Control method, control system, and storage medium

Abstract

The invention provides a control method, a control system and a computer readable storage medium, the control method is applied to a cloud server, and comprises the following steps: obtaining the communication quality of a communication network, the communication network being used for communication between the cloud server and a first automated guided vehicle; according to the communication quality of the communication network, a control instruction is generated, and the control instruction is used for adjusting the operation mode and / or the data transmission frequency of the first automated guided vehicle; and sending the control instruction to the first automated guided vehicle. According to the method and the device, the influence of the communication quality of the communication network on the clouded AGV is considered, and the control instruction is generated according to the communication quality to adjust the working state of the clouded AGV so as to adapt to the network state of the current communication network, so that the operation reliability of the clouded AGV is improved.

Description

Technical Field

[0001] The present application relates to the field of control technology, and in particular to a control method, a control system, and a computer-readable storage medium. Background Art

[0002] Automated guided vehicle (AGV) technology is being widely used in unmanned logistics, warehousing and industrial production processes. As demand continues to increase, the requirements for AGV intelligent scheduling are also getting higher and higher.

[0003] In order to improve the intelligence of AGV, in related technologies, modules that require complex computing power in AGV are moved to cloud servers to meet the growing computing power requirements of AGV, thus forming cloud AGV. However, the operating status of cloud AGV is greatly affected by the communication quality of the wireless communication network, and its reliability needs to be improved. Summary of the invention

[0004] The present application provides a control method, a control system, and a computer-readable storage medium to improve the reliability of the operation of a cloud-based AGV. The following is an introduction from the following aspects.

[0005] In a first aspect, a control method is provided, which is applied to a cloud server, comprising: obtaining the communication quality of a communication network, the communication network being used for communication between the cloud server and a first automated guided vehicle; generating a control instruction based on the communication quality of the communication network, the control instruction being used to adjust the operation mode and / or data transmission frequency of the first automated guided vehicle; and sending the control instruction to the first automated guided vehicle.

[0006] In some possible implementations, the operation mode includes one or more of the following: an operation speed of the first automated guided vehicle; an operation route of the first automated guided vehicle; controlling the first automated guided vehicle based on a cloud server or autonomously controlling the first automated guided vehicle.

[0007] In some possible implementations, a control instruction is generated based on the communication quality of the communication network, including: if the communication quality of the communication network is less than or equal to a first threshold, a control instruction is generated, and the control instruction is used to execute one or more of the following: reduce the operating speed of the first automated guided vehicle; increase the frequency of data transmission of the first automated guided vehicle; re-plan the operating route of the first automated guided vehicle.

[0008] In some possible implementations, a control instruction is generated based on the communication quality of the communication network, including: if the communication quality of the communication network is less than or equal to a second threshold, a control instruction is generated, the control instruction being used to switch the control of the first automated guided vehicle based on the cloud server to autonomous control of the first automated guided vehicle.

[0009] In some possible implementations, the communication quality of the communication network includes: communication quality obtained by detection; and / or communication quality obtained by prediction.

[0010] In some possible implementations, the communication quality of the communication network is determined based on one or more of the following: transmission delay, packet loss rate, available bandwidth, and transmission jitter.

[0011] In a second aspect, a control method is provided, which is applied to a first automatic guided vehicle, comprising: receiving a control instruction sent by a cloud server, the control instruction being generated based on the communication quality of a communication network between the cloud server and the first automatic guided vehicle; and adjusting the operating mode and / or data transmission frequency of the first automatic guided vehicle based on the control instruction.

[0012] In some possible implementations, the operation mode includes one or more of the following: an operation speed of the first automated guided vehicle; an operation route of the first automated guided vehicle; controlling the first automated guided vehicle based on a cloud server or autonomously controlling the first automated guided vehicle.

[0013] In a third aspect, a control system is provided, the device comprising: a memory and a processor, the memory is used to store program code, and the processor is used to call the program code in the memory so that the device executes the method in the first aspect or the second aspect above.

[0014] In a fourth aspect, a readable storage medium is provided, which stores a program code. When the computer program code runs on a computer, the computer executes the method in the first aspect or the second aspect.

[0015] This application takes into account the impact of the communication quality of the communication network on the cloud AGV, and generates control instructions based on the communication quality to adjust the working state of the cloud AGV to adapt to the current network state of the communication network, thereby helping to improve the reliability of the operation of the cloud AGV. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a schematic diagram of the structure of a traditional AGV.

