Whole house map generation method and device, electronic equipment and storage medium

Abstract

The invention discloses a whole house map generation method and apparatus, an electronic device and a storage medium. The method comprises the steps of obtaining a first whole house map corresponding to a whole house area; in the process that the mobile robot scans the whole house area, N intelligent devices in the whole house area are recognized, the position information and the device type of each intelligent device are determined, and N is a positive integer; and marking the N intelligent devices on the first whole house map based on the position information and the device type of each intelligent device, and generating a second whole house map. According to the scheme, the positioning accuracy of the intelligent equipment is improved, and the user experience is improved.

Description

Technical Field

[0001] The present invention belongs to the field of computer technology, and in particular relates to a method, device, electronic equipment and storage medium for generating a whole-house map. Background Art

[0002] In the whole house intelligence, the whole house map is used as a visualization carrier of home appliances, home furnishings, air quality, etc. in the home environment. It is usually carried on the central control screen, wired controller and other carriers of the smart home, which can intuitively allow users to observe the status of the room and support the user's semantic operations. In related technologies, smart devices in the whole house map usually need to be added manually by users, and there are large errors in the position of smart devices on the map. On the one hand, it leads to low layout accuracy of the final map, and on the other hand, it depends on manual settings, affecting the user experience. Summary of the invention

[0003] In view of the above-mentioned technical problems in the related art, an embodiment of the present invention provides a method, device, electronic device and storage medium for generating a whole-house map.

[0004] In a first aspect, an embodiment of the present invention provides a method for generating a whole-house map, wherein a whole-house map is constructed by a mobile robot, and the method comprises:

[0005] Obtaining a first whole-house map corresponding to the whole-house area;

[0006] In the process of the mobile robot scanning the whole house area, N smart devices in the whole house area are identified, and the location information and device type of each smart device are determined, where N is a positive integer;

[0007] Based on the location information and device type of each smart device, the N smart devices are marked on the first whole-house map to generate a second whole-house map.

[0008] In some embodiments, in the process of the mobile robot scanning the whole house area, identifying N smart devices in the whole house area includes:

[0009] During the process of the mobile robot scanning the whole house area, broadcasting a first positioning request to the current environment through a target channel;

[0010] If first feedback information for the first positioning request is received, the device sending the first feedback information is used as the target smart device among the N smart devices, wherein the feedback information includes a device identifier and a device type of the corresponding device.

[0011] In some implementations, if first feedback information for the first positioning request is received, after the device sending the first feedback information is used as a target smart device among the N smart devices, the method further includes:

[0012] Control the mobile robot to broadcast a second positioning request to the current environment at M positions respectively, wherein the M positions are different and M is an integer greater than 1;

[0013] For each location, receiving second feedback information for the second positioning request at the location, and determining a signal reception strength for receiving the second feedback information, wherein the device identifier in the second feedback information is the same as the device identifier in the first feedback information;

[0014] Determining the location information and device type of each smart device includes:

[0015] Determining the location information of the target smart device based on the signal reception strength corresponding to each of the locations; and

[0016] The device type in the first feedback information is used as the device type of the target smart device.

[0017] In some implementations, determining the location information of the target smart device based on the signal reception strength corresponding to each location includes:

[0018] Determine an environmental attenuation factor of a current environment and a preset signal reception strength when the target smart device is at a preset distance;

[0019] For each of the locations, determining a distance between the target smart device and the location based on the environmental attenuation factor, the preset signal reception strength, and the signal reception strength corresponding to the location;

[0020] Based on the distance between the target smart device and each of the locations, the location information of the target smart device on the first whole-house map is determined.

[0021] In some implementations, the whole-house area includes a plurality of room areas, and before generating the second whole-house map, the method further includes:

[0022] Filter out K smart devices bound to room types from the N smart devices;

[0023] Based on the location information of each smart device among the K smart devices and the room type bound to each smart device, determine the room type of the room area where the K smart devices are located, so as to mark the room type of the room area where the K smart devices are located on the second whole-house map.

[0024] In some implementations, the whole-house area includes a plurality of room areas, and before generating the second whole-house map, the method further includes:

[0025] Determine, based on the location information of the N smart devices, a smart device included in each of the multiple room areas;

[0026] For each room area, based on the device type of the smart device in the room area and a first preset correspondence between the device type and the P room type probabilities, determine the probability that the room area belongs to the P room types, where P is a positive integer;

[0027] For each room area, based on the probability that the room area belongs to the P room types, the room type of the room area is determined, so as to mark the room type of the room area on the second whole-house map.

[0028] In some implementations, the whole-house area includes a plurality of room areas, and before generating the second whole-house map, the method further includes:

[0029] Determine the relative area between each room area and the whole house area;

[0030] For each room area, based on the relative area of ​​the room area and a second preset correspondence between the relative area of ​​the room and the probabilities of the Q room types, determine the probability that the room area belongs to the Q room types, where Q is a positive integer;

[0031] For each room area, based on the probability that the room area belongs to the Q room types, the room type of the room area is determined, so as to mark the room type of the room area on the second whole-house map.

[0032] In some implementations, the whole-house area includes a plurality of room areas, and before generating the second whole-house map, the method further includes:

[0033] Identify the entrance to each room area and determine the size of the entrance to each room area;

[0034] For each room area, based on the entrance size of the room area and a third preset correspondence between the entrance size and the S room type probabilities, determine the probability that the room area belongs to the S room types, where S is a positive integer;

[0035] For each room area, based on the probability that the room area belongs to the S room types, the room type of the room area is determined, so as to mark the room type of the room area on the second whole-house map.

