Warehouse logistics scheduling method and device and terminal equipment

Abstract

The invention discloses a warehouse logistics scheduling method and apparatus, and a terminal device. The method comprises the steps of obtaining a logistics scheduling task, vehicle use data of a logistics vehicle, historical order data, historical transportation data of a driver, robot loading data, robot unloading data and warehouse capacity data; screening according to the logistics scheduling task, the vehicle use data and the historical order data to obtain a target logistics vehicle; screening and determining a final logistics scheduling vehicle according to the corresponding historical transportation data; a loading robot is determined according to the logistics scheduling task and the robot loading data, so that the loading robot loads goods to a logistics scheduling vehicle; determining a target storage warehouse according to the warehouse capacity data and the cargo capacity corresponding to the logistics scheduling task; and according to the logistics scheduling task and the robot unloading data, an unloading robot is determined, so that the unloading robot unloads the to-be-scheduled goods to a target storage warehouse. According to the invention, the efficiency of the whole logistics scheduling process is improved.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to a warehouse logistics scheduling method, device and terminal equipment. Background Art

[0002] With the rapid development of information technology, especially the widespread application of advanced technologies such as the Internet of Things, big data and cloud computing, the warehousing and logistics industry is gradually transforming towards intelligence and automation. The existing warehousing and logistics scheduling methods are based on logistics scheduling tasks, scheduling suitable logistics transport vehicles for corresponding logistics transportation and selecting loading and unloading areas corresponding to logistics scheduling tasks for loading and unloading. When scheduling transport vehicles, only the idle state of the transport vehicles is considered for simple allocation, without comprehensively considering the adaptability of the drivers of the vehicles to the scheduling tasks. When transporting goods, it is assumed that the driver's historical transportation data does not match the scheduling tasks well, which will not only increase the transportation risk, but also directly lead to low scheduling efficiency and the inability to accurately and efficiently complete the scheduling tasks. Summary of the invention

[0003] The embodiments of the present invention provide a warehouse logistics scheduling method, device and terminal equipment, which can effectively solve the problem that the prior art does not comprehensively consider the compatibility of the driver of the vehicle and the scheduling task, and cannot accurately and efficiently complete the scheduling task.

[0004] An embodiment of the present invention provides a storage logistics scheduling method, including:

[0005] Obtain logistics dispatch tasks, vehicle usage data of logistics vehicles, historical order data, historical transportation data of drivers corresponding to logistics vehicles, robot loading data, robot unloading data, and warehouse capacity data of warehouses to be loaded;

[0006] Perform vehicle screening according to the logistics scheduling task, the vehicle usage data, and the historical order data to obtain a target logistics vehicle;

[0007] According to the historical transportation data corresponding to the target logistics vehicles, the target logistics vehicles are screened to determine the final logistics dispatch vehicles;

[0008] Determine a loading robot according to the logistics scheduling task and the robot loading data, so that the loading robot loads the goods to be scheduled onto the logistics scheduling vehicle;

[0009] When the logistics dispatch vehicle arrives at the warehouse to be loaded, determining the target storage warehouse according to the warehouse capacity data and the cargo capacity corresponding to the logistics dispatch task;

[0010] According to the logistics scheduling task and the robot unloading data, an unloading robot is determined so that the unloading robot unloads the goods to be scheduled on the logistics scheduling vehicle to the target storage warehouse for storage.

[0011] Furthermore, the vehicle usage data includes: average vehicle transportation rate and remaining stay time; the historical order data includes: total cargo damage rate and transportation overtime rate;

[0012] Vehicle screening is performed according to the logistics scheduling task, the vehicle usage data, and the historical order data to obtain a target logistics vehicle, including:

[0013] According to the logistics scheduling task, determine the departure preparation time and cargo transportation rate corresponding to the logistics scheduling task;

[0014] Compare the average vehicle transport rate with the cargo transport rate; and compare the remaining stay time with the departure preparation time;

[0015] When the average transport rate of the vehicle is greater than or equal to the cargo transport rate, and the remaining stay time is less than or equal to the departure preparation time, the corresponding logistics vehicle is used as the first target vehicle;

[0016] Calculating according to the total damage rate of the cargo of the first target vehicle, the transportation overtime rate, the preset standard damage rate, the preset standard overtime rate and the preset first weight factor to obtain the damage index of the first target vehicle;

[0017] Comparing according to the damage index and a preset damage threshold;

[0018] When the damage index is less than or equal to a preset damage threshold, the corresponding first target vehicle is used as the target logistics vehicle.

[0019] Furthermore, the historical transportation data includes: historical transportation speed, historical transportation location and historical transportation status; the historical transportation status includes qualified and unqualified;

[0020] According to the historical transportation data corresponding to the target logistics vehicle, the target logistics vehicle is screened to determine the final logistics dispatch vehicle, including:

[0021] According to the historical transportation data, the historical transportation speed corresponding to the qualified historical transportation status is used as the first historical transportation speed;

[0022] According to the historical transportation data, using the historical freight speed as the second historical freight speed of the target logistics vehicle;

[0023] sorting according to the second historical freight speeds, and taking the largest second historical freight speed as the optimal freight speed;

[0024] Determine, based on a comparison between the first historical freight speed and the optimal freight speed, a first transportation number at which the first historical freight speed is greater than the optimal freight speed;

[0025] The historical shipping location corresponding to the qualified historical shipping status is used as the first historical shipping location, and the second transportation number of the first historical shipping location is determined;

[0026] Calculate the transport index of the target logistics vehicle according to the first transport number, the second transport number, the preset standard transport number, and the preset second weight factor;

[0027] Comparison is made based on the transport index and a preset transport threshold;

[0028] When the transportation index is greater than or equal to a preset transportation threshold, the corresponding target logistics vehicle is used as the final logistics scheduling vehicle.