[0017] Figure 2 This is a schematic diagram of the structure of a traditional cloud-based AGV.

[0018] Figure 3 This is a schematic diagram of the system architecture of a traditional cloud-based AGV.

[0019] Figure 4 A flow chart of a control method provided in an embodiment of the present application.

[0020] Figure 5A schematic diagram of the structure of the cloud-based AGV provided in an embodiment of the present application.

[0021] Figure 6 A schematic diagram of the system architecture of a control system provided in an embodiment of the present application.

[0022] Figure 7 A schematic block diagram of a control system provided in accordance with an embodiment of the present application.

[0023] Figure 8 A schematic block diagram of a control system provided in accordance with another embodiment of the present application.

[0024] Fig. 9 A schematic block diagram of a control system provided in accordance with another embodiment of the present application. DETAILED DESCRIPTION

[0025] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments.

[0026] To facilitate understanding, first combine Figure 1 , let’s introduce the traditional AGV in related technologies.

[0027] like Figure 1 As shown in the figure, traditional AGV mainly relies on on-board computing and sensors for autonomous navigation and control. According to its functions, it includes servo system control module, sensor control module, autonomous navigation and positioning module, safety system module and wireless network communication function module. The role of each functional module is introduced below.

[0028] Servo system control module: responsible for the basic motion control of AGV.

[0029] Sensor control module: uses laser radar, ultrasonic sensors, cameras and other devices for environmental perception, and supports obstacle detection and avoidance.

[0030] Navigation and positioning module: includes path planning unit, simultaneous localization and mapping (SLAM) unit and map management unit. This module stores and updates the map of the driving environment locally and can perform autonomous navigation in a dynamic environment. It usually relies on a preset navigation path, such as magnetic tape, magnetic stripe or QR code navigation.

[0031] Safety system module: It has multiple built-in safety mechanisms, such as slowing down when driving into obstacles and setting safety areas, to ensure the safety of personnel and equipment during operation.

[0032] Wireless network communication function module (not shown): has simple wireless communication capabilities and is used for basic status reporting and remote monitoring.

[0033] There are many problems with traditional AGVs in actual application. For example, traditional AGVs have poor flexibility. Traditional AGVs usually rely on preset navigation, such as magnetic stripe and QR code navigation. In the production workshop, the production layout may be frequently adjusted according to the production requirements of vehicle models, process improvements, etc. Every time the layout changes, it is necessary to re-lay or change the navigation signs, which is not only time-consuming and labor-intensive, but also causes the production line to stop working and affects production efficiency. Navigation methods such as magnetic stripes and QR codes may be easily affected by environmental factors, such as damage to the magnetic stripe and contamination of the QR code. For example, on the one hand, when encountering an obstacle, the AGV automatically stops, and will not continue to drive until the obstacle is evacuated for 5S-10S. It cannot directly bypass the obstacle, affecting efficiency; on the other hand, the control center is mainly responsible for task assignment, path planning, map management, etc., and cannot monitor the operating status and data of each AGV in real time, so it cannot flexibly adjust the operating path of the AGV.

[0034] Another example is that the stability of traditional AGVs needs to be improved. When the AGVs drive to the junction of wireless access points, they are prone to disconnection, resulting in loss of connection, which requires on-site processing by maintenance personnel, which may waste more than 2 minutes; when the network status is relatively poor, the data cannot be returned in time, which may cause AGV congestion, requiring on-site processing by maintenance personnel, which may waste 3-5 minutes.

[0035] For another example, traditional AGVs cannot fully utilize network resources. Traditional AGVs have a fixed driving speed and cannot flexibly adjust their running speed based on network status, resulting in a waste of network resources or reduced scheduling efficiency; the real-time and accuracy of positioning cannot be adjusted based on network status, resulting in reduced scheduling efficiency.

[0036] For another example, the hardware cost of traditional AGV is relatively high. Each AGV needs to be equipped with a separate controller for autonomous control, which increases the cost and power consumption of the AGV.

[0037] Another example is that the maintenance cost of traditional AGV is high. The hardware equipment of traditional AGV (such as navigation sensors, controllers, etc.) is relatively complex, and due to its localized calculation and control methods, once a failure occurs, it is difficult to troubleshoot and repair. Professional technicians are required to go to the site for diagnosis and maintenance, which takes a long time to repair, resulting in increased AGV downtime and affecting production continuity.

