional embodiment of the present application, the environmental feature information of the current floor where the robot is currently located may be laser point cloud information of the current floor obtained by laser radar scanning when the robot is on the current floor. Optionally, the laser point cloud information includes point cloud information of the environmental feature information of the current floor.

[0070] In another optional embodiment of the present application, the environmental feature information of the current floor where the robot is currently located may be image information obtained by scanning the current floor when the robot is on the current floor. Optionally, the image information may be visual feature information, and the visual feature information may be visual feature information obtained by the robot scanning the current floor through a visual sensor.

[0071] Step S202, obtaining first environmental information in a map corresponding to a target floor.

[0072] In an embodiment of the present application, the target floor is a pre-set floor where the robot performs a task. The first environment information of the target floor is map information corresponding to the local environment in the first environment map of the target floor pre-stored inside the robot, and the map information corresponding to the local environment is related to the current first posture information of the robot. Exemplarily, the first environment information is map information corresponding to the environment that can be scanned by the robot in the current first posture when the robot is on the target floor.

[0073] For example, Figure 3 As shown, Figure 3 yes Figure 2 The specific implementation flow chart of step S202 in FIG. Figure 3 It can be seen that step S202 includes steps S2021 to S2024, which are described in detail as follows:

[0074] Step S2021, obtaining a first environment map corresponding to the target floor.

[0075] In an embodiment of the present application, the first environment map may be a grid map or a visual feature map.

[0076] Step S2022, obtaining the current posture information of the robot on the current floor.

[0077] In the embodiment of the present application, the current posture information of the robot on the current floor is the current position and posture of the robot, which may be the position and posture of the robot's end effector relative to the base. The current posture information of the robot on the current floor may be obtained by an existing common robot posture information acquisition method, for example, a common sensor acquires position information and determines the posture information in combination with a position coordinate system.

[0078] Step S2023: project the current posture information onto the first environment map to obtain the first posture information of the robot in the first environment map.

[0079] Exemplarily, if the first environment map is a grid map, the current posture information can be projected onto the first environment map according to the information transformation relationship between the preset grid map of the target floor and the grid map of the current floor. If the first environment map is a visual feature map, the current posture information can be projected onto the first environment map according to the information transformation relationship between the preset visual feature map of the target floor and the visual feature map of the current floor.

[0080] Step S2024: determine the first environment information according to the first posture information and the first environment map.

[0081] In this embodiment, a mapping relationship between the robot's posture information and environmental information may be preset. After the first posture information of the robot on the target floor is obtained, the first environmental information of the robot on the target floor is determined according to the mapping relationship.

[0082] Step S203: determining a first matching score between the environmental characteristic information and the first environmental information according to the environmental characteristic information and the first environmental information.

[0083] In the embodiment of the present application, the environmental feature information may be point cloud information or visual feature information. The first environmental information may be represented by a grid map or a visual map.

[0084] Determining the first matching score between the environmental feature information and the first environmental information according to the environmental feature information and the first environmental information may include: calculating the probability value of each grid map contained in the first environmental information being occupied by the point cloud information, and determining the first matching score between the point cloud information and the first environmental information according to the mapping relationship between the preset probability value and the matching score. It can be understood that the greater the probability value of each grid being occupied by the point cloud information, the higher the corresponding first matching score.

[0085] Alternatively, determining the first matching score between the environmental feature information and the first environmental information based on the environmental feature information and the first environmental information may include: calculating the similarity between the visual feature information contained in the first environmental information and the visual characteristics in the visual map, and determining the first matching score between the point cloud information and the first environmental information based on the similarity. It can be understood that the higher the similarity, the higher the corresponding first matching score.

[0086] It can be understood that when the robot gets off the elevator at a non-target floor, and the environment of the non-target floor is greatly different from that of the target floor, for example, different objects are arranged on the non-target floor and the target floor, or the spatial layout of the non-target floor and the target floor is different, the corresponding first matching score is low. When the robot gets off the elevator at a non-target floor, and the environment of the non-target floor is less different from that of the target floor, for example, the same objects are arranged on the non-target floor and the target floor, and the spatial layout of the non-target floor and the target floor is the same, the corresponding first matching score is high.

[0087] Step S204: judging whether the current floor is the target floor according to the first matching score.