[0036] In a second aspect, an embodiment of the present invention provides a whole-house map generating device, which constructs a whole-house map by a mobile robot, including:

[0037] An acquisition module, used for acquiring a first whole-house map corresponding to the whole-house area;

[0038] An intelligent device identification module, used to identify N intelligent devices in the whole house area and determine the location information and device type of each intelligent device during the process of the mobile robot scanning the whole house area, where N is a positive integer;

[0039] A processing module is used to mark the N smart devices on the first whole-house map based on the location information and device type of each smart device to generate a second whole-house map.

[0040] In a third aspect, an embodiment of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in any embodiment of the first aspect when executing the program.

[0041] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in any embodiment of the first aspect.

[0042] One or more technical solutions provided by the embodiments of the present invention achieve at least the following technical effects or advantages:

[0043] The whole-house map generation method provided in the embodiment of this specification scans the whole house area through a mobile robot to detect N smart devices in the whole house area, and determines the location information and device type of each smart device, and marks them in the whole-house map based on the location information and device type of each smart device, so as to obtain a whole-house map marked with the location and type of the smart device. In this solution, the positioning and type determination of smart devices are realized by mobile robots without human intervention, which greatly improves the accuracy of smart device positioning and improves the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0045] Figure 1A flowchart of a whole-house map generation method provided in an embodiment of this specification;

[0046] Figure 2 A flowchart of another whole-house map generation method provided in an embodiment of this specification;

[0047] Figure 3 A schematic diagram of a whole-house map generating device provided in an embodiment of this specification;

[0048] Figure 4 A schematic diagram of an electronic device provided in an embodiment of this specification. DETAILED DESCRIPTION

[0049] The embodiments of this specification provide a whole-house map generation method, device, electronic device and storage medium, the method comprising: obtaining a first whole-house map corresponding to a whole-house area; in the process of the mobile robot scanning the whole-house area, identifying N smart devices in the whole-house area, and determining the location information and device type of each smart device, N is a positive integer; based on the location information and device type of each smart device, marking the N smart devices on the first whole-house map to generate a second whole-house map.

[0050] The solution in the embodiments of this specification realizes the positioning and type determination of smart devices through mobile robots without human intervention, which greatly improves the accuracy of smart device positioning and improves user experience.

[0051] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only a part of the embodiment of the present invention, not all the embodiments. Based on the embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0053] like Figure 1 As shown, it is a flowchart of a whole-house map generation method provided in an embodiment of this specification. The method constructs a whole-house map by a mobile robot, and specifically includes the following steps:

[0054] Step S101: obtaining a first whole-house map corresponding to the whole-house area;

[0055] Step S102: in the process of the mobile robot scanning the whole house area, N smart devices in the whole house area are identified, and the location information and device type of each smart device are determined, where N is a positive integer;

[0056] Step S103: Based on the location information and device type of each smart device, the N smart devices are marked on the first whole-house map to generate a second whole-house map.

[0057] The solution provided in the embodiments of this specification can be applied to a mobile robot or other terminal devices, wherein the mobile robot can be a sweeping robot, a movable cleaning robot, etc. The solution can also be applied to a server, where the server is connected to the mobile robot in communication, and the mobile robot sends the detected data to the server so that the server processes the received data to generate the final whole-house map. In addition, the solution can also be applied to a system consisting of a mobile robot and a server, which is not limited here.

[0058] In step S101, the whole house area can be the user's residence, or it can be a workplace, or it can be other places, which are not limited here. The first whole house map corresponding to the whole house area can be obtained in a variety of ways. Taking the whole house area as the area corresponding to the user's residence as an example, the first whole house map can be a map that can characterize the user's residence type. In some embodiments, the first whole house map can be obtained by loading the floor plan corresponding to the residence. For example, the floor plans of each community can be stored on the server. The user can upload the community name of the residence to the server through the terminal device, and select the corresponding apartment type to determine the accurate floor plan as the first whole house map. In other embodiments, the first whole house map can be constructed by scanning the whole house area by a mobile robot. For example, the mobile robot is provided with a laser radar. When the mobile robot detects a mapping instruction, the laser radar is started and moved in the whole house area. During the movement, the whole house area is detected by the laser radar, and the first whole house map is constructed according to the collected laser radar data.

[0059] It should be noted that after the mobile robot completes the mapping, it can also divide the room into zones according to the room distribution. The zones can be divided by the detected room entrances, or by other methods, which are not limited here. Through the partition operation, the first whole house map can divide and display the areas of each room.

[0060] Taking into account the possible fuzzy and irregular room boundaries during the mapping process of the mobile robot, in some embodiments, after the partitioning is completed, the partitioned map can be expanded and eroded, and the boundary contour of each partition can be fitted with a minimum rectangle to make each partition a rectangle, so as to avoid the above-mentioned fuzzy and irregular room boundaries.

[0061] In step S102, if a mobile robot is used to construct the first whole-house map, since the mobile robot will scan the whole house area in the process of constructing the first whole-house map, that is, the movement trajectory will cover the whole house area, then the smart device can be identified at the same time during the map construction process of the mobile robot. Of course, in some embodiments, after the mobile robot has built the map, the whole house smart devices can be identified in the subsequent work process. For example, if the mobile robot is a sweeping robot, the whole house smart devices can be identified during the whole house area cleaning process after the sweeping robot completes the map construction.

