CN114430582A - Network selection method, network selection device, robot and storage medium - Google Patents

Abstract

The present application discloses a network selection method, a network selection device, a robot and a storage medium. The network selection method includes: collecting network quality data of the robot; calculating and obtaining a current network quality parameter according to a preset algorithm based on the network quality data; determining the current network quality level according to the current network quality parameter; when the current network quality level is lower than the network quality level threshold In the case of , adjust the network access policy of the robot. In this way, the current network quality parameters are calculated through the collected network quality data, and then the current network quality level is determined through the current network quality parameters, so as to quickly and more accurately determine the wireless network quality when the robot is working; When the current network quality level is lower than the minimum value, you can adjust the network access policy of the robot to improve the network reliability of the robot and prevent the robot from disconnecting or seriously freezing and other problems that affect the business.

Description

Network selection method, network selection device, robot and storage medium

technical field

The present application relates to the field of robotics, and in particular, to a network selection method, a network selection device, a robot and a storage medium.

Background technique

The industrial work scene of autonomous mobile robots has certain complexity and particularity. The wireless network, which is the communication carrier for autonomous mobile robots to move and dispatch, is prone to interference, which makes the autonomous mobile robots run unstable during work, and is prone to pauses and crashes. Lines and other problems affect the quality and efficiency of the robot's work.

SUMMARY OF THE INVENTION

The present application provides a network selection method, a network selection device, a robot and a storage medium.

The present application provides a network selection method for robots, characterized in that the network selection method includes:

collect network quality data for the bot;

Based on the network quality data, calculate and obtain the current network quality parameter according to a preset algorithm;

Determine the current network quality level according to the current network quality parameter;

In the case that the current network quality level is lower than the network quality level threshold, the network access policy of the robot is adjusted.

In the network selection method in the present application, the current network quality parameter is obtained by calculating the collected network quality data, and then the current network quality level is determined according to the current network quality parameter, so as to quickly and more accurately judge the wireless network quality when the robot is working ; In addition, when it is judged that the current network quality level is lower than the minimum value, the network access policy of the robot can be adjusted to improve the network reliability of the robot and prevent the robot from being disconnected or seriously stuck. .

In some embodiments, the network quality data includes at least one of signal-to-noise ratio, received signal strength, network bandwidth parameters negotiated between the robot and the wireless access point, and delay from the robot to the wireless gateway .

In some embodiments, when the current network quality level is lower than a network quality level threshold, adjusting the network access policy of the robot includes:

Confirm whether there is a new network with higher signal strength and the same name as the current access network of the robot;

When the new network does not exist, the robot is allowed to access a network below the network quality level threshold.

In some embodiments, the network selection method includes:

In the case that the robot accesses a network lower than the network quality level threshold, alarm information is sent to the user and/or the dispatch control system.

In some embodiments, when the current network quality level is lower than a network quality level threshold, adjusting the network access policy of the robot includes:

When the new network exists, a roaming is performed to allow the robot to access the new network.

In some embodiments, the network selection method includes:

In the case of accessing the new network, re-determining the current network quality level;

When the re-determined current network quality level is lower than the network quality level threshold, alarm information is sent to the user and/or the scheduling control system.

In some embodiments, the network selection method includes:

Combining the current network quality parameter and the working data of the robot to obtain combined data;

sending the combined data to a dispatch control system at a predetermined frequency;

Execute the scheduling adjustment instruction returned by the scheduling control system according to the combined data.

The present application provides a network selection device, characterized in that it includes:

The collection module is used to collect the network quality data of the robot;

a calculation module, configured to calculate and obtain a current network quality parameter according to a preset algorithm based on the network quality data;

a determining module, configured to determine the current network quality level according to the current network quality parameter;

An adjustment module, configured to adjust the network access policy of the robot when the current network quality level is lower than the network quality level threshold.

The present application provides a robot, the robot includes: a main body, a memory, a processor, and a computer program stored on the memory and executable on the processor, the memory and the processor are provided in the On the ontology, when the processor executes the computer program, the network selection method described in any one of the above embodiments is implemented.

