Intelligent high-position stereoscopic warehouse management method and system based on space planning

Abstract

The invention discloses an intelligent high-position stereoscopic warehouse management method and system based on space planning, and relates to the field of garage intelligent management, and the method comprises the steps: obtaining vehicle basic information at a first time node, including vehicle geometric features and vehicle warehousing features, carrying out the clustering analysis of a to-be-warehoused vehicle, and obtaining a to-be-warehoused vehicle information; generating a first-level vehicle clustering result and generating a second-level vehicle clustering result; basic information of the multi-layer garage is obtained, wherein the basic information comprises garage parking space distribution information and garage channel distribution information; parking space planning is carried out, and a parking space virtual identification generation result is generated; and according to the garage channel distribution information, based on the parking space virtual identifier generation result and the secondary vehicle clustering result, carrying out garage entering path planning, generating a garage entering path planning result, and carrying out stereo garage management. The technical problem that in the prior art, a user needs to find a parking space, and the user experience feeling is poor is solved. And by carrying out strategy optimization on the warehousing path, the warehousing intelligence and the user experience are improved.

Description

Technical Field

[0001] The present application relates to the technical field of intelligent garage management, and in particular to an intelligent high-rise warehouse management method and system based on space planning. Background Art

[0002] With the continuous development of social economy, the number of vehicles in society has not only increased, but in order to solve the problem of parking difficulties, the concept of multi-story parking garages has emerged and has become an important direction for the future development of garages.

[0003] Garage management is the work of allocating parking spaces to vehicles entering the garage. Current garage management usually requires vehicles to find parking spaces when entering the garage, and then pay for parking after confirming the parking spaces. With the increasing demand for multi-story garages, vehicles need to find parking spaces when entering the garage, which reduces the user experience.

[0004] The existing technology has a technical problem of poor user experience because users need to find parking spaces. Summary of the Invention

[0005] The purpose of this application is to provide an intelligent high-rise warehouse management method and system based on space planning, so as to solve the technical problem in the prior art that users have to look for parking spaces, resulting in poor user experience.

[0006] In view of the above problems, the present application provides an intelligent high-rise warehouse management method and system based on space planning.

[0007] In a first aspect, the present application provides an intelligent high-rise stereoscopic warehouse management method based on space planning, wherein the method is implemented through an intelligent high-rise stereoscopic warehouse management system based on space planning, and the system is applied to the management of a stereoscopic garage, wherein the stereoscopic garage includes a multi-story garage, and the parking space lines of the multi-story garage can be dynamically adjusted, including: obtaining basic vehicle information at a first time node, wherein the basic vehicle information includes vehicle geometric characteristics and vehicle entry characteristics; performing cluster analysis on vehicles to be entered into the garage according to the vehicle geometric characteristics to generate a first-level vehicle clustering result; performing cluster analysis on vehicles to be entered into the garage according to the vehicle entry characteristics to generate a second-level vehicle clustering result; obtaining basic information of a multi-story garage, wherein the basic information of the multi-story garage includes garage parking space distribution information and garage channel distribution information; performing parking space planning based on the first-level vehicle clustering result according to the garage parking space distribution information to generate a parking space virtual identification generation result; performing entry path planning based on the parking space virtual identification generation result and the second-level vehicle clustering result according to the garage channel distribution information to generate an entry route planning result; and managing the stereoscopic garage according to the parking space virtual identification generation result and the entry route planning result.

[0008] On the other hand, the present application also provides an intelligent high-level stereoscopic warehouse management system based on space planning, which is applied to the management of stereoscopic garages, wherein the stereoscopic garages include multi-story garages, and the parking space lines of the multi-story garages can be dynamically adjusted, including: a vehicle information acquisition module, used to obtain basic vehicle information at a first time node, wherein the basic vehicle information includes vehicle geometric features and vehicle entry features; a first vehicle clustering module, used to perform cluster analysis on vehicles to be entered into the warehouse according to the vehicle geometric features, and generate a first-level vehicle clustering result; a second vehicle clustering module, used to perform cluster analysis on vehicles to be entered into the warehouse according to the vehicle entry features, and generate a second-level vehicle clustering result; a vehicle A garage information acquisition module is used to obtain basic information of a multi-story garage, wherein the basic information of the multi-story garage includes garage parking space distribution information and garage channel distribution information; a parking space identification generation module is used to perform parking space planning based on the first-level vehicle clustering result according to the garage parking space distribution information, and generate a parking space virtual identification generation result; a garage entry route planning module is used to perform garage entry path planning based on the garage channel distribution information, the parking space virtual identification generation result and the second-level vehicle clustering result, and generate a garage entry route planning result; a stereo garage management module is used to manage the stereo garage according to the parking space virtual identification generation result and the garage entry route planning result.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] This application obtains the geometric features and entry features of the vehicles by obtaining the information of the vehicles to be entered at the first time node; further, cluster analysis is performed on the vehicles to be entered according to the geometric features and the entry features, and a first-level vehicle clustering result and a second-level vehicle clustering result are generated; further, basic information of a multi-layer garage is obtained, wherein the basic information of the multi-layer garage includes the parking space distribution information of the garage and the aisle distribution information of the garage; parking space planning is performed according to the parking space distribution information of the garage and the first-level vehicle clustering result, and a parking space virtual identification generation result is generated; then, entry path planning is performed according to the garage aisle distribution information, the parking space virtual identification generation result and the second-level vehicle clustering result, and an entry route planning result is generated; and stereo garage management is performed according to the parking space virtual identification generation result and the entry route planning result. Since parking space allocation and entry strategy optimization decision under entry route planning are performed according to the user's vehicle information and the real-time status information of the garage, automatic matching of parking spaces and intelligent navigation of entry are realized, thereby achieving the technical effect of improving user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in this application or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely exemplary, and a person of ordinary skill in the art can obtain other drawings based on the provided drawings without any creative work.

