CN111528739A - Sweeping mode switching method and system, electronic equipment, storage medium and sweeper - Google Patents
Sweeping mode switching method and system, electronic equipment, storage medium and sweeper Download PDFInfo
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- CN111528739A CN111528739A CN202010386251.3A CN202010386251A CN111528739A CN 111528739 A CN111528739 A CN 111528739A CN 202010386251 A CN202010386251 A CN 202010386251A CN 111528739 A CN111528739 A CN 111528739A
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
- A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
- A47L11/24—Floor-sweeping machines, motor-driven
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
- A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
- A47L11/40—Parts or details of machines not provided for in groups A47L11/02 - A47L11/38, or not restricted to one of these groups, e.g. handles, arrangements of switches, skirts, buffers, levers
- A47L11/4011—Regulation of the cleaning machine by electric means; Control systems and remote control systems therefor
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
- A47L2201/00—Robotic cleaning machines, i.e. with automatic control of the travelling movement or the cleaning operation
- A47L2201/06—Control of the cleaning action for autonomous devices; Automatic detection of the surface condition before, during or after cleaning
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Abstract
The invention provides a sweeping mode switching method, a sweeping mode switching system, electronic equipment, a storage medium and a sweeper. The method comprises the following steps: carrying out scene recognition in the sweeping process of the sweeper; determining a cleaning mode corresponding to a scene recognition result according to a preset corresponding relation between a scene and the cleaning mode; and controlling the sweeper to switch to a sweeping mode corresponding to the scene recognition result. According to the sweeping machine, the corresponding sweeping modes are switched according to different scenes in the sweeping process of the sweeping machine, the sweeping machine is controlled to work in a proper sweeping mode, the problem that the sweeping efficiency of the whole environment is low due to the fact that a single sweeping mode is adopted can be effectively solved, and the sweeping efficiency is improved.
Description
Technical Field
The invention relates to the technical field of sweeper, in particular to a sweeping mode switching method, a sweeping mode switching system, electronic equipment, a storage medium and a sweeper.
Background
At present, with the continuous development of intellectualization, the intellectualization is embodied in the life. The floor sweeping robot is used as a mobile robot and can realize indoor space division, complete sweeping, automatic recharging and other functions. The degree of dirtying of each area in the environment to be cleaned is usually different, and the existing sweeping robot usually adopts a single sweeping mode to complete sweeping of the whole environment, so that the time consumption is long, the power consumption is large, and the sweeping efficiency is low.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a sweeping mode switching method, a sweeping mode switching system, electronic equipment, a storage medium and a sweeper.
In a first aspect, the present invention provides a cleaning mode switching method, including:
carrying out scene recognition in the sweeping process of the sweeper;
determining a cleaning mode corresponding to a scene recognition result according to a preset corresponding relation between a scene and the cleaning mode;
and controlling the sweeper to switch to a sweeping mode corresponding to the scene recognition result.
Further, the scene recognition is performed in the sweeping process of the sweeper, and the scene recognition method comprises the following steps:
acquiring shape data and image data in real time in the sweeping process of the sweeper;
carrying out object recognition processing on the shape data and the image data, and determining an object corresponding to the shape data and the image data;
and carrying out scene recognition processing on the object by using a preset scene recognition algorithm, and determining a scene corresponding to the object.
Further, the performing an object recognition process on the shape data and the image data to determine an object corresponding to the shape data and the image data includes:
extracting the characteristics of the shape data and the image data by using a preset characteristic extraction algorithm;
comparing the extracted characteristic data with the characteristic data of a pre-stored object model;
and determining an object corresponding to the shape data and the image data.
Furthermore, the pre-stored object model is obtained by training through a deep learning algorithm by using feature data of different objects.
In a second aspect, the present invention provides a cleaning mode switching system, including:
the recognition module is used for carrying out scene recognition in the sweeping process of the sweeper;
the determining module is used for determining a cleaning mode corresponding to the scene recognition result according to the preset corresponding relation between the scene and the cleaning mode;
and the control module is used for controlling the sweeper to switch to the cleaning mode corresponding to the scene recognition result.
In a third aspect, the present invention provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer program is executed by the processor to implement the cleaning mode switching method according to the first aspect.