[0029] Further, the robot loading data includes: loading robot model, historical loading volume, loading movement speed, loading cargo damage rate and loading energy consumption;

[0030] Determining a loading robot according to the logistics scheduling task and the robot loading data includes:

[0031] According to each loading movement speed of each loading robot model, the historical loading volume at each loading movement speed of each loading robot model is sorted;

[0032] The maximum historical loading volume at each loading moving speed of each loading robot model is used as the target loading volume;

[0033] According to the robot loading data, determining the loading cargo damage rate corresponding to each target loading volume as the target loading cargo damage rate, and the loading energy consumption corresponding to each target loading volume as the target loading energy consumption;

[0034] Calculate according to the target loading cargo damage rate, the target loading energy consumption, the preset loading damage rate, the preset loading energy consumption threshold and the preset loading weight factor to obtain a first usage index at each loading movement speed of each loading robot model;

[0035] comparing the first usage index with a preset loading index threshold;

[0036] When the first usage index is greater than or equal to a preset loading index threshold, the loading robot model at the corresponding loading movement speed is used as a first model for characterizing the available loading robot models;

[0037] Determine the cargo capacity of the cargo to be dispatched according to the logistics dispatch task;

[0038] A loading robot is determined according to the cargo capacity and the first model.

[0039] Further, determining a loading robot according to the cargo capacity and the first model includes:

[0040] Sorting the first usage indexes at each loading movement speed of the first model, and taking the maximum first usage index as the first target usage index of the first model;

[0041] Determine a first working state and a first loadable quantity corresponding to the first model and a preset loading robot database; wherein the first working state includes idle;

[0042] Determine a first idle number of loading robots whose first working state is idle according to the first working state and the first model;

[0043] Calculate the first loading quantity of each first model according to the first free quantity and the corresponding first loading quantity;

[0044] According to the first loading quantity, the cargo capacity and the first target usage index, a loading robot is determined in descending order according to the first target usage index.

[0045] Furthermore, the warehouse capacity data includes: remaining warehouse capacity, standard warehouse capacity, and goods stored in the warehouse;

[0046] Determining a target storage warehouse according to the warehouse capacity data and the cargo capacity corresponding to the logistics scheduling task includes:

[0047] The warehouse storage index is obtained by calculating according to the remaining capacity of the warehouse, the cargo capacity, the remaining capacity of the preset standard warehouse, the remaining space of the preset standard cargo and the preset warehouse weight factor;

[0048] The warehouse corresponding to the warehouse storage index greater than the preset warehouse index threshold is used as the target storage warehouse.

[0049] Furthermore, the robot unloading data includes: unloading robot model, historical unloading volume, unloading movement speed, unloading cargo damage rate and unloading energy consumption;

[0050] Determining the unloading robot according to the logistics scheduling task and the robot unloading data includes:

[0051] According to each unloading moving speed of each unloading robot model, the historical unloading volume at each unloading speed of each unloading robot model is sorted;

[0052] The maximum historical unloading volume at each unloading moving speed of each unloading robot model is taken as the target unloading volume;

[0053] According to the robot unloading data, determining the unloading cargo damage rate corresponding to each target unloading volume as the target unloading cargo damage rate, and the unloading energy consumption corresponding to each target unloading volume as the target unloading energy consumption;

[0054] Calculate according to the target unloading cargo damage rate, the target unloading energy consumption, the preset unloading damage rate, the preset unloading energy consumption threshold and the preset unloading weight factor to obtain a second usage index at each unloading moving speed of each unloading robot model;

[0055] comparing the second usage index with a preset unloading index threshold;

[0056] When the second usage index is greater than or equal to a preset unloading index threshold, the unloading robot model at the corresponding unloading moving speed is used as the second model for characterizing the available unloading robot model;

[0057] An unloading robot is determined according to the cargo capacity and the second model.

[0058] Further, determining the unloading robot according to the cargo capacity and the second model includes:

[0059] Sorting according to the second usage index at each unloading movement speed of the second model, and taking the maximum second usage index as the second target usage index of the second model;

[0060] Determine the corresponding second working state and the second unloading amount according to the second model and the preset unloading robot database; wherein the second working state includes idle;

[0061] Determine, according to the second working state and the second model, a second idle number of unloading robots whose second working state is idle;

[0062] Calculate the second loading quantity of each second model according to the second free quantity and the corresponding second unloadable quantity;

[0063] According to the second loading quantity, the cargo capacity and the second target usage index, an unloading robot is determined in descending order according to the second target usage index.

[0064] As an improvement of the above solution, another embodiment of the present invention provides a storage logistics scheduling device, including:

[0065] The scheduling data acquisition module is used to obtain logistics scheduling tasks, vehicle usage data of logistics vehicles, historical order data, historical transportation data of drivers corresponding to logistics vehicles, robot loading data, robot unloading data, and warehouse capacity data of warehouses to be loaded;

[0066] A first screening module is used to screen vehicles according to the logistics scheduling tasks, the vehicle usage data and the historical order data to obtain target logistics vehicles;

[0067] The second screening module is used to screen the target logistics vehicles according to the historical transportation data corresponding to the target logistics vehicles to determine the final logistics dispatching vehicles;

[0068] A dispatching and loading module, used for determining a loading robot according to the logistics dispatching task and the robot loading data, so that the loading robot loads the goods to be dispatched onto the logistics dispatching vehicle;

[0069] A third screening module is used to determine the target storage warehouse according to the warehouse capacity data and the cargo capacity corresponding to the logistics scheduling task when the logistics scheduling vehicle arrives at the waiting warehouse;

[0070] The scheduling and unloading module is used to determine the unloading robot according to the logistics scheduling task and the robot unloading data, so that the unloading robot unloads the goods to be scheduled on the logistics scheduling vehicle to the target storage warehouse for storage.

[0071] Another embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, a warehouse logistics scheduling method as described in the above embodiment is implemented.

[0072] Another embodiment of the present invention provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute a warehouse logistics scheduling method described in the above embodiment.