[0038] At present, AGV is widely used in unmanned logistics, warehousing and industrial production processes. As demand continues to increase, the requirements for AGV intelligent scheduling are also getting higher and higher. However, as mentioned above, traditional AGVs have many problems and cannot meet the requirements of AGV intelligent scheduling.

[0039] In order to meet the requirements of AGV intelligent scheduling, in related technologies, modules that require complex computing power in AGV, such as path planning, map management, and SLAM, are moved to cloud servers (also called cloud platforms or cloud) to meet the growing computing power requirements of AGV, thus forming cloud AGV. Figure 2 , and gives examples to introduce the division of functional modules of cloud AGV.

[0040] like Figure 2 As shown in FIG. 1 , in the cloud AGV, the path planning unit, map management unit, and SLAM unit in the traditional AGV are moved to the cloud server, while the servo system control module, sensor control module, and safety system module are still retained on the AGV side.

[0041] The AGV side is mainly responsible for sensor data collection and executing navigation instructions issued by the cloud. The hardware configuration is relatively simple, which reduces the cost and complexity of the AGV. The cloud server can monitor the status of multiple AGVs in real time, perform unified task allocation, path planning and resource scheduling for the entire AGV fleet, and rely on the network for real-time data interaction. The following is an introduction to the functional division of cloud AGV.

[0042] Cloud computing capabilities: undertake complex computing tasks such as path planning, map construction, and data analysis, and support efficient collaborative scheduling.

[0043] Real-time status monitoring: The cloud platform monitors the status information of AGV in real time, including location information, status reports, and battery power, for unified management.

[0044] Navigation command reception and execution: AGV is mainly responsible for receiving navigation commands sent from the cloud and performing simple actions based on sensor data.

[0045] Dynamic task allocation: The cloud platform can dynamically adjust task allocation based on real-time data to improve AGV work efficiency and resource utilization.

[0046] Network communication: There are high requirements for the stability and low latency of the wireless communication network, and 5G network needs to be deployed. When the wireless communication network between AGV and the cloud platform is unstable (such as poor network coverage or network congestion causing packet loss), it will more obviously affect the operation of AGV. For example, the accuracy and timeliness of some motion control may decrease.

[0047] In traditional AGVs, the control system is deployed by deploying servers on the line, which occupies production space and is not conducive to the flexible adjustment of production lines. Cloud AGVs, on the other hand, are based on 5G networks and use cloud computing and expansion capabilities to achieve intelligent scheduling of AGVs.

[0048] The following takes 5G communication network as an example. Figure 3 , the communication method between the cloud server and AGV in the related technology is introduced in detail.

[0049] like Figure 3 As shown in the figure, 5G network is deployed in the factory to ensure high-speed and low-latency communication between AGV and cloud server. 5G network can provide high-bandwidth, low-latency and high-reliability connection to meet the real-time requirements of AGV data transmission.

[0050] AGV integrates a 5G communication module, which can communicate directly with the 5G network, and the module supports the high rate and low latency characteristics of the 5G network. AGV is equipped with a variety of sensors, such as visual sensors, laser radars, etc., for environmental perception and obstacle detection. AGV uploads position, motion information, sensor data, etc. to the cloud server in real time through the 5G network. These data include but are not limited to the vehicle's real-time coordinates, speed, direction, power, working status, and surrounding environment information detected by vision or radar. The cloud server sends control instructions to the AGV, such as task allocation, path planning, motion control, etc.

[0051] The above article introduces that the cloud server issues control instructions based on the wireless communication network to control the operation of the AGV. In this way, the operation status of the cloud AGV is greatly affected by the communication quality of the wireless communication network, and its reliability needs to be improved. The following is an illustrative introduction to the problems existing in the cloud AGV in several related technologies.

[0052] For example, since 5G networks may be affected by factors such as coverage, interference, and network congestion in actual applications, the stability of data transmission is insufficient, affecting the real-time communication between cloud servers and AGVs.

[0053] For example, when data packets are lost due to network instability, or encounter transmission delays or transmission jitter, the cloud server cannot obtain the AGV's sensor data in a timely manner, affecting the calculation of the AGV's position information, thereby delaying the sending of navigation commands.

