CN114326721A - Drawing establishing method and device, cloud server and robot - Google Patents
Drawing establishing method and device, cloud server and robot Download PDFInfo
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- CN114326721A CN114326721A CN202111566751.6A CN202111566751A CN114326721A CN 114326721 A CN114326721 A CN 114326721A CN 202111566751 A CN202111566751 A CN 202111566751A CN 114326721 A CN114326721 A CN 114326721A
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Abstract
The method for establishing the image applied to the robot responds to an image establishing request of the robot, enters an image establishing state, obtains available wireless network access points in an unknown area where the robot is located, confirms a first network signal strength value of each wireless network access point at the current moment, and controls the robot to move towards the direction with the maximum network signal strength value until the image establishing of the unknown area is completed. In an unknown area, the robot is guided to build a map by using the network signal strength value, so that the autonomous decision-making capability of the robot in the map building process can be greatly improved, the robot can flexibly cope with emergency situations in the map building process, the intelligence level of the robot is improved, manual customer service intervention is reduced, and the labor cost is saved.
Description
Technical Field
The invention relates to the field of communication, in particular to a drawing establishing method and device, a cloud server and a robot.
Background
In order to realize a typical intelligent movement of a moving object (for example, a robot, a mobile terminal carried by a user, etc.) in an unknown scene, a map construction and navigation capability is required. The quality of the map directly influences the positioning and navigation capacity of the robot in the environment. In order to help the mobile object adapt to various application environments, after the mobile object enters an unknown area, the unknown area needs to be mapped, namely the unknown area is mapped so as to provide an original map for path planning required by subsequent work.
However, with the development of communication technology, the mobile object has an increasingly strong demand for external communication, and the mobile object travels according to the result of path planning provided by the related technology, and may travel to a place where the communication signal strength is weak or even no communication signal exists, thereby affecting or even interrupting the interaction between the mobile object and the outside.
Disclosure of Invention
To overcome the problems in the related art, the present disclosure provides a mapping method, an apparatus, a computer program product, a non-transitory computer-readable storage medium, a cloud server, and a robot.
The present disclosure provides a path planning method applied to a robot, including:
responding to a path planning request of the robot, and entering a path planning state;
acquiring available wireless network access points in an unknown area where the robot is located, and confirming a first network signal strength value of each wireless network access point at the current moment;
and controlling the robot to move towards the direction with the maximum network signal intensity value until the path planning of the unknown area is completed.
As an alternative, the acquiring available wireless network access points in an unknown area where the robot is located, and determining a first network signal strength value of each wireless network access point at the current time includes:
the robot scans the mobile network base stations of available operators in the unknown area, connects one mobile network base station, and automatically switches and connects the cellular network base stations of different operators to obtain a first signal intensity value of each mobile network base station.
As an alternative, the acquiring available wireless network access points in an unknown area where the robot is located, and determining a first network signal strength value of each wireless network access point at the current time includes:
the robot obtains the change numerical value of the network signal strength of each local area network intelligent device in a static state and/or a moving state, obtains the position and the angle of the robot relative to the local area network intelligent devices, and confirms the first network signal strength value of each local area network intelligent device.
As an alternative, the method further comprises:
when the robot enters a road junction to be diverted, the self posture or the direction of the signal receiver is adjusted to confirm the network signal intensity distribution situation around the position where the robot is located, the second network signal intensity value with the maximum signal intensity is confirmed from the network signal intensity distribution situation, and the robot is controlled to rotate towards the direction where the second network signal intensity value is located.
As an alternative, the method further comprises the following steps:
the robot collects an environment image of an unknown area, identifies the environment image to confirm the direction of a window of the unknown area, and controls the robot to move towards the direction of the window when a network signal is unavailable.