[0062] In the embodiments of this specification, a communication module may be provided on the smart device to enable wireless communication with the mobile robot. For example, a WIFI and / or Bluetooth module may be provided on the smart device to communicate with the mobile robot via the WIFI and / or Bluetooth module. The types of smart devices may include, but are not limited to, smart TVs, smart speakers, smart air conditioners, smart refrigerators, etc., which are not limited here.

[0063] The N smart devices may be all smart devices set in the whole house area, where N is a positive integer. When the whole house area includes multiple smart devices, the multiple smart devices may be distributed in the same room or in different rooms. In order to identify all smart devices, the mobile robot needs to scan the whole house area, that is, the trajectory of the mobile robot needs to cover each room area.

[0064] In some embodiments, the mobile robot can identify N smart devices in the following manner: while the mobile robot is scanning the entire house area, a first positioning request is broadcast to the current environment through a target channel; if first feedback information is received in response to the first positioning request, the device that sends the first feedback information is used as the target smart device among the N smart devices, wherein the feedback information includes the device identification and device type of the corresponding device.

[0065] Specifically, during the whole-house scanning process, the mobile robot can continuously broadcast the first positioning request to the current environment through the target channel, where the target channel can be determined according to the communication method between the mobile robot and the smart device. For example, if the mobile robot and the smart device communicate via Bluetooth, then the target channel can be the channel corresponding to the Bluetooth communication.

[0066] In order to illustrate the communication process between the mobile robot and the smart device, take the target smart device as an example, where the target smart device can be any device in the whole house smart device. When the target smart device detects the first positioning request sent by the mobile robot, it responds to the first positioning request and sends the first feedback information, where the first feedback information includes the device identification and device type of the target smart device. The device identification can be the device ID of the target smart device, and the device type can be the specific type of the target smart device, including but not limited to air conditioner cabinet, air conditioner wall unit, or refrigerator, etc. Of course, the first feedback information can also include other information, which will not be given one by one here.

[0067] It should be noted that after the mobile robot sends the first positioning request at position A, if there are one or more smart devices near position A, it may receive first feedback information from one or more smart devices. Based on the device identification and device type of each first feedback information, one or more smart devices located near position A can be identified.

[0068] It is understandable that during the whole-house scanning process, the mobile robot may receive one or more feedback information at multiple locations, and these feedback information may contain information sent by the same device. Therefore, the same device can be screened by the device identifier of each feedback information, thereby determining N smart devices with different device identifiers.

[0069] In addition to the above method of identifying N smart devices by sending the first positioning request by the mobile robot, other methods can also be used to determine the smart devices in the whole house area. For example, the smart device actively sends the location information, and the mobile robot identifies the N smart devices according to the received location information during the whole house scanning process. Of course, those skilled in the art can also choose other identification methods according to actual needs, and no examples are given here.

[0070] In the embodiments of this specification, the location information and device type of the smart device can be determined in a variety of ways. In some embodiments, the location information and device type of the smart device can be obtained through the following steps: control the mobile robot to broadcast a second positioning request to the current environment at M locations respectively, wherein the M locations are different and M is an integer greater than 1; for each location, receive second feedback information for the second positioning request at the location, and determine the signal reception strength of receiving the second feedback information, wherein the device identifier in the second feedback information is the same as the device identifier in the first feedback information; determine the location information of the target smart device based on the signal reception strength corresponding to each location; and use the device type in the first feedback information as the device type of the target smart device.

[0071] Specifically, taking the determination of the location information and device type of the target smart device as an example, when the mobile robot receives the first feedback information fed back by the target smart device, it can directly enter the positioning process of the target smart device, that is, the mobile robot selects M positions to locate the target smart device. The value of M can be selected according to actual needs. For example, the value of M is 2 or 3. For the sake of convenience, M is 3 as an example. The mobile robot broadcasts the second positioning request at position 1, position 2, and position 3 respectively. The second positioning request can be the same as the first positioning request or different from the first positioning request, which is not limited here.

[0072] After the mobile robot sends the second positioning request at position 1, if there are multiple smart devices near position 1, the mobile robot may receive multiple feedback information. In order to locate the target smart device, the feedback information sent by the target smart device can be screened out from the multiple feedback information as the second feedback information based on the device identification of the target smart device, wherein the device identification of the target smart device can be obtained from the first feedback information. In addition, the signal reception strength of the second feedback information received by the mobile robot can also be obtained. In some embodiments, when the mobile robot receives the feedback information sent by each smart device, it can record the corresponding signal reception strength, and then screen out the signal reception strength of the second feedback information sent by the target smart device. Based on the same method, the signal reception strength of the second feedback information sent by the target smart device received by the mobile robot at position 2 and the signal reception strength of the second feedback information sent by the target smart device received by the mobile robot at position 3 can be obtained.

[0073] Based on the signal reception strength of the second feedback information corresponding to each position received by the mobile robot, the position information of the target smart device is determined. In some embodiments, the position information of the target smart device can be determined by: determining the environmental attenuation factor of the current environment and the preset signal reception strength at a preset distance from the target smart device; for each position, based on the environmental attenuation factor, the preset signal reception strength and the signal reception strength corresponding to the position, determining the distance between the target smart device and the position; based on the distance between the target smart device and each position, determining the position information of the target smart device on the first whole-house map.