In a fourth aspect, the present invention provides a storage medium having stored thereon a computer program which, when executed by one or more processors, implements the cleaning mode switching method according to the first aspect.
In a fifth aspect, the present invention provides a sweeper, comprising:
the image acquisition system is connected with the processing device and is used for acquiring shape data and image data in real time in the sweeping process of the sweeper;
the processing device is used for acquiring the shape data and the image data acquired by the image acquisition system, identifying scenes, determining a cleaning mode corresponding to a scene identification result according to a preset corresponding relation between the scenes and the cleaning mode, and controlling the sweeper to switch to the cleaning mode corresponding to the scene identification result.
Still further, the image acquisition system comprises:
the structured light system is connected with the processing device and is used for acquiring shape data in real time in the sweeping process of the sweeper;
the camera is connected with the processing device and used for collecting image data in real time in the sweeping process of the sweeper.
Still further, the processing apparatus includes:
the GPU is connected with the image acquisition system and is used for acquiring shape data and image data in real time in the sweeping process of the sweeper; carrying out object recognition processing on the shape data and the image data, and determining an object corresponding to the shape data and the image data; carrying out scene recognition processing on the object by using a preset scene recognition algorithm, and determining a scene corresponding to the object; determining a cleaning mode corresponding to the scene recognition result according to a preset corresponding relation between the scene and the cleaning mode, and controlling the sweeper to switch to the cleaning mode corresponding to the scene recognition result;
and the AI chip is connected with the GPU and used for storing a preset scene recognition algorithm.
The invention has the beneficial effects that: the sweeping machine is controlled to work in a proper sweeping mode according to the corresponding sweeping modes switched according to different scenes in the sweeping process, the problem that the sweeping efficiency is low when a single sweeping mode is adopted to complete the whole environment can be effectively solved, and the sweeping efficiency is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a schematic view of a sweeper according to a first embodiment of the present invention;
fig. 2 is a flowchart of a cleaning mode switching method according to an embodiment of the present invention;
fig. 3 is a flowchart of another sweeping mode switching method according to an embodiment of the present invention;
fig. 4 is a flowchart of another sweeping mode switching method according to an embodiment of the present invention;
fig. 5 is a block diagram of a cleaning mode switching system according to a second embodiment of the present invention;
fig. 6 is a block diagram of a sweeper according to a fifth embodiment of the present invention;
fig. 7 is a schematic diagram of a prior art image acquisition system.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
Example one
Different types of environmental objects exist in the cleaning environment of the sweeper, such as tables, chairs, beds, tea tables and the like, and also include various types of objects to be cleaned, such as paper scraps, dust, oil stains, water and the like, and different objects are usually present in different scenes, such as a bedroom on a bed. The degree of cleaning required for each scene is usually different, for example, a bedroom only needs to be cleaned normally, and a restaurant needs to be cleaned forcefully. Therefore, the present embodiment provides a method for switching a sweeping mode, which is applied to a sweeper, for example, the sweeper shown in fig. 1, please refer to fig. 2, and the method includes the following steps:
s100, carrying out scene recognition in the sweeping process of the sweeper;
s200, determining a cleaning mode corresponding to a scene recognition result according to a preset corresponding relation between a scene and the cleaning mode;
and step S300, controlling the sweeper to switch to a sweeping mode corresponding to the scene recognition result.
The sweeping mode of the sweeper of the present embodiment may include, but is not limited to: a normal cleaning mode, a powerful cleaning mode, and an important cleaning mode. Scenarios may include, but are not limited to: bedrooms, kitchens, restaurants, areas of trash accumulation, etc. For example, the preset correspondence relationship between the scene and the sweeping mode may include: the bedroom corresponds to a common cleaning mode, the kitchen corresponds to a powerful cleaning mode, and the garbage collection area corresponds to a key cleaning mode. Therefore, when the current scene is identified as the kitchen in the sweeping process of the sweeper, the sweeping mode is determined to be the powerful sweeping mode, and the sweeper is controlled to work under the powerful sweeping mode.