As an alternative, when a map building failure occurs, the method further comprises the following steps:
the robot sends a current environment image and a manual assistance request to a cloud server, receives a target position confirmed by the cloud server based on the current environment image, controls the robot to advance towards the target position, records image establishing information generated in advancing and stores the image establishing information locally, or
The robot follows the movable object to travel when confirming that the movable object exists in the area, records the mapping information generated in the traveling process and stores the mapping information locally, and stops following the movable object and travels towards the direction with the maximum network signal intensity value when the network signal intensity value reaches a preset threshold value, or
And the robot enters an obstacle avoidance advancing state, the connection with the cloud server is disconnected, the mapping information is stored locally until the network signal intensity value reaches a preset threshold value, and the robot advances towards the direction with the maximum network signal intensity value.
The present disclosure provides a mapping method applied to a cloud server, including:
acquiring a path planning request of a request terminal;
controlling the request terminal to acquire available wireless network access points in an unknown area, and confirming a first network signal strength value of each wireless network access point at the current moment;
and controlling the request terminal to move towards the direction with the maximum network signal intensity value according to the distribution condition of the first network signal intensity value until the path planning of the unknown area is completed.
As an alternative, when a map building failure occurs, the method comprises the following steps:
the cloud server receives a current environment image and a manual assistance request sent by the request end, and sends a target position to the request end based on the target position confirmed by the current environment image so that the request end moves to the target position.
The utility model provides a build picture device is applied to the robot, includes:
the system comprises an initial module, a path planning module and a path planning module, wherein the initial module is used for responding to a mapping request of a robot and entering a path planning state;
the network scanning module is used for acquiring available wireless network access points in an unknown area where the robot is located and confirming a first network signal strength value of each wireless network access point at the current moment;
and the control module is used for controlling the robot to move towards the direction with the maximum network signal intensity value until the mapping of the unknown area is completed.
The utility model provides a path planning device is applied to high in the clouds server, includes:
the acquisition module is used for acquiring a mapping request of a request end;
the control module is used for controlling the request terminal to acquire available wireless network access points in an unknown area and confirming a first network signal strength value of each wireless network access point at the current moment;
the control module is further used for controlling the request terminal to move towards the direction with the maximum network signal intensity value according to the distribution situation of the first network signal intensity value until the mapping of the unknown area is completed.
The present disclosure provides a robot, comprising: a travel drive, a non-transitory computer readable storage medium; and
one or more processors to execute a program in the non-transitory computer readable storage medium; the non-transitory computer readable storage medium has stored therein instructions for performing the above-described mapping method applied to the robot.
The present disclosure provides a cloud server, comprising: a non-transitory computer-readable storage medium; and one or more processors to execute the programs in the non-transitory computer-readable storage medium; the non-transitory computer readable storage medium stores instructions for executing the mapping method applied to the cloud server.
The present disclosure provides a non-transitory computer readable storage medium including one or more programs for performing the mapping method applied to the robot described above.
The present disclosure provides a computer program product comprising a computer program executable by a programmable apparatus, the computer program having code portions for performing the above-described mapping method applied to a robot when executed by the programmable apparatus.
According to the technical scheme, the embodiment of the invention has the following advantages:
the mapping method applied to the robot is used for more autonomously completing the mapping requirement of an area, responding to the mapping request of the robot, entering the mapping state, acquiring available wireless network access points in the unknown area where the robot is located, confirming the first network signal strength value of each wireless network access point at the current moment, and controlling the robot to move towards the direction with the maximum network signal strength value until the mapping of the unknown area where the robot is located is completed. The robot is guided to build the map by utilizing the network signal strength value, so that the autonomous decision-making capability of the robot in the map building process can be greatly improved, the robot can flexibly cope with emergency situations occurring in the route planning process, the intelligence level of the robot is improved, manual customer service intervention is reduced, and the labor cost is saved.
Drawings
Fig. 1 is a schematic diagram of an implementation environment according to various embodiments of the present disclosure.
Fig. 2 is a flowchart illustrating a mapping method applied to a robot according to an exemplary embodiment.
Fig. 3 is a flowchart illustrating a mapping method applied to a server according to an exemplary embodiment.
Fig. 4 is a block diagram illustrating a structure of a mapping apparatus according to an exemplary embodiment.
Fig. 5 is a block diagram illustrating a structure of a map creation apparatus according to another exemplary embodiment.
Fig. 6 is a block diagram illustrating a structure of a map creation apparatus according to another exemplary embodiment.