[0054] For example, when the communication quality is poor, the cloud server cannot obtain the AGV's position measurement data in time, resulting in a decrease in the cloud server's estimation accuracy of the AGV's position, affecting the AGV's navigation performance and safety. For example, when the communication quality is normal, the AGV speed is 3.6km / h, and the cloud server's AGV position estimation deviation can be controlled within ±10mm, but when the communication quality is poor, due to packet loss, transmission delay, and transmission jitter, the AGV position estimation error may increase to ±20mm, which is not conducive to the precise operation of the AGV.

[0055] For example, in the scenario of multi-AGV coordinated scheduling, insufficient positioning accuracy will directly affect production efficiency, safety and overall system performance. For example, if the positioning deviation between AGVs is too large, it may cause the vehicles to collide when approaching each other, causing damage or safety accidents.

[0056] In order to solve the above problems, the present application takes into account the impact of the communication quality of the communication network on the cloud AGV, and generates control instructions according to the communication quality to adjust the working state of the cloud AGV to adapt to the current network state of the communication network, thereby helping to improve the reliability of the operation of the cloud AGV.

[0057] Combined with the following Figure 4 , the control method provided in the embodiment of the present application is introduced in detail. Figure 4 The method can be executed by a cloud server.

[0058] See also Figure 4 In step S410, the communication quality of the communication network is obtained. Here, the communication network is used for communication between the cloud server and the first automated guided vehicle. In other words, the communication network is used to send the control instructions of the cloud server to the first automated guided vehicle. For example, the communication network can be a 5G network.

[0059] It should be understood that the first automatic guided vehicle here can be one AGV or multiple AGVs.

[0060] The communication quality of the communication network mentioned above may be determined by one or more of the following: transmission delay, packet loss rate, available bandwidth, and transmission jitter.

[0061] The communication quality may be the communication quality of the communication network actually detected, or may be the communication quality of the communication network predicted. For example, the communication quality may be the communication quality predicted within any future time period.

[0062] The embodiments of the present application do not limit the manner of determining the communication quality. In some implementations, the communication quality can be determined based on the communication network or the cloud server. For example, relevant modules for monitoring the communication quality can be deployed in the base station or other parts based on the slicing capability of the communication network. In other implementations, the communication quality can be determined based on the AGV. For example, a network diagnostic tool can be set in the AGV to detect the communication quality of the communication network.

[0063] In step S420, a control instruction is generated according to the communication quality of the communication network. The control instruction is used to adjust the operation mode and / or data transmission frequency of the first automated guided vehicle.

[0064] The data transmission frequency can be understood as the frequency at which the AGV uploads data to the cloud server. It can be the transmission frequency of the measurement data uploaded by the AGV to the cloud service mentioned above, for example, as mentioned above, the AGV uploads position information, motion information, and sensor data through the communication network. Exemplarily, these data may include the real-time coordinates, speed, direction, power, working status of the vehicle, and surrounding environment information detected by vision or radar.

[0065] There are many types of AGV operation modes that can be adjusted based on the control instruction. For example, the operation mode may include one or more of the following: the operation speed of the AGV; the operation route of the AGV; the control of the AGV based on the cloud server or the autonomous control of the AGV.

[0066] Taking the example of adjusting the running speed of the AGV by the control instruction, the AGV can reduce or increase the running speed after receiving the control instruction. Or, taking the example of adjusting the running route of the AGV by the control instruction, the AGV can re-plan the running route of the AGV after receiving the control instruction. Or, taking the example of adjusting the control method of the AGV, the AGV can switch from cloud server-based AGV control to AGV autonomous control after receiving the control instruction, or switch from AGV autonomous control to cloud server-based AGV control.

[0067] In step S430, a control instruction is sent to the first automatic guided vehicle. Accordingly, the first automatic guided vehicle receives the control instruction sent by the cloud server.

[0068] In step S440, based on the control instruction, the first automated guided vehicle adjusts the operating mode and / or the data transmission frequency.

[0069] This application takes into account the impact of the communication quality of the communication network on the cloud AGV, and generates control instructions based on the communication quality to adjust the working state of the cloud AGV to adapt to the current network state of the communication network, thereby helping to improve the reliability of the operation of the cloud AGV.

[0070] As mentioned above, cloud-based AGVs have high requirements for the communication quality of the communication network. When the communication network is unstable, such as poor network coverage or network congestion, the operation of the AGV will be more significantly affected. For example, the accuracy and timeliness of some motion control may decrease. Therefore, when the communication quality of the communication network deteriorates, step S430 can adjust the working state of the AGV based on the generated control instructions to adapt to the deteriorated communication quality. The following is an exemplary introduction to several implementation methods of adjusting the working state of the AGV based on control instructions.