[0012] Figure 1 A flowchart of an intelligent high-rise warehouse management method based on space planning provided in an embodiment of the present application;

[0013] Figure 2 A schematic diagram of a process for determining the first-level vehicle clustering results in a method for managing an intelligent high-rise warehouse based on space planning provided in an embodiment of the present application;

[0014] Figure 3 A schematic diagram of a process for determining secondary vehicle clustering results in a space planning-based intelligent high-bay warehouse management method provided in an embodiment of the present application;

[0015] Figure 4 This is a structural diagram of an intelligent high-rise warehouse management system based on space planning for this application.

[0016] Explanation of the reference numerals: vehicle information acquisition module 11 , first vehicle clustering module 12 , second vehicle clustering module 13 , garage information acquisition module 14 , parking space identification generation module 15 , parking route planning module 16 , and stereo garage management module 17 . DETAILED DESCRIPTION

[0017] The embodiments of the present application disclose an intelligent high-rise warehouse management method and system based on space planning. Since parking spaces are allocated and routes into the warehouse are planned according to the user's vehicle information and the real-time status information of the garage, automatic matching of parking spaces and intelligent navigation for entering the warehouse are realized, achieving the technical effect of improving the user experience.

[0018] The acquisition, storage, use, and processing of data in this application's technical solution comply with relevant national laws and regulations.

[0019] Below, the technical solutions in this application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of this application, rather than all the embodiments of this application. It should be understood that this application is not limited to the example embodiments described herein. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application. It should also be noted that, for the convenience of description, only the parts related to this application, rather than all of them, are shown in the accompanying drawings.

[0020] Example 1

[0021] like Figure 1 As shown, the present application provides an intelligent high-rise warehouse management method based on space planning, wherein the method is implemented through an intelligent high-rise warehouse management system based on space planning, and the system is applied to the management of a stereo garage, wherein the stereo garage includes a multi-story garage, and the parking space lines of the multi-story garage can be dynamically adjusted, comprising the steps of:

[0022] Specifically, the difference between the multi-story parking garage in the embodiment of the present application and the traditional multi-story parking garage is that each parking space in the garage in the embodiment of the present application is not fixedly divided, that is, for each row of parking spaces, the width and length of the parking spaces can be dynamically adjusted. The preferred implementation method is: different parking space positions are calibrated by rays, and the parking spaces marked by rays correspond one to one with the virtual parking space signs in the intelligent high-rise multi-story warehouse management system based on space planning, which is convenient for guiding users into specific parking areas.

[0023] S100: Obtaining basic vehicle information at a first time point, wherein the basic vehicle information includes vehicle geometric features and vehicle entry features;

[0024] Specifically, the first time node refers to any time point when a vehicle corresponding to any time point in the divided area of ​​the multi-story parking garage submits an application for entry. Preferably, the vehicles applying for entry at multiple application time points are queued and processed in chronological order; the basic information of the vehicle at the first time node refers to the basic information of the set of vehicles applying for entry into the multi-story parking garage, which is reserved online or set by the staff at the first time node; the basic information of any vehicle includes at least: vehicle owner information, vehicle geometric characteristics, vehicle entry characteristics, etc., among which the vehicle geometric characteristics refer to the geometric data such as the maximum height, maximum length, maximum width, etc. of the vehicle determined based on the vehicle model data uploaded when applying for entry; the vehicle entry characteristics include at least: the order of application for entry, recorded as the time node of the vehicle application for entry, the entry port number data, etc.

[0025] By using vehicle geometric characteristics and vehicle entry characteristics as the basic information for analyzing vehicle parking space allocation and entry path planning, the interference of other redundant data is reduced, and the efficiency of garage intelligent management is improved.