Detailed Description
In order to make the technical solutions of the present invention better understood, 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. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Before describing the method for creating a diagram provided by the present disclosure, an application scenario related to the present disclosure is first described, and fig. 1 is a schematic structural diagram of an implementation environment related to various embodiments of the present disclosure. Referring to fig. 1, the implementation environment may include: the request terminal 100 is a terminal driven by itself to travel or a terminal carried by a user to travel, and may be, for example, the above-mentioned moving object (e.g., a robot, a mobile terminal carried by a user, etc.), or an automobile with an automatic driving function, or the like. The cloud server 200 may include one server, or a server cluster composed of several servers, or may be a cloud computing service center.
The method for establishing the graph comprises the following steps: the method is applied to the robot mapping and the server mapping. First, the method for constructing the image applied to the robot provided by the present disclosure will be explained. The image building method applied to the robot is carried out when an unknown area is built through a cloud server, the autonomous decision-making capability of a request end is improved while too much intervention of manual customer service is reduced, the image building method applied to the robot is novel, and the image building method applied to the robot is explained below.
Referring to fig. 2, fig. 2 is a flowchart illustrating a mapping method applied to a robot according to an exemplary embodiment. As shown in fig. 2, the method comprises the steps of:
s201, responding to a mapping request of the robot, and entering a mapping state.
S202, obtaining available wireless network access points in an unknown area where the robot is located, and confirming a first network signal strength value of each wireless network access point at the current moment.
S203, controlling the robot to move towards the direction with the maximum network signal intensity value until the mapping of the unknown area is completed.
In the disclosure, a robot is an intelligent machine capable of semi-autonomous or fully-autonomous working, such as a sweeping robot, a distribution robot, a vending robot, and the like, during initial working, a working area is usually required to be mapped, that is, an unknown area is mapped, where the unknown area is a space area in which no map data is stored in the robot or a cloud server, the map data may be point cloud data scanned by a radar, three-dimensional image sensing data, and the like, and the robot cannot perform subsequent path planning and other operations in the unknown area without mapping the unknown area, and the robot performs a mapping state by operating on the robot by a user or issuing an instruction through the cloud server, and after entering the mapping state, the robot scans a wireless network access point in the unknown area, where the wireless network access point may include a cellular network or a local area network intelligent device, the method comprises the steps of obtaining a network signal distribution condition by obtaining a first network signal strength value of a wireless network access point in an unknown area, determining the direction of the wireless network access point with the largest first network signal strength value, controlling the robot to move towards the direction, continuously scanning the first network signal strength values of the wireless network access points around in the advancing process, and always controlling the direction towards the largest first network signal strength value until the mapping work of the unknown area is completed, so that the robot can complete the mapping work more autonomously, and in the unknown area, the robot is guided to move by utilizing the network signal strength value, the mapping of the unknown area is further completed, the intervention of artificial customer service is reduced, the intelligence level of the robot is improved, and the user experience is improved.
Optionally, in an embodiment of S202, the wireless network access point employs a cellular network, which is a mobile network, in order to enable the robot to connect to cellular network base stations of different operators, a SIM (Subscriber Identity Module) card or a virtual SIM card of multiple operators is configured in advance for the robot, the robot is automatically switched to the cellular network base stations of other operators after connecting to one of the cellular network base stations, so as to obtain a network distribution of each cellular network base station around the unknown area where the robot is located, each cellular network base station may include a base station name, a location direction and a network first network signal strength value, and by comparing the strength of the first network signal strength value, the direction of the cellular network base station where the first network signal strength value is the largest in the unknown area at the current time may be determined, the robot moves towards the direction, continuously acquires the network distribution condition corresponding to the current position in the process of moving, and always controls the robot to move towards the direction with the maximum first network signal intensity value, so that the robot continuously moves forwards by utilizing the network signal intensity value condition of the unknown area until the image building work is completed.