In some embodiments, the embodiments of the present application provide a non-volatile computer-readable storage medium storing a computer program, when the computer program is executed by one or more processors, the implementation of any of the above embodiments can be implemented. The network selection method described above.

Additional aspects and advantages of the present application will be set forth, in part, from the following description, and in part will become apparent from the following description, or may be learned by practice of the present application.

Description of drawings

The above and/or additional aspects and advantages of the present application will become apparent and readily understood from the following description of embodiments taken in conjunction with the accompanying drawings, wherein:

1 is a schematic flowchart of a network selection method according to an embodiment of the present application;

2 is a schematic block diagram of a network selection apparatus according to an embodiment of the present application;

3 is a schematic diagram of a scenario in which a robot communicates with a dispatch control system and a terminal device according to an embodiment of the present application;

FIG. 4 is a schematic flowchart of a network selection method according to an embodiment of the present application

5 is a schematic flowchart of a network selection method according to an embodiment of the present application;

6 is a schematic flowchart of a network selection method according to an embodiment of the present application;

7 is a schematic flowchart of a network selection method according to an embodiment of the present application;

8 is a schematic flowchart of a network selection method according to an embodiment of the present application;

FIG. 9 is a schematic flowchart of a network selection method according to an embodiment of the present application.

Description of main components and symbols:

The robot 10 , the main body 11 , the memory 12 , the processor 13 , the network selection device 20 , the collection module 21 , the calculation module 22 , the determination module 23 , the adjustment module 24 , the scheduling control system 30 , and the terminal device 40 .

Detailed ways

Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary, only used to explain the present application, and should not be construed as a limitation on the present application.

To simplify the disclosure of the present application, the components and arrangements of specific examples are described below. Of course, they are only examples and are not intended to limit the application. Furthermore, this application may repeat reference numerals and/or reference letters in different instances for the purpose of simplicity and clarity, and does not in itself indicate a relationship between the various embodiments and/or arrangements discussed.

Referring to FIG. 1 , an embodiment of the present application provides a network selection method for the robot 10 . Among them, the network selection method includes:

Step S10: collecting network quality data of the robot 10;

Step S20: Based on the network quality data, calculate and obtain the current network quality parameter according to a preset algorithm;

Step S30: determining the current network quality level according to the current network quality parameter;

Step S40: Adjust the network access policy of the robot 10 when the current network quality level is lower than the network quality level threshold.

In the network selection method in the present application, the current network quality parameter is obtained by calculating the collected network quality data, and then the current network quality level is determined according to the current network quality parameter, so as to quickly and more accurately determine the wireless network when the robot 10 is working In addition, when it is judged that the current network quality level is lower than the minimum value, the network access policy of the robot 10 can be adjusted to improve the network reliability of the robot 10 and prevent the robot 10 from being disconnected or severely stuck. business conduct issues.

Referring to FIG. 2 , an embodiment of the present application provides a network selection apparatus 20 . The network selection apparatus 20 includes a collection module 21 , a calculation module 22 , a determination module 23 and an adjustment module 24 . The network selection method in this embodiment of the present application may be implemented by the network selection apparatus 20 provided in this application. For example, step S10 may be implemented by the collection module 21, step S20 may be implemented by the calculation module 22, and step S30 may be implemented by the determination module 23 , and step S40 may be implemented by the adjustment module 24 .

That is to say, the collection module 21 is used to collect the network quality data of the robot 10; the calculation module 22 is used to calculate and obtain the current network quality parameter according to the preset algorithm based on the network quality data; the determination module 23 is used to determine according to the current network quality parameter. Current network quality level; the adjustment module 24 is configured to adjust the network access policy of the robot 10 when the current network quality level is lower than the network quality level threshold.

Referring to FIG. 3, an embodiment of the present application provides a robot 10. The robot 10 includes a main body 11, a memory 12, a processor 13, and a computer program stored on the memory 12 and executable on the processor 13. The memory 12 and The processor 13 is provided on the main body 11 .