[0026] S200: performing cluster analysis on the incoming vehicles based on the vehicle geometric features to generate a first-level vehicle clustering result;

[0027] Further, such as Figure 2 As shown, the cluster analysis is performed on the incoming vehicles according to the vehicle geometric features to generate a first-level vehicle clustering result. Step S200 includes the following steps:

[0028] S210: Obtaining a vehicle width feature, a vehicle length feature, and a vehicle height feature based on the vehicle geometric features;

[0029] S220: performing cluster analysis on the vehicles to be entered into the warehouse according to the vehicle width characteristics to generate a first-level clustering result;

[0030] S230: performing cluster analysis on the first-level clustering results according to the vehicle length feature to generate a second-level clustering result;

[0031] S240: Perform cluster analysis on the second-level clustering results according to the vehicle height characteristics to generate the first-level vehicle clustering results.

[0032] Specifically, the first-level vehicle clustering results refer to the results of clustering incoming vehicles based on their geometric characteristics. First, vehicles with the same maximum width are clustered together based on vehicle width, resulting in the first-level clustering results. Then, vehicles with the same maximum length within each category of the first-level clustering results are clustered together based on vehicle length, resulting in the first-level clustering results. Finally, vehicles with the same maximum height within each category of the second-level clustering results are clustered together based on vehicle height, resulting in the first-level clustering results for each category with consistent height, width, and length. This lays the data foundation for the subsequent differentiated parking space allocation based on vehicle type.

[0033] S300: performing cluster analysis on the vehicles to be entered into the warehouse according to the vehicle entry characteristics, and generating a secondary vehicle clustering result;

[0034] Further, such as Figure 3 As shown, the cluster analysis is performed on the vehicles to be entered into the warehouse according to the vehicle entry characteristics to generate a secondary vehicle clustering result. Step S300 includes the following steps:

[0035] S310: Acquire entry location characteristics and entry time characteristics based on the vehicle entry characteristics;

[0036] S320: performing cluster analysis on the vehicles to be entered into the warehouse according to the entry position characteristics, and generating an entry position clustering result;

[0037] S330: Perform cluster analysis on the entry location clustering results according to the entry time characteristics to generate the secondary vehicle clustering results.

[0038] Specifically, the secondary vehicle clustering results refer to the results of clustering analysis of incoming vehicles based on their entry characteristics. Specifically, the following steps are performed: First, a cluster analysis is performed on incoming vehicles based on their entry location characteristics, grouping vehicles with the same entry location into one category to obtain the entry location clustering results. For example, the entry location characteristics include the entry entrance number determined based on vehicle positioning data. Furthermore, a cluster analysis is performed on the set of vehicles within each category of the entry location clustering results based on their entry time characteristics, grouping vehicles with the same entry time agreed upon upon application into one category. This results in the secondary vehicle clustering results for any category with the same entry time and entry location. This lays the data foundation for subsequent differentiated parking space allocation and route planning based on vehicle category.

[0039] S400: Obtaining basic information of a multi-story garage, wherein the basic information of the multi-story garage includes garage parking space distribution information and garage aisle distribution information;

[0040] Furthermore, the step S400 of obtaining basic information of a multi-story garage, wherein the basic information of the multi-story garage includes parking space distribution information and aisle distribution information of the garage, includes the following steps:

[0041] S410: Traversing a multi-story garage to extract parking space status information and garage aisle distribution information, wherein the parking space status information includes the vacant area of ​​a planned parking space area, the vacant height of the planned parking space area, and distribution information of the planned vacant parking space area;

[0042] S420: adding the idle area of ​​the parking space planning area, the idle height of the parking space planning area, and the distribution information of the parking space planning idle area to the parking space distribution information of the garage;

[0043] S430: Adding the garage channel distribution information and the garage parking space distribution information to the multi-storey garage basic information.

[0044] Specifically, the basic information of a multi-story garage refers to the status data of the multi-story garage, which at least includes the garage parking space distribution information and garage aisle distribution information: the garage parking space distribution information refers to the distribution location data and distribution geometry data of the vacant areas in the garage that can be divided into parking spaces; the garage aisle distribution information refers to the vehicle aisle layout data in the garage.

[0045] Furthermore, the parking space distribution information of the garage includes at least information representing the free area of ​​the parking space planning area, the free height of the parking space planning area and the distribution information of the free area of ​​the parking space planning area. The free area of ​​the parking space planning area refers to the free area value of the parking space that can be planned. Preferably, any one-layer garage has multiple areas that can be divided into parking spaces, any area is a single row, and any parking space in the area needs to be directly connected to the vehicle passage, and the free area of ​​the parking space planning area is also stored and determined in association with the multiple areas that can be divided into parking spaces. Therefore, the free area of ​​the parking space planning area is a plurality of area data corresponding to multiple free areas of multiple layers; the free height of the parking space planning area refers to the multiple available space height data corresponding to multiple free areas of multiple layers; the distribution information of the parking space planning free area refers to the multiple groups of length data, width data, distribution position data, etc. corresponding to multiple free areas of multiple layers.

[0046] The garage channel distribution information and garage parking space distribution information are set to a response state. In the subsequent step, the parking space allocation and path planning work of the first time node can be carried out in combination with the vehicle data, thereby realizing intelligent garage management.

[0047] S500: performing parking space planning based on the first-level vehicle clustering result according to the parking space distribution information of the garage, and generating a parking space virtual identification generation result;

[0048] Furthermore, the parking space planning is performed based on the first-level vehicle clustering result according to the parking space distribution information of the garage, and a parking space virtual identification generation result is generated. Step S500 includes the following steps:

[0049] S510: Traversing the first-level vehicle clustering results to generate parameters of an n-th type of parking space, wherein the parameters of the n-th type of parking space include a length threshold of an n-th type of parking space, a width threshold of an n-th type of parking space, a height threshold of an n-th type of parking space, and a number threshold of an n-th type of parking space;

[0050] S520: According to the idle area of ​​the parking space planning area, the idle height of the parking space planning area and the distribution information of the parking space planning idle area, parking space planning is performed based on the n-th type parking space length threshold, the n-th type parking space width threshold, the n-th type parking space height threshold and the n-th type parking space quantity threshold, and the parking space virtual identification generation result is generated.

[0051] Further, the parking space space planning is performed based on the idle area of ​​the parking space planning area, the idle height of the parking space planning area, and the distribution information of the parking space planning idle area, based on the n-th type parking space length threshold, the n-th type parking space width threshold, the n-th type parking space height threshold, and the n-th type parking space quantity threshold, and the parking space virtual identification generation result is generated. Step S520 includes the steps of:

[0052] S521: Acquire the mth free area, the mth free height, and the mth parking space area distribution information according to the free area of ​​the planned parking space area, the free height of the planned parking space area, and the parking space area distribution information;

[0053] S522: Setting the n-type parking space length threshold, the n-type parking space width threshold, and the n-type parking space height threshold as single parking space classification criteria;

[0054] S523: Setting the nth type parking space quantity threshold as the first constraint; setting the mth vacant area as the second constraint; and setting the mth vacant height as the third constraint;

[0055] S524: Allocating parking spaces based on the single parking space division standard according to the mth parking space area distribution information, and generating a parking space allocation result;

[0056] S525: When the first constraint condition is met, generating a virtual identifier of the n-th type of parking space;

[0057] S526: When the second constraint condition is satisfied, or / and the third constraint condition is satisfied, parking space allocation stops, and a virtual identifier of the mth parking space is generated;

[0058] S527: traverse the m+1th idle area, the m+1th idle height, and the m+1th parking space area distribution information to perform parking space allocation and generate the nth type parking space virtual identifier;

[0059] S528: Add the n-th type parking space virtual identifier and the m-th parking space virtual identifier to the parking space virtual identifier generation result.

[0060] Specifically, the result of generating a virtual parking space identification refers to the dynamic planning result of the parking space determined based on the garage parking space status information in the garage parking space distribution information and the vehicle information in the first-level vehicle clustering result. It is a virtual identification representing the location of the parking space generated in the visual interface in the user's car. During navigation, when the user's vehicle and the generated result of the virtual parking space identification completely overlap, it is considered that the parking is completed and billing begins.

[0061] The specific process of determining the result of generating the virtual parking space logo is as follows, taking an example without setting any restrictions:

[0062] Traverse the first-level vehicle clustering results to generate first-type parking space parameters up to n-type parking space parameters. The first-type parking space parameters up to n-type parking space parameters refer to parking space parameters determined by the basic vehicle information of the vehicle to be parked, that is, the length, width and height of the parking space are determined according to the length, width and height of the vehicle. Preferably, the n-type parking space parameters are taken as an example: the n-type parking space parameters include an n-type parking space length threshold, preferably longer than the length of the n-type vehicle; an n-type parking space width threshold, preferably wider than the width of the n-type vehicle; an n-type parking space height threshold, preferably higher than the height of the n-type vehicle; and an n-type parking space quantity threshold, determined by the number of clustered vehicles.

[0063] Furthermore, based on the idle area of ​​the parking space planning area, the idle height of the parking space planning area and the distribution information of the parking space planning idle area, parking space planning is performed based on the n-th type parking space length threshold, the n-th type parking space width threshold, the n-th type parking space height threshold and the n-th type parking space quantity threshold.

[0064] The parking space planning process is as follows:

[0065] Extract the free area, free height and distribution information of the parking space planning area in a certain area, and record them as the mth free area, the mth free height and the mth parking space area distribution information; set the single parking space division standard according to the nth type parking space length threshold, the nth type parking space width threshold and the nth type parking space height threshold to characterize the spatial information of a single vehicle of the nth type; further, set the nth type parking space number threshold as the first constraint condition; set the mth free area as the second constraint condition; and set the mth free height as the third constraint condition.

[0066] When planning, parking spaces are allocated based on the length, width, and height of the corresponding area stored in the mth parking space area distribution information and the single parking space division standard. Since the total length, total width, and height of the divided area, as well as the standard of the unit parking space, are known, and a single-row distribution is required, the division process can be started directly from one side edge, and no further details will be given here.

