DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Remarks
This final office action is a response to the reply received on 07/14/2026. Claims 1-20 are pending. Claims 1-3, 6, 7-10, 13, 15-17, and 20 have been amended.
Response to Arguments
Applicant’s arguments/amendments overcome the previous 112b rejections. The examiner notes that because of the “or” condition, the some of the dependent claims may not be required.
The arguments with respect to the 101 rejections have been considered but are not persuasive. The updated language of “applied to a scenario of multiple picking tasks assigned to multiple picking robots” does not overcome the 101 rejection because the language of the claim still reads as a mental process. A person can mentally (or with pen and paper) determine, upon receiving data, a schedule for picking robots, even if the scheduling is intended for multiple robots and there are multiple picking tasks involved.
Applicant’s additional arguments with respect to Claims 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception of an abstract idea without significantly more.
Re Claim 1 recites: A method for scheduling picking robots, applied to a scenario of multiple picking tasks assigned to multiple picking robots, comprising: determining, in response to receiving the multiple picking tasks, a sorting indicator for each picking task of the multiple picking tasks based on task association information corresponding to the picking tasks, and sorting the multiple picking tasks based on sorting indicators, to obtain a task sorting result, the task association information comprising at least one of total quantity of items of items to be picked corresponding to the picking tasks, packing information, or category information; and scheduling a picking robot to execute the picking tasks according to a working stage of the picking robot and the task sorting result, the working stage comprising at least one of a picking stage, a packing stage, a replenishment stage, an idle stage, or a maintenance stage.
Under Step 1: Claim 1 is a method.
Under Step 2A Prong 1: The claim recites an judicial exception of abstract idea of mental processes. The additional elements are crossed out below.
A method for scheduling picking robots
The amendment intended to address the 101 rejection does not overcome the 101 rejection. A person, based on the received data, can mentally decide/determine a schedule for picking robots, even if the scheduling is intended for multiple robots and there are multiple picking tasks involved.
Under Step 2A Prong 2: The additional elements as crossed out above, is a part of the data being used to perform the abstract idea, which does not make the abstract idea into a practical application.
Under Step 2B, the additional elements are the same as Step 2A Prong 2. For the same reasons, the additional elements also are not sufficient to amount to significantly more than the abstract idea.
Re Claim 8 recites:
An electronic device, comprising:
Under Step 1: Claim 8 is a device
Under Step 2A Prong 1: Claim 8 is the device and hardware utilized to perform the method of Claim 1. The analysis of the abstract idea the same as Claim 1.
Under Step 2A Prong 2: The additional elements as crossed out above, are the memory and processor, which are merely tools being used to execute the abstract idea, and the data being used to perform the abstract idea, which does not make the abstract idea into a practical application.
Under Step 2B, the additional elements are the same as Step 2A Prong 2. For the same reasons, the additional elements also are not sufficient to amount to significantly more than the abstract idea.
Re Claim 15 recites:
A non-transitory storage medium containing computer- executable instructions
Under Step 1: Claim 15 is a non-transitory storage medium
Under Step 2A Prong 1: Claim15 is the storage hardware that stores the program/instructions utilized to perform the method of Claim 1. The analysis of the abstract idea the same as Claim 1.
Under Step 2A Prong 2: The additional elements as crossed out above, is the processor, which is merely a tool being used to execute the abstract idea, and the data being used to perform the abstract idea, which does not make the abstract idea into a practical application.
Under Step 2B, the additional elements are the same as Step 2A Prong 2. For the same reasons, the additional elements also are not sufficient to amount to significantly more than the abstract idea.
Re Claims 2, 9, and 16 recite:
Under Step 2A Prong 2/Step 2B: The packing information is mere data being used to perform the abstract idea and is not enough to make the abstract idea into a practical application or be significantly more.
Re Claims 3, 10, and 17 recite:
wherein sorting the multiple picking tasks based on task association information corresponding to the picking tasks comprises: determining a first ratio based on the total quantity of items and the number of packages, and determining a second ratio based on the total quantity of items and a number of categories
Under Step 2A Prong 1: A human can mentally analyze the received data in order to determine the first and second ratio and determine how to sort the picking tasks.
Under Step 2A Prong 2/Step 2B: The category information is mere data being used to perform the abstract idea and is not enough to make the abstract idea into a practical application or be significantly more.
Re Claims 4 and 11 (and similarly 18) recite: after sorting the multiple picking tasks based on task association information corresponding to the picking tasks to obtain a task sorting result, further comprising: and in response to the latest start time for the picking tasks being reached and the picking tasks being not assigned to the picking robot, generating task prompt information corresponding to the picking tasks,
Under Step 2A Prong 1: A human can mentally determine 'task prompt' information in response to the human learning that the latest start time has been reached and the tasks haven't been assigned. For example, a human can mentally determine that if a task hasn’t been assigned by the latest start time, then that task is likely not to be completed in time unless there is an intervention/assistance.
Under Step 2A Prong 2/Step 2B: The displaying of information is an additional element and is not enough to make the abstract idea into a practical application or be significantly more.
Re Claims 5, 12, and 19 recite: wherein determining a latest start time for the picking robot to begin executing the picking tasks comprises: determining a latest completion time for the picking tasks and a picking execution time for the picking robot; and determining the latest start time for the picking robot to begin executing the picking tasks based on the latest completion time and the picking execution time.
Under Step 2A Prong 1: A human could mentally determine/calculate what time a task needs to be completed and how long a task will take, and additionally from that can determine what the latest start time is in order for the task to be completed on time.