Wherein, the processor 13 is used for collecting the network quality data of the robot 10, and is also used for calculating the current network quality parameter according to the preset algorithm based on the network quality data, and is also used for determining the current network quality level according to the current network quality parameter, and using In the case that the current network quality level is lower than the network quality level threshold, the network access policy of the robot 10 is adjusted.

Specifically, the robot 10 in the present application may be an industrial robot, such as an autonomous mobile robot (Autonomous Mobile Robot, AMR). Among them, especially autonomous mobile robots can be used in modern automated warehouse management. Autonomous mobile robots can carry and pick goods, and perform operations including warehousing, picking, packaging and transportation.

There are cameras, built-in sensors, laser scanners, and some complex software in autonomous mobile robots. So the robot can detect the surrounding environment and choose the most efficient path to reach the target. The robot is able to work autonomously, in a scenario where a forklift, pallet, person or other obstacle appears in front of it, the robot will use the best alternative route to safely bypass them.

It can be understood that in this application, in order to realize the work of the robot 10, in the work scenario, the autonomous mobile robot needs to pass the wireless network and the dispatching control system 30 (as shown in FIG. 3 ) and the terminal device 40 (as shown in FIG. 3 ) For communication between devices, the scheduling control system 30 may be a server or the like. Wireless networks are often used as communication carriers for autonomous mobile robots to move and dispatch. At present, the common application methods include 4G, 5G, wifi and other types of wireless networks with different radio frequencies.

In a working scenario, the wireless controller cooperates with the networking of the wireless access points to achieve wireless network coverage in the operating area of the autonomous mobile robot, so that the autonomous mobile robot connects to the wireless network transmitted by the wireless controller and interacts with the dispatching control system 30 . The user can connect to the network in real time through the terminal device 40 to access resources such as scheduling or operation of the autonomous mobile robot.

In view of the particularity of the industrial scene, the wireless network may be disturbed or the scene changes in the environment, resulting in that the wireless network coverage quality in some areas cannot meet the use requirements of the autonomous mobile robot, making the robot 10 prone to pause, disconnection, and inability to communicate with the robot. Service data transmission is realized between the scheduling control systems 30 . Therefore, the robot 10 needs to be able to accurately identify the wireless network problems that may exist in the current scene, and report it to the user or the operation and maintenance personnel, so that the user experience is better and the robot 10 runs more stably; it is also necessary that the robot 10 can detect the poor network quality when In this case, certain strategies can be taken to improve network reliability.

In view of this, the present application provides a network selection method, which can accurately judge the quality of the network currently accessed by the robot 10, and adjust the network access policy of the robot 10 when the network quality is poor, thereby improving the robot 10. reliability of operation.

In step S10 and step S20, considering the accuracy of judging the quality of the network to which the robot 10 is connected, the network quality data may include a number of data, such as real-time signal-to-noise ratio, network transmission delay, etc. Set the algorithm to calculate the current network quality parameters. The frequency of collecting network quality data can be set according to actual needs, but it is understandable that in order to ensure the real-time nature of the data and accurately judge the real-time status of the network, the frequency needs to be high.

In steps S30 and S40, the standard of the network quality level can be set in advance according to different network quality parameters in a one-to-one correspondence, and then recorded in the memory 12, so that after the current network quality parameter is calculated and obtained in step S20, The current network quality level can be easily obtained by comparison, and further, the network quality level threshold can also be preset and obtained according to the actual situation of analyzing the working state of the robot 10 under different network quality environments.

When it is determined that the current network quality level is too low and is already lower than the network quality level threshold, in order to prevent the robot 10 from being disconnected, the processor 13 can adjust the network access policy of the robot 10, for example, it can be set that the robot 10 can temporarily It allows access to a network with a lower quality, thereby preventing the robot 10 from stopping work, improving the reliability of the network, and making the work of the robot 10 more reliable.

In some embodiments, the network quality data may include at least one of signal-to-noise ratio, received signal strength, negotiated network bandwidth parameters between the robot 10 and the wireless access point, and delay from the robot 10 to the wireless gateway.