[0088] It can be understood that the first matching score represents the matching score between the environmental feature information scanned by the robot on the current floor and the first environmental information in the first environmental map of the preset target floor. In this embodiment, a score can be preset, and by comparing the size relationship between the first matching score and the preset score, it is identified whether the current floor is the target floor.

[0089] For example, Figure 4 As shown, Figure 4 yes Figure 2 The specific implementation flow chart of step S204 in FIG. Figure 4 It can be seen that step S204 includes steps S2041 to S2045, which are described in detail as follows:

[0090] Step S2041: If the first matching score is greater than or equal to a preset score, it is determined that the current floor is the target floor.

[0091] Step S2042: If the first matching score is less than the preset score, second environment information in the map corresponding to at least one other floor is obtained, wherein the other floor is a floor other than the current floor.

[0092] In this embodiment, the obtaining of the second environment information in the map corresponding to at least one other floor may include: obtaining the second environment map corresponding to at least one other floor; obtaining the current posture information of the robot on the current floor; projecting the current posture information on each of the second environment maps to respectively obtain the second posture information of the robot in each of the second environment maps; and determining the at least one second environment information based on the at least one second posture information and the at least one second environment map.

[0093] Step S2043: respectively determine the second matching scores between the environmental feature information and each of the second environmental information.

[0094] Step S2044: If there is a matching score greater than or equal to the first matching score among the at least one of the second matching scores, it is determined that the current floor is not the target floor.

[0095] Step S2045: If none of the at least one second matching score has a matching score greater than or equal to the first matching score, it is determined that the current floor is the target floor.

[0096] It is understandable that if there is a score greater than the first matching score in the second matching score, it is determined that the current floor is not the target floor. Optionally, after determining that the current floor is not the target floor, the robot can return to the elevator entrance and re-enter the elevator to continue to perform the task.

[0097] Optionally, since there is a scenario where the environmental information of a non-target floor is similar to that of a target floor, if the first matching score is greater than or equal to the preset score, there may also be a phenomenon of misjudgment. In this case, the robot may perform tasks on a non-target floor. For example, assuming that the robot plans to deliver an item to a customer in room 402 on the 4th floor, after actually arriving at the 3rd floor, it gets off the elevator on the 3rd floor due to the wrong floor recognition, and since the spatial layout of the 3rd and 4th floors is exactly the same, the robot may deliver the item to room 302 on the 3rd floor.

[0098] In order to avoid this phenomenon, in another embodiment of the present application, after the robot arrives at the target location, the robot can perform visual or voice recognition to determine whether it is the correct target location. For example, after the robot arrives at the door of the room, it visually recognizes the house number to determine whether the house number is correct, and further determines whether it has arrived at the correct room. Alternatively, after the robot delivers the item to the door of the room, it will call the phone of the corresponding room and determine whether it has arrived at the correct room by recognizing the ringtone of the phone. If the robot further determines that it has not arrived at the target location, it can return to the elevator entrance, take the elevator again, and choose to re-execute the task.

[0099] Optionally, in some application scenarios, when the robot arrives at a location on a non-target floor, it may not be able to determine whether the arrived location is the preset destination through visual recognition or voice recognition. At this time, the robot may mistakenly believe that it has reached the target location and place the corresponding items at the arrived location.

[0100] In an embodiment of the present application, in order to further enable the robot to detect whether it has arrived at the target location, a preset target object is placed on the floor. If the first matching score is greater than or equal to the preset score, it is detected whether there is a preset target object on the current floor; if the preset target object is detected, the current floor is determined to be the target floor. Exemplarily, the preset target object is a charging pile, and if the robot detects the charging pile on the current floor, the current floor is determined to be the target floor.

[0101] Further, if the robot meets the preset charging conditions, it is charged on the current floor according to the position and direction of the charging pile. For example, if the robot's power is less than a preset value (e.g., 20%), the robot meets the preset charging conditions and is charged on the current floor according to the position and direction of the charging pile.

[0102] If the robot cannot detect the charging pile on the current floor, the robot needs to further determine the target floor by matching the second environmental information of at least one other floor. It can be understood that after determining the target floor, the robot can return to the elevator and take the elevator again to ensure that it can continue to perform the task.