Because some scenes are high in utilization rate and easy to be dirty, after cleaning is carried out according to a fixed cleaning mode, objects to be cleaned possibly remain after cleaning, and cleaning needs to be carried out again, so that the cleaning time is prolonged, more power consumption is brought, and the cleaning efficiency is low. And some scenes have low utilization rate, do not usually have too many objects to clean, do not need to clean for a long time with great strength, clean the back according to fixed mode of cleaning, cause the waste of time and electric energy, and clean inefficiency. Therefore, different scenes are matched with different cleaning modes in the embodiment, and the cleaning modes of the sweeper are switched in real time through scene recognition so as to improve the cleaning efficiency.
It is understood that the cleaning time, cleaning power and power consumption of the different cleaning modes may be the same or different, for example, in some cases, the cleaning modes are ordered as follows: (1) cleaning time length: powerful cleaning mode > focused cleaning mode > ordinary cleaning mode; (2) cleaning force: powerful cleaning mode > focused cleaning mode > ordinary cleaning mode; (3) power consumption amount: powerful cleaning mode > focused cleaning mode > ordinary cleaning mode.
According to the embodiment, the sweeping machine is controlled to work in a proper sweeping mode according to the corresponding sweeping modes switched according to different scenes in the sweeping process, the problem that the sweeping efficiency is low when a single sweeping mode is adopted to complete the whole environment can be effectively solved, and the sweeping efficiency is improved.
Preferably, the present embodiment further provides a cleaning mode switching method as shown in fig. 3, and the step S100 may further include the following sub-steps:
step S110, acquiring shape data and image data in real time in the sweeping process of the sweeper;
step S120, carrying out object recognition processing on the shape data and the image data, and determining an object corresponding to the shape data and the image data;
step S130, carrying out scene recognition processing on the object by using a preset scene recognition algorithm, and determining a scene corresponding to the object.
Specifically, when scene recognition is performed, object recognition processing is performed on shape data and image data acquired in real time, the shape data can reflect shape characteristics of an object, the image data can reflect plane characteristics and color characteristics of the object, the shape data and the image data are used as data of object recognition, object recognition accuracy can be improved, the problems that the accuracy of object recognition is not high and results are prone to misjudgment or no result is recognized by only using the image data are solved, meanwhile, the object is used as an important characteristic of different scenes, scene recognition processing is performed on the object by using a preset scene recognition algorithm, a scene corresponding to the object can be accurately determined, and accordingly cleaning mode switching can be performed subsequently, and it can be understood that one or more objects may be obtained in results of the object recognition processing.
Preferably, the preset scene recognition algorithm may be, but is not limited to: one of AlexNet, VGG-Net and ResNet.
Further, the present embodiment further provides a cleaning mode switching method as shown in fig. 4, and the step S120 may further include the following sub-steps:
step S121, extracting the characteristics of the shape data and the image data by using a preset characteristic extraction algorithm;
step S122, comparing the extracted characteristic data with characteristic data of a pre-stored object model;
and step S123, determining the object corresponding to the shape data and the image data.
Preferably, the preset feature extraction algorithm may be, but is not limited to: scale-invariant feature transform (SIFT), Histogram of Oriented Gradients (HOG) or Local Binary Patterns (LBP).
Preferably, the pre-stored object model is obtained by training with a deep learning algorithm using feature data of different objects, and the deep learning algorithm may be, but is not limited to, a Convolutional Neural Network (CNN). The pre-stored object models may include, but are not limited to: environmental object models, such as models of tables, chairs, sofas, tea tables, beds, greens, doors, walls, etc.; models of objects to be cleaned, e.g. paper dust, dirt etc. After the extracted feature data is compared with the feature data of the pre-stored object model, the object corresponding to the currently acquired shape data and image data can be determined from the plurality of pre-stored object models.
In the embodiment, the preset feature extraction algorithm is used for extracting the features of the shape data and the image data which are acquired in real time, the objects corresponding to the shape data and the image data are determined from the plurality of pre-stored object models, the object identification accuracy can be improved, the identified objects are used as important features of scenes, the scenes where the sweeper is located are determined by the preset scene identification algorithm, the sweeping mode can be switched in real time according to the scenes where the sweeper is located, the sweeper can work in the optimal sweeping mode, and the sweeping efficiency is improved.