[0073] By implementing the present invention, at least the following beneficial effects are achieved:

[0074] The present invention provides a warehouse logistics scheduling method, device and terminal equipment, wherein the method can obtain logistics scheduling tasks, vehicle usage data of logistics vehicles, historical order data, historical transportation data of drivers corresponding to logistics vehicles, robot loading data, robot unloading data and warehouse capacity data of warehouses to be loaded; according to the logistics scheduling tasks, the vehicle usage data and the historical order data, vehicles are screened to obtain target logistics vehicles; according to the historical transportation data corresponding to the target logistics vehicles, the target logistics vehicles are screened to determine the final logistics scheduling vehicles; according to the logistics scheduling tasks and the robot loading data, a loading robot is determined so that the loading robot loads the goods to be scheduled onto the logistics scheduling vehicle; when the logistics scheduling vehicle arrives at the warehouse to be loaded, a target storage warehouse is determined according to the warehouse capacity data and the cargo capacity corresponding to the logistics scheduling task; according to the logistics scheduling tasks and the robot unloading data, an unloading robot is determined so that the unloading robot unloads the goods to be scheduled on the logistics scheduling vehicle to the target storage warehouse for storage. By integrating the driving data of drivers, warehouse capacity data and the loading and unloading data of robots, the entire process of logistics scheduling and transportation vehicles and cargo loading and unloading is optimized. Not only are transportation vehicles screened based on vehicle usage data and historical vehicle order data, but the historical transportation data of drivers is also integrated to select vehicles that are more suitable for scheduling tasks and to select logistics scheduling vehicles based on the historical transportation data of the drivers corresponding to the vehicles. This improves the utilization rate of logistics vehicles and combines the loading and unloading data of robots to quickly and accurately select suitable loading and unloading robots for operations, thereby improving the efficiency of the entire logistics scheduling process and the accuracy of scheduling. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 It is a flow chart of a storage logistics scheduling method provided by one embodiment of the present invention;

[0076] Figure 2 It is a structural schematic diagram of a warehouse logistics scheduling device provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0077] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0078] See also Figure 1, is a flow chart of a warehousing logistics scheduling method provided by an embodiment of the present invention, including:

[0079] S1. Obtain logistics dispatching tasks, vehicle usage data of logistics vehicles, historical order data, historical transportation data of drivers corresponding to logistics vehicles, robot loading data, robot unloading data, and warehouse capacity data of warehouses to be loaded;

[0080] Specifically, logistics scheduling tasks include the cargo capacity of the goods to be scheduled, the departure preparation time (i.e., the estimated waiting time of the loading vehicle), and the cargo transportation rate (i.e., the speed at which the goods are required to be transported). Vehicle usage data refers to the current status data of the transport vehicle, including the average transportation rate of the vehicle and the remaining stay time. The remaining stay time of a logistics vehicle is a time indicator used to measure how long the logistics vehicle is expected to stay at the current location (such as a loading point or a transfer station). This time is usually calculated based on factors such as the vehicle's current task progress, schedule, and possible delays. If the remaining stay time is equal to zero, it means that the logistics vehicle has no planned stay time at the current location. That is, according to the current plan and progress, the vehicle no longer needs to stay at the current location and can immediately start to perform the next task or go to the next destination, indicating that the logistics vehicle is an idle vehicle. Based on the above two points, when the remaining stay time of the logistics vehicle is equal to zero, we can infer that the vehicle has no ongoing tasks at the current time point and is not scheduled to stay at the current location at a certain point in the future. Therefore, the vehicle can be regarded as being in an idle state, that is, it is not occupied and can accept new transportation tasks at any time. The historical order data represents the order information of the logistics vehicle's previous transportation. Generally, there is a one-to-one correspondence between logistics vehicles and drivers, so the driver's historical transportation data is associated with the historical order data of the logistics vehicle. The historical transportation data includes: historical delivery speed, historical delivery location, and historical delivery status. The robot loading data represents the data of the loading robot loading, including the loading robot model, historical loading volume, loading movement speed, loading cargo damage rate, and loading energy consumption. The robot unloading data represents the data of the unloading robot unloading, including the unloading robot model, historical unloading volume, unloading movement speed, unloading cargo damage rate, and unloading energy consumption.

[0081] S2. Screening vehicles according to the logistics scheduling task, the vehicle usage data and the historical order data to obtain a target logistics vehicle;

[0082] Specifically, the vehicle usage data includes: average vehicle transportation rate and remaining stay time; the historical order data includes: total cargo damage rate and transportation overtime rate;

[0083] Vehicle screening is performed according to the logistics scheduling task, the vehicle usage data, and the historical order data to obtain a target logistics vehicle, including:

[0084] According to the logistics scheduling task, determine the departure preparation time and cargo transportation rate corresponding to the logistics scheduling task;

[0085] Compare the average vehicle transport rate with the cargo transport rate; and compare the remaining stay time with the departure preparation time;

[0086] When the average transport rate of the vehicle is greater than or equal to the cargo transport rate, and the remaining stay time is less than or equal to the departure preparation time, the corresponding logistics vehicle is used as the first target vehicle;

[0087] Calculating according to the total damage rate of the cargo of the first target vehicle, the transportation overtime rate, the preset standard damage rate, the preset standard overtime rate and the preset first weight factor to obtain the damage index of the first target vehicle;

[0088] Comparing according to the damage index and a preset damage threshold;

[0089] When the damage index is less than or equal to a preset damage threshold, the corresponding first target vehicle is used as the target logistics vehicle.

[0090] Preferably, the total damage rate of goods represents the total damage rate of goods in the historical orders of the logistics vehicle; the transportation overtime rate represents the probability of the logistics vehicle's previous orders overtime. First, according to the logistics scheduling task, determine the departure preparation time and cargo transportation rate corresponding to the logistics scheduling task, and then compare the average vehicle transportation rate with the cargo transportation rate; and compare the remaining stay time with the departure preparation time; when the average vehicle transportation rate is greater than or equal to the cargo transportation rate (the average vehicle transportation rate meets the cargo transportation rate), and the remaining stay time is less than or equal to the departure preparation time (the logistics vehicle can immediately start to perform the next task or go to the next destination) (the cargo transportation rate and departure preparation time corresponding to the logistics scheduling task need to be met at the same time), the corresponding logistics vehicle is taken as the first target vehicle. Then, according to the total damage rate of goods, transportation overtime rate, preset standard damage rate, preset standard overtime rate and preset first weight factor of the first target vehicle, the damage index of the first target vehicle is obtained. Assuming that the total damage rate of goods C au , Transportation overtime rate D au , a is the number of each loading vehicle, a=1,2……m, m>2, u is the number of the cargo transportation rate, u=1,2……n, n>2, substitute into the damage index calculation formula The damage index α of the cargo transportation rate b of logistics vehicle a is obtained au , C′ a and D′ a are the preset standard damage rate and preset standard overtime rate of logistics vehicle a respectively, ε1 and ε2 are the transport damage rate weight factor and transport overtime rate weight factor in the preset first weight factor respectively, ε1>0, ε2>0, ε1+ε2=1; finally, comparison is made based on the damage index and the preset damage threshold; when the damage index is less than or equal to the preset damage threshold, the corresponding first target vehicle is used as the target logistics vehicle.

