An intelligent control method based on time synchronization applied to logistics system

Abstract

The present invention proposes an intelligent control method based on time synchronization for use in a logistics system. The method realizes intelligent control by system initialization, path planning, and control of driving devices. The method can ensure that the goods are transported to the designated destination according to the planned path under the control instructions pre-set at each node. Such an algorithm can effectively improve the working efficiency of the transmission system. The intelligent control method based on time synchronization proposed by the present invention can transport goods to the designated location in a relatively short time with extremely high accuracy in a logistics warehouse center that covers a large area, has a large amount of goods, and has high requirements for timeliness and accuracy, thereby effectively improving the transportation efficiency of goods.

Description

Technical Field

[0001] The present invention belongs to the field of artificial intelligence technology, and in particular relates to an intelligent control method based on time synchronization applied to a logistics system. Background Art

[0002] The current existing logistics control systems mainly use the sensor-server method to sense and locate objects, and realize motion control through server-edge device-control device. The modules are connected by communication cables or local wireless networks, which can effectively control the transportation of objects.

[0003] However, this system has the disadvantage of communication delay. This problem mainly exists in the communication between sensors and host computers, and between host computers and distributed edge devices. Due to the existence of time delay, there is huge uncertainty in multi-directional logistics control at high speed, which makes it difficult to meet the accuracy required by the system.

[0004] At the same time, when the control device of the system is expanded to a certain extent, message queue congestion will occur in the communication: when the corresponding instruction does not arrive at the specified time node, the message will accumulate in the transmission queue and cause congestion, but when the system arrives at the specified time node, multiple data packets will be transmitted at the same time, which will cause problems such as data coverage or queuing delay, which will further aggravate the negative effects of time delay. Summary of the invention

[0005] The purpose of the present invention is to solve the problems in the prior art and propose an intelligent control method based on time synchronization applied to a logistics system.

[0006] The present invention is implemented by the following technical solutions. The present invention proposes an intelligent control method based on time synchronization applied to a logistics system. The method is specifically as follows:

[0007] Based on the time of the host computer, the distributed edge devices are synchronized with it to unify the time to complete the initialization preparation of the control method. The distributed edge devices need to be resynchronized regularly to ensure high-precision accuracy.

[0008] Predict the time when the goods enter the logistics system, and use this time as a benchmark to call the A* algorithm to plan the route of the goods. According to the feedback of the linear speed and drive control, the movement trajectory of the object is predicted, and the time required for the goods to arrive at each node and the control instructions required to be issued at the node are calculated;

[0009] Design a message queue with priority. The format of the message content is: priority, running time, control instruction. The message content is issued according to the time when the goods enter the logistics system. After the distributed edge device receives the data, it sorts all current instructions according to the set priority-running time, and issues control instructions to the drive device at the specified running time.

[0010] Furthermore, when the visual sensor detects a collision of goods, the host computer will call the RVO algorithm to recalculate the movement trajectory of the goods, and increase the priority of the current instruction to the highest, insert it to the front of the queue for distribution, and when the distributed edge device receives a message with a higher priority, the same drive device or the same time, it will overwrite the instruction that has been issued to the local machine.

[0011] Furthermore, PTPd is selected to obtain the network driver layer time and perform time synchronization of distributed edge devices.

[0012] Furthermore, the PTPd moves the generation position of the timestamp from the physical layer to the network driver layer, and the formula for calculating the time deviation is:

[0013]

[0014] Furthermore, the distributed edge device is connected to the host computer via a high-speed real-time bus, and the sensor and the host computer adopt POWERLINK or EtherCAT real-time industrial Ethernet.

[0015] Furthermore, during the path planning process:

[0016] When transportation begins, the goods are placed at the starting point of the logistics system. After the visual or pressure sensor confirms the condition of the goods, it will notify the host computer to start calculations.

[0017] The host computer uses the A* algorithm for path planning to meet the planning requirements of the goods from any starting point to any end point along the optimal path. After completing the path planning, the host computer will calculate the acceleration required by the drive device when the goods pass through each node, as well as the estimated time for the goods to pass through the node based on the planned path and the set cargo transportation speed;

[0018] After completing the calculation, the host computer will synthesize the calculated control instructions of each node together with the time node into a message of the specified format, and send it to the edge device to which each node belongs. The edge device determines whether there will be a conflict between the existing control instructions and the instructions to be sent. If so, the conflict will be reported to the host computer, and the host computer will call the RVO algorithm to recalculate the corresponding data; if no conflict occurs, the edge device needs to send the control instructions to the specified drive device when it arrives at the recorded time node.