Optionally, in an embodiment of S202, the wireless network access point uses a lan smart device, a plurality of lan smart devices are configured in an unknown area where the robot is located, the robot and the lan smart devices may be connected in a plurality of manners, such as bluetooth, bluetooth wireless MESH network MESH, Wi-Fi wireless fidelity network, Zigbee, UWB (english: Ultra Wide Band, chinese: Ultra Wide Band), RS485 bus, KNX protocol, PLC remote control, multimode gateway, and the like, the lan smart devices may be in a stationary state or in a mobile state, which is not limited to this, the robot obtains a variation value of network signal strength of each lan smart device in the stationary state and/or in the mobile state, the robot obtains a position and an angle of the robot relative to the lan smart devices, and confirms a first network signal strength value of each lan smart device, the direction in which the first network signal strength value of the unknown area is the largest at the current moment can be judged by comparing the strength of the first network signal strength value of each local area network intelligent device, the robot acts towards the direction, the network distribution condition corresponding to the current position is continuously obtained in the advancing process, the robot is always controlled to move towards the direction in which the first network signal strength value is the largest, and the advancing is continuously carried out by utilizing the network signal strength value condition of the unknown area until the mapping work is completed.
Optionally, in an embodiment of S202, the wireless network access point includes both a cellular network base station and a local area network smart device, the robot obtains first network signal strength values of all the cellular network base station and the local area network smart device, determines a direction in which the first network strength value is the largest, and controls the robot to move toward the direction, so as to complete mapping.
Optionally, in an embodiment of the present disclosure, before S203, the method further includes:
s2021, when the robot enters a road junction to be switched, adjusting the posture of the robot or the direction of a signal receiver to confirm the distribution situation of the network signal strength around the position where the robot is located, confirming a second network signal strength value with the maximum signal strength from the distribution situation of the network signal strength, and controlling the robot to rotate towards the direction where the second network signal strength value is located.
When the robot enters a road junction to be switched, the robot is connected to a wireless network access point at the moment, the robot acquires the network signal distribution situation of the wireless network access point at the periphery at the current position, namely, the second network signal intensity value of the wireless network access point in which direction is the largest is determined, and in the acquisition process, the robot can be controlled to rotate towards the direction with the largest second network signal intensity value and move continuously along the direction by rotating the receiving direction of the self-adjusted signal receiver in situ or adjusting the receiving direction of the signal receiver when the signal receiver is provided with a direction adjusting device to determine the network signal intensity distribution situation around.
Optionally, in an embodiment of the present disclosure, before S203, the method further includes:
s2022, the robot collects an environment image of the unknown area, identifies the environment image to confirm the direction of a window of the unknown area, and controls the robot to move towards the direction of the window when the network signal is unavailable.
The robot is provided with a camera for collecting environmental images, the camera can work according to a preset rule, for example, the camera may be continuously turned on or turned on at intervals, in this embodiment, the camera is always in an on state, the robot may continuously acquire an environmental image of an unknown area where the robot is located, and by identifying the environmental image, the position of the window in the environment image can be identified, the robot is controlled to move towards the direction of the window through the environment image when the network signal of the wireless network access point in the unknown area cannot be used for building the image, thus, the autonomous decision making capability of the robot in the process of drawing construction can be greatly improved, the robot can flexibly deal with the emergency situation in the process of route planning, the intelligent level of the robot is improved, manual customer service intervention is reduced, and labor cost is saved.
Optionally, in a situation that a network signal difference occurs in an unknown area, the access point is switched to another wireless network and still cannot connect to a better network signal, so that a mapping failure is caused, the present disclosure provides an embodiment to solve such problems, where the method includes:
s204, the robot sends a current environment image and a manual assistance request to a cloud server, receives a target position confirmed by the cloud server based on the current environment image, controls the robot to advance towards the target position, records image building information generated in the advancing process and stores the image building information locally.
The robot self-rescue first mode is characterized in that the robot sends a current environment image and a manual assistance request to the cloud server, a real-time video mode can be adopted, no limitation is made to the current environment image, the cloud server identifies the current environment image to confirm a target position in the current environment image, the robot controls the robot to move towards the target position according to the target position confirmed by the cloud server, and the robot stores collected mapping information in the local robot.