In this way, the collected multiple pieces of network quality data can more fully and accurately judge the quality of the network currently accessed by the robot 10, thereby improving the reliability of judging the network quality.

Specifically, in order to enable the robot 10 to accurately identify possible wireless network problems in the current working environment, so as to subsequently report to the user or notify the dispatch control system 30 to facilitate investigation, location and resolution of network problems, and to make the robot 10 run more stably, processing The controller 13 needs to collect network quality data in real time at a certain frequency.

In some previous embodiments, the dispatching control system 30 that transmits fixed-size data packets to the robot 10 in real time is adopted, and the transmission time of the data packets from the robot 10 to the dispatching control system 30 is used as the standard for evaluating the current network quality of the robot 10 , however, the above-mentioned implementation has many disadvantages.

First of all, the transmission delay of the wireless network has many factors that affect the jitter phenomenon. For example, there are other radios at the current position where the robot 10 is working, or other objects, such as forklifts, cargo boxes, appear in the space of the work site of the robot 10. Obstacles such as people will have a certain impact. Only considering the transmission delay data of the wireless network to confirm the network quality of the robot 10 has great limitations, which does not meet the operating environment of the robot 10 in industrial use scenarios.

Secondly, the network problem cannot be accurately located by using the above-mentioned implementation manner. The network quality is determined by the transmission delay between the central control system of the robot 10 and the robot 10. In an industrial scenario, a wired network and a wireless network may be used together between the two devices of the robot 10 and the dispatching control system 30. Often, in order to improve reliability, the dispatching control system 30 can be accessed through wired means such as network cables and optical fibers, and the robot 10 can be accessed through a wireless network. At this time, if the delay is used as the network quality confirmation method alone, the wireless network quality and the wired network quality cannot be accurately confirmed, the usage requirements of industrial scenarios cannot be met, and network problems cannot be accurately located.

In addition, the robot 10 needs to transmit large files during the operation of the industrial scenario. In the normal communication process, the transmission of large files will occupy the bandwidth and cause the delay to increase. In such application scenarios, only the robot 10 and the server device are used. The network transmission delay is difficult to accurately confirm the network quality as an evaluation standard. In addition, it is difficult to generate a graph that feeds back the quality of the network only by using the delay parameter to meet the display requirements of the robot 10 in an industrial scene.

Therefore, in an embodiment of the present application, the network quality data collected by the processor 13 may include multiple items, that is to say, the present application combines more determination factors to more accurately calibrate the wireless network quality, and can The quality parameter generates the environmental network quality table, which reflects the real-time situation for the user. Among them, the multiple pieces of network quality data may include signal-to-noise ratio, which can be used as an important indicator for measuring communication quality; and may also include received signal strength, which is also the received signal strength of wireless signals, which can be used to judge link quality, and Whether to increase the transmission intensity of the broadcast can also be used to implement positioning technology; and can include the negotiated network bandwidth parameter between the robot 10 and the wireless access point and the delay from the robot 10 to the wireless gateway as parameters. In this way, the current network quality parameter of the robot 10 can be obtained from the above-mentioned at least one parameter through a preset algorithm.

Referring to FIG. 4, in some embodiments, when the current network quality level is lower than the network quality level threshold, the network access policy of the robot 10 is adjusted (step S40), including:

Step S41: Confirm whether there is a new network with higher signal strength and the same name as the current access network of the robot 10;

Step S42: In the case that there is no new network, allow the robot 10 to access a network lower than the network quality level threshold.

In some embodiments, steps S41 and S42 may be implemented by the adjustment module 24, that is to say, the adjustment module 24 may be used to confirm whether there is a higher signal strength and is consistent with the name of the current access network of the robot 10 and is used to allow the robot 10 to access a network below the network quality level threshold when no new network exists.

In some embodiments, the processor 13 may be used to confirm whether there is a new network with a higher signal strength and a name consistent with the current network access network of the robot 10, and to allow the robot if no new network exists 10 Access to a network below the network quality level threshold.