[0019] The present invention proposes an intelligent control system based on time synchronization for use in a logistics system, wherein the system is specifically:

[0020] Initialization module: It is used to synchronize the distributed edge devices with the host computer based on the time of the host computer to unify the time and complete the initialization preparation of the control method. The distributed edge devices need to resynchronize the time regularly to ensure high accuracy.

[0021] Prediction module: used to predict the time when the goods enter the logistics system, and use this time as a benchmark to call the A* algorithm to plan the route of the goods, and predict the movement trajectory of the object based on the linear speed and drive control feedback, calculate the time required for the goods to arrive at each node, and the control instructions required to be issued at the node;

[0022] Control module: used to design a message queue with priority. The format of the message content is: priority, running time, control instruction. The message content is issued according to the time when the goods enter the logistics system. After the distributed edge device receives the data, it sorts all current instructions according to the set priority-running time, and issues control instructions to the drive device at the specified running time.

[0023] Furthermore, once new goods enter the logistics system, or the visual sensor detects a collision, the host computer will be notified in real time to re-plan the path using the RVO algorithm. After the host computer completes the planning again, it will synthesize a higher priority message and send it down.

[0024] The present invention also proposes an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the intelligent control method based on time synchronization applied to a logistics system are implemented.

[0025] The present invention also proposes a computer-readable storage medium for storing computer instructions, which, when executed by a processor, implement the steps of the intelligent control method based on time synchronization applied to a logistics system.

[0026] Beneficial effects of the present invention:

[0027] The present invention proposes an intelligent control method based on time synchronization for use in logistics systems. With the increase in the amount of goods, the logistics transportation system is gradually improving the transmission speed, but the current control algorithm has certain limitations in this environment, and an effective intelligent control algorithm is urgently needed to ensure the stability of transmission. The intelligent control method based on time synchronization proposed in the present invention can transport goods to designated locations with extremely high accuracy in logistics warehouse centers that cover a large area, have a large amount of goods, and have high requirements for timeliness and accuracy, thereby effectively improving the transportation efficiency of goods. In particular, the intelligent control method can also be applied to similar systems that require predictive control, such as factory robotic arms, and smart cars and other systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0029] Figure 1 It is the basic flow chart of the intelligent control method;

[0030] Figure 2 It is the flow chart of PTP algorithm;

[0031] Figure 3 Select eth0 port for client to connect to the network cable and do not perform clock synchronization;

[0032] Figure 4 Select eth0 port for client to connect the network cable and perform clock synchronization. DETAILED DESCRIPTION

[0033] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0034] The present invention proposes an intelligent control method based on time synchronization and path planning technology, which can be directly applied to the cargo transportation of the logistics system.

[0035] Combination Figure 1-Figure 4 The present invention proposes an intelligent control method based on time synchronization for use in a logistics system, and the method is specifically as follows:

[0036] Based on the time of the host computer, the distributed edge devices are synchronized with it to unify the time to complete the initialization preparation of the control method. The distributed edge devices need to be resynchronized regularly to ensure high-precision accuracy.

[0037] Predict the time when the goods enter the logistics system, and use this time as a benchmark to call the A* algorithm to plan the route of the goods. According to the feedback of the linear speed and drive control, the movement trajectory of the object is predicted, and the time required for the goods to arrive at each node and the control instructions required to be issued at the node are calculated;

[0038] Design a message queue with priority. The format of the message content is: priority, running time, control instructions. The running time and control instructions are the data calculated above. The message content is issued according to the time when the goods enter the logistics system. After the distributed edge device receives the data, it sorts all current instructions according to the set priority-running time, and issues control instructions to the drive device at the specified running time.

[0039] In particular, when the visual sensor detects a collision of goods, the host computer will call the RVO algorithm to recalculate the movement trajectory of the goods, and increase the priority of the current instruction to the highest, insert it to the front of the queue for distribution, and when the distributed edge device receives a message with a higher priority, the same drive device or the same time, it will overwrite the instruction that has been issued to the local machine.

[0040] 1. Time synchronization of distributed edge devices:

[0041] PTPd is used to obtain the network driver layer time and synchronize the time of distributed edge devices.

[0042] Since there are great differences in the selection of distributed edge devices in different control systems, and considering that not all devices support the hardware-precision PTP protocol, in order to improve the compatibility of the control algorithm, the PTPd protocol that can obtain the network driver layer is selected in this invention.

[0043] PTPd (Precision Time Protocol daemon) is an implementation of the PTP protocol defined in the IEEE1588 standard. It can provide precise time coordination for computers connected to Ethernet.