Optionally, when the map building fails, the present disclosure provides another embodiment to solve such problems, the method includes:
s205, when the robot confirms that the movable object exists in the area, the robot follows the movable object to travel, image building information generated in the traveling process is recorded and stored locally, and when the network signal intensity value reaches a preset threshold value, the robot stops following the movable object and travels towards the direction with the maximum network signal intensity value.
The robot confirms that the movable object exists in the region and then follows the movable object to advance, the movable object can be a person, assistance is requested to the person, the robot follows the person to advance, image establishing information generated in advancing is recorded and stored locally, when the network signal strength value reaches a preset threshold value, the robot stops following the movable object and advances towards the direction with the maximum network signal strength value, and therefore the autonomous image establishing is achieved.
Optionally, in case of a failure in building a map, the present disclosure provides another embodiment to solve such a problem, where the method includes:
and S206, the robot enters an obstacle avoidance advancing state, the connection with the cloud server is disconnected, the mapping information is stored locally, and the robot advances towards the direction with the maximum network signal intensity value until the network signal intensity value reaches a preset threshold value.
In the third mode of robot self-rescue, the robot is disconnected from the cloud server, enters an obstacle avoidance advancing state, and senses environmental characteristics through a sensor of the robot, so that autonomous image building and obstacle avoidance are achieved.
It should be noted that the above three self-rescue modes can be flexibly configured by the robot, and the execution sequence and the number of execution modes are not limited.
The mapping method comprises the steps of responding to a mapping request of a robot, entering a mapping state, obtaining available wireless network access points in an unknown area where the robot is located, confirming a first network signal strength value of each wireless network access point at the current moment, controlling the robot to move towards the direction with the largest network signal strength value until mapping of the unknown area where the robot is located is completed, and making a strategy for automatically implementing mapping by giving judgment to the network signal strength value to the robot, so that the autonomous decision-making capability of the robot in the mapping process can be greatly improved, the robot can flexibly cope with emergency situations occurring in the route planning process, the intelligent level of the robot is improved, manual customer service intervention is reduced, and labor cost is saved.
With reference to fig. 3, the foregoing part describes a path planning method applied to a robot, and here describes a mapping method applied to a cloud server, where the method includes:
s301, acquiring a mapping request of a request end;
s302, controlling the request terminal to obtain available wireless network access points in an unknown area, and confirming a first network signal strength value of each wireless network access point at the current moment;
s303, controlling the request end to move towards the direction with the maximum network signal intensity value according to the distribution situation of the first network signal intensity value until the mapping of the unknown area is completed.
The method comprises the steps that a communication link is established between a request end and a cloud server, the mapping request of the request end can be a mapping request of a new machine on an unknown area, the request end can be a robot, the request end connects available wireless network access points in the area one by one to determine a first network signal strength value of each wireless network access point, the wireless network access points can be cellular networks or local area network intelligent equipment, the request end controls the request end to move towards the direction until the mapping of the unknown area is completed by using the direction where the first network signal strength value is the largest, and in the unknown area, the robot is guided to move by using the network signal strength value, the mapping of the unknown area is further completed, the intervention of artificial customer service is reduced, and the use experience of a user is improved.
Optionally, as a way of requesting end self-rescue, the present disclosure provides an embodiment, when a graph building failure occurs, including:
s304, the cloud server receives the current environment image and the manual assistance request sent by the robot, and sends the target position to the robot based on the target position confirmed by the current environment image, so that the robot moves to the target position.
The request end sends a current environment image and a manual assistance request to the cloud server, a real-time video mode can be adopted, no limitation is made on the current environment image and the manual assistance request, the cloud server receives the assistance request sent by the request end, the cloud server identifies the current environment image and confirms a target position in the current environment image, the request end controls the request end to move towards the target position according to the target position confirmed by the cloud server, and the request end stores collected mapping information in the local area.
In conjunction with fig. 4, correspondingly, the present disclosure further provides a mapping apparatus 400, applied to a robot, including:
an initial module 401, configured to enter a mapping state in response to a mapping request of a robot;
a network scanning module 402, configured to obtain available wireless network access points in an unknown area where the robot is located, and determine a first network signal strength value of each wireless network access point at a current time;
and the control module 403 is configured to control the robot to move towards the direction with the maximum network signal strength value until the mapping of the unknown area is completed.