[0074] Specifically, for each location, the distance d between the target smart device and the location can be calculated by the following formula:

[0075]

[0076] Among them, RSSI is the signal reception strength of the second feedback information received at this location, n is the environmental attenuation factor, A is the preset signal reception strength when it is at a preset distance from the target smart device. In the embodiment of this specification, A can be the signal strength received by the receiving device when the wireless transceiver device is 1m away.

[0077] In some embodiments, the values ​​of A and n may be preset. For example, for different smart devices, the corresponding A values ​​are set when they leave the factory. The A values ​​may be stored on a server. When calculating the above distance, the A value may be obtained by sending a query request to the server. In some embodiments, the value range of n may be 1.5 to 2.0.

[0078] Using the example of the three positions above, the above formula can be used to obtain the distance d1 between the target smart device and position 1, the distance d2 between the target smart device and position 2, and the distance d3 between the target smart device and position 3. Positioning is performed using the three-point method. Specifically, a sphere can be drawn with each position as the center and the corresponding distance as the radius, and the intersection of the spheres can be used as the three-dimensional coordinates of the target smart device.

[0079] It should be noted that if the first whole-house map is a three-dimensional map, the three-dimensional coordinates of the target smart device obtained above can be mapped to the first whole-house map to obtain the location information of the target smart device on the first whole-house map. If the first whole-house map is a two-dimensional map, the three-dimensional coordinates of the target smart device can be projected onto the plane of the first whole-house map to obtain the location information of the target smart device.

[0080] As for the device type of the target smart device, since the first feedback information includes the device type, the device type in the first feedback information can be used as the device type of the target smart device.

[0081] Of course, in addition to the above-mentioned method of determining the location information of the target smart device based on the signal reception strength, the location information of the target smart device can also be determined by other methods. For example, a model is pre-trained to determine the device location information based on the signal reception strength. After detecting the signal reception strength corresponding to the target smart device, it is input into the trained model to output the location information of the target smart device.

[0082] In the embodiments of this specification, for the smart devices whose location information and device types have been determined, the device identifications of these located smart devices can also be recorded to establish a located device identification set. When the mobile robot moves to another location, the device identifications not included in the above device identification set are screened out according to the device identifications in the received feedback information, and the location information and device type of the smart devices corresponding to the screened device identifications are determined, thereby avoiding repeated positioning of the same device.

[0083] In step S103, after obtaining the location information and device type of each smart device in the entire house area, each smart device can be marked on the first whole-house map according to the corresponding location information and device type. In some embodiments, based on the device type, a corresponding visualization component can be provided. For example, when the device type is an air conditioner hanging machine, the visualization component corresponding to the air conditioner hanging machine can be displayed on the first whole-house map to realize the visualization of the smart device on the whole-house map.

[0084] In the embodiments of the present specification, since the whole house area may include multiple room areas, such as a living room area, a bedroom area, a kitchen area, etc., when obtaining the partitioned whole house map, in order to facilitate the user to view the room type of each area, the room type of each room area can be determined and the room type can be marked on the second map.

[0085] Determining the room type of each room area can be achieved in many ways. In the embodiments of this specification, the room type of each room area can be determined by the area parameters corresponding to each room area and / or the device parameters of the smart devices in each room area, wherein the device parameters may include parameters such as the room type and device type bound to the device. Several of them are described below.

[0086] The first implementation method: filter out K smart devices bound to room types from the N smart devices; determine the room type of the room area where the K smart devices are located based on the location information of each smart device among the K smart devices and the room type bound to each smart device; mark the room type of the room area where the K smart devices are located on the second whole-house map.

[0087] Specifically, when the smart device is put into use, the user can set the room type of the area where the smart device is located through the terminal or remote control device. For example, there are multiple air conditioners installed in the user's living environment. In order to facilitate the control of the air conditioners in each area, the user can bind each air conditioner to the corresponding room type, such as the room type bound to air conditioner 1 is the master bedroom, the room type bound to air conditioner 2 is the second bedroom, and the room type bound to air conditioner 3 is the living room. When air conditioners 1, 2, and 3 are all smart devices, since the location of the smart device can be determined according to the method described above, it is possible to obtain the room area where the smart device is located, and determine the room type of the room area as the room type bound to the smart device, and mark it on the second whole house map.

[0088] It should be noted that, among the N smart devices in the whole house area, some smart devices may be bound to room types, and some smart devices may not be bound to room types. In the specific implementation process, K smart devices bound to room types can be screened out. In addition, for K smart devices, they may be distributed in multiple room areas. For each room area, if there is only one smart device in the room area, the room type bound to the smart device can be used as the type of the room area. If there are multiple smart devices in a room area, there may be a situation where the room types bound to multiple smart devices are different. At this time, the room types corresponding to the multiple smart devices in the room area can be counted, and the number of smart devices under each room type will be determined, and the room type with the largest number of smart devices is used as the room type of the room area. For example, if a room area includes the following three smart devices: a smart TV, a smart air conditioner, and a smart speaker, where the room type bound to the smart TV is the living room, the room type bound to the smart air conditioner is the bedroom, and the room type bound to the smart speaker is the living room, then the room type of the room area is determined to be the living room.

[0089] If the smart device in the room is not bound to the room type, or there is no smart device in the room, you can determine the room type in the following way.