Re Claims 6, 13, and 20 recite: wherein scheduling the picking robot to execute the picking tasks according to a working stage of the picking robot and the task sorting result comprises: in the presence of the multiple picking robots, individually
Under Step 2A Prong 1: A human could mentally, based on the data/information, determine how to schedule the picking robots.
Under Step 2A Prong 2/Step 2B: The energy storage information is data being used to perform the abstract idea and is not enough to make the abstract idea into a practical application or be significantly more.
Re Claims 7 and 14 recite: before scheduling the picking robot to execute the picking tasks according to a working stage of the picking robot and the task sorting result, further comprising:
Under Step 2A Prong 1: A human could mentally, based on the location data/information, determine the working stage of the robot based on a relative position between the location and working area.
Under Step 2A Prong 2/Step 2B: The acquiring location information and warehouse working areas are data being used to perform the abstract idea and is not enough to make the abstract idea into a practical application or be significantly more.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 7-8, and 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Li et. al. (US 20200302391 A1) in view of Leonardo et. al. (US 20230022085 A1) and Lert, JR et. al. (US 20180194556 A1).
Regarding Claim 1, Li discloses:
A method for scheduling picking robots, applied to a scenario of multiple picking tasks assigned to multiple picking robots, comprising: (See at least Figure 2 and Figure 10A via Robots 10 and Order Pool 202.)
(See at least Figure 2 and ¶0057-¶0059 via "In step S10, at least one pending order is received, and the at least one pending order is placed in an order pool…In step S20, part or all of the pending orders in the order pool are divided into at least one batch of task…In step S30, for any of the at least one batch of task, the batch of task is allocated to a corresponding target workstation" as well as ¶0072 via "the batch of task can be disbursed to the appropriate target workstations…Exemplarily, a warehouse management system on a warehouse server disburses the batch of tasks to corresponding target workstations according to parameters of order items in pending orders in each batch of task, such as name of the order item, manufacturer, information of the inventory container where the order item is located, the number of order items in each order, and the like" *Wherein the pool of orders corresponds to the multiple picking tasks, and the division into the batch(es) of task(s) + assigning to workstations corresponds to the sorting/sorting result that is based on task association information such as the number of order items in each order.)
the task association information comprising at least one of total quantity of items of items to be picked corresponding to the picking tasks,(See at least ¶0072 via "Exemplarily, a warehouse management system on a warehouse server disburses the batch of tasks to corresponding target workstations according to parameters of order items in pending orders in each batch of task, such as name of the order item, manufacturer, information of the inventory container where the order item is located, the number of order items in each order, and the like")
scheduling a picking robot to execute the picking tasks according to a working stage of the picking robot and the task sorting result, (See at least ¶0074 via Step S140 as well as ¶0077 via " A robot whose navigation distance does not exceed a distance threshold is found at least partly based on the position information of the target workstation" and ¶0079 via "According to the robot scheduling algorithm, the robot scheduling system software of the warehouse server is used for determining the navigation path, and the robot which is currently in the idle state and has the shortest moving distance for carrying the inventory container is scheduled preferentially, which can reduce the navigation time of the robot for carrying the inventory container and further help to improve the picking efficiency")
the working stage comprising at least one of a picking stage, (See at least ¶0079 via "According to the robot scheduling algorithm, the robot scheduling system software of the warehouse server is used for determining the navigation path, and the robot which is currently in the idle state).
However, Li does not explicitly disclose the packing information or category information within the same embodiment. Additionally, Li does not disclose the different stages within the same embodiment. Nevertheless, Li discloses:
packing information (See at least ¶0222 via " In step S1540, order item information of single-item-single-piece type orders in a picking box (or order tote) is determined, and order item lists and/or express bills of the single-item-single-piece type orders are printed according to order item information of the single-item-single-piece type orders. The order item list and/or the express bill are packed together with the order item, where the quantity of packed packing boxes is the same as the quantity of single-item-single-piece type orders in the picking box." *Wherein the packing information is the quantity of packages for an order, and is the same as the quantity of single-item-single-piece orders in the picking box)
or category information; (See at least ¶0208 via "After a user purchases goods and places an order in the network mall, the order enters an Order Management System (OMS), a warehouse is determined according to the OMS, and order information is sent to an order pool of a Warehouse Management System (WMS). The order information includes the express information, a category and quantity of an order item, and so on. According to the category and quantity of the order item, the order form of each order is determined")
at least one of a picking stage, a packing stage, a replenishment stage, an idle stage, or (See at least ¶0279 via "State 000 denotes an idle state, state 001 denotes a carrying state, and state 011 denotes that all carrying tasks are completed and the robot is returning." **Which correspond to the idle stage, picking stage, and replenishment stage respectively. Furthermore, Li discloses robot(s) packing in ¶0013 via "One or more robots are controlled to pick and pack the order items in the first type order from the inventory container")
Therefore, it would have been obvious to combine the embodiments of Li to account for categories of items and single-item-single-piece type orders which are packaged individually in order to expand the range of picking orders that can be processed while ensuring they are picked and packaged effectively, while also improving the efficiency of the system through classification of such orders: "single-item-single-piece type orders including the same order item are classified into one class, or single-item-single-piece type orders with the same order destination are classified into one class" [Li ¶0210]. Furthermore, it would have been obvious to account for the robots being in different stages/states in order to select a robot that is available or meets the desired standard to carry out a task: "If all the robots are with state code 001, a robot that meets a standard may be selected according to the preset control strategy, and the carrying instruction may be sent to the instruction queue of the robot" [Li ¶0279].
However, although Li discloses order priority (See at least ¶0068), modified Li does not explicitly disclose the sorting indicator.
Nevertheless, Leonardo--who is directed towards systems and methods for prioritