An unattended automatic induction intelligent warehouse management system and method

Abstract

The application discloses an unattended automatic induction intelligent warehouse management system and method, relates to the technical field of intelligent warehousing, and comprises a monitoring center, wherein the monitoring center is communicatively connected with a goods shelf information module, a robot management module, a data acquisition module, an intelligent scheduling module, a route planning module, a goods transportation module and a goods updating module; basic information of each goods shelf in the intelligent warehouse is acquired through the goods shelf information module, basic parameters of the track robot are acquired through the robot management module, robot operation data of the track robot and goods information of the goods to be stored are acquired through a deployment data acquisition terminal, a storage position of the goods is acquired according to the goods information of the goods to be stored and the basic information of the goods shelf, an optimal driving path is generated to transport the goods to be stored into the warehouse, and the basic information of the goods shelf is updated according to the warehousing result; the method guarantees the automation and the intelligentization of the whole process and promotes the management of the unattended intelligent warehouse.

Description

Technical Field

[0001] The present invention relates to the field of intelligent warehousing technology, and in particular to an unmanned automatic sensing intelligent warehouse management system and method. Background Art

[0002] With the large-scale development of the logistics industry and the explosive growth of e-commerce orders, warehouse management efficiency, accuracy and operating cost control have become the key to a company's core competitiveness;

[0003] The traditional warehouse management model mainly relies on manual operation or single automated equipment to complete the operation process. When faced with the needs of dynamic inventory control and multi-equipment collaborative scheduling, many problems are exposed. For example, manual entry of inventory data leads to errors, the internal route planning of the warehouse is not specific enough, and the single automated equipment only transports according to a fixed path. It lacks the ability to allocate dynamic priorities for multiple tasks, resulting in redundant cargo transportation paths, congestion in storage locations, transportation collisions, and cargo falling. At the same time, inventory management and intelligent scheduling of equipment still rely on manual intervention, which requires high manpower costs and reduces response speed, affecting the intelligence level of the warehouse. Therefore, realizing warehouse management with unmanned operation throughout the entire process, intelligent coordination of equipment, and dynamic closed-loop data is a problem we need to solve. To this end, an unmanned automatic sensing intelligent warehouse management system and method are now provided. Summary of the Invention

[0004] The purpose of the present invention is to provide an unmanned automatic sensing intelligent warehouse management system and method.

[0005] The object of the present invention can be achieved by the following technical solutions: an unmanned automatic sensing intelligent warehouse management system, comprising a monitoring center, wherein the monitoring center is communicatively connected to a shelf information module, a robot management module, a data acquisition module, an intelligent scheduling module, a route planning module, a cargo transportation module, and a cargo update module;

[0006] The shelf information module stores basic information of each shelf in the smart warehouse;

[0007] The robot management module is used to store basic parameters of the track robot;

[0008] The data acquisition module is used for the robot operation data of the track robot and the cargo information of the cargo to be stored;

[0009] The intelligent scheduling module is used to obtain the storage location of the goods according to the goods information of the goods to be stored and the basic information of each shelf;

[0010] The route planning module is used to generate an optimal driving path for the rail robot according to the storage location of the goods;

[0011] The cargo transportation module is used to transport the cargo to be stored to the shelf according to the optimal driving path and obtain the warehousing results of the cargo to be stored;

[0012] The goods updating module updates the basic information of the shelf according to the goods entry result.

[0013] Furthermore, the basic information of the shelf includes the shelf location, shelf storage capacity and shelf maximum capacity;

[0014] The basic parameters of the rail robot include the maximum load capacity and the type of cargo that can be carried.

[0015] Furthermore, the data acquisition module is composed of several data acquisition terminals, which are deployed at the warehouse entrance and inside the track robot;

[0016] Real-time information on goods to be stored is obtained through data collection terminals deployed at the warehouse entrance;

[0017] The cargo information of the cargo to be stored includes cargo weight and cargo order attributes;

[0018] The robot operation data of the track robot is obtained in real time through the data acquisition terminal deployed in the track robot;

[0019] The robot operation data includes the standard driving speed of the track robot and the real-time position of the track robot.