Correspondingly, as shown in fig. 5, an embodiment of the present disclosure further provides a graph creating apparatus 500, where the apparatus is applied to a cloud server, and the apparatus includes:
an obtaining module 501, configured to obtain a mapping request of a robot;
the control module 502 is configured to control the robot to obtain available wireless network access points in an unknown area, and determine a first network signal strength value of each wireless network access point at the current time;
the control module 502 is further configured to control the robot to move toward the direction with the maximum network signal strength value according to the distribution of the first network signal strength value until the mapping of the unknown area is completed.
Fig. 6 is another block diagram illustrating an apparatus 600 for creating a map according to an example embodiment, where the apparatus 600 may be a server. As shown in fig. 6, the apparatus 600 may include: a processor 601, a memory 602, multimedia components 603, input/output (I/O) interfaces 604, and communication components 605.
The processor 601 is configured to control the overall operation of the apparatus 600, so as to complete all or part of the steps in the above-described mapping method. The memory 602 is used to store various types of data to support operation of the apparatus 600, such as instructions for any application or method operating on the apparatus 600, and application-related data, such as contact data, messaging, pictures, audio, video, and so forth. The Memory 602 may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk or optical disk. The multimedia components 603 may include a screen and audio components. Wherein the screen may be, for example, a touch screen and the audio component is used for outputting and/or inputting audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may further be stored in the memory 602 or transmitted through the communication component 605. The audio assembly also includes at least one speaker for outputting audio signals. The I/O interface 604 provides an interface between the processor 601 and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 605 is used for wired or wireless communication between the apparatus 600 and other devices. Wireless Communication, such as Wi-Fi, bluetooth, Near Field Communication (NFC), 2G, 3G, or 4G, or a combination of one or more of them, so that the corresponding Communication component 605 may include: Wi-Fi module, bluetooth module, NFC module.
In an exemplary embodiment, the apparatus 600 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components for performing the above-described method of creating a map.
Correspondingly, the present disclosure also provides a robot, wherein, includes: a travel drive, a non-transitory computer readable storage medium; and
one or more processors to execute a program in the non-transitory computer readable storage medium; the non-transitory computer readable storage medium has stored therein instructions for performing the above-described mapping method applied to the robot.
Correspondingly, this disclosure still provides a cloud server, wherein, includes: a non-transitory computer-readable storage medium; and one or more processors to execute the programs in the non-transitory computer-readable storage medium; the non-transitory computer readable storage medium stores instructions for executing the mapping method applied to the cloud server.
Accordingly, the present disclosure also provides a computer program product, wherein the computer program product comprises a computer program executable by a programmable apparatus, the computer program having code portions for performing the above-described mapping method applied to a robot when executed by the programmable apparatus.
Accordingly, the present disclosure also provides a non-transitory computer readable storage medium, wherein the non-transitory computer readable storage medium includes one or more programs for executing the method for mapping applied to the robot.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (14)
1. A mapping method is applied to a robot and comprises the following steps:
responding to a mapping request of the robot, and entering a mapping state;
acquiring available wireless network access points in an unknown area where the robot is located, and confirming a first network signal strength value of each wireless network access point at the current moment;
and controlling the robot to move towards the direction with the maximum network signal intensity value until the mapping of the unknown area is completed.
2. The mapping method according to claim 1, wherein the wireless network access points include a mobile network base station, and the obtaining available wireless network access points in an unknown area where the robot is located and determining the first network signal strength value of each wireless network access point at the current time includes:
the robot scans the mobile network base stations of available operators in the unknown area, connects one mobile network base station, and automatically switches and connects the cellular network base stations of different operators to obtain a first signal intensity value of each mobile network base station.
3. The mapping method according to claim 1, wherein the wireless network access points include local area network smart devices, and the obtaining available wireless network access points in an unknown area where the robot is located and determining the first network signal strength value of each wireless network access point at the current time includes:
the robot obtains the change numerical value of the network signal strength of each local area network intelligent device in a static state and/or a moving state, obtains the position and the angle of the robot relative to the local area network intelligent devices, and confirms the first network signal strength value of each local area network intelligent device.