[0091] By comparing the average transport rate of the vehicle with the cargo transport rate required for the logistics scheduling task, it can be ensured that the selected vehicle can meet the transport speed requirements, thereby improving the overall efficiency of logistics. At the same time, comparing the remaining dwell time with the departure preparation time can ensure that the vehicle can be ready within the specified time to avoid delays. Not only the transportation capacity of the vehicle is taken into account, but also the historical performance of the vehicle (such as the total cargo damage rate and transportation overtime rate) is combined, so that a more comprehensive assessment of whether the vehicle is suitable for performing specific logistics tasks can be made. This helps to optimize the allocation of logistics resources and ensure that the most suitable vehicles are assigned to the most needed tasks.

[0092] S3. Screen the target logistics vehicles according to the historical transportation data corresponding to the target logistics vehicles to determine the final logistics dispatching vehicles;

[0093] Specifically, the historical transportation data includes: historical transportation speed, historical transportation location and historical transportation status; the historical transportation status includes qualified and unqualified;

[0094] According to the historical transportation data corresponding to the target logistics vehicle, the target logistics vehicle is screened to determine the final logistics dispatch vehicle, including:

[0095] According to the historical transportation data, the historical transportation speed corresponding to the qualified historical transportation status is used as the first historical transportation speed;

[0096] According to the historical transportation data, using the historical freight speed as the second historical freight speed of the target logistics vehicle;

[0097] sorting according to the second historical freight speeds, and taking the largest second historical freight speed as the optimal freight speed;

[0098] Determine, based on a comparison between the first historical freight speed and the optimal freight speed, a first transportation number at which the first historical freight speed is greater than the optimal freight speed;

[0099] The historical shipping location corresponding to the qualified historical shipping status is used as the first historical shipping location, and the second transportation number of the first historical shipping location is determined;

[0100] Calculate the transport index of the target logistics vehicle according to the first transport number, the second transport number, the preset standard transport number, and the preset second weight factor;

[0101] Comparison is made based on the transport index and a preset transport threshold;

[0102] When the transportation index is greater than or equal to a preset transportation threshold, the corresponding target logistics vehicle is used as the final logistics scheduling vehicle.

[0103] Schematically, after completing an order, the driver will make a qualified or unqualified evaluation, which will be recorded in the historical transportation data. According to the historical transportation data, the historical transportation speed corresponding to the qualified historical transportation status is used as the first historical transportation speed; according to the historical transportation data, the historical transportation speed is used as the second historical transportation speed of the target logistics vehicle; then the second historical transportation speeds are sorted, and the largest second historical transportation speed is used as the best transportation speed; according to the comparison between the first historical transportation speed and the best transportation speed, the first transportation number in which the first historical transportation speed is greater than the best transportation speed is determined; the historical transportation location corresponding to the qualified historical transportation status is used as the first historical transportation location, and the second transportation number of the first historical transportation location is determined. Schematically, the first transportation number is E. b , the second transport frequency is F b , b is the serial number of each target logistics vehicle, b=1,2...i, i>2, according to the first transportation number, the second transportation number, the preset standard transportation number and the preset second weight factor, substitute into the transportation index calculation formula The transportation index β of the target logistics vehicle b is obtained by calculation b , E' and F' are respectively the preset standard speed transportation times and the preset standard location transportation times in the preset standard transportation times, φ1 and φ2 are respectively the speed weight factor and the location weight factor of the preset second weight factor. Finally, the transportation index and the preset transportation threshold are compared; when the transportation index is greater than or equal to the preset transportation threshold, the corresponding target logistics vehicle is used as the final logistics scheduling vehicle.

[0104] Considering the historical freight status (qualified or unqualified) and the related historical freight speed, vehicles that often appear unqualified in historical transportation can be excluded to ensure that the selected vehicles have stable transportation quality and reduce the risk of cargo damage or delay. At the same time, vehicles with excellent performance and fast transportation speed in historical transportation are selected to ensure that the final logistics dispatch vehicle can complete the transportation task with high efficiency and reduce transportation time and cost.

[0105] S4. Determine a loading robot according to the logistics dispatching task and the robot loading data, so that the loading robot loads the goods to be dispatched onto the logistics dispatching vehicle;

[0106] Preferably, the robot loading data includes: loading robot model, historical loading volume, loading movement speed, loading cargo damage rate and loading energy consumption;

[0107] Determining a loading robot according to the logistics scheduling task and the robot loading data includes:

[0108] According to each loading movement speed of each loading robot model, the historical loading volume at each loading movement speed of each loading robot model is sorted;

[0109] The maximum historical loading volume at each loading moving speed of each loading robot model is used as the target loading volume;

[0110] According to the robot loading data, determining the loading cargo damage rate corresponding to each target loading volume as the target loading cargo damage rate, and the loading energy consumption corresponding to each target loading volume as the target loading energy consumption;

[0111] Calculate according to the target loading cargo damage rate, the target loading energy consumption, the preset loading damage rate, the preset loading energy consumption threshold and the preset loading weight factor to obtain a first usage index at each loading movement speed of each loading robot model;

[0112] comparing the first usage index with a preset loading index threshold;

[0113] When the first usage index is greater than or equal to a preset loading index threshold, the loading robot model at the corresponding loading movement speed is used as a first model for characterizing the available loading robot models;

[0114] Determine the cargo capacity of the cargo to be dispatched according to the logistics dispatch task;

[0115] A loading robot is determined according to the cargo capacity and the first model.