[0020] Furthermore, the process of obtaining the storage location of goods according to the information of goods to be stored and the basic information of each shelf by the intelligent scheduling module includes:

[0021] Match the order attributes of the goods with the types of goods that the rail robot can carry, and select the rail robot that can be used to transport the goods to be stored;

[0022] Match the maximum load capacity and the type of cargo that can be carried by the screened rail robot with the weight of the cargo to be stored, and select the corresponding rail robot based on the matching result;

[0023] Select a corresponding shelf according to the remaining capacity of the shelf and the weight of the goods to be stored, and record the selected shelf as the storage location of the goods;

[0024] Mark the warehouse entrance as the starting point and the shelf location where the goods to be stored are to be stored as the end point.

[0025] Furthermore, the process of the route planning module generating the optimal driving path of the rail robot according to the storage location of the goods includes:

[0026] Generate several alternative paths from the starting point to the end point based on the marked starting point and end point, and obtain the total length of each alternative path;

[0027] Divide each alternative path into several track segments and mark the corresponding turning nodes in the alternative path;

[0028] Set the shortest length of all alternative paths, the ratio of the number of track segments to the total number of track robots, the total number of turning nodes in each alternative path, and the total number of track robots in each alternative path;

[0029] Based on the total route length of each alternative path, the total number of track robots in each alternative path, and the total number of turning nodes in each alternative path, the priority coefficient of the alternative path is obtained, and the alternative path with the highest priority coefficient is selected as the optimal driving path based on the priority coefficients of the obtained alternative paths.

[0030] Furthermore, the process of the cargo transportation module transporting the cargo to be stored to the shelf according to the optimal driving route and obtaining the warehousing result of the cargo to be stored includes:

[0031] Set the safe distance threshold between track robots;

[0032] Get the standard driving speed of the track robot;

[0033] When the track robot enters a track segment on the optimal driving path, the location of the track robot is recorded as the first node, and it is determined whether there are other track robots on the track segment;

[0034] A maximum of two track robots can exist on the same track segment at the same time;

[0035] When there are no other rail robots, a deceleration node of the rail robot relative to the next turning node is generated according to the weight of the cargo carried by the rail robot, and the deceleration node is recorded as the first deceleration node;

[0036] When there are other rail robots, the positions of the other rail robots are recorded as the second node, and the deceleration node of the other rail robots relative to the next turning node is recorded as the second deceleration node;

[0037] When the first deceleration node is between the first node and the second deceleration node, it means that there is no collision risk between the two track robots;

[0038] When the first deceleration node is between the turning node and the second deceleration node, the estimated arrival time t1 of the first node at each position between the second deceleration node and the turning node is obtained respectively;

[0039] and the estimated arrival time t2 of the second node at each position from the second deceleration node to the turning node;

[0040] At any position between the second deceleration node and the turning node, if t1≤t2, or the distance between the two rail robots is less than the set safety distance threshold, it means that there is a collision risk between the two rail robots, and the position of the first deceleration node is replanned. If t1>t2, and the distance between the two rail robots is not less than the set safety distance threshold, it means that there is no collision risk between the two rail robots.

[0041] Furthermore, the process of the cargo transportation module generating a deceleration node of the rail robot relative to the next turning node according to the weight of the cargo carried by the rail robot includes:

[0042] Set the maximum braking force of the track robot;

[0043] Obtaining the acceleration of the rail robot according to the weight of the cargo carried by the rail robot and the maximum braking force of the rail robot;

[0044] The distance of the deceleration node of the rail robot relative to the next turning node is obtained according to the acceleration of the rail robot and the standard driving speed of the rail robot.

[0045] Furthermore, when there is a collision risk between two rail robots in the cargo transport module, the process of replanning the position of the first deceleration node is as follows:

[0046] Get the time difference;

[0047] Obtaining the acceleration of the rail robot starting from the first node according to the maximum braking force of the rail robot and the weight of the cargo carried by the rail robot;

[0048] According to the acceleration of the track robot starting from the first node and the standard driving speed of the track robot, the speed of the corresponding track robot at the time t2 is obtained;

[0049] According to the speed, time difference and acceleration of the corresponding track robot at time t2, the theoretical safe distance of the corresponding track robot without collision is obtained;

[0050] Get the distance between the first deceleration node and the next turning node;

[0051] According to the obtained theoretical non-collision distance of the corresponding track robots and the safety distance threshold between the track robots, the distance between the first deceleration node and the next turning node after adjustment is obtained;

[0052] The rail robot transports the goods to be stored to the corresponding shelves, obtains the warehousing results of the goods to be stored and uploads them to the monitoring center.