[0067] Satisfying the first constraint means that all vehicles of type n have been planned, allowing parking space planning for other types of vehicles. Satisfying the second constraint means that the remaining area of ​​the area is no longer sufficient for the allocation of vehicles of type n. Satisfying the third constraint means that the remaining height of the area is no longer sufficient for the allocation of vehicles of type n. At this point, the area has been allocated, and a virtual identifier for the mth parking space of type n is generated. The m+1th free area, m+1th free height, and m+1th parking space distribution information are then searched for to allocate parking spaces. This process continues until all vehicles of type n have been allocated, resulting in the generation of the virtual identifier. If, during the allocation process, the entire parking garage fails to accommodate vehicles of type n, then entry rejection data is generated for the remaining vehicles.

[0068] To more clearly illustrate the parking space planning algorithm process, let's take an example of parking space planning without any restrictions:

[0069] For any vacant area that can be divided into parking spaces, if the vehicle type is a motorcycle, electric vehicle, etc., the required distribution space is determined by the length * width of the vehicle's basic information. The required distribution space is generally larger than the length * width, and the required space height is determined by the height. Preferably, the highest height of the rider when riding can be calculated. Based on the distribution information of the vacant area of ​​the parking space planning, one or more areas that meet the requirements in length, width, and height are selected, the area of ​​the area is extracted, and the distribution space is retrieved to calculate the number of allocable parking spaces. The length, width, and height of the aforementioned distribution space are the length, width, and height of the parking space, and the allocated parking space location distribution data and geometric parameters and other information can be determined.

[0070] Furthermore, the garage can be pre-divided into zones for different types of vehicles. These zones, for example, include at least zones for electric vehicles or motorcycles, zones for cars, and zones for large vehicles. Different types of vehicles can then be assigned to corresponding zones, improving the efficiency of parking space planning. Furthermore, if a specific type of parking zone is no longer available, the application for parking for that type of vehicle will be rejected. This reduces the number of steps users have to take to find parking spaces and improves the user experience.

[0071] S600: performing entry route planning based on the garage channel distribution information, the parking space virtual identifier generation result, and the secondary vehicle clustering result to generate an entry route planning result;

[0072] Furthermore, the step S600 includes the following steps: performing entry route planning based on the parking space virtual identification generation result and the secondary vehicle clustering result according to the garage channel distribution information to generate an entry route planning result.

[0073] S610: Obtaining a time sequence of an n-type vehicle entering the parking space and a position sequence of an n-type vehicle entering the parking space according to the secondary vehicle clustering result and the parking space virtual identifier generation result;

[0074] S620: Allocate the nth type of vehicle to the nearest location according to the nth type of vehicle entry position sequence to generate an initial sequence of entry routes for the nth type of vehicle;

[0075] S630: When the entry position sequences of the n-th type of vehicles are the same, adjusting the initial entry route sequence of the n-th type of vehicles according to the order of the entry time sequences of the n-th type of vehicles to generate an entry path planning result for the n-th type of vehicles;

[0076] S640: Add the entry path planning result of the n-th type of vehicle to the entry route planning result.

[0077] S700: Performing parking garage management according to the parking space virtual identification generation result and the parking route planning result.

[0078] Specifically, the entry route planning result refers to the entry route planning data determined based on the vehicle entry data and garage aisle distribution information. Based on the aforementioned allocation of parking spaces for the nth type of vehicle and the known location of the parking spaces, each vehicle needs to be bound to a parking space.

[0079] The process is as follows: The n-type vehicle entry time sequence refers to the set of vehicle entry times, preferably sorted by chronological order. The n-type vehicle entry location sequence refers to the vehicle entry entrance number information. The n-type vehicle entry route initial sequence refers to the allocation of parking spaces based on their location and distance to the entry location, thereby obtaining multiple parking space sets corresponding to each entry location and route data from the entry location to the parking space. Furthermore, based on the vehicle entry time of each entry location, multiple parking space sets are allocated in sequence to obtain specific parking space-vehicle entry route data, which is recorded as the n-type vehicle entry path planning result. All first-level vehicle clusters are traversed to obtain the entry route planning result.

[0080] Furthermore, the vehicle is guided to the parking space based on the results of the parking route planning, and is guided into the parking space based on the generated parking space virtual sign. This achieves the technical effect of improving user experience and enhancing the intelligence of garage management.

[0081] In summary, the intelligent high-rise warehouse management method based on space planning provided by this application has the following technical effects:

[0082] 1. By obtaining the information of vehicles to be entered at a first time node, the geometric characteristics and entry characteristics of the vehicles are obtained; further, cluster analysis is performed on the vehicles to be entered based on the vehicle geometric characteristics and vehicle entry characteristics, generating first-level vehicle clustering results and second-level vehicle clustering results; further, basic information of the multi-story garage is obtained, where the multi-story garage basic information includes garage parking space distribution information and garage aisle distribution information; parking space space planning is performed based on the garage parking space distribution information and the first-level vehicle clustering results, and parking space virtual identification generation results are generated; then, entry path planning is performed based on the garage aisle distribution information, the parking space virtual identification generation results, and the second-level vehicle clustering results, and an entry route planning result is generated; and the three-dimensional garage is managed based on the parking space virtual identification generation results and the entry route planning results. Since parking space allocation and garage management strategy optimization under entry route planning are performed based on the user's vehicle information and the real-time status information of the garage, automatic parking space matching and intelligent entry navigation are achieved, achieving the technical effect of improving the user experience.