In this way, the robot 10 can be prevented from being disconnected or other service problems caused by network problems, thereby improving the network reliability of the robot 10 .

Specifically, in step S41, the name of the current access network is the SSID (Service Set Identifier, service set identifier), and the SSID is the name of a wireless local area network. Using the SSID technology, a wireless local area network can be divided into several different sub-systems. network. When the robot 10 detects that the currently accessed network has a low quality level and is lower than the network level threshold, the processor 13 can confirm whether there is a new network with the same SSID value and higher signal strength around.

In step S42, it should be pointed out that the new network specifically refers to a wireless network with better signal strength and consistent with the SSID of the currently accessed network. Considering the roaming policy set by default inside the robot 10, that is, when the current network quality level is lower than the network quality level threshold, the processor 13 activates roaming to switch to the wireless network released by the signal source with better signal at the current location. At this time, it can be understood that if the processor 13 does not detect a new network that meets the above requirements, performing roaming may cause the robot 10 to directly disconnect the current network, and cannot access the network because the network quality level of the previously accessed network is too low. The previously connected network, whereby the robot 10 is disconnected, affects work. Therefore, through step S42, the network access policy of the robot 10 can be adjusted to allow the network quality level to be lower than the network quality level threshold, so as to ensure that the robot 10 can re-select the previous network access even if it roams, preventing the robot 10 from being disconnected and affecting the robot 10 work.

In addition, it should be pointed out that the permission in step S42 is a time-limited permission, for example, the robot 10 can be allowed to access a network lower than the network quality level threshold within one hour, or it can also be a time limit of half an hour, two hours, half a day, etc. , which is not inherently limited in this application.

Referring to FIG. 5, in some embodiments, the network selection method may include:

Step S43: When the robot 10 accesses a network lower than the network quality level threshold, send alarm information to the user and/or the dispatch control system 30.

In some embodiments, step S43 may be implemented by the adjustment module 24, and the adjustment module 24 may be configured to send a message to the user and/or the dispatch control system 30 when the robot 10 accesses a network lower than the network quality level threshold Warning information.

In some embodiments, the processor 13 may be configured to send alert information to the user and/or the dispatch control system 30 if the robot 10 is connected to a network below the network quality level threshold.

In this way, it is helpful for users and operation and maintenance personnel to understand the network problem status of the robot 10 at the first time, which is beneficial to prevent risks in advance, and facilitates the scheduling control system 30 to make scheduling adjustments according to the real-time network conditions of the robot 10 .

Specifically, in step S43, the user may include operation and maintenance personnel, the robot 10 may send alarm information to the user through the terminal device 40, and the terminal device 40 may be a smart phone, a laptop computer, a portable Internet device, other handheld devices, and other devices such as Smart watches, smart headphones, etc., or other wearable devices (eg, head mounted devices (HMDs) such as smart glasses, smart clothes, smart bracelets, smart necklaces, or smart watches).

The alarm information may include the current network quality parameters, the current network quality level, and further, may also include information such as the current robot position, robot number, etc., so as to help the user and the first time to understand the network problem status of the robot 10, and determine the status of the robot 10. The location is beneficial to prevent risks in advance and facilitate the scheduling control system 30 to make scheduling adjustments according to the real-time network conditions of the robot 10 .

In one embodiment, after receiving the alarm information sent by the robot 10, the scheduling control system 30 may issue a scheduling adjustment instruction, and the content of the instruction may be to notify other robots 10 to run around the area with poor network quality, so as not to affect other robots 10. Business.

Referring to FIG. 6, in some embodiments, when the current network quality level is lower than the network quality level threshold, the network access policy of the robot 10 is adjusted (step S40), including:

Step S44: When there is a new network, perform roaming to enable the robot 10 to access the new network.

In some embodiments, step S44 may be implemented by the adjustment module 24. Specifically, the adjustment module 24 may be configured to perform roaming to enable the robot 10 to access the new network when there is a new network.