[0071] Implementation method 1

[0072] When the communication quality of the communication network is less than or equal to a preset threshold (such as the first threshold), the generated control instructions can reduce the running speed of the AGV. As mentioned earlier, when the network is unstable or the available bandwidth is insufficient, packet loss, delay, and jitter occur during data transmission. The cloud server cannot obtain the position measurement data of the AGV in time, and the estimation accuracy of the AGV position decreases. The error of the control instructions it issues increases, resulting in a decrease in the running accuracy of the AGV. In this implementation, when the communication quality is poor, by reducing the running speed of the AGV, the cloud server can obtain more position measurement data at the same time, thereby improving the estimation accuracy of the AGV position, which helps to improve the running accuracy of the AGV.

[0073] Exemplarily, when it is detected that there is no packet loss (or transmission delay, transmission jitter) in the communication network during data transmission, the running speed of the AGV can be controlled at a higher speed level, such as 3.6km / hour, and the cloud server can control the position estimation deviation of the AGV to ±10mm. When it is detected that the communication network has packet loss during data transmission, such as when the packet loss rate exceeds the preset threshold, if no adjustment is made based on step S430, the position estimation deviation of the AGV by the cloud server may increase to ±20mm. By reducing the speed of the AGV to, for example, 1.8km / hour through the control instruction in step S430, the position estimation deviation of the AGV by the cloud server can be controlled to ±10mm, thereby improving the estimation accuracy of the AGV position.

[0074] Implementation method 2

[0075] When the communication quality of the communication network is less than or equal to a preset threshold (such as a first threshold), the generated control instruction may increase the data transmission frequency of the AGV.

[0076] As mentioned above, when the network is unstable or the available bandwidth is insufficient, the cloud server cannot obtain the AGV's position measurement data in time, and the estimation accuracy of the AGV's position decreases. In this implementation, when the communication quality is poor, the frequency of AGV data transmission can be increased to offset the impact of packet loss, transmission delay, and transmission jitter through frequent data transmission, thereby improving the estimation accuracy of the AGV's position.

[0077] Implementation method three

[0078] When the communication quality of the communication network is less than or equal to a preset threshold (such as a first threshold), the generated control instruction can re-plan the running route of the AGV.

[0079] When the network is unstable or the available bandwidth is insufficient, controlling the operation of multiple AGVs based on the cloud server may cause network congestion problems, and the estimation accuracy of the AGV position will decrease. At this time, when multiple AGVs are running, if the running routes are too dense, safety issues such as collisions will occur. In this implementation, when the communication quality is poor, the AGV's running route can be replanned. For example, in areas with poor communication quality, the number of running AGVs can be reduced to alleviate network pressure, or the AGV's running route can be directly planned to avoid the area. For another example, the density of the AGV's running route can be reduced, and the safety distance reserved for each AGV when running can be increased to reduce the probability of collision.

[0080] Implementation method 4

[0081] When the communication quality of the communication network is less than or equal to a preset threshold (such as a second threshold), the generated control instruction can control the AGV to switch to autonomous control of the AGV based on the cloud server. The second threshold here can be greater than the first threshold mentioned above. In other words, implementation method four can be executed only when the communication quality becomes worse, or in other words, implementation method four can be executed when the network environment is severe and the data transmission quality is significantly reduced. For ease of understanding, the following text combines Figure 5 , and the implementation method is introduced in detail with examples.

[0082] Figure 5 The schematic diagram of the structure of the cloud AGV in the embodiment of the present application is shown. Figure 5 As shown, the cloud-based AGV can also be called a hybrid AGV. The difference from the cloud-based AGV in the related art is that the hybrid AGV is equipped with a path planning unit, a map management unit, and a SLAM unit in the cloud server, and also in the AGV. In this way, the hybrid AGV can support the switching between cloud server navigation and traditional autonomous navigation, ensuring safe operation when the network is unstable or fails.

[0083] In some implementations, the map data can be jointly maintained on the AGV and the cloud server, and real-time navigation can be performed using the local map. At the same time, the data can be synchronized to the cloud server for global optimization to improve the accuracy of navigation.