[0083] 2. Guide the vehicle to the parking space based on the planned entry route and then guide the vehicle into the parking space based on the generated virtual parking space marker. This improves the user experience and enhances the intelligence of garage management.

[0084] Example 2

[0085] Based on the same inventive concept as the intelligent high-rise warehouse management method based on space planning in the above embodiment, Figure 4 As shown, the present application also provides an intelligent high-level stereoscopic warehouse management system based on space planning, wherein an intelligent high-level stereoscopic warehouse management system based on space planning is applied to the management of a stereoscopic garage, wherein the stereoscopic garage includes a multi-story garage, and the parking space lines of the multi-story garage can be dynamically adjusted, including:

[0086] The vehicle information acquisition module 11 is used to acquire basic vehicle information at a first time point, wherein the basic vehicle information includes vehicle geometric features and vehicle entry features;

[0087] A first vehicle clustering module 12 is configured to perform cluster analysis on the incoming vehicles based on the vehicle geometric characteristics and generate a first-level vehicle clustering result;

[0088] The second vehicle clustering module 13 is used to perform cluster analysis on the vehicles to be entered into the warehouse according to the vehicle entry characteristics and generate a secondary vehicle clustering result;

[0089] The garage information acquisition module 14 is used to acquire basic information of a multi-story garage, wherein the basic information of the multi-story garage includes garage parking space distribution information and garage aisle distribution information;

[0090] A parking space identification generation module 15 is configured to perform parking space planning based on the first-level vehicle clustering result according to the parking space distribution information of the garage, and generate a parking space virtual identification generation result;

[0091] The entry route planning module 16 is configured to perform entry route planning based on the garage channel distribution information, the parking space virtual identifier generation result, and the secondary vehicle clustering result, and generate an entry route planning result;

[0092] The three-dimensional parking garage management module 17 is used to manage the three-dimensional parking garage according to the parking space virtual identification generation result and the parking route planning result.

[0093] Furthermore, the first vehicle clustering module 12 executes the following steps:

[0094] Obtaining a vehicle width feature, a vehicle length feature, and a vehicle height feature according to the vehicle geometric features;

[0095] Performing cluster analysis on the vehicles to be entered into the warehouse according to the vehicle width characteristics to generate a first-level clustering result;

[0096] Performing cluster analysis on the first-level clustering results according to the vehicle length feature to generate a second-level clustering result;

[0097] The second-level clustering result is traversed and cluster analysis is performed according to the vehicle height characteristics to generate the first-level vehicle clustering result.

[0098] Furthermore, the second vehicle clustering module 13 executes the following steps:

[0099] According to the vehicle entry characteristics, obtaining the entry location characteristics and the entry time characteristics;

[0100] Performing cluster analysis on the vehicles to be entered into the warehouse according to the entry position characteristics to generate an entry position clustering result;

[0101] The entry location clustering results are traversed and cluster analysis is performed according to the entry time characteristics to generate the secondary vehicle clustering results.

[0102] Furthermore, the garage information acquisition module 14 executes the following steps:

[0103] Traversing a multi-story garage, extracting garage parking space status information and garage aisle distribution information, wherein the garage parking space status information includes the vacant area of ​​a planned parking space area, the vacant height of the planned parking space area, and the distribution information of the planned vacant area of ​​the parking space;

[0104] Adding the free area of ​​the parking space planning area, the free height of the parking space planning area and the distribution information of the parking space planning free area to the parking space distribution information of the garage;

[0105] The garage channel distribution information and the garage parking space distribution information are added to the multi-storey garage basic information.

[0106] Furthermore, the parking space identification generating module 15 executes the following steps:

[0107] Traversing the first-level vehicle clustering results to generate n-type parking space parameters, wherein the n-type parking space parameters include an n-type parking space length threshold, an n-type parking space width threshold, an n-type parking space height threshold, and an n-type parking space quantity threshold;

[0108] According to the idle area of ​​the parking space planning area, the idle height of the parking space planning area and the distribution information of the parking space planning idle area, parking space planning is performed based on the n-th type parking space length threshold, the n-th type parking space width threshold, the n-th type parking space height threshold and the n-th type parking space quantity threshold to generate the parking space virtual identification generation result.