In some embodiments, the processor 13 may be configured to perform a roaming to enable the robot 10 to access the new network when a new network exists.

In this way, the network selection of the robot 10 can be adjusted in time, the working network of the robot 10 can be improved, and the operation reliability of the robot 10 and the reliability of the network can be improved.

Specifically, in step S44, it should be pointed out that the new network specifically refers to a wireless network with better signal strength and consistent with the SSID of the currently accessed network. It should be noted that a roaming policy may be set in the robot 10 by default. The roaming policy refers to: when the current network quality level is lower than the network quality level threshold, the processor 13 activates roaming to select the wireless network released by switching the network to the signal source with better signal at the current location, that is, the above-mentioned new network. In this way, the robot 10 can rely on intelligent decision-making to complete a better network path selection for its own work, so as to make its own work more stable and improve the reliability of the working network of the robot 10 .

Referring to FIG. 7, in some embodiments, the network selection method may include:

Step S45: in the case of accessing a new network, re-determine the current network quality level;

Step S46 : in the case that the re-determined current network quality level is lower than the network quality level threshold, send alarm information to the user and/or the scheduling control system 30 .

In some embodiments, steps S45 and S46 may be implemented by the adjustment module 24. Specifically, the adjustment module 24 may be used to re-determine the current network quality level in the case of accessing a new network, and to When the re-determined current network quality level is lower than the network quality level threshold, alarm information is sent to the user and/or the scheduling control system 30 .

In some embodiments, the processor 13 may be configured to re-determine the current network quality level in the case of accessing a new network, and to re-determine the current network quality level if the re-determined current network quality level is lower than the network quality level threshold. Alert information is sent to the user and/or the dispatch control system 30 .

In this way, it is beneficial to continuously monitor the quality of the real-time access network of the robot 10, and sending alarm information to the user/dispatching control system 30 is helpful for the user and the first time to understand the network problem status of the robot 10, which is beneficial to prevent risks in advance and facilitate scheduling. The control system 30 makes scheduling adjustments according to the real-time network conditions of the robot 10 .

Specifically, in step S45 , the network quality data of the robot 10 may be collected by holding to obtain network quality parameters through recalculation, and then the network quality level may be re-determined.

In step S46, the re-determined network quality level may be compared with the network quality level threshold, so as to determine whether the currently accessed network quality level meets the requirements. In addition, the user may include operation and maintenance personnel, and the robot 10 may send alarm information to the user through the terminal device 40, and the terminal device 40 may be a smart phone, a laptop computer, a portable Internet device, other handheld devices, as well as smart watches, smart headphones, etc. , or other wearable devices (eg, head mounted devices (HMDs) such as smart glasses, smart clothes, smart bracelets, smart necklaces, or smart watches).

The alarm information may include current network quality parameters, current network quality level, and further, may also include information such as the current position of the robot 10, the number of the robot 10, etc., so as to help the user and the first time to understand the network problem status of the robot 10 and determine the robot 10. The location of the robot 10 is beneficial to prevent risks in advance and facilitate the scheduling control system 30 to make scheduling adjustments according to the real-time network conditions of the robot 10 .

In one embodiment, after receiving the alarm information sent by the robot 10, the scheduling control system 30 may issue a scheduling adjustment instruction, and the content of the instruction may be to notify other robots 10 to run around the area with poor network quality, so as not to affect other robots 10. Business.

Referring to FIG. 8 and FIG. 9, in some embodiments, the network selection method may further include:

Step S50: combining the current network quality parameter and the working data of the robot 10 to obtain combined data;

Step S60: Send the combined data to the scheduling control system 30 at a predetermined frequency;

Step S70: Execute the scheduling adjustment instruction returned by the scheduling control system 30 according to the combined data.

In some embodiments, the network selection apparatus 20 may further include a combining module, a sending module and an executing module. Step S50 may be implemented by a combining module, step S60 may be implemented by a sending module, and step S70 may be implemented by an executing module. Further, the combination module can be used to combine the current network quality parameters and the work data of the robot 10 to obtain combined data; the sending module can be used to send the combined data to the dispatch control system 30 at a predetermined frequency; the execution module can be used to execute the dispatch control system 30 Adjust the instruction based on the schedule returned by the combined data.