[0090] The second implementation method: based on the location information of the N smart devices, determine the smart devices included in each of the multiple room areas; for each of the room areas, based on the device type of the smart devices in the room area, and a first preset correspondence between the device type and the P room type probabilities, determine the probability that the room area belongs to the P room types, where P is a positive integer; for each of the room areas, based on the probability that the room area belongs to the P room types, determine the room type of the room area, and mark the room type of the room area on the second whole-house map.

[0091] Specifically, for the presence of smart devices in the room, if the smart device is not bound to a room type, the room type can be determined based on the device type of the smart device. It is understandable that the types of smart devices set for different room types are also different. For example, the living room is usually equipped with a TV and an air-conditioning cabinet, the bedroom is usually equipped with a TV and an air-conditioning wall unit, the bathroom is usually equipped with a smart toilet and a smart bathroom heater, and the kitchen is usually equipped with a refrigerator, a range hood, etc. Therefore, in the embodiment of this specification, a first preset correspondence between the device type of the smart device and the probability of P types of room types can be pre-set, wherein the P types of room types can be set according to actual needs, such as the P types of room types include living rooms, bedrooms, bathrooms, kitchens, balconies, etc.

[0092] In some embodiments, the first preset correspondence relationship may be: the probability that the smart toilet and smart bathroom heater correspond to the bathroom is 1; the probability that the smart range hood and smart dishwasher correspond to the kitchen is 1; the probability that the smart clothes drying rack corresponds to the balcony is 1; the probability that the washing machine corresponds to the balcony is 0.7, and the probability that it corresponds to the bathroom is 0.3; the probability that the air conditioner cabinet corresponds to the living room is 0.9, and the probability that it corresponds to the bedroom is 0.1; the probability that the air conditioner wall unit corresponds to the bedroom is 0.7, and the probability that it corresponds to the living room is 0.2, and the probability that it corresponds to the dining room is 0.1; the probability that the refrigerator corresponds to the kitchen is 0.6, and the probability that it corresponds to the dining room is 0.3, and the probability that it corresponds to the balcony is 0.1; the probability that the TV corresponds to the bedroom is 0.4, and the probability that it corresponds to the living room is 0.6. Of course, the above correspondence relationships can be adjusted according to actual needs, and are not limited here.

[0093] Based on the device type of the smart device in the room area and the first preset correspondence, the probability that the room area belongs to each room type can be obtained. Continuing with the above-mentioned first preset correspondence, if the smart devices in the room area include a TV and an air conditioner cabinet, by querying the first preset correspondence, the probability that the TV corresponds to the bedroom is 0.4, the probability that the TV corresponds to the living room is 0.6, the probability that the air conditioner cabinet corresponds to the living room is 0.9, and the probability that the air conditioner cabinet corresponds to the bedroom is 0.1. In the specific implementation process, if there is a probability that multiple smart devices belong to the same room type, the maximum value of the multiple probabilities can be used as the probability that the room area belongs to the room type. Then, since the probability that the TV corresponds to the living room is 0.6 and the probability that the air conditioner cabinet corresponds to the living room is 0.9, the probability that the room area is the living room is 0.9. In addition, since the probability that the TV corresponds to the bedroom is 0.4 and the probability that the air conditioner cabinet corresponds to the bedroom is 0.1, the probability that the room area is the bedroom is 0.4. Furthermore, by comparing the probabilities that the room area belongs to different room types, the room type with the highest probability is taken as the final room type. Then, using the above example, the probability that the room area is a living room is 0.9, and the probability that it is a bedroom is 0.4, that is, the probability that the room area belongs to a living room is greater, and the room type of the room area can be determined as a living room.

[0094] For each room area, the room type can be determined in this way and the room type can be marked on the second map.

[0095] The third implementation method: determine the relative area between each room area and the whole house area; for each room area, based on the relative area of ​​the room area and a second preset correspondence between the relative area of ​​the room and the probabilities of Q room types, determine the probability that the room area belongs to the Q room types, where Q is a positive integer; for each room area, based on the probability that the room area belongs to the Q room types, determine the room type of the room area, and mark the room type of the room area on the second whole house map.

[0096] Specifically, if there is no smart device in the room, the room type can be determined based on the relative area of ​​the room area. It is understandable that different room areas correspond to different room types. For example, the area of ​​the living room is usually the largest, and the area of ​​the bathroom is the smallest. Therefore, in the embodiment of this specification, a second preset correspondence between the relative area of ​​the room and the probability of Q room types can be pre-set, where the Q room types can be set according to actual needs, such as the Q room types include living room, bedroom, bathroom, kitchen, balcony, etc.

[0097] In some embodiments, the second preset correspondence relationship may be: the probability that the largest relative area corresponds to the living room is 0.8, and the probability that it corresponds to the bedroom is 0.2; the probability that the smallest relative area corresponds to the bathroom is 0.8, and the probability that it corresponds to the kitchen is 0.2; the probability that other relative areas correspond to the bedroom is 0.8, the probability that they correspond to the kitchen is 0.1, and the probability that they correspond to the bathroom is 0.1. Of course, the above correspondence relationship can be adjusted according to actual needs and is not limited here.

[0098] In the embodiments of this specification, the proportion of the actual area of ​​the room area in the whole house area can be used as the relative area, and each room area can be arranged according to the area size, and the relative position of each room area in the arrangement result can be used to represent the relative area.