[0116] In a preferred embodiment of the present invention, the loading robots have different models, so it is necessary to record the loading robot models; according to each loading movement speed of each loading robot model, the historical loading volume of each loading robot model at each loading movement speed is sorted; then the maximum historical loading volume at each loading movement speed of each loading robot model is used as the target loading volume; then, according to the robot loading data, the loading cargo damage rate corresponding to each target loading volume is determined as the target loading cargo damage rate, and the loading energy consumption corresponding to each target loading volume is determined as the target loading energy consumption. Assuming that the target loading cargo damage rate is G ct , the target loading energy consumption is H ct , c is the number of each model of robot, c = 1, 2 ... x, x > 2, t is the number of the robot loading movement speed, t = 1, 2 ... y, y > 2; according to the target loading cargo damage rate, the target loading energy consumption, the preset loading damage rate, the preset loading energy consumption threshold and the preset loading weight factor, substitute them into the usage index calculation formula The first usage index γ of each loading robot model c at each loading movement speed t is calculated. ct ; G′ and H′ are respectively the preset loading damage rate and the preset loading energy consumption threshold, δ1 and δ2 are respectively the cargo damage rate weight factor and the total energy consumption weight factor of the preset loading weight factor, δ1>0, δ1>0, δ1+δ2=1. Finally, the first usage index is compared with the preset loading index threshold; when the first usage index is greater than or equal to the preset loading index threshold, the loading robot model at the corresponding loading moving speed is used as the first model for characterizing the available loading robot model; according to the logistics scheduling task, the cargo capacity of the cargo to be scheduled is determined; according to the cargo capacity and the first model, the loading robot is determined.

[0117] By comparing the historical loading volumes of different loading robot models at different loading moving speeds, the robot model and moving speed combination with the highest loading efficiency can be screened out. This helps ensure that the selected loading robot can complete the loading task at a faster speed, reducing waiting time and cost. At the same time, by calculating the first usage index and considering multiple factors such as the target loading cargo damage rate, target loading energy consumption, preset loading damage rate, preset loading energy consumption threshold, and preset loading weight factor, a more comprehensive and objective performance evaluation of different loading robot models and moving speed combinations can be performed. This helps ensure that the selected loading robot not only has a high loading efficiency, but also completes the task while maintaining a low cargo damage rate and energy consumption.

[0118] In a preferred embodiment of the present invention, determining a loading robot according to the cargo capacity and the first model includes:

[0119] Sorting the first usage indexes at each loading movement speed of the first model, and taking the maximum first usage index as the first target usage index of the first model;

[0120] Determine a first working state and a first loadable quantity corresponding to the first model and a preset loading robot database; wherein the first working state includes idle;

[0121] Determine a first idle number of loading robots whose first working state is idle according to the first working state and the first model;

[0122] Calculate the first loading quantity of each first model according to the first free quantity and the corresponding first loading quantity;

[0123] According to the first loading quantity, the cargo capacity and the first target usage index, a loading robot is determined in descending order according to the first target usage index.

[0124] By sorting the first usage index of each loading movement speed of the first model and selecting the maximum first usage index as the first target usage index of the first model, it can be ensured that the selected loading robot is optimal in performance and efficiency, which helps to optimize resource utilization and improve loading efficiency; according to the first idle number of loading robots whose first working state is idle, the currently available robot resources can be accurately understood. Calculating the first loading volume of each first model in combination with the first loadable volume can ensure that the selected robot can meet the cargo capacity requirements. This helps to improve the accuracy of logistics scheduling.

[0125] S5. When the logistics dispatch vehicle arrives at the warehouse to be loaded, determine the target storage warehouse according to the warehouse capacity data and the cargo capacity corresponding to the logistics dispatch task;

[0126] Specifically, the warehouse capacity data includes: warehouse remaining capacity, warehouse standard capacity, and warehouse stored goods;

[0127] Determining a target storage warehouse according to the warehouse capacity data and the cargo capacity corresponding to the logistics scheduling task includes:

[0128] The warehouse storage index is obtained by calculating according to the remaining capacity of the warehouse, the cargo capacity, the remaining capacity of the preset standard warehouse, the remaining space of the preset standard cargo and the preset warehouse weight factor;

[0129] The warehouse corresponding to the warehouse storage index greater than the preset warehouse index threshold is used as the target storage warehouse.

[0130] In a preferred embodiment of the present invention, according to the remaining capacity V' of the warehouse d , the cargo capacity V, the preset standard warehouse remaining capacity W' d , the preset standard cargo remaining space W″ and the preset warehouse weight factor of the warehouse remaining space weight factor ρ1 and the warehouse order cargo remaining space weight factor ρ2 are substituted The storage index calculation formula is used to calculate the warehouse storage index η d , V″ is the preset remaining space for goods, ρ1>ρ, ρ2>0, ρ1+ρ2=1, and the warehouse with the largest warehouse storage index is selected as the target storage warehouse d.

[0131] By calculating the warehouse storage index, taking into account multiple factors such as the remaining capacity of the warehouse, the cargo capacity, the remaining capacity of the preset standard warehouse, and the remaining space of the preset standard cargo, the remaining capacity of the warehouse can be accurately matched with the cargo capacity requirements of the logistics scheduling task, which helps to avoid insufficient warehouse capacity or excessive waste and improve the utilization of warehouse space. Using warehouses with a warehouse storage index greater than the preset warehouse index threshold as target storage warehouses can ensure that the selected warehouses can meet the requirements of the logistics scheduling task in terms of capacity and storage conditions, which helps to reduce the number and time of cargo transfers between warehouses, optimize the logistics scheduling process, and improve overall logistics efficiency.

[0132] S6. Determine an unloading robot according to the logistics scheduling task and the robot unloading data, so that the unloading robot unloads the goods to be scheduled on the logistics scheduling vehicle to the target storage warehouse for storage.