[0103] Based on the above embodiments, it can be known that in the floor identification method provided in the present application, by obtaining the environmental characteristic information of the current floor where the robot is currently located; obtaining the first environmental information in the map corresponding to the target floor; determining the first matching score between the environmental characteristic information and the first environmental information based on the environmental characteristic information and the first environmental information; judging whether the current floor is the target floor based on the first matching score, it is possible to effectively identify whether the floor where the robot is currently located is the target floor, thereby avoiding the robot from performing tasks on non-target floors.

[0104] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0105] Based on the floor identification method provided by the above embodiment, the embodiment of the present invention further provides an apparatus embodiment for implementing the above method embodiment.

[0106] See also Figure 5 , Figure 5 Schematic diagram of a floor identification device provided in an embodiment of the present application. The modules or units included are used to execute Figure 2 For details, please refer to the steps in the corresponding embodiment. Figure 2 For the convenience of explanation, only the parts related to this embodiment are shown. Figure 5 , the floor identification device 5 comprises:

[0107] The first acquisition module 501 is used to acquire the environmental characteristic information of the current floor where the robot is currently located;

[0108] The second acquisition module 502 is used to acquire first environmental information in the map corresponding to the target floor;

[0109] A determination module 503, configured to determine a first matching score between the environmental feature information and the first environmental information according to the environmental feature information and the first environmental information;

[0110] The judgment module 504 is used to judge whether the current floor is the target floor according to the first matching score.

[0111] In an optional implementation, the judgment module 504 is also used to: if the first matching score is greater than or equal to a preset score, determine that the current floor is the target floor; if the first matching score is less than the preset score, obtain the second environmental information in the map corresponding to at least one other floor, wherein the other floor is a floor other than the current floor; respectively determine the second matching scores between the environmental feature information and each of the second environmental information; if there is a matching score greater than or equal to the first matching score among the at least one second matching score, determine that the current floor is not the target floor; if there is no matching score greater than or equal to the first matching score among the at least one second matching score, determine that the current floor is the target floor.

[0112] In an optional implementation, the second acquisition module 502 is also used to: obtain the first environment map corresponding to the target floor; obtain the current posture information of the robot on the current floor; project the current posture information on the first environment map to obtain the first posture information of the robot in the first environment map; determine the first environment information based on the first posture information and the first environment map.

[0113] In an optional implementation, the judgment module 504 is also used to: obtain a second environment map corresponding to at least one of the other floors; obtain current posture information of the robot on the current floor; project the current posture information on each of the second environment maps to respectively obtain the second posture information of the robot in each of the second environment maps; determine the at least one second environment information based on the at least one second posture information and the at least one second environment map.

[0114] In an optional implementation, the judgment module 504 is further used to: if the first matching score is greater than or equal to the preset score, detect whether there is a preset target object on the current floor; if the preset target object is detected, determine that the current floor is the target floor.

[0115] In an optional implementation, the preset target object is a charging pile; and the floor recognition device further includes:

[0116] The charging module is used to charge the robot on the current floor according to the position and direction of the charging pile if the robot meets the preset charging conditions.

[0117] In an optional implementation, the first acquisition module 501 is specifically configured to:

[0118] Performing laser scanning on the current floor to obtain point cloud information of the environmental characteristic information; and / or performing image scanning on the current floor to obtain image information of the environmental characteristic information.

[0119] It should be noted that the information interaction, execution process and other contents between the above-mentioned modules are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0120] Figure 6 Schematic diagram of a floor identification device provided in an embodiment of the present application. Figure 6 As shown, the floor identification device 6 of this embodiment includes: a processor 600, a memory 601, and a computer program 602 stored in the memory 601 and executable on the processor 600, such as a floor identification program. When the processor 600 executes the computer program 602, the steps in the above-mentioned various floor identification method embodiments are implemented, such as Figure 2 Alternatively, when the processor 600 executes the computer program 602, the functions of each module / unit in the above-mentioned device embodiments are realized, for example Figure 5 Functions of modules 501 to 504 are shown.

[0121] Exemplarily, the computer program 602 may be divided into one or more modules / units, which are stored in the memory 601 and executed by the processor 600 to complete the present application. The one or more modules / units may be a series of computer program instruction segments that can complete specific functions, and the instruction segments are used to describe the execution process of the computer program 602 in the floor identification device 6. For example, the computer program 602 may be divided into a first acquisition module 501, a second acquisition module 502, a determination module 503, and a judgment module 503. For the specific functions of each module, please refer to Figure 5 The relevant descriptions in the corresponding embodiments are not repeated here.