[0044] In this intelligent control algorithm, when the device is started, the host computer time is used as the benchmark to synchronize the time of all distributed edge devices using the PTPd protocol to complete the initialization preparation of the algorithm. And it is necessary to resynchronize the edge devices regularly (1-2s) to ensure the accuracy of the accuracy.

[0045] PTPd is based on the implementation of the PTP protocol. The implementation process of PTP is as follows Figure 2 shown.

[0046] The main difference between PTPd and PTP is that the generation location of the timestamp is moved from the physical layer to the network driver layer. Its calculation method still uses the PTP formula. The formula for calculating the time deviation is:

[0047]

[0048] 2. Network communication under time synchronization:

[0049] In order to minimize the negative effects of network delays, distributed edge devices are connected to the host computer through a high-speed real-time bus. In particular, sensors and host computers can consider using real-time industrial Ethernet such as POWERLINK or EtherCAT to reduce the delay in message sending and ensure the real-time performance of the system.

[0050] Based on the intelligent control method proposed in the present invention, message scheduling only consists of messages required to complete system clock synchronization and necessary control instruction messages, and the sending time of all messages can be configured in advance, which can effectively avoid blocking of message queues, improve bus utilization, and ensure the real-time performance of the system.

[0051] 3. Intelligent control method based on path planning:

[0052] During path planning:

[0053] When transportation begins, the goods are placed at the starting point of the logistics system. After the visual or pressure sensor confirms the condition of the goods, it will notify the host computer to start calculations.

[0054] The host computer uses the A* algorithm for path planning, which can meet the planning requirements of goods from any starting point to any destination along the optimal path. After completing the path planning, the host computer will calculate the acceleration required by the drive device when the goods pass through each node, as well as the estimated time for the goods to pass through the node based on the planned path and the set cargo transportation speed;

[0055] After completing the calculation, the host computer will synthesize the calculated control instructions of each node together with the time node into a message of the specified format, and send it to the edge device to which each node belongs. The edge device determines whether there will be a conflict between the existing control instructions and the instructions to be sent. If so, the conflict will be reported to the host computer, and the host computer will call the RVO algorithm to recalculate the corresponding data; if no conflict occurs, the edge device needs to send the control instructions to the specified drive device when it arrives at the recorded time node.

[0056] The present invention proposes an intelligent control system based on time synchronization for use in a logistics system, wherein the system is specifically:

[0057] Initialization module: It is used to synchronize the distributed edge devices with the host computer based on the time of the host computer to unify the time and complete the initialization preparation of the control method. The distributed edge devices need to resynchronize the time regularly to ensure high accuracy.

[0058] Prediction module: used to predict the time when the goods enter the logistics system, and use this time as a benchmark to call the A* algorithm to plan the route of the goods, and predict the movement trajectory of the object based on the linear speed and drive control feedback, calculate the time required for the goods to arrive at each node, and the control instructions required to be issued at the node;

[0059] Control module: used to design a message queue with priority. The format of the message content is: priority, running time, control instruction. The message content is issued according to the time when the goods enter the logistics system. After the distributed edge device receives the data, it sorts all current instructions according to the set priority-running time, and issues control instructions to the drive device at the specified running time.

[0060] In particular, once new goods enter the logistics system, or the visual sensor detects a collision, the host computer will be notified in real time to use the RVO algorithm to re-plan the path. After the host computer completes the planning again, it will synthesize a higher priority message and send it down.

[0061] The method and system of the present invention can ensure that the goods can be transported to the designated destination along the planned path under the control instructions pre-set at each node. Such an algorithm can effectively improve the working efficiency of the transmission system.

[0062] The present invention mainly solves a series of problems caused by time delay in the logistics transportation system, and in particular, experimentally verifies the necessity of time synchronization.

[0063] In the experiment, the server was selected as the host computer and the Raspberry Pi as the edge device. The transmission delay between the server and the client was tested with or without time synchronization and whether the bus was selected for connection. Figure 3 as well as Figure 4 It is proved that in the case of time synchronization, selecting a bus can effectively reduce the delay to millisecond level, which meets the accuracy requirements of the present invention.

[0064] The present invention also proposes an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the intelligent control method based on time synchronization applied to a logistics system are implemented.

[0065] The present invention also proposes a computer-readable storage medium for storing computer instructions, which, when executed by a processor, implement the steps of the intelligent control method based on time synchronization applied to a logistics system.

[0066] The memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM bus RAM (DRRAM). It should be noted that the memory of the method described in the present invention is intended to include, but is not limited to, these and any other suitable types of memory.

[0067] 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 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 a computer can access 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 high-density digital video disc (DVD)), or a semiconductor medium (eg, a solid state disc (SSD)).