[0084] In some implementations, flexible task scheduling can be performed based on the network status, with high-value tasks that need to be supported being processed first on the cloud server, while local tasks are executed on the AGV at the same time, to fully utilize network resources and improve work efficiency.

[0085] It should be understood that the above implementations 1 to 4 can be used alone or in combination, and the present application embodiment does not specifically limit this. For example, when the communication quality of the communication network deteriorates, the running speed of the AGV can be reduced while the data transmission frequency of the AGV can be increased, thereby improving the estimation accuracy of the AGV position.

[0086] The above describes that when the communication quality of the communication network deteriorates, the working state of the AGV is adjusted based on the generated control instructions to adapt to the deteriorated communication quality. In addition, Figure 4 The method shown can also adjust the working state of the AGV based on the generated control instructions to adapt to the improved communication quality after the communication quality is improved. The communication quality improvement here can be to restore the deteriorated communication quality to normal communication quality, or to improve the normal communication quality to better communication quality.

[0087] For example, when the communication quality of the communication network is improved from a normal level to a preset threshold, the generated control instructions can increase the operating speed of the AGV. Exemplarily, when it is detected that the data transmission capability of the communication network is in a normal state, the operating speed of the AGV can be controlled at a higher speed level, such as 3.6km / hour, at which time the cloud server can control the position estimation deviation of the AGV to ±10mm. When it is detected that the data transmission capability of the communication network is higher than the normal state, the operating speed of the AGV can be controlled at a higher speed level, such as 4.6km / hour, at which time the cloud server can also control the position estimation deviation of the AGV to ±10mm.

[0088] For another example, when the communication quality of the communication network increases from a normal level to a preset threshold, the generated control instructions can re-plan the AGV's running route, for example, the density of the AGV's running route can be increased in the working area, or the number of running AGVs can be increased.

[0089] The above methods can fully utilize network resources and help improve the working efficiency of AGV.

[0090] As mentioned above, the communication quality mentioned in the embodiments of the present application can be the actual detected communication quality or the predicted communication quality. Compared with the actual detected communication quality, the change in communication quality in the future time period can be determined based on the predicted communication quality, and then the working state of the AGV can be adjusted in advance, so that the working state of the AGV can always be kept matching the communication quality of the current communication network, thereby helping to further improve the reliability of the operation of the cloud AGV. For ease of understanding, the following exemplifies how to adjust the working state of the AGV based on the predicted communication quality.

[0091] For example, taking the implementation method 1 in the above text as an example, when it is predicted that the communication quality is less than or equal to the preset threshold in the first time period in the future, the generated control instruction can reduce the running speed of the AGV in advance before the first time period. For another example, taking the implementation method 2 in the above text as an example, when it is predicted that the communication quality is less than or equal to the preset threshold in the second time period in the future, the generated control instruction can increase the data transmission frequency of the AGV in advance before the second time period. This helps the cloud server to maintain the estimation accuracy of the AGV position at a normal level, thereby improving the running accuracy of the AGV.

[0092] For another example, taking the third implementation method as an example, when it is predicted that the communication quality is less than or equal to the preset threshold in the third time period in the future, the generated control instruction can re-plan the AGV's operation route in advance before the third time period. For example, the density of the AGV operation route in the working area can be reduced in advance before the third time period. This helps to avoid the increased probability of collisions between multiple AGVs due to poor operation accuracy when the communication quality is poor.

[0093] For another example, taking the fourth implementation method as an example, when it is predicted that the communication quality is less than or equal to the preset threshold in the fourth time period in the future, the generated control instruction can switch the AGV control based on the cloud server to the autonomous control of the AGV before the fourth time period. Switching the AGV to autonomous control in advance can prevent the AGV from losing control due to the failure to receive navigation instructions when the communication quality deteriorates, or avoid collisions due to poor operating accuracy.

[0094] Combination of the above Figures 1 to 5 , describes the method embodiment of the present application in detail, and the following is combined with Figures 6 to 9 , describes the device embodiment of the present application in detail. It should be understood that the description of the method embodiment corresponds to the description of the device embodiment, so the parts not described in detail can refer to the previous method embodiment.

[0095] Figure 6 Schematic diagram of the system architecture of the control system of the present application embodiment. Figure 6 As shown, the control system includes AGV610, 5G network 620 and cloud server 630.