[0133] Specifically, the robot unloading data includes: unloading robot model, historical unloading volume, unloading movement speed, unloading cargo damage rate and unloading energy consumption;

[0134] Determining the unloading robot according to the logistics scheduling task and the robot unloading data includes:

[0135] According to each unloading moving speed of each unloading robot model, the historical unloading volume at each unloading speed of each unloading robot model is sorted;

[0136] The maximum historical unloading volume at each unloading moving speed of each unloading robot model is taken as the target unloading volume;

[0137] According to the robot unloading data, determining the unloading cargo damage rate corresponding to each target unloading volume as the target unloading cargo damage rate, and the unloading energy consumption corresponding to each target unloading volume as the target unloading energy consumption;

[0138] Calculate according to the target unloading cargo damage rate, the target unloading energy consumption, the preset unloading damage rate, the preset unloading energy consumption threshold and the preset unloading weight factor to obtain a second usage index at each unloading moving speed of each unloading robot model;

[0139] comparing the second usage index with a preset unloading index threshold;

[0140] When the second usage index is greater than or equal to a preset unloading index threshold, the unloading robot model at the corresponding unloading moving speed is used as the second model for characterizing the available unloading robot model;

[0141] An unloading robot is determined according to the cargo capacity and the second model.

[0142] In a preferred embodiment of the present invention, the loading robot and the unloading robot belong to two different areas, so it is necessary to screen out suitable loading robots and unloading robots respectively. First, according to each unloading moving speed of each unloading robot model, the historical unloading volume of each unloading robot model at each unloading speed is sorted; the maximum historical unloading volume at each unloading moving speed of each unloading robot model is used as the target unloading volume; then, according to the robot unloading data, the unloading cargo damage rate corresponding to each target unloading volume is determined as the target unloading cargo damage rate, and the unloading energy consumption corresponding to each target unloading volume is determined as the target unloading energy consumption; according to the target unloading cargo damage rate, the target unloading energy consumption, the preset unloading damage rate, the preset unloading energy consumption threshold and the preset unloading weight factor, a second usage index at each unloading moving speed of each unloading robot model is calculated; finally, the second usage index is compared with the preset unloading index threshold; when the second usage index is greater than or equal to the preset unloading index threshold, the unloading robot model at the corresponding unloading moving speed is used as the second model for characterizing the available unloading robot models; the unloading robot is determined according to the cargo capacity and the second model.

[0143] Specifically, determining the unloading robot according to the cargo capacity and the second model includes:

[0144] Sorting according to the second usage index at each unloading movement speed of the second model, and taking the maximum second usage index as the second target usage index of the second model;

[0145] Determine the corresponding second working state and the second unloading amount according to the second model and the preset unloading robot database; wherein the second working state includes idle;

[0146] Determine, according to the second working state and the second model, a second idle number of unloading robots whose second working state is idle;

[0147] Calculate the second loading quantity of each second model according to the second free quantity and the corresponding second unloadable quantity;

[0148] According to the second loading quantity, the cargo capacity and the second target usage index, an unloading robot is determined in descending order according to the second target usage index.

[0149] By comprehensively considering multiple factors such as the unloading robot's historical unloading volume, unloading movement speed, unloading cargo damage rate, and unloading energy consumption, it is possible to accurately match the unloading requirements of the logistics scheduling task and ensure that the selected robot meets the requirements in terms of unloading efficiency, cargo safety, and energy consumption. Taking the maximum historical unloading volume of each unloading robot model at each unloading speed as the target unloading volume helps to select the robot model with the highest unloading efficiency, shorten the unloading time, reduce the cargo in transit time, and improve the overall logistics efficiency. By considering the unloading cargo damage rate and selecting a robot model with a lower damage rate, the risk of cargo damage during the unloading process can be reduced.

[0150] By implementing this embodiment, logistics scheduling tasks, vehicle usage data of logistics vehicles, historical order data, historical transportation data of drivers corresponding to logistics vehicles, robot loading data, robot unloading data and warehouse capacity data of warehouses to be loaded are obtained; vehicles are screened according to the logistics scheduling tasks, the vehicle usage data and the historical order data to obtain target logistics vehicles; the target logistics vehicles are screened according to the historical transportation data corresponding to the target logistics vehicles to determine the final logistics scheduling vehicles; a loading robot is determined according to the logistics scheduling tasks and the robot loading data so that the loading robot loads the goods to be scheduled onto the logistics scheduling vehicle; when the logistics scheduling vehicle arrives at the warehouse to be loaded, a target storage warehouse is determined according to the warehouse capacity data and the cargo capacity corresponding to the logistics scheduling tasks; an unloading robot is determined according to the logistics scheduling tasks and the robot unloading data so that the unloading robot unloads the goods to be scheduled on the logistics scheduling vehicle to the target storage warehouse for storage. By integrating the driving data of drivers, warehouse capacity data and the loading and unloading data of robots, the entire process of logistics scheduling and transportation vehicles and cargo loading and unloading is optimized. Not only are transportation vehicles screened based on vehicle usage data and historical vehicle order data, but the historical transportation data of drivers is also integrated to select vehicles that are more suitable for scheduling tasks and to select logistics scheduling vehicles based on the historical transportation data of the drivers corresponding to the vehicles. This improves the utilization rate of logistics vehicles and combines the loading and unloading data of robots to quickly and accurately select suitable loading and unloading robots for operations, thereby improving the efficiency of the entire logistics scheduling process and the accuracy of scheduling.

[0151] See also Figure 2 , is a schematic diagram of the structure of a storage logistics scheduling device provided by an embodiment of the present invention, comprising:

[0152] The scheduling data acquisition module is used to obtain logistics scheduling tasks, vehicle usage data of logistics vehicles, historical order data, historical transportation data of drivers corresponding to logistics vehicles, robot loading data, robot unloading data, and warehouse capacity data of warehouses to be loaded;

[0153] A first screening module is used to screen vehicles according to the logistics scheduling tasks, the vehicle usage data and the historical order data to obtain target logistics vehicles;

[0154] The second screening module is used to screen the target logistics vehicles according to the historical transportation data corresponding to the target logistics vehicles to determine the final logistics dispatching vehicles;

[0155] A dispatching and loading module, used for determining a loading robot according to the logistics dispatching task and the robot loading data, so that the loading robot loads the goods to be dispatched onto the logistics dispatching vehicle;

[0156] A third screening module is used to determine the target storage warehouse according to the warehouse capacity data and the cargo capacity corresponding to the logistics scheduling task when the logistics scheduling vehicle arrives at the waiting warehouse;

[0157] The scheduling and unloading module is used to determine the unloading robot according to the logistics scheduling task and the robot unloading data, so that the unloading robot unloads the goods to be scheduled on the logistics scheduling vehicle to the target storage warehouse for storage.