Example two
Correspondingly to the embodiment, the embodiment provides a cleaning mode switching system, as shown in fig. 5, including the following modules:
the recognition module 100 is used for carrying out scene recognition in the sweeping process of the sweeper;
the determining module 200 is configured to determine a cleaning mode corresponding to the scene recognition result according to a preset corresponding relationship between the scene and the cleaning mode;
and the control module 300 is configured to control the sweeper to switch to the sweeping mode corresponding to the scene recognition result.
It is understood that the identification module 100 may be configured to execute the step S100 in the first embodiment, the determination module 200 may be configured to execute the step S200 in the first embodiment, and the control module 300 may be configured to execute the step S300 in the first embodiment, where specific contents of each step are please refer to the first embodiment, and are not described herein again.
According to the embodiment, the sweeping machine is controlled to work in a proper sweeping mode according to the corresponding sweeping modes switched according to different scenes in the sweeping process, the problem that the sweeping efficiency is low when one sweeping mode is adopted to complete the whole environment can be effectively solved, and the sweeping efficiency is improved.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, or they may be separately fabricated into various integrated circuit modules, or multiple modules or steps thereof may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
EXAMPLE III
The present embodiment provides an electronic device, which includes a memory and a processor, where the memory stores a computer program, and the computer program is executed by the processor to implement the cleaning mode switching method according to the first embodiment.
The Processor may be an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a controller, a microcontroller, a microprocessor, or other electronic components. For details of the cleaning mode switching method, please refer to embodiment one, which is not described herein again.
Example four
The present embodiment provides a storage medium, which stores a computer program, and when the computer program is executed by one or more processors, the cleaning mode switching method of the first embodiment is implemented.
The storage medium may be a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application mall, etc. For details of the cleaning mode switching method, please refer to embodiment one, which is not described herein again.
EXAMPLE five
The present embodiment provides a sweeper, as shown in fig. 6, including:
the image acquisition system is connected with the processing device and is used for acquiring shape data and image data in real time in the sweeping process of the sweeper;
the processing device is used for acquiring the shape data and the image data acquired by the image acquisition system, identifying scenes, determining a cleaning mode corresponding to a scene identification result according to a preset corresponding relation between the scenes and the cleaning mode, and controlling the sweeper to switch to the cleaning mode corresponding to the scene identification result.
According to the embodiment, the shape data and the image data are collected in real time through the image collection system in the sweeping process of the sweeper, scene recognition is carried out according to the shape data and the image data collected in real time, corresponding sweeping modes can be switched according to different scenes, the sweeper is controlled to work in the best sweeping mode, the problem that the sweeping efficiency is low when one sweeping mode is adopted to complete the sweeping of the whole environment can be effectively avoided, and the sweeping efficiency is improved.
Preferably, the image acquisition system may include:
and the structured light system is connected with the processing device and is used for acquiring shape data in real time in the sweeping process of the sweeper. The structured light system can be realized by adopting a structure in the prior art, and comprises a structured light emitter and a structured light receiver, wherein the structured light emitter is used for emitting structured light detection light, and the structured light receiver is used for receiving the reflected structured light so as to obtain the shape data of the object.
The camera is connected with the processing device and used for collecting image data in real time in the sweeping process of the sweeper.
For example, the image capturing system may be an image capturing system shown in fig. 7 in the prior art, but is not limited thereto, a camera may be installed in front of or on both sides of the structured light system to capture image data and shape data at the same time, and the installation position of the camera does not affect the structured light system to capture shape data, and is not limited to the front of or on both sides of the structured light system.
Preferably, the processing means may comprise:
the GPU, namely an image processor, is connected with the image acquisition system and is used for acquiring shape data and image data in real time in the sweeping process of the sweeper; carrying out object recognition processing on the shape data and the image data, and determining an object corresponding to the shape data and the image data; carrying out scene recognition processing on the object by using a preset scene recognition algorithm, and determining a scene corresponding to the object; and determining a cleaning mode corresponding to the scene recognition result according to the preset corresponding relation between the scene and the cleaning mode, and controlling the sweeper to switch to the cleaning mode corresponding to the scene recognition result.
And the AI chip is connected with the GPU and is used for storing a preset scene recognition algorithm and a preset feature extraction algorithm.