[0099] In some embodiments, after obtaining the actual area of ​​each room area, each room area can be arranged according to the actual area size. For example, for the room area with the largest area, since the probability of the room corresponding to the living room is 0.8 and the probability of the room corresponding to the bedroom is 0.2, the room type corresponding to the maximum probability can be used as the type of the room area. Then, it can be determined that the room type of the room area is a living room.

[0100] For each room area, the room type can be determined in this way and the room type can be marked on the second map.

[0101] The fourth implementation method: identifying the entrance of each room area and determining the entrance size of each room area; for each room area, based on the entrance size of the room area and a third preset correspondence between the entrance size and the S room type probabilities, determining the probability that the room area belongs to the S room types, where S is a positive integer; for each room area, based on the probability that the room area belongs to the S room types, determining the room type of the room area, and marking the room type of the room area on the second whole-house map.

[0102] Specifically, when constructing a whole house map, since the entrance area of ​​each room is not blocked, the entrance size of each room area can be obtained from the divided whole house map. It is understandable that different entrance sizes will correspond to different room types. Therefore, in the embodiment of this specification, a third preset correspondence between the entrance size and the probability of S room types can be pre-set, wherein the S room types can be set according to actual needs, such as the S room types include living room, bedroom, bathroom, kitchen, balcony, etc.

[0103] In some embodiments, the third preset corresponding relationship may be: the probability that the entrance size is greater than or equal to 3m corresponds to the living room is 1; the probability that the entrance size is less than 3m and greater than 1m corresponds to the kitchen is 0.8, and the probability that it corresponds to the study is 0.2; the probability that the entrance size is less than or equal to 1m corresponds to the bedroom is 0.7, and the probability that it corresponds to the bathroom is 0.3. Of course, the above corresponding relationship can be adjusted according to actual needs and is not limited here.

[0104] For example, if the entrance size of the room area is 2m, the probability that the room area corresponds to the kitchen is 0.8 and the probability that the room area corresponds to the study is 0.2. The room type corresponding to the maximum probability can be used as the room type of the room area, and the room type of the room area is the living room.

[0105] For each room area, the room type can be determined in this way and the room type can be marked on the second map.

[0106] It should be noted that, considering that only one of the above implementation methods may result in errors or fail to determine the room types of all room areas, the above four implementation methods can be combined with each other. For example, the second implementation method and the third implementation method can be combined as follows: for a certain room area, determine the first probability of belonging to each room type according to the room area, and then determine the second probability of belonging to each room type according to the equipment type of the room area. For each room type, compare the first probability and the second probability, and take the maximum probability of the two as the final probability of the room type, then compare the final probabilities corresponding to each room type, and select the maximum final probability as the room type of the room area.

[0107] In some implementations, the second implementation, the third implementation, and the fourth implementation may be combined. Then, when determining the room type, the following steps may be performed:

[0108] For each room area, based on the device type of the smart device in the room area and the first preset correspondence between the device type and the P room type probabilities, determine the probability that the room area belongs to the P room types; based on the relative area of ​​the room area and the second preset correspondence between the relative area of ​​the room and the Q room type probabilities, determine the probability that the room area belongs to the Q room types; based on the entrance size of the room area and the third preset correspondence between the entrance size and the S room type probabilities, determine the probability that the room area belongs to the S room types; for each room area, based on the maximum probability that the room area belongs to the P room types, the maximum probability that the room area belongs to the Q room types, and the maximum probability that the room area belongs to the S room types, determine the room type of the room area, so as to mark the room type of the room area on the second whole-house map.

[0109] Specifically, determine the probability P of a room area belonging to a certain room type r It can be determined by the following formula:

[0110] P r =max(max(P E1 :P En ), P area , P entry )

[0111] Among them, P E is the probability that a single appliance is located in a certain room type, P area is the probability that the relative area of ​​a room is a certain room type, P entry is the probability that the room entrance size is a certain room type.

[0112] Let's take an example to illustrate the above formula. If a room has the largest relative area, there are two home appliances, a TV and an air conditioner cabinet, and the room entrance size is greater than 3m, by querying the first preset corresponding relationship, the second preset corresponding relationship, and the third preset corresponding relationship, we can get: the probability P that the TV belongs to the living room E1 is 0.6, the probability P that the air conditioner cabinet belongs to the living room E2 is 0.9, and the probability P that the largest relative area belongs to the living room area is 0.8, and the probability P that the entrance size is greater than 3m belongs to the living room entry is 1, and the probability P of the room type being a living room is obtained by substituting it into the above formula. r for:

[0113] P r =max(max(0.6,0.9),0.8,1)=1

[0114] Then, determine that the room type is a living room.

[0115] It should be noted that the probability of a room belonging to each room type can be determined in the above manner, and then the room type with the greatest probability is used as the room type of the room.

[0116] To better understand the whole house map generation method provided in the embodiments of this specification, please refer to Figure 2 , is a flow chart of a method for generating a whole house map provided in an embodiment of this specification. In this process, a mobile robot is used to realize mapping and partitioning of the whole house area, including the following steps:

[0117] Step S201: Mobile robot builds map;

[0118] Step S202: Determine whether a smart device is detected, if so, execute step S203, if not, execute step S205;

[0119] Step S203: Calculating the distance between the smart device and the mobile robot;

[0120] Step S204: Calculate the location information of the smart device;

[0121] Step S205: Determine whether the map is completed, if yes, execute step S206, if no, execute step S201;

[0122] Step S206: The mobile robot divides the whole house map into zones;

[0123] Step S207: performing minimum rectangle fitting on the boundary contour of each partition;

[0124] Step S208: Determine the room type of each partition;

[0125] Step S209: marking the location information and device type of the smart devices in each partition.