In some embodiments, the processor 13 may be used to combine the current network quality parameters and the working data of the robot 10 to obtain combined data, and to send the combined data to the dispatch control system 30 at a predetermined frequency, and to execute the dispatch control system 30 Adjust the instruction according to the schedule returned by the combined data.

In this way, the scheduling control system 30 can judge the current network quality of the robot 10 through the combined data, and can also locate the network problem of the robot 10 through the combined data, and issue corresponding scheduling adjustment instructions to adjust the working route of the robot 10 to further improve the work of the robot 10 reliability.

Specifically, in step S50, the working data of the robot 10 may include the relevant state data of the robot 10, the current map position information of the robot 10, the serial number of the robot 10, etc., wherein the current map position information of the robot 10 Run the map coordinates to get. The processor 13 may combine the above working data with the current network quality parameter calculated in step S20 to form combined data.

In step S60 , it should be noted that the robot 10 is provided with a device for transmitting data packets with the scheduling control system 30 , and the above-mentioned device can send and receive data packets during the operation of the robot 10 . The predetermined frequency for the robot 10 to send the combined data through the device can be once a second, or other frequencies, which can be set according to actual needs, the working conditions of the robot 10 and the performance of the device for sending messages.

In step S70, in one embodiment, after the scheduling control system 30 receives the data packet with the combined data, it is analyzed that the current network quality level of the robot 10 is lower than the network quality level threshold, and the network at this location is poor. , so that the scheduling control system 30 issues a scheduling adjustment instruction to notify the remaining robots 10 to avoid the relevant areas with poor network quality. After receiving the scheduling adjustment instruction, the relevant robot 10 executes the instruction to optimize its own working path, thus reflecting The application value of the combined data in the scheduling of the robot 10, when an extreme network problem is detected in a certain location and there is a risk of the robot 10 going offline, the scheduling control system 30 can notify other online robots 10 to bypass the area.

In this way, to avoid affecting the business of the other robots 10, it is helpful to understand the network problem at the first time, and prevent risks in advance, so that the work of the robot 10 has higher reliability, and the robot 10 can make intelligent decisions to complete its own work. network path.

Embodiments of the present application provide a non-volatile computer-readable storage medium containing a computer-executable program. When the computer-executable program is executed by one or more processors 13, the network selection method in any of the foregoing embodiments is implemented. .

In the description of this specification, reference to the terms "one embodiment," "some embodiments," "exemplary embodiment," "example," "specific example," or "some examples" or the like is meant to be used in conjunction with the described embodiments. A particular feature, structure, material, or characteristic described in a manner or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

Any description of a process or method in the flowcharts or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing a specified logical function or step of the process , and the scope of the preferred embodiments of the present application includes alternative implementations in which the functions may be performed out of the order shown or discussed, including performing the functions substantially concurrently or in the reverse order depending upon the functions involved, which should It is understood by those skilled in the art to which the embodiments of the present application belong.

The logic and/or steps represented in flowcharts or otherwise described herein, for example, may be considered an ordered listing of executable instructions for implementing the logical functions, may be embodied in any computer-readable medium, For use by an instruction execution system, apparatus or apparatus (such as a computer-based system, a system including a processing module, or other system that can fetch instructions from and execute instructions from an instruction execution system, apparatus or apparatus), or in conjunction with such instruction execution system, apparatus or equipment. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport the program for use by or in connection with an instruction execution system, apparatus, or apparatus. More specific examples (non-exhaustive list) of computer readable media include the following: electrical connections with one or more wiring (electronic devices), portable computer disk cartridges (magnetic devices), random access memory (RAM), Read Only Memory (ROM), Erasable Editable Read Only Memory (EPROM or Flash Memory), Fiber Optic Devices, and Portable Compact Disc Read Only Memory 12 (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program may be printed, as the paper or other medium may be optically scanned, for example, followed by editing, interpretation, or other suitable medium as necessary process to obtain the program electronically and then store it in computer memory 12 .