Since a GPU (Graphics Processing Unit) needs to perform feature extraction on shape data and image data by using a preset feature extraction algorithm, a scene recognition Processing needs to be performed on an object by using a preset scene recognition algorithm in a scene recognition Processing process, and the preset feature extraction algorithm and the preset scene recognition algorithm occupy a large amount of storage space, in order to improve the speed and efficiency of the object recognition Processing and the scene recognition Processing of the GPU and ensure the real-time performance of mode switching, the preset feature extraction algorithm and the preset scene recognition algorithm are stored by an AI chip, so that the storage pressure of the GPU is reduced and the Processing capability is improved.
In the embodiment, object identification processing is carried out on the shape data and the image data through the GPU, scene identification is further achieved, compared with a CPU, the processing speed is greatly improved, for the sweeper, the shape data and the image data of objects in the environment are accurately acquired through the structured light system and the camera, the GPU carries out object identification processing and scene identification processing on the shape data and the image data, the processing speed is effectively improved, the sweeping mode is switched in real time according to the scene, the scene identification speed is high, mode switching delay is avoided, the sweeping efficiency is obviously improved, and meanwhile the power consumption of the sweeper can be reduced.
Further, the sweeper of the embodiment further comprises a storage system, wherein the storage system is used for storing the pre-stored object model required by object identification, the pre-stored object model in the embodiment is stored in the storage system, the storage space of the GPU and the storage space of the AI chip are not occupied, and the operation speed of the GPU is not influenced. The pre-stored object model is obtained by training feature data of different objects by using a deep learning algorithm, and after the extracted feature data is compared with the feature data of the pre-stored object model in the object recognition process, an object corresponding to the currently acquired shape data and image data can be determined from the plurality of pre-stored object models, and the deep learning algorithm used may be, but is not limited to, a Convolutional Neural Network (CNN). The pre-stored object models may include, but are not limited to: environmental object models, such as models of tables, chairs, sofas, tea tables, beds, greens, doors, walls, etc.; models of objects to be cleaned, e.g. paper dust, dirt etc.
The storage system may further store a computer program, and the computer program, when executed by the GPU, implements the cleaning mode switching method according to the first embodiment.
The application environment of the sweeper is likely to change, so that the pre-stored object model can be updated at any time according to the application environment of the sweeper to adapt to object recognition and scene recognition of the sweeper in different environments, and the pre-stored object model is obtained through off-line training, so that real-time processing time is not required to be occupied.
It can be understood that, the sweeper in this embodiment may further include: the device comprises a traveling system, a driving system, a sensor system and a cleaning system.
Wherein, traveling system includes: left and right traveling wheels and universal wheels; the drive system includes: the left and right travelling wheel driving motors and the universal wheel motor; the driving system can drive the walking system to realize the walking mode switching, for example, the walking mode can comprise a normal walking mode, an acceleration walking mode and a deceleration walking mode.
In some cases, the sweeper may be controlled to switch to the corresponding walking mode while controlling the sweeper to switch to the sweeping mode corresponding to the scene recognition result, and since requirements of different sweeping modes for the walking mode may be different, the corresponding walking mode may be switched while switching the sweeping mode in association with each other, for example, the following correspondence may exist between the sweeping mode and the walking mode:
the normal cleaning mode corresponds to the normal walking mode;
the powerful cleaning mode corresponds to the deceleration walking mode;
the key cleaning mode corresponds to the deceleration traveling mode.
For example, when the sweeper recognizes that the current scene is a kitchen in the sweeping process, the sweeping mode is determined to be a powerful sweeping mode, and the sweeper is controlled to work in the powerful sweeping mode and switched to the speed reduction walking mode at the same time, so that the sweeper can walk at a reduced speed under a state of large sweeping force, and powerful sweeping of a kitchen area is achieved.
Further, the above cleaning system includes: the side brush, the rolling brush and the dust collecting box collect the object to be cleaned to the dust collecting box through the side brush and the rolling brush under different cleaning modes. The sensor system includes: the infrared sensor, cliff sensor, keep away barrier sensor etc. realize the different signal acquisition of machine of sweeping the in-process through these sensors.