4. The mapping method according to claim 1, wherein the method further comprises:
when the robot enters a road junction to be diverted, the self posture or the direction of the signal receiver is adjusted to confirm the network signal intensity distribution situation around the position where the robot is located, the second network signal intensity value with the maximum signal intensity is confirmed from the network signal intensity distribution situation, and the robot is controlled to rotate towards the direction where the second network signal intensity value is located.
5. The mapping method according to claim 1, further comprising:
the robot collects an environment image of an unknown area, identifies the environment image to confirm the direction of a window of the unknown area, and controls the robot to move towards the direction of the window when a network signal is unavailable.
6. The mapping method according to claim 4, wherein when mapping failure occurs, further comprising:
the robot sends a current environment image and a manual assistance request to a cloud server, receives a target position confirmed by the cloud server based on the current environment image, controls the robot to advance towards the target position, records image establishing information generated in advancing and stores the image establishing information locally, or
The robot follows the movable object to travel when confirming that the movable object exists in the area, records the mapping information generated in the traveling process and stores the mapping information locally, and stops following the movable object and travels towards the direction with the maximum network signal intensity value when the network signal intensity value reaches a preset threshold value, or
And the robot enters an obstacle avoidance advancing state, the connection with the cloud server is disconnected, the mapping information is stored locally until the network signal intensity value reaches a preset threshold value, and the robot advances towards the direction with the maximum network signal intensity value.
7. A mapping method is applied to a cloud server and comprises the following steps:
acquiring a mapping request of a request end;
controlling the request terminal to acquire available wireless network access points in an unknown area, and confirming a first network signal strength value of each wireless network access point at the current moment;
and controlling the request terminal to move towards the direction with the maximum network signal intensity value according to the distribution condition of the first network signal intensity value until the mapping of the unknown area is completed.
8. The mapping method according to claim 7, wherein when mapping failure occurs, the mapping method comprises:
the cloud server receives a current environment image and a manual assistance request sent by the request end, and sends a target position to the request end based on the target position confirmed by the current environment image so that the request end moves to the target position.
9. An apparatus for mapping, applied to a robot, comprising:
the system comprises an initial module, a drawing module and a drawing module, wherein the initial module is used for responding to a drawing request of a robot and entering a drawing state;
the network scanning module is used for acquiring available wireless network access points in an unknown area where the robot is located and confirming a first network signal strength value of each wireless network access point at the current moment;
and the control module is used for controlling the robot to move towards the direction with the maximum network signal intensity value until the mapping of the unknown area is completed.
10. The utility model provides a build picture device, wherein, is applied to cloud end server, includes:
the acquisition module is used for acquiring a mapping request of a request end;
the control module is used for controlling the request terminal to acquire available wireless network access points in an unknown area and confirming a first network signal strength value of each wireless network access point at the current moment;
the control module is further used for controlling the request terminal to move towards the direction with the maximum network signal intensity value according to the distribution situation of the first network signal intensity value until the mapping of the unknown area is completed.
11. A robot, comprising: a travel drive, a non-transitory computer readable storage medium; and
one or more processors to execute a program in the non-transitory computer readable storage medium; the non-transitory computer readable storage medium having stored therein instructions for performing the method of any of claims 1-6.
12. A cloud server, comprising: a non-transitory computer-readable storage medium; and one or more processors to execute the programs in the non-transitory computer-readable storage medium; the non-transitory computer readable storage medium having stored therein instructions for performing the method of claim 7 or 8.
13. A non-transitory computer readable storage medium, wherein the non-transitory computer readable storage medium includes one or more programs for performing the method of any of claims 1-6.
14. A computer program product, wherein the computer program product comprises a computer program executable by a programmable apparatus, the computer program having code portions for performing the method of any one of claims 1 to 6 when executed by the programmable apparatus.
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| CN202111566751.6A CN114326721A (en) | 2021-12-20 | 2021-12-20 | Drawing establishing method and device, cloud server and robot |
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