[0053] Further, the process of updating the basic information of the shelf according to the storage result of the goods includes:

[0054] updating the basic information of the shelf according to the storage result and synchronizing to the monitoring center.

[0055] Further, a smart warehouse management method of an unattended automatic induction smart warehouse management system includes the following steps:

[0056] obtaining robot running data of the track robot, goods information of the goods to be stored, and a loadable goods type;

[0057] determining the goods information of the goods to be stored and obtaining a storage position of the goods, and generating an optimal driving path;

[0058] updating the basic information of the shelf according to the storage result.

[0059] Compared with the prior art, the beneficial effects of the present application are: through the shelf information module, the basic information of each shelf in the smart warehouse is obtained; through the robot management module, the basic parameters of the track robot are obtained; through the deployment data acquisition terminal, the robot running data of the track robot and the goods information of the goods to be stored are obtained; according to the goods information of the goods to be stored and the basic information of each shelf, the storage position of the goods is obtained, and the optimal driving path of the track robot is generated to transport the goods to be stored to the corresponding shelf for storage; according to the storage result of the goods to be stored, the basic information of the shelf is updated; through artificial intelligence technology, the automation and intelligentization of the whole process are ensured, and the efficiency, precision and sustainable evolution of the unattended smart warehouse management are promoted. BRIEF DESCRIPTION OF DRAWINGS

[0060] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments described in the present application, and other drawings can also be obtained by those skilled in the art according to these drawings.

[0061] Figure 1 The system block diagram of the present application. DETAILED DESCRIPTION

[0062] As shown in Figure 1 An unattended automatic induction smart warehouse management system, including a monitoring center, the monitoring center is in communication with a shelf information module, a robot management module, a data acquisition module, an intelligent scheduling module, a route planning module, a goods transportation module and a goods update module;

[0063] The shelf information module stores basic information of each shelf in the intelligent warehouse.

[0064] The robot management module is used for storing basic parameters of the track robot.

[0065] The data acquisition module is used for acquiring robot running data of the track robot and goods information of the goods to be stored.

[0066] The intelligent scheduling module is used for obtaining a storage position of the goods according to the goods information of the goods to be stored and the basic information of each shelf.

[0067] The route planning module is used for generating an optimal driving path of the track robot according to the storage position of the goods.

[0068] The goods transportation module is used for transporting the goods to be stored to the shelf according to the optimal driving path and obtaining a storage result of the goods to be stored.

[0069] The goods updating module updates the basic information of the shelf according to the storage result of the goods.

[0070] The basic information of the shelf includes a shelf position, a shelf stored capacity and a shelf maximum capacity.

[0071] The basic parameters of the track robot include a maximum load and a loadable goods type.

[0072] The data acquisition module is composed of a plurality of data acquisition terminals, and the data acquisition terminals are arranged at a warehouse entrance and in the track robot.

[0073] The data acquisition terminals arranged at the warehouse entrance are used for acquiring the goods information of the goods to be stored in real time.

[0074] The goods information of the goods to be stored includes a goods weight and an order attribute of the goods.

[0075] The data acquisition terminals arranged in the track robot are used for acquiring the robot running data of the track robot in real time.

[0076] The robot running data includes a standard driving speed of the track robot and a real-time position of the track robot.

[0077] The process of obtaining the storage position of the goods by the intelligent scheduling module according to the goods information of the goods to be stored and the basic information of each shelf includes:

[0078] Matching the order attribute of the goods with the loadable goods type of the track robot, and screening out the track robot that can be used to transport the goods to be stored.