[0126] To sum up, the solution provided in the embodiments of this specification can automatically determine the room type of each room, as well as the location and device type of each smart device, and generate a digital floor plan. The operation is simple and easy, and no human intervention is required. While improving the positioning accuracy of smart devices, it also improves the user experience.

[0127] Based on the same inventive concept, the embodiment of the present invention provides a whole house map generating device, referring to Figure 3 As shown, the device comprises:

[0128] An acquisition module 301 is used to acquire a first whole-house map corresponding to the whole-house area;

[0129] The smart device identification module 302 is used to identify N smart devices in the whole house area and determine the location information and device type of each smart device during the process of the mobile robot scanning the whole house area, where N is a positive integer;

[0130] The processing module 303 is used to mark the N smart devices on the first whole-house map based on the location information and device type of each smart device to generate a second whole-house map.

[0131] In some implementations, the smart device identification module 302 is configured to:

[0132] During the process of the mobile robot scanning the whole house area, broadcasting a first positioning request to the current environment through a target channel;

[0133] If first feedback information for the first positioning request is received, the device sending the first feedback information is used as the target smart device among the N smart devices, wherein the feedback information includes a device identifier and a device type of the corresponding device.

[0134] In some embodiments, the device further comprises:

[0135] A sending module, used for controlling the mobile robot to broadcast a second positioning request to the current environment at M positions respectively, wherein the M positions are different and M is an integer greater than 1;

[0136] a signal strength determination module, configured to receive, for each location, second feedback information for the second positioning request at the location, and determine a signal reception strength for receiving the second feedback information, wherein the device identifier in the second feedback information is the same as the device identifier in the first feedback information;

[0137] The smart device identification module 302 is used to determine the location information of the target smart device based on the signal reception strength corresponding to each location; and use the device type in the first feedback information as the device type of the target smart device.

[0138] In some implementations, the smart device identification module 302 is configured to:

[0139] Determine an environmental attenuation factor of a current environment and a preset signal reception strength when the target smart device is at a preset distance;

[0140] For each of the locations, determining a distance between the target smart device and the location based on the environmental attenuation factor, the preset signal reception strength, and the signal reception strength corresponding to the location;

[0141] Based on the distance between the target smart device and each of the locations, the location information of the target smart device on the first whole-house map is determined.

[0142] In some embodiments, the device further comprises:

[0143] A screening module, used to screen out K smart devices bound to room types from the N smart devices;

[0144] The first room type determination module is used to determine the room type of the room area where the K smart devices are located based on the location information of each smart device among the K smart devices and the room type bound to each smart device, so as to mark the room type of the room area where the K smart devices are located on the second whole-house map.

[0145] In some embodiments, the whole house area includes multiple room areas, and the device further includes:

[0146] A device determination module, configured to determine a smart device included in each of the plurality of room areas based on the location information of the N smart devices;

[0147] A first probability determination module is used to determine, for each room area, a probability that the room area belongs to the P room types based on the device type of the smart device in the room area and a first preset correspondence between the device type and the P room type probabilities, where P is a positive integer;

[0148] The second room type determination module is used to determine the room type of each room area based on the probability that the room area belongs to the P room types, so as to mark the room type of the room area on the second whole-house map.

[0149] In some embodiments, the whole house area includes multiple room areas, and the device further includes:

[0150] A relative area determination module, used to determine the relative area between each room area and the whole house area;

[0151] A second probability determination module is used to determine, for each room area, the probability that the room area belongs to the Q room types based on the relative area of ​​the room area and a second preset correspondence between the relative area of ​​the room and the probabilities of the Q room types, where Q is a positive integer;

[0152] The third room type determination module is used to determine the room type of each room area based on the probability that the room area belongs to the Q room types, so as to mark the room type of the room area on the second whole-house map.

[0153] In some embodiments, the whole house area includes multiple room areas, and the device further includes:

[0154] An entrance size determination module, used for identifying the entrance of each room area and determining the entrance size of each room area;

[0155] A third probability determination module is used to determine, for each room area, a probability that the room area belongs to the S room types based on the entrance size of the room area and a third preset correspondence between the entrance size and the probabilities of the S room types, where S is a positive integer;

[0156] The fourth room type determination module is used to determine the room type of each room area based on the probability that the room area belongs to the S room types, so as to mark the room type of the room area on the second whole-house map.

[0157] Regarding the above-mentioned device, the specific functions of each module therein have been described in detail in the embodiment of the whole-house map generation method provided in the embodiment of this specification, and will not be elaborated here.

[0158] Based on the same inventive concept, an embodiment of the present invention provides an electronic device, referring to Figure 4 As shown, it includes: a memory 404, a processor 402, and a computer program stored in the memory 404 and executable on the processor 402. When the processor 402 executes the program, any implementation method of the whole-house map generation method embodiment is implemented.

[0159] Among them, Figure 4 In the embodiment of the present invention, a bus architecture (represented by bus 400) is shown, which may include any number of interconnected buses and bridges, and bus 400 links various circuits including one or more processors represented by processor 402 and memory represented by memory 404. Bus 400 may also link various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and are therefore not further described herein. Bus interface 405 provides an interface between bus 400 and receiver 401 and transmitter 403. Receiver 401 and transmitter 403 may be the same element, namely a transceiver, providing a unit for communicating with various other devices over a transmission medium. Processor 402 is responsible for managing bus 400 and general processing, while memory 404 may be used to store data used by processor 402 when performing operations.