[0068] In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in a processor or an instruction in the form of software. The steps of the method 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 a processor for execution. The software module can be located in a storage medium mature 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 a memory, and the processor reads the information in the memory and completes the steps of the above method in conjunction with its hardware. To avoid repetition, it is not described in detail here.

[0069] It should be noted that the processor in the embodiment of the present application can be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method embodiment can be completed by an integrated logic circuit of hardware in the processor or an instruction in the form of software. The above processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in the embodiment of the present application can be directly embodied as a hardware decoding processor to perform, or the hardware and software modules in the decoding processor can be combined and performed. The software module can be located in a mature storage medium in the field 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 a memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0070] The above is a detailed introduction to the intelligent control method based on time synchronization applied to the logistics system proposed in the present invention. Specific examples are used in this article to illustrate the principle and implementation mode of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present invention, there will be changes in the specific implementation mode and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. An intelligent control method based on time synchronization applied to a logistics system, characterized in that: The method is specifically as follows: Based on the time of the host computer, the distributed edge devices are synchronized with it to unify the time to complete the initialization preparation of the control method. The distributed edge devices need to be resynchronized regularly to ensure high-precision accuracy. Predict the time when the goods enter the logistics system, and use this time as a benchmark to call the A* algorithm to plan the route of the goods. According to the feedback of the linear speed and drive control, the movement trajectory of the object is predicted, and the time required for the goods to arrive at each node and the control instructions required to be issued at the node are calculated; Design a message queue with priority. The format of the message content is: priority, running time, control instruction. The message content is issued according to the time when the goods enter the logistics system. After the distributed edge device receives the data, it sorts all the current instructions according to the set priority-running time, and issues control instructions to the drive device at the specified running time. When the visual sensor detects a collision between goods, the host computer will call the RVO algorithm to recalculate the movement trajectory of the goods, and increase the priority of the current instruction to the highest, insert it to the front of the queue for distribution, and when the distributed edge device receives a message with a higher priority, the same drive device or the same time, it will overwrite the instruction that has been issued to the local machine.

2. The method according to claim 1, characterized in that: PTPd is used to obtain the network driver layer time and synchronize the time of distributed edge devices.

3. The method according to claim 2, characterized in that: The PTPd moves the generation position of the timestamp from the physical layer to the network driver layer, and the formula for calculating the time deviation is:

4. The method according to claim 1, characterized in that: The distributed edge device is connected to the host computer via a high-speed real-time bus, and the sensor and the host computer adopt POWERLINK or EtherCAT real-time industrial Ethernet.

5. The method according to claim 1, characterized in that: During path planning: When transportation begins, the goods are placed at the starting point of the logistics system. After the visual or pressure sensor confirms the condition of the goods, it will notify the host computer to start calculations. The host computer uses the A* algorithm for path planning to meet the planning requirements of the goods from any starting point to any end point along the optimal path. After completing the path planning, the host computer will calculate the acceleration required by the drive device when the goods pass through each node, as well as the estimated time for the goods to pass through the node based on the planned path and the set cargo transportation speed; After completing the calculation, the host computer will synthesize the calculated control instructions of each node together with the time node into a message of the specified format, and send it to the edge device to which each node belongs. The edge device determines whether there will be a conflict between the existing control instructions and the instructions to be sent. If so, the conflict will be reported to the host computer, and the host computer will call the RVO algorithm to recalculate the corresponding data; if no conflict occurs, the edge device needs to send the control instructions to the specified drive device when it arrives at the recorded time node.

6. An intelligent control system based on time synchronization applied to a logistics system, characterized in that: The system is specifically: Initialization module: It is used to synchronize the distributed edge devices with the host computer based on the time of the host computer to unify the time and complete the initialization preparation of the control method. The distributed edge devices need to resynchronize the time regularly to ensure high accuracy. Prediction module: used to predict the time when the goods enter the logistics system, and use this time as a benchmark to call the A* algorithm to plan the route of the goods, and predict the movement trajectory of the object based on the linear speed and drive control feedback, calculate the time required for the goods to arrive at each node, and the control instructions required to be issued at the node; Control module: used to design a message queue with priority. The format of the message content is: priority, running time, control instruction. The message content is issued according to the time when the goods enter the logistics system. After the distributed edge device receives the data, it sorts all the current instructions according to the set priority-running time, and issues control instructions to the drive device at the specified running time. Once new goods enter the logistics system, or the visual sensor detects a collision, the host computer will be notified in real time to re-plan the path using the RVO algorithm. After the host computer completes the planning again, it will synthesize a higher priority message and send it down.

7. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium for storing computer instructions, characterized in that: When the computer instructions are executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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