[0096] Among them, a 5G terminal / gateway is installed on the AGV 610, and the AGV 610 is connected to the 5G base station through the 5G terminal / gateway and realizes communication between the cloud server 630 and the AGV 610. The communication data includes sensor information, that is, information uploaded from the AGV 610 to the cloud server 630 through the 5G network 620, and control / path planning information, that is, information sent from the cloud server 630 to the AGV 610 through the 5G network 620.

[0097] The 5G base station is deployed with an AGV communication quality function module to predict or monitor the communication quality of the 5G network 620 (such as packet loss rate, transmission delay, transmission jitter, available bandwidth, etc.) in real time, and report the results to the cloud server 630.

[0098] The cloud server 630 uses the communication quality provided by the 5G base station to send instructions in real time to adjust the working status of AGV610, such as updating the path planning of AGV610 (for example, avoiding areas with poor coverage of the 5G network 620, or areas with network congestion), reducing the operating speed of AGV610, or switching from controlling AGV610 based on the cloud server 630 to autonomous control of AGV610.

[0099] Figure 7 is a schematic block diagram of a control system of an embodiment of the present application. The control system is applied to the control method described above. Figure 7 As shown, the control system 700 includes an acquisition module 710 , a generation module 720 and a sending module 730 .

[0100] The acquisition module 710 is used to acquire the communication quality of the communication network, where the communication network is used for communication between the cloud server and the first automated guided vehicle.

[0101] The generating module 720 is used to generate a control instruction according to the communication quality of the communication network, wherein the control instruction is used to adjust the operation mode and / or data transmission frequency of the first automated guided vehicle.

[0102] The sending module 730 is used to send the control instruction to the first automatic guided vehicle.

[0103] In some possible implementations, the operation mode includes one or more of the following:

[0104] the operating speed of the first automated guided vehicle;

[0105] an operating route of the first automated guided vehicle;

[0106] The first automated guided vehicle is controlled based on the cloud server or the first automated guided vehicle is autonomously controlled.

[0107] In some possible implementations, generating a control instruction according to the communication quality of the communication network includes:

[0108] If the communication quality of the communication network is less than or equal to the first threshold, the control instruction is generated, and the control instruction is used to execute one or more of the following:

[0109] reducing the operating speed of the first automated guided vehicle;

[0110] increasing the frequency of data transmission by the first automated guided vehicle;

[0111] Replan the operation route of the first automated guided vehicle.

[0112] In some possible implementations, generating a control instruction according to the communication quality of the communication network includes:

[0113] If the communication quality of the communication network is less than or equal to a second threshold, the control instruction is generated, wherein the control instruction is used to switch the control of the first automated guided vehicle based on the cloud server to autonomous control of the first automated guided vehicle.

[0114] In some possible implementations, the communication quality of the communication network includes: communication quality obtained by detection; and / or communication quality obtained by prediction.

[0115] In some possible implementations, the communication quality of the communication network is determined based on one or more of the following: transmission delay, packet loss rate, available bandwidth, and transmission jitter.

[0116] Figure 8 is a schematic block diagram of a control system of another embodiment of the present application. The control system is applied to the control method described above. Figure 8 As shown, the control system 800 includes a receiving module 810 and an adjusting module 820 .

[0117] The receiving module 810 is used to receive a control instruction sent by a cloud server, where the control instruction is generated based on the communication quality of the communication network between the cloud server and the first automated guided vehicle.

[0118] The adjustment module 820 adjusts the operation mode and / or data transmission frequency of the first automated guided vehicle based on the control instruction.

[0119] In some possible implementations, the operation mode includes one or more of the following:

[0120] the operating speed of the first automated guided vehicle;

[0121] an operating route of the first automated guided vehicle;

[0122] The first automated guided vehicle is controlled based on the cloud server or the first automated guided vehicle is autonomously controlled.

[0123] In some possible implementations, the control instruction is used to perform one or more of the following:

[0124] reducing the operating speed of the first automated guided vehicle;

[0125] increasing the frequency of data transmission by the first automated guided vehicle;

[0126] Replan the operation route of the first automated guided vehicle.

[0127] In some possible implementations, the control instruction is used to switch control of the first automated guided vehicle based on the cloud server to autonomous control of the first automated guided vehicle.

[0128] In some possible implementations, the communication quality of the communication network includes: communication quality obtained by detection; and / or communication quality obtained by prediction.

[0129] In some possible implementations, the communication quality of the communication network is determined based on one or more of the following: transmission delay, packet loss rate, available bandwidth, and transmission jitter.