[0079] Match the maximum load capacity and the type of cargo that can be carried by the screened rail robot with the weight of the cargo to be stored, and select the corresponding rail robot based on the matching result;

[0080] Select a corresponding shelf according to the remaining capacity of the shelf and the weight of the goods to be stored, and record the selected shelf as the storage location of the goods;

[0081] Mark the warehouse entrance as the starting point and the shelf location where the goods to be stored are required to be stored as the end point.

[0082] The process of the route planning module generating the optimal driving path of the rail robot according to the storage location of the goods includes:

[0083] Generate several alternative paths from the starting point to the end point based on the marked starting point and end point, and obtain the total length of each alternative path, recorded as L;

[0084] Divide each alternative path into several track segments and mark the corresponding turning nodes in the alternative path as S;

[0085] The turning node is the position where the track direction changes in the path, and the deflection direction is set to a left turning node and a right turning node;

[0086] Set the shortest length of all alternative paths to ;

[0087] Set the ratio of the number of track segments to the total number of track robots to 1:2;

[0088] Set the total number of turn nodes in each alternative path. The maximum number of turn nodes for a track segment is ;

[0089] Get the total number of track robots in each alternative path, recorded as R;

[0090] According to the total length of each alternative path, the total number of track robots in each alternative path, and the total number of turning nodes in each alternative path, the priority coefficient of the alternative path is obtained, which is recorded as ,in , 、 、 are weight coefficients and + + =1, where is the total number of track robots in all alternative paths;

[0091] According to the obtained priority coefficients of the various alternative paths, the alternative path with the highest priority coefficient is selected as the optimal driving path.

[0092] The process of the cargo transportation module transporting the cargo to be stored to the shelf according to the optimal driving route and obtaining the warehousing result of the cargo to be stored includes:

[0093] Set the safety distance threshold between track robots, denoted as ;

[0094] Get the standard driving speed of the track robot, denoted as v;

[0095] When the track robot enters a track segment on the optimal driving path, the location of the track robot is recorded as the first node, and it is determined whether there are other track robots on the track segment;

[0096] It should be noted that at most two track robots can exist on the same track segment at the same time;

[0097] When there are no other rail robots, a deceleration node of the rail robot relative to the next turning node is generated according to the weight of the cargo carried by the rail robot, and the deceleration node is recorded as the first deceleration node;

[0098] When there are other rail robots, the positions of the other rail robots are recorded as the second node, and the deceleration node of the other rail robots relative to the next turning node is recorded as the second deceleration node;

[0099] When the first deceleration node is between the first node and the second deceleration node, it means that there is no collision risk between the two track robots;

[0100] When the first deceleration node is between the turning node and the second deceleration node, the estimated arrival time of the first node at each position between the second deceleration node and the turning node is obtained, which is recorded as t1;

[0101] and the estimated arrival time of the second node at each location from the second deceleration node to the turning node, denoted as t2;

[0102] At any position between the second deceleration node and the turning node, if t1≤t2, or the distance between the two rail robots is less than the set safety distance threshold, it means that there is a collision risk between the two rail robots, and the position of the first deceleration node is replanned. If t1>t2, and the distance between the two rail robots is not less than the set safety distance threshold, it means that there is no collision risk between the two rail robots.

[0103] It should be further explained that the process of generating the deceleration node of the rail robot relative to the next turning node according to the weight of the cargo carried by the rail robot includes:

[0104] Set the maximum braking force of the track robot to F;

[0105] According to the weight of the cargo carried by the track robot and the maximum braking force of the track robot, the acceleration of the track robot is obtained and recorded as ,in , M is the weight of the cargo carried by the track robot;

[0106] According to the acceleration of the track robot and the standard driving speed of the track robot, the distance of the deceleration node of the track robot relative to the next turning node is obtained and recorded as ,in .