The sweeper in this embodiment can realize control and display functions through APP, and APP can be realized in PC end or cell-phone end APP. For example, the APP provides a cleaning mode selection interface, the user can autonomously select the cleaning mode, and the remote control sweeper switches the cleaning mode. The APP provides a display interface, and a scene recognition result and a current cleaning mode of the sweeper are displayed.
In summary, according to the cleaning mode switching method, the cleaning mode switching system, the electronic device, the storage medium and the sweeper provided by the invention, the corresponding cleaning mode is switched according to different scenes in the sweeping process of the sweeper, the sweeper is controlled to work in a proper cleaning mode, the problem of low cleaning efficiency of the whole environment by adopting a single cleaning mode can be effectively avoided, and the cleaning efficiency is improved. Furthermore, the preset feature extraction algorithm is used for extracting features of the shape data and the image data which are acquired in real time, objects corresponding to the shape data and the image data are determined from the plurality of pre-stored object models, the object identification accuracy rate can be improved, the identified objects are used as important features of a scene, the scene where the sweeper is located is determined by the preset scene identification algorithm, the sweeping mode can be switched in real time according to the scene where the sweeper is located, and the sweeper can work in the optimal sweeping mode.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
It should be noted that, in the present invention, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. The term "comprising" is used to specify the presence of stated features, integers, steps, operations, elements, components, and/or groups thereof, but does not exclude the presence of other similar features, integers, steps, operations, components, or groups thereof.
Although the embodiments of the present invention have been described above, the above description is only for the convenience of understanding the present invention, and is not intended to limit the present invention. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A cleaning mode switching method is characterized by comprising the following steps:
carrying out scene recognition in the sweeping process of the sweeper;
determining a cleaning mode corresponding to a scene recognition result according to a preset corresponding relation between a scene and the cleaning mode;
and controlling the sweeper to switch to a sweeping mode corresponding to the scene recognition result.
2. The cleaning mode switching method according to claim 1, wherein the scene recognition during the cleaning process of the sweeper comprises:
acquiring shape data and image data in real time in the sweeping process of the sweeper;
carrying out object recognition processing on the shape data and the image data, and determining an object corresponding to the shape data and the image data;
and carrying out scene recognition processing on the object by using a preset scene recognition algorithm, and determining a scene corresponding to the object.
3. The cleaning mode switching method according to claim 2, wherein the performing of the object recognition processing on the shape data and the image data to determine the object corresponding to the shape data and the image data includes:
extracting the characteristics of the shape data and the image data by using a preset characteristic extraction algorithm;
comparing the extracted characteristic data with the characteristic data of a pre-stored object model;
and determining an object corresponding to the shape data and the image data.
4. The cleaning mode switching method according to claim 3, wherein the pre-stored object model is obtained by training with a deep learning algorithm using feature data of different objects.
5. A sweeping mode switching system, comprising:
the recognition module is used for carrying out scene recognition in the sweeping process of the sweeper;
the determining module is used for determining a cleaning mode corresponding to the scene recognition result according to the preset corresponding relation between the scene and the cleaning mode;
and the control module is used for controlling the sweeper to switch to the cleaning mode corresponding to the scene recognition result.
6. An electronic device comprising a memory and a processor, the memory having stored thereon a computer program that, when executed by the processor, implements the cleaning mode switching method according to any one of claims 1 to 4.
7. A storage medium having stored thereon a computer program which, when executed by one or more processors, implements the cleaning mode switching method according to any one of claims 1 to 4.
8. A sweeper is characterized by comprising:
the image acquisition system is connected with the processing device and is used for acquiring shape data and image data in real time in the sweeping process of the sweeper;
the processing device is used for acquiring the shape data and the image data acquired by the image acquisition system, identifying scenes, determining a cleaning mode corresponding to a scene identification result according to a preset corresponding relation between the scenes and the cleaning mode, and controlling the sweeper to switch to the cleaning mode corresponding to the scene identification result.
9. The sweeper of claim 8, wherein the image acquisition system comprises:
the structured light system is connected with the processing device and is used for acquiring shape data in real time in the sweeping process of the sweeper;
the camera is connected with the processing device and used for collecting image data in real time in the sweeping process of the sweeper.