[0109] Furthermore, the parking space identification generating module 15 executes the following steps:

[0110] According to the idle area of ​​the parking space planning area, the idle height of the parking space planning area and the distribution information of the parking space planning idle area, obtaining the mth idle area, the mth idle height and the mth parking space area distribution information;

[0111] The length threshold of the n-th type of parking space, the width threshold of the n-th type of parking space, and the height threshold of the n-th type of parking space are set as single parking space classification standards;

[0112] The number threshold of the nth type of parking spaces is set as the first constraint condition; the mth vacant area is set as the second constraint condition; and the mth vacant height is set as the third constraint condition;

[0113] According to the mth parking space area distribution information, allocating parking spaces based on the single parking space division standard to generate a parking space allocation result;

[0114] When the first constraint condition is met, a virtual identifier of the nth type of parking space is generated;

[0115] When the second constraint condition is satisfied, or / and the third constraint condition is satisfied, parking space allocation stops and a virtual identifier of the mth parking space is generated;

[0116] Traversing the m+1th idle area, the m+1th idle height, and the m+1th parking space area distribution information to perform parking space allocation, and generating the nth type parking space virtual identifier;

[0117] The n-th type parking space virtual identifier and the m-th parking space virtual identifier are added to the parking space virtual identifier generation result.

[0118] Furthermore, the steps executed by the warehousing route planning module 16 include:

[0119] Obtaining a time sequence of an n-type vehicle entering the parking space and a position sequence of an n-type vehicle entering the parking space according to the secondary vehicle clustering result and the parking space virtual identifier generation result;

[0120] Allocate the nth type of vehicle to the nearest location according to the nth type of vehicle entry position sequence to generate an initial sequence of entry routes for the nth type of vehicle;

[0121] When the entry position sequence of the n-type vehicles is the same, adjusting the initial entry route sequence of the n-type vehicles according to the order of the entry time sequence of the n-type vehicles to generate an entry path planning result for the n-type vehicles;

[0122] The entry path planning result of the n-th type vehicle is added to the entry route planning result.

[0123] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. Figure 1 The intelligent high-rise warehouse management method based on space planning and the specific examples in Example 1 are also applicable to the intelligent high-rise warehouse management system based on space planning in this embodiment. Through the above detailed description of the intelligent high-rise warehouse management method based on space planning, those skilled in the art can clearly understand the intelligent high-rise warehouse management system based on space planning in this embodiment. Therefore, for the sake of brevity of the specification, it will not be described in detail here. As for the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method description.

[0124] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An intelligent high-rise warehouse management method based on space planning, characterized in that: The system is implemented by an intelligent high-rise warehouse management system based on space planning. The system is applied to the management of a three-dimensional parking garage, which includes a multi-story garage. The parking space lines of the multi-story garage can be dynamically adjusted, including: Obtaining basic vehicle information at a first time point, wherein the basic vehicle information includes vehicle geometric characteristics and vehicle entry characteristics; Performing cluster analysis on the incoming vehicles based on the vehicle geometric features to generate a first-level vehicle clustering result; Performing cluster analysis on the vehicles to be entered into the warehouse according to the vehicle entry characteristics to generate a secondary vehicle clustering result; Obtaining basic information of a multi-story garage, wherein the basic information of the multi-story garage includes garage parking space distribution information and garage aisle distribution information; According to the parking space distribution information of the garage, parking space planning is performed based on the first-level vehicle clustering result to generate a parking space virtual identification generation result; According to the garage channel distribution information, based on the parking space virtual identification generation result and the secondary vehicle clustering result, a parking route planning result is generated; The three-dimensional parking garage is managed according to the parking space virtual identification generation result and the parking route planning result.

2. The intelligent high-rise warehouse management method based on space planning according to claim 1 is characterized in that: The cluster analysis of the incoming vehicles based on the vehicle geometric features to generate a first-level vehicle clustering result includes: Obtaining a vehicle width feature, a vehicle length feature, and a vehicle height feature according to the vehicle geometric features; Performing cluster analysis on the vehicles to be entered into the warehouse according to the vehicle width characteristics to generate a first-level clustering result; Performing cluster analysis on the first-level clustering results according to the vehicle length feature to generate a second-level clustering result; The second-level clustering result is traversed and cluster analysis is performed according to the vehicle height characteristics to generate the first-level vehicle clustering result.

3. The intelligent high-rise warehouse management method based on space planning according to claim 1 is characterized in that: The cluster analysis of the vehicles to be entered into the warehouse according to the vehicle entry characteristics to generate a secondary vehicle clustering result includes: According to the vehicle entry characteristics, obtaining the entry location characteristics and the entry time characteristics; Performing cluster analysis on the vehicles to be entered into the warehouse according to the entry position characteristics to generate an entry position clustering result; The entry location clustering results are traversed and cluster analysis is performed according to the entry time characteristics to generate the secondary vehicle clustering results.