[0107] It should be further explained that when there is a collision risk between two track robots, the process of replanning the position of the first deceleration node is as follows:

[0108] Get the time difference as ,in ;

[0109] According to the maximum braking force of the track robot and the weight of the cargo carried by the track robot, the acceleration of the track robot starting from the first node is obtained and recorded as ,in ;

[0110] According to the acceleration of the track robot starting from the first node and the standard driving speed of the track robot, the speed of the corresponding track robot at time t2 is obtained and recorded as ,in ;

[0111] According to the speed, time difference and acceleration of the corresponding track robot at time t2, the theoretical safe distance of the corresponding track robot without collision is obtained as ,in ;

[0112] Get the distance from the first deceleration node to the next turning node and record it as ;

[0113] According to the theoretical non-collision distance of the corresponding track robot and the safety distance threshold between the track robots, the distance from the first deceleration node to the next turning node after adjustment is obtained and recorded as ,in ;

[0114] The rail robot transports the goods to be stored to the corresponding shelves, obtains the warehousing results of the goods to be stored and uploads them to the monitoring center.

[0115] The process of the goods updating module updating the basic information of the shelf according to the goods warehousing result includes:

[0116] The basic information of the shelf is updated according to the warehousing results and synchronized to the monitoring center.

[0117] The present invention also discloses an unmanned automatic sensing intelligent warehouse management method, comprising the following steps:

[0118] Obtain robot operation data of the rail robot, cargo information of the cargo to be stored, and the types of cargo that can be carried;

[0119] Determine the cargo information of the goods to be stored and obtain the storage location of the goods to generate the optimal driving route;

[0120] Update the basic information of the shelf based on the warehousing results.

[0121] The above description is merely a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Although the present invention has been disclosed as a preferred embodiment as above, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications to equivalent embodiments using the technical contents disclosed above without departing from the scope of the technical solution of the present invention. However, any modification or equivalent replacement of the above embodiments made according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still falls within the scope of the technical solution of the present invention.

Claims

1. An unmanned automatic sensing intelligent warehouse management system, including a monitoring center, characterized in that: The monitoring center is communicatively connected to a shelf information module, a robot management module, a data acquisition module, an intelligent scheduling module, a route planning module, a cargo transportation module, and a cargo update module; The shelf information module stores basic information of each shelf in the smart warehouse; The robot management module is used to store basic parameters of the track robot; The data acquisition module is used for the robot operation data of the track robot and the cargo information of the cargo to be stored; The intelligent scheduling module is used to obtain the storage location of the goods according to the goods information of the goods to be stored and the basic information of each shelf; The route planning module is used to generate an optimal driving path for the rail robot according to the storage location of the goods; The cargo transportation module is used to transport the cargo to be stored to the shelf according to the optimal driving path and obtain the warehousing results of the cargo to be stored; The goods update module updates the basic information of the shelf according to the goods warehousing result; The process of the cargo transportation module transporting the cargo to be stored to the shelf according to the optimal driving route and obtaining the warehousing result of the cargo to be stored includes: Set the safe distance threshold between track robots; Get the standard driving speed of the track robot; When the track robot enters a track segment on the optimal driving path, the location of the track robot is recorded as the first node, and it is determined whether there are other track robots on the track segment; When there are no other rail robots, a deceleration node of the rail robot relative to the next turning node is generated according to the weight of the cargo carried by the rail robot, and the deceleration node is recorded as the first deceleration node; When there are other rail robots, the positions of the other rail robots are recorded as the second node, and the deceleration node of the other rail robots relative to the next turning node is recorded as the second deceleration node; When the first deceleration node is between the first node and the second deceleration node, it means that there is no collision risk between the two track robots; When the first deceleration node is between the turning node and the second deceleration node, the estimated arrival time t1 of the first node at each position between the second deceleration node and the turning node is obtained respectively; and the estimated arrival time t2 of the second node at each position from the second deceleration node to the turning node; At any position between the second deceleration node and the turning node, if t1≤t2, or the distance between the two rail robots is less than the set safety distance threshold, it means that there is a collision risk between the two rail robots, and the position of the first deceleration node is replanned. If t1>t2, and the distance between the two rail robots is not less than the set safety distance threshold, it means that there is no collision risk between the two rail robots.

2. The unmanned automatic sensing intelligent warehouse management system according to claim 1 is characterized in that: The basic information of the shelf includes the shelf location, shelf storage capacity and shelf maximum capacity; The basic parameters of the rail robot include the maximum load capacity and the type of cargo that can be carried.