10. The sweeper of claim 8, wherein the processing device comprises:
the GPU is connected with the image acquisition system and is used for acquiring shape data and image data in real time in the sweeping process of the sweeper; carrying out object recognition processing on the shape data and the image data, and determining an object corresponding to the shape data and the image data; carrying out scene recognition processing on the object by using a preset scene recognition algorithm, and determining a scene corresponding to the object; determining a cleaning mode corresponding to the scene recognition result according to a preset corresponding relation between the scene and the cleaning mode, and controlling the sweeper to switch to the cleaning mode corresponding to the scene recognition result;
and the AI chip is connected with the GPU and used for storing a preset scene recognition algorithm.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010386251.3A CN111528739A (en) | 2020-05-09 | 2020-05-09 | Sweeping mode switching method and system, electronic equipment, storage medium and sweeper |
Applications Claiming Priority (1)
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113110176A (en) * | 2021-04-15 | 2021-07-13 | 北京云迹科技有限公司 | Robot-based running state control method and related equipment |
| WO2022166640A1 (en) * | 2021-02-03 | 2022-08-11 | 追觅创新科技(苏州)有限公司 | Control method for intelligent cleaning device, and intelligent cleaning device |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180113467A1 (en) * | 2016-10-25 | 2018-04-26 | Lg Electronics Inc. | Cleaner and controlling method thereof |
| CN109452914A (en) * | 2018-11-01 | 2019-03-12 | 北京石头世纪科技有限公司 | Intelligent cleaning equipment, cleaning mode selection method, computer storage medium |
| CN110955235A (en) * | 2018-09-27 | 2020-04-03 | 广东美的生活电器制造有限公司 | Control method and control device of sweeping robot |
| CN110960138A (en) * | 2019-12-30 | 2020-04-07 | 科沃斯机器人股份有限公司 | Structured light module and autonomous mobile device |
| CN110974088A (en) * | 2019-11-29 | 2020-04-10 | 深圳市杉川机器人有限公司 | Sweeping robot control method, sweeping robot and storage medium |
| CN110989631A (en) * | 2019-12-30 | 2020-04-10 | 科沃斯机器人股份有限公司 | Self-moving robot control method, device, self-moving robot and storage medium |
| CN111012261A (en) * | 2019-11-18 | 2020-04-17 | 深圳市杉川机器人有限公司 | Sweeping method and system based on scene recognition, sweeping equipment and storage medium |
| CN111123278A (en) * | 2019-12-30 | 2020-05-08 | 科沃斯机器人股份有限公司 | Partitioning method, device and storage medium |
-
2020
- 2020-05-09 CN CN202010386251.3A patent/CN111528739A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180113467A1 (en) * | 2016-10-25 | 2018-04-26 | Lg Electronics Inc. | Cleaner and controlling method thereof |
| CN110955235A (en) * | 2018-09-27 | 2020-04-03 | 广东美的生活电器制造有限公司 | Control method and control device of sweeping robot |
| CN109452914A (en) * | 2018-11-01 | 2019-03-12 | 北京石头世纪科技有限公司 | Intelligent cleaning equipment, cleaning mode selection method, computer storage medium |
| CN111012261A (en) * | 2019-11-18 | 2020-04-17 | 深圳市杉川机器人有限公司 | Sweeping method and system based on scene recognition, sweeping equipment and storage medium |
| CN110974088A (en) * | 2019-11-29 | 2020-04-10 | 深圳市杉川机器人有限公司 | Sweeping robot control method, sweeping robot and storage medium |
| CN110960138A (en) * | 2019-12-30 | 2020-04-07 | 科沃斯机器人股份有限公司 | Structured light module and autonomous mobile device |
| CN110989631A (en) * | 2019-12-30 | 2020-04-10 | 科沃斯机器人股份有限公司 | Self-moving robot control method, device, self-moving robot and storage medium |
| CN111123278A (en) * | 2019-12-30 | 2020-05-08 | 科沃斯机器人股份有限公司 | Partitioning method, device and storage medium |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2022166640A1 (en) * | 2021-02-03 | 2022-08-11 | 追觅创新科技(苏州)有限公司 | Control method for intelligent cleaning device, and intelligent cleaning device |
| CN113110176A (en) * | 2021-04-15 | 2021-07-13 | 北京云迹科技有限公司 | Robot-based running state control method and related equipment |
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Application publication date: 20200814 |