The processor 13 may be a central processing unit (Central Processing Unit, CPU), or other general-purpose processors, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), an off-the-shelf processor Field-Programmable Gate Array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor 13 may be any conventional processor or the like.

It should be understood that various parts of the embodiments of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented by any one or a combination of the following techniques known in the art: Discrete logic circuits, application specific integrated circuits with suitable combinational logic gates, Programmable Gate Arrays (PGA), Field Programmable Gate Arrays (FPGA), etc.

Those of ordinary skill in the art can understand that all or part of the steps carried by the methods of the above embodiments can be completed by instructing the relevant hardware through a program, and the program can be stored in a computer-readable storage medium, and the program is stored in a computer-readable storage medium. When executed, one or a combination of the steps of the method embodiment is included.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing module, or each unit may exist physically alone, or two or more units may be integrated into one module. The above-mentioned integrated modules can be implemented in the form of hardware, and can also be implemented in the form of software function modules. If the integrated modules are implemented in the form of software functional modules and sold or used as independent products, they may also be stored in a computer-readable storage medium.

The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, and the like.

Although the embodiments of the present application have been shown and described above, it should be understood that the above embodiments are exemplary and should not be construed as limitations to the present application. Embodiments are subject to variations, modifications, substitutions and alterations.

Claims (10)

1. a network selection method, for robot, is characterized in that, described network selection method comprises: collect network quality data for the bot; Based on the network quality data, calculate and obtain the current network quality parameter according to a preset algorithm; Determine the current network quality level according to the current network quality parameter; In the case that the current network quality level is lower than the network quality level threshold, the network access policy of the robot is adjusted. 2 . The network selection method according to claim 1 , wherein the network quality data includes signal-to-noise ratio, received signal strength, network bandwidth parameters negotiated between the robot and the wireless access point, and the robot to At least one of the delays of the wireless gateway. 3. The network selection method according to claim 1, wherein, when the current network quality level is lower than a network quality level threshold, adjusting the network access policy of the robot comprises: Confirm whether there is a new network with higher signal strength and the same name as the current access network of the robot; When the new network does not exist, the robot is allowed to access a network below the network quality level threshold. 4. The network selection method according to claim 3, wherein the network selection method comprises: In the case that the robot accesses a network lower than the network quality level threshold, alarm information is sent to the user and/or the dispatch control system. 5 . The network selection method according to claim 3 , wherein, when the current network quality level is lower than a network quality level threshold, adjusting the network access policy of the robot comprises: 5 . When the new network exists, a roaming is performed to allow the robot to access the new network. 6. The network selection method according to claim 5, wherein the network selection method comprises: In the case of accessing the new network, re-determining the current network quality level; In the case that the re-determined current network quality level is lower than the network quality level threshold, alarm information is sent to the user and/or the scheduling control system. 7. The network selection method according to claim 1, wherein the network selection method comprises: Combining the current network quality parameter and the working data of the robot to obtain combined data; sending the combined data to a dispatch control system at a predetermined frequency; Execute the scheduling adjustment instruction returned by the scheduling control system according to the combined data. 8. A network selection device, comprising: The collection module is used to collect the network quality data of the robot; a calculation module, configured to calculate and obtain a current network quality parameter according to a preset algorithm based on the network quality data; a determining module, configured to determine the current network quality level according to the current network quality parameter; An adjustment module, configured to adjust the network access policy of the robot when the current network quality level is lower than the network quality level threshold. 9. A robot, characterized in that the robot comprises a main body, a memory, a processor, and a computer program stored on the memory and running on the processor, and the memory and the processor are provided in the On the main body, the processor implements the network selection method according to any one of claims 1-7 when the processor executes the computer program. 10. A non-volatile computer-readable storage medium of computer-executable instructions, characterized in that, when the computer-executable instructions are executed by one or more processors, the processor is caused to execute claims 1- The network selection method described in any one of 7.

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