[0160] The functions described herein may be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions may be stored as one or more instructions or codes on a computer-readable medium or transmitted via a computer-readable medium. Other examples and implementations are within the scope and spirit of the present invention and the appended claims. For example, due to the nature of software, the functions described above may be implemented using software executed by a processor, hardware, firmware, hard wiring, or a combination of any of these. In addition, each functional unit may be integrated into a processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit.

[0161] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0162] The units described as separate components may or may not be physically separated, and the components of the control device may or may not be physical units, that is, they may be located in one place or distributed in multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0163] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0164] The above description is only an embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present invention shall be included in the scope of the claims of the present invention.

Claims

1. A method for generating a whole house map, characterized in that: The whole house map is constructed by mobile robots, including: Obtaining a first whole-house map corresponding to the whole-house area; In the process of the mobile robot scanning the whole house area, N smart devices in the whole house area are identified, and the location information and device type of each smart device are determined, where N is a positive integer; Based on the location information and device type of each smart device, the N smart devices are marked on the first whole-house map to generate a second whole-house map.

2. The method according to claim 1, characterized in that In the process of the mobile robot scanning the whole house area, identifying N smart devices in the whole house area includes: During the process of the mobile robot scanning the whole house area, broadcasting a first positioning request to the current environment through a target channel; If first feedback information for the first positioning request is received, the device sending the first feedback information is used as the target smart device among the N smart devices, wherein the feedback information includes a device identifier and a device type of the corresponding device.

3. The method according to claim 2, characterized in that If first feedback information for the first positioning request is received, after the device sending the first feedback information is used as a target smart device among the N smart devices, the method further includes: Control the mobile robot to broadcast a second positioning request to the current environment at M positions respectively, wherein the M positions are different and M is an integer greater than 1; For each location, receiving second feedback information for the second positioning request at the location, and determining a signal reception strength for receiving the second feedback information, wherein the device identifier in the second feedback information is the same as the device identifier in the first feedback information; Determining the location information and device type of each smart device includes: Determining the location information of the target smart device based on the signal reception strength corresponding to each of the locations; and The device type in the first feedback information is used as the device type of the target smart device.

4. The method according to claim 3, characterized in that The determining the location information of the target smart device based on the signal reception strength corresponding to each location includes: Determine an environmental attenuation factor of a current environment and a preset signal reception strength when the target smart device is at a preset distance; For each of the locations, determining a distance between the target smart device and the location based on the environmental attenuation factor, the preset signal reception strength, and the signal reception strength corresponding to the location; Based on the distance between the target smart device and each of the locations, the location information of the target smart device on the first whole-house map is determined.

5. The method according to claim 1, characterized in that The whole house area includes a plurality of room areas. Before generating the second whole house map, the method further includes: Filter out K smart devices bound to room types from the N smart devices; Based on the location information of each smart device among the K smart devices and the room type bound to each smart device, determine the room type of the room area where the K smart devices are located, so as to mark the room type of the room area where the K smart devices are located on the second whole-house map.

6. The method according to claim 1, characterized in that The whole house area includes a plurality of room areas. Before generating the second whole house map, the method further includes: Determine, based on the location information of the N smart devices, a smart device included in each of the multiple room areas; For each room area, based on the device type of the smart device in the room area and a first preset correspondence between the device type and the P room type probabilities, determine the probability that the room area belongs to the P room types, where P is a positive integer; For each room area, based on the probability that the room area belongs to the P room types, the room type of the room area is determined, so as to mark the room type of the room area on the second whole-house map.

7. The method according to claim 1, characterized in that The whole house area includes a plurality of room areas. Before generating the second whole house map, the method further includes: Determine the relative area between each room area and the whole house area; For each room area, based on the relative area of ​​the room area and a second preset correspondence between the relative area of ​​the room and the probabilities of the Q room types, determine the probability that the room area belongs to the Q room types, where Q is a positive integer; For each room area, based on the probability that the room area belongs to the Q room types, the room type of the room area is determined, so as to mark the room type of the room area on the second whole-house map.

8. The method according to claim 1, characterized in that The whole house area includes a plurality of room areas. Before generating the second whole house map, the method further includes: Identify the entrance to each room area and determine the size of the entrance to each room area; For each room area, based on the entrance size of the room area and a third preset correspondence between the entrance size and the S room type probabilities, determine the probability that the room area belongs to the S room types, where S is a positive integer; For each room area, based on the probability that the room area belongs to the S room types, the room type of the room area is determined, so as to mark the room type of the room area on the second whole-house map.

9. A whole house map generating device, characterized in that: The whole house map is constructed by mobile robots, including: An acquisition module, used for acquiring a first whole-house map corresponding to the whole-house area; An intelligent device identification module, used to identify N intelligent devices in the whole house area and determine the location information and device type of each intelligent device during the process of the mobile robot scanning the whole house area, where N is a positive integer; A processing module is used to mark the N smart devices on the first whole-house map based on the location information and device type of each smart device to generate a second whole-house map.

10. An electronic device, characterized in that: include: A memory, a processor, 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 8 when executing the program.

11. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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