4. The intelligent high-rise warehouse management method based on space planning according to claim 1, characterized in that: The obtaining of basic information of a multi-storey garage, wherein the basic information of the multi-storey garage includes garage parking space distribution information and garage aisle distribution information, includes: Traversing a multi-story garage, extracting garage parking space status information and garage aisle distribution information, wherein the garage parking space status information includes the vacant area of ​​a planned parking space area, the vacant height of the planned parking space area, and the distribution information of the planned vacant area of ​​the parking space; Adding the free area of ​​the parking space planning area, the free height of the parking space planning area and the distribution information of the parking space planning free area to the parking space distribution information of the garage; The garage channel distribution information and the garage parking space distribution information are added to the multi-storey garage basic information.

5. The intelligent high-rise warehouse management method based on space planning according to claim 4 is characterized in that: The method of performing parking space planning based on the first-level vehicle clustering result according to the parking space distribution information of the garage and generating a parking space virtual identification generation result includes: Traversing the first-level vehicle clustering results to generate n-type parking space parameters, wherein the n-type parking space parameters include an n-type parking space length threshold, an n-type parking space width threshold, an n-type parking space height threshold, and an n-type parking space quantity threshold; According to the idle area of ​​the parking space planning area, the idle height of the parking space planning area and the distribution information of the parking space planning idle area, parking space planning is performed based on the n-th type parking space length threshold, the n-th type parking space width threshold, the n-th type parking space height threshold and the n-th type parking space quantity threshold to generate the parking space virtual identification generation result.

6. The intelligent high-rise warehouse management method based on space planning according to claim 5 is characterized in that: The generating of the parking space virtual identifier generation result by performing parking space planning based on the n-type parking space length threshold, the n-type parking space width threshold, the n-type parking space height threshold, and the n-type parking space quantity threshold according to the idle area of ​​the parking space planning area, the idle height of the parking space planning area, and the distribution information of the parking space planning idle area, includes: According to the idle area of ​​the parking space planning area, the idle height of the parking space planning area and the distribution information of the parking space planning idle area, obtaining the mth idle area, the mth idle height and the mth parking space area distribution information; The length threshold of the n-th type of parking space, the width threshold of the n-th type of parking space, and the height threshold of the n-th type of parking space are set as single parking space classification standards; The number threshold of the nth type of parking spaces is set as the first constraint condition; the mth vacant area is set as the second constraint condition; and the mth vacant height is set as the third constraint condition; According to the mth parking space area distribution information, allocating parking spaces based on the single parking space division standard to generate a parking space allocation result; When the first constraint condition is met, a virtual identifier of the nth type of parking space is generated; When the second constraint condition is satisfied, or / and the third constraint condition is satisfied, parking space allocation stops and a virtual identifier of the mth parking space is generated; Traversing the m+1th idle area, the m+1th idle height, and the m+1th parking space area distribution information to perform parking space allocation, and generating the nth type parking space virtual identifier; The n-th type parking space virtual identifier and the m-th parking space virtual identifier are added to the parking space virtual identifier generation result.

7. The intelligent high-rise warehouse management method based on space planning according to claim 6 is characterized in that: The method of performing entry route planning based on the garage channel distribution information, the parking space virtual identification generation result, and the secondary vehicle clustering result to generate an entry route planning result includes: Obtaining a time sequence of an n-type vehicle entering the parking space and a position sequence of an n-type vehicle entering the parking space according to the secondary vehicle clustering result and the parking space virtual identifier generation result; Allocate the nth type of vehicle to the nearest location according to the nth type of vehicle entry position sequence to generate an initial sequence of entry routes for the nth type of vehicle; When the entry position sequence of the n-type vehicles is the same, adjusting the initial entry route sequence of the n-type vehicles according to the order of the entry time sequence of the n-type vehicles to generate an entry path planning result for the n-type vehicles; The entry path planning result of the n-th type vehicle is added to the entry route planning result.

8. An intelligent high-rise warehouse management system based on space planning, characterized in that: Applied to the management of a stereoscopic parking garage, the stereoscopic parking garage includes a multi-story garage, and the parking space lines of the multi-story garage can be dynamically adjusted, including: A vehicle information acquisition module, configured to acquire basic vehicle information at a first time point, wherein the basic vehicle information includes vehicle geometric features and vehicle entry features; A first vehicle clustering module is used to perform cluster analysis on the incoming vehicles according to the vehicle geometric characteristics and generate a first-level vehicle clustering result; A second vehicle clustering module is used to perform cluster analysis on the vehicles to be entered into the warehouse according to the vehicle entry characteristics and generate a secondary vehicle clustering result; A garage information acquisition module is used to acquire basic information of a multi-story garage, wherein the basic information of the multi-story garage includes garage parking space distribution information and garage aisle distribution information; A parking space identification generation module is used to perform parking space planning based on the first-level vehicle clustering result according to the parking space distribution information of the garage, and generate a parking space virtual identification generation result; a parking route planning module, configured to plan a parking route according to the garage channel distribution information, the parking space virtual identifier generation result, and the secondary vehicle clustering result, and generate a parking route planning result; The three-dimensional parking garage management module is used to manage the three-dimensional parking garage according to the parking space virtual identification generation result and the parking route planning result.

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