[0122] The floor recognition device may include, but is not limited to, a processor 600 and a memory 601. Those skilled in the art will appreciate that Figure 6It is only an example of the floor identification device 6 and does not constitute a limitation of the floor identification device 6. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the floor identification device may also include input and output devices, network access devices, buses, etc.

[0123] The processor 600 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0124] The memory 601 may be an internal storage unit of the floor identification device 6, such as a hard disk or memory of the floor identification device 6. The memory 601 may also be an external storage device of the floor identification device 6, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the floor identification device 6. Further, the memory 601 may also include both an internal storage unit and an external storage device of the floor identification device 6. The memory 601 is used to store the computer program and other programs and data required by the floor identification device. The memory 601 may also be used to temporarily store data that has been output or is to be output.

[0125] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned video stabilization method can be implemented.

[0126] An embodiment of the present application provides a computer program product. When the computer program product runs on a floor identification device, the floor identification device can implement the above-mentioned floor identification method when executing the computer program product.

[0127] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0128] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0129] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0130] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A floor recognition method, characterized in that: include: Get the environmental feature information of the current floor where the robot is currently located; Acquiring first environmental information in a map corresponding to a target floor, including: acquiring a first environmental map corresponding to the target floor; acquiring current position information of the robot on the current floor; projecting the current position information onto the first environmental map to obtain first position information of the robot in the first environmental map; determining the first environmental information according to the first position information and the first environmental map, wherein the first environmental map is map information corresponding to a local environment of the target floor pre-stored in the robot, and the first environmental map is a visual feature map; Determining a first matching score between the environmental feature information and the first environmental information according to the environmental feature information and the first environmental information; According to the first matching score, it is determined whether the current floor is the target floor.

2. The method according to claim 1, characterized in that The determining, according to the first matching score, whether the current floor is the target floor includes: If the first matching score is greater than or equal to a preset score, determining that the current floor is the target floor; If the first matching score is less than the preset score, obtaining second environment information in the map corresponding to at least one other floor, wherein the other floor is a floor other than the current floor; respectively determining a second matching score between the environmental feature information and each of the second environmental information; If there is a matching score greater than or equal to the first matching score among the at least one of the second matching scores, determining that the current floor is not the target floor; If none of the at least one second matching score has a matching score greater than or equal to the first matching score, it is determined that the current floor is the target floor.

3. The method according to claim 2, characterized in that The obtaining of second environment information in a map corresponding to at least one other floor includes: Acquire a second environment map corresponding to at least one of the other floors; Obtaining current position information of the robot on the current floor; Projecting the current posture information onto each of the second environment maps to obtain second posture information of the robot in each of the second environment maps; Determine the at least one second environment information according to the at least one second posture information and the at least one second environment map.

4. The method according to claim 2, characterized in that: If the first matching score is greater than or equal to a preset score, determining that the current floor is the target floor includes: If the first matching score is greater than or equal to the preset score, detecting whether there is a preset target object on the current floor; If the preset target object is detected, the current floor is determined to be the target floor.

5. The method according to claim 4, characterized in that The preset target object is a charging pile; if the preset target object is detected, then after determining that the current floor is the target floor, The method further comprises: If the robot meets the preset charging conditions, it is charged on the current floor according to the position and direction of the charging pile.

6. The method according to any one of claims 1 to 5, characterized in that: The step of obtaining the environmental characteristic information of the current floor where the robot is currently located includes: Performing laser scanning on the current floor to obtain point cloud information of the environmental characteristic information; and / or performing image scanning on the current floor to obtain image information of the environmental characteristic information.

7. A floor identification device, characterized in that: include: The first acquisition module is used to obtain the environmental feature information of the current floor where the robot is currently located; The second acquisition module is used to acquire the first environment information in the map corresponding to the target floor, including: acquiring the first environment map corresponding to the target floor; acquiring the current posture information of the robot on the current floor; projecting the current posture information on the first environment map to obtain the first posture information of the robot in the first environment map; determining the first environment information according to the first posture information and the first environment map, wherein the first environment map is map information corresponding to the local environment of the target floor pre-stored in the robot, and the first environment map is a visual feature map; a determination module, configured to determine a first matching score between the environmental feature information and the first environmental information according to the environmental feature information and the first environmental information; A judgment module is used to judge whether the current floor is the target floor according to the first matching score.

8. A floor identification device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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