[0158] The present invention provides a warehousing logistics scheduling device, which acquires logistics scheduling tasks, vehicle usage data of logistics vehicles, historical order data, historical transportation data of drivers corresponding to logistics vehicles, robot loading data, robot unloading data and warehouse capacity data of warehouses to be loaded according to a scheduling data acquisition module; in a first screening module, vehicles are screened according to the logistics scheduling tasks, the vehicle usage data and the historical order data to obtain target logistics vehicles; in a second screening module, the target logistics vehicles are screened according to the historical transportation data corresponding to the target logistics vehicles to determine the final logistics scheduling vehicles; in a scheduling loading module, a loading robot is determined according to the logistics scheduling tasks and the robot loading data, so that the loading robot loads the goods to be scheduled onto the logistics scheduling vehicle; through a third screening module, when the logistics scheduling vehicle arrives at the warehouse to be loaded, a target storage warehouse is determined according to the warehouse capacity data and the cargo capacity corresponding to the logistics scheduling task; in a scheduling unloading module, an unloading robot is determined according to the logistics scheduling tasks and the robot unloading data, so that the unloading robot unloads the goods to be scheduled on the logistics scheduling vehicle to the target storage warehouse for storage. By integrating the driving data of drivers, warehouse capacity data and the loading and unloading data of robots, the entire process of logistics scheduling and transportation vehicles and cargo loading and unloading is optimized. Not only are transportation vehicles screened based on vehicle usage data and historical vehicle order data, but the historical transportation data of drivers is also integrated to select vehicles that are more suitable for scheduling tasks and to select logistics scheduling vehicles based on the historical transportation data of the drivers corresponding to the vehicles. This improves the utilization rate of logistics vehicles and combines the loading and unloading data of robots to quickly and accurately select suitable loading and unloading robots for operations, thereby improving the efficiency of the entire logistics scheduling process and the accuracy of scheduling.

[0159] It should be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art may understand and implement it without paying any creative effort.

[0160] Those skilled in the art can clearly understand that, for the sake of convenience and brevity, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0161] Another embodiment of the present invention further provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements a warehouse logistics scheduling method as described in the above embodiment when executing the computer program. The terminal device may be a computing device such as a desktop computer, a notebook, a PDA, and a cloud server. The terminal device may include, but is not limited to, a processor and a memory.

[0162] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, and uses various interfaces and lines to connect various parts of the entire terminal device.

[0163] The memory can be used to store the computer program, and the processor realizes various functions of the terminal device by running or executing the computer program stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function, etc.; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device or other volatile solid-state storage device.

[0164] Another embodiment of the present invention provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute a warehouse logistics scheduling method described in the above embodiment.

[0165] The storage medium is a computer-readable storage medium, and the computer program is stored in the computer-readable storage medium. When the computer program is executed by the processor, the steps of each of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium.

[0166] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A warehouse logistics scheduling method, characterized in that: include: Obtain logistics dispatch tasks, vehicle usage data of logistics vehicles, historical order data, historical transportation data of drivers corresponding to logistics vehicles, robot loading data, robot unloading data, and warehouse capacity data of warehouses to be loaded; Perform vehicle screening according to the logistics scheduling task, the vehicle usage data, and the historical order data to obtain a target logistics vehicle; According to the historical transportation data corresponding to the target logistics vehicles, the target logistics vehicles are screened to determine the final logistics dispatch vehicles; Determine a loading robot according to the logistics scheduling task and the robot loading data, so that the loading robot loads the goods to be scheduled onto the logistics scheduling vehicle; When the logistics dispatch vehicle arrives at the warehouse to be loaded, determining the target storage warehouse according to the warehouse capacity data and the cargo capacity corresponding to the logistics dispatch task; According to the logistics scheduling task and the robot unloading data, an unloading robot is determined so that the unloading robot unloads the goods to be scheduled on the logistics scheduling vehicle to the target storage warehouse for storage.

2. A warehouse logistics scheduling method according to claim 1, characterized in that: The vehicle usage data includes: the average transportation speed and the remaining stay time of the vehicle; the historical order data includes: the total damage rate of goods and the transportation overtime rate; Vehicle screening is performed according to the logistics scheduling task, the vehicle usage data, and the historical order data to obtain a target logistics vehicle, including: According to the logistics scheduling task, determine the departure preparation time and cargo transportation rate corresponding to the logistics scheduling task; Compare the average vehicle transport rate with the cargo transport rate; and compare the remaining stay time with the departure preparation time; When the average transport rate of the vehicle is greater than or equal to the cargo transport rate, and the remaining stay time is less than or equal to the departure preparation time, the corresponding logistics vehicle is used as the first target vehicle; Calculating according to the total damage rate of the cargo of the first target vehicle, the transportation overtime rate, the preset standard damage rate, the preset standard overtime rate and the preset first weight factor to obtain the damage index of the first target vehicle; Comparing according to the damage index and a preset damage threshold; When the damage index is less than or equal to a preset damage threshold, the corresponding first target vehicle is used as the target logistics vehicle.

3. A warehouse logistics scheduling method as claimed in claim 2, characterized in that: The historical transportation data includes: historical transportation speed, historical transportation location and historical transportation status; the historical transportation status includes qualified and unqualified; According to the historical transportation data corresponding to the target logistics vehicle, the target logistics vehicle is screened to determine the final logistics dispatch vehicle, including: According to the historical transportation data, the historical transportation speed corresponding to the qualified historical transportation status is used as the first historical transportation speed; According to the historical transportation data, using the historical freight speed as the second historical freight speed of the target logistics vehicle; sorting according to the second historical freight speeds, and taking the largest second historical freight speed as the optimal freight speed; Determine, based on a comparison between the first historical freight speed and the optimal freight speed, a first transportation number at which the first historical freight speed is greater than the optimal freight speed; The historical shipping location corresponding to the qualified historical shipping status is used as the first historical shipping location, and the second transportation number of the first historical shipping location is determined; Calculate the transport index of the target logistics vehicle according to the first transport number, the second transport number, the preset standard transport number, and the preset second weight factor; Comparison is made based on the transport index and a preset transport threshold; When the transportation index is greater than or equal to a preset transportation threshold, the corresponding target logistics vehicle is used as the final logistics scheduling vehicle.