[0130] Fig. 9 A schematic block diagram of a control system according to an embodiment of the present application. Fig. 9 The system 900 shown may include: a memory 910, a processor 920, and an input / output interface 930. The memory 910, the processor 920, and the input / output interface 930 are connected via an internal connection path, the memory 910 is used to store instructions, and the processor 920 is used to execute the instructions stored in the memory 920 to control the input / output interface 930 to receive input data and information, output data such as operation results, and control the transceiver 940 to send signals.

[0131] It should be understood that in the embodiment of the present application, the processor 920 can adopt a general central processing unit (CPU), a microprocessor, an application specific integrated circuit (ASIC), or one or more integrated circuits to execute relevant programs to implement the technical solution provided in the embodiment of the present application.

[0132] The memory 910 may include a read-only memory and a random access memory, and provides instructions and data to the processor 920. A portion of the processor 920 may also include a nonvolatile random access memory. For example, the processor 920 may also store information on the device type.

[0133] In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in the processor 920 or an instruction in the form of software. The method for requesting uplink transmission resources disclosed in conjunction with the embodiment of the present application can be directly embodied as a hardware processor for execution, or a combination of hardware and software modules in the processor for execution. The software module can be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 910, and the processor 920 reads the information in the memory 910 and completes the steps of the above method in conjunction with its hardware. To avoid repetition, it will not be described in detail here.

[0134] It should be understood that in the embodiments of the present application, the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0135] It should be understood that in the embodiment of the present application, "B corresponding to A" means that B is associated with A, and B can be determined according to A. However, it should also be understood that determining B according to A does not mean determining B only according to A, and B can also be determined according to A and / or other information.

[0136] It should be understood that the term "and / or" in this article is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0137] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0138] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0139] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0140] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0141] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that can be read by a computer or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital video disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0142] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A control method, characterized in that: The control method is applied to a cloud server, comprising: Acquiring a communication quality of a communication network, wherein the communication network is used for communication between the cloud server and the first automated guided vehicle; generating a control instruction according to the communication quality of the communication network, wherein the control instruction is used to adjust the operation mode and / or data transmission frequency of the first automated guided vehicle; The control instruction is sent to the first automatic guided vehicle.

2. The method according to claim 1, characterized in that The operation mode includes one or more of the following: the operating speed of the first automated guided vehicle; an operating route of the first automated guided vehicle; The first automated guided vehicle is controlled based on the cloud server or the first automated guided vehicle is autonomously controlled.

3. The method according to claim 1 or 2, characterized in that: The generating a control instruction according to the communication quality of the communication network includes: If the communication quality of the communication network is less than or equal to the first threshold, the control instruction is generated, and the control instruction is used to execute one or more of the following: reducing the operating speed of the first automated guided vehicle; increasing the data transmission frequency of the first automated guided vehicle; Replan the operation route of the first automated guided vehicle.

4. The method according to claim 1 or 2, characterized in that: The generating of the control instruction according to the communication quality of the communication network comprises: If the communication quality of the communication network is less than or equal to a second threshold, the control instruction is generated, where the control instruction is used to switch the control of the first automated guided vehicle based on the cloud server to autonomous control of the first automated guided vehicle.

5. The method according to claim 1, characterized in that The communication quality of the communication network includes: the detected communication quality; and / or, Predicted communication quality.

6. The method according to claim 1, characterized in that The communication quality of the communication network is determined based on one or more of the following: Transmission delay, packet loss rate, available bandwidth, and transmission jitter.

7. A control method, characterized in that: The control method is applied to a first automatic guided vehicle, comprising: receiving a control instruction sent by a cloud server, wherein the control instruction is generated based on the communication quality of a communication network between the cloud server and the first automated guided vehicle; Based on the control instruction, the operation mode and / or data transmission frequency of the first automated guided vehicle is adjusted.

8. The method according to claim 7, characterized in that The operation mode includes one or more of the following: the operating speed of the first automated guided vehicle; an operating route of the first automated guided vehicle; The first automated guided vehicle is controlled based on the cloud server or the first automated guided vehicle is autonomously controlled.

9. A control system, characterized in that: include: A memory for storing program codes; A processor, configured to execute the program code to perform the method according to any one of claims 1 to 6 or claims 7 to 8.

10. A computer-readable storage medium, characterized in that: A program code for executing the method according to any one of claims 1 to 6 or claims 7 to 8 is stored thereon.

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