3. The unmanned automatic sensing intelligent warehouse management system according to claim 2 is characterized in that: The data acquisition module consists of several data acquisition terminals, which are deployed at the warehouse entrance and inside the track robot; Real-time information on goods to be stored is obtained through data collection terminals deployed at the warehouse entrance; The cargo information includes cargo weight and cargo order attributes; The robot operation data of the track robot is obtained in real time through the data acquisition terminal deployed in the track robot; The robot operation data includes the standard driving speed of the track robot and the real-time position of the track robot.

4. The unmanned automatic sensing intelligent warehouse management system according to claim 3 is characterized in that: The process of obtaining the storage location of goods by the intelligent scheduling module according to the goods information of the goods to be stored and the basic information of each shelf includes: Match the order attributes of the goods with the types of goods that the rail robot can carry, and select the rail robot that can be used to transport the goods to be stored; Match the maximum load capacity and the type of cargo that can be carried by the screened rail robot with the weight of the cargo to be stored, and select the corresponding rail robot based on the matching result; Select a corresponding shelf according to the remaining capacity of the shelf and the weight of the goods to be stored, and record the selected shelf as the storage location of the goods; Mark the warehouse entrance as the starting point and the shelf location where the goods to be stored are to be stored as the end point.

5. The unmanned automatic sensing intelligent warehouse management system according to claim 4 is characterized in that: The process of the route planning module generating the optimal driving path of the rail robot according to the storage location of the goods includes: Generate several alternative paths from the starting point to the end point based on the marked starting point and end point, and obtain the total length of each alternative path; Divide each alternative path into several track segments and mark the corresponding turning nodes in the alternative path; Set the shortest length of all alternative paths, the ratio of the number of track segments to the total number of track robots, the total number of turning nodes in each alternative path, and the total number of track robots in each alternative path; Based on the total route length of each alternative path, the total number of track robots in each alternative path, and the total number of turning nodes in each alternative path, the priority coefficient of the alternative path is obtained, and the alternative path with the highest priority coefficient is selected as the optimal driving path based on the priority coefficients of the obtained alternative paths.

6. The unmanned automatic sensing intelligent warehouse management system according to claim 5 is characterized in that: The process of the cargo transportation module generating a deceleration node of the rail robot relative to the next turning node according to the weight of the cargo carried by the rail robot includes: Set the maximum braking force of the track robot; Obtaining the acceleration of the rail robot according to the weight of the cargo carried by the rail robot and the maximum braking force of the rail robot; The distance of the deceleration node of the rail robot relative to the next turning node is obtained according to the acceleration of the rail robot and the standard driving speed of the rail robot.

7. The unmanned automatic sensing intelligent warehouse management system according to claim 6 is characterized in that: When there is a collision risk between two track robots in the cargo transport module, the process of replanning the position of the first deceleration node is as follows: Get the time difference; Obtaining the acceleration of the rail robot starting from the first node according to the maximum braking force of the rail robot and the weight of the cargo carried by the rail robot; According to the acceleration of the track robot starting from the first node and the standard driving speed of the track robot, the speed of the corresponding track robot at the time t2 is obtained; According to the speed, time difference and acceleration of the corresponding track robot at time t2, the theoretical safe distance of the corresponding track robot without collision is obtained; Get the distance between the first deceleration node and the next turning node; According to the obtained theoretical non-collision distance of the corresponding track robots and the safety distance threshold between the track robots, the distance between the first deceleration node and the next turning node after adjustment is obtained; The rail robot transports the goods to be stored to the corresponding shelves, obtains the warehousing results of the goods to be stored and uploads them to the monitoring center.

8. The unmanned automatic sensing intelligent warehouse management system according to claim 7 is characterized in that: The process of the goods updating module updating the basic information of the shelf according to the goods warehousing result includes: The basic information of the shelf is updated according to the warehousing results and synchronized to the monitoring center.

9. The intelligent warehouse management method of an unmanned automatic sensing intelligent warehouse management system according to any one of claims 1 to 8, characterized in that: The following steps are involved: Obtain robot operation data of the rail robot, cargo information of the cargo to be stored, and the types of cargo that can be carried; Determine the cargo information of the goods to be stored and obtain the storage location of the goods to generate the optimal driving route; Update the basic information of the shelf based on the warehousing results.

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