4. A storage logistics scheduling method as claimed in claim 3, characterized in that: The robot loading data includes: loading robot model, historical loading volume, loading movement speed, loading cargo damage rate and loading energy consumption; Determining a loading robot according to the logistics scheduling task and the robot loading data includes: According to each loading movement speed of each loading robot model, the historical loading volume at each loading movement speed of each loading robot model is sorted; The maximum historical loading volume at each loading moving speed of each loading robot model is used as the target loading volume; According to the robot loading data, determining the loading cargo damage rate corresponding to each target loading volume as the target loading cargo damage rate, and the loading energy consumption corresponding to each target loading volume as the target loading energy consumption; Calculate according to the target loading cargo damage rate, the target loading energy consumption, the preset loading damage rate, the preset loading energy consumption threshold and the preset loading weight factor to obtain a first usage index at each loading movement speed of each loading robot model; comparing the first usage index with a preset loading index threshold; When the first usage index is greater than or equal to a preset loading index threshold, the loading robot model at the corresponding loading movement speed is used as a first model for characterizing the available loading robot models; Determine the cargo capacity of the cargo to be dispatched according to the logistics dispatch task; A loading robot is determined according to the cargo capacity and the first model.

5. A warehouse logistics scheduling method as claimed in claim 4, characterized in that: Determining a loading robot according to the cargo capacity and the first model includes: Sorting the first usage indexes at each loading movement speed of the first model, and taking the maximum first usage index as the first target usage index of the first model; Determine a first working state and a first loadable quantity corresponding to the first model and a preset loading robot database; wherein the first working state includes idle; Determine a first idle number of loading robots whose first working state is idle according to the first working state and the first model; Calculate the first loading quantity of each first model according to the first free quantity and the corresponding first loading quantity; According to the first loading quantity, the cargo capacity and the first target usage index, a loading robot is determined in descending order according to the first target usage index.

6. A storage logistics scheduling method as claimed in claim 5, characterized in that: The warehouse capacity data includes: remaining warehouse capacity, standard warehouse capacity, and goods stored in the warehouse; Determining a target storage warehouse according to the warehouse capacity data and the cargo capacity corresponding to the logistics scheduling task includes: The warehouse storage index is obtained by calculating according to the remaining capacity of the warehouse, the cargo capacity, the remaining capacity of the preset standard warehouse, the remaining space of the preset standard cargo and the preset warehouse weight factor; The warehouse corresponding to the warehouse storage index greater than the preset warehouse index threshold is used as the target storage warehouse.

7. A storage logistics scheduling method as claimed in claim 6, characterized in that: The robot unloading data includes: unloading robot model, historical unloading volume, unloading movement speed, unloading cargo damage rate and unloading energy consumption; Determining the unloading robot according to the logistics scheduling task and the robot unloading data includes: According to each unloading moving speed of each unloading robot model, the historical unloading volume at each unloading speed of each unloading robot model is sorted; The maximum historical unloading volume at each unloading moving speed of each unloading robot model is taken as the target unloading volume; According to the robot unloading data, determining the unloading cargo damage rate corresponding to each target unloading volume as the target unloading cargo damage rate, and the unloading energy consumption corresponding to each target unloading volume as the target unloading energy consumption; Calculate according to the target unloading cargo damage rate, the target unloading energy consumption, the preset unloading damage rate, the preset unloading energy consumption threshold and the preset unloading weight factor to obtain a second usage index at each unloading moving speed of each unloading robot model; comparing the second usage index with a preset unloading index threshold; When the second usage index is greater than or equal to a preset unloading index threshold, the unloading robot model at the corresponding unloading moving speed is used as the second model for characterizing the available unloading robot model; An unloading robot is determined according to the cargo capacity and the second model.

8. A storage logistics scheduling method as claimed in claim 7, characterized in that: Determining an unloading robot according to the cargo capacity and the second model includes: Sorting according to the second usage index at each unloading movement speed of the second model, and taking the maximum second usage index as the second target usage index of the second model; Determine the corresponding second working state and the second unloading amount according to the second model and the preset unloading robot database; wherein the second working state includes idle; Determine, according to the second working state and the second model, a second idle number of unloading robots whose second working state is idle; Calculate the second loading quantity of each second model according to the second free quantity and the corresponding second unloadable quantity; According to the second loading quantity, the cargo capacity and the second target usage index, an unloading robot is determined in descending order according to the second target usage index.

9. A storage logistics scheduling device, characterized in that: include: The scheduling data acquisition module is used to obtain logistics scheduling tasks, vehicle usage data of logistics vehicles, historical order data, historical transportation data of drivers corresponding to logistics vehicles, robot loading data, robot unloading data, and warehouse capacity data of warehouses to be loaded; A first screening module is used to screen vehicles according to the logistics scheduling tasks, the vehicle usage data and the historical order data to obtain target logistics vehicles; The second screening module is used to screen the target logistics vehicles according to the historical transportation data corresponding to the target logistics vehicles to determine the final logistics dispatching vehicles; A dispatching and loading module, used for determining a loading robot according to the logistics dispatching task and the robot loading data, so that the loading robot loads the goods to be dispatched onto the logistics dispatching vehicle; A third screening module is used to determine the target storage warehouse according to the warehouse capacity data and the cargo capacity corresponding to the logistics scheduling task when the logistics scheduling vehicle arrives at the waiting warehouse; The scheduling and unloading module is used to determine the unloading robot according to the logistics scheduling task and the robot unloading data, so that the unloading robot unloads the goods to be scheduled on the logistics scheduling vehicle to the target storage warehouse for storage.

10. A terminal device, characterized in that: It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, it implements a warehouse logistics scheduling method as described in any one of claims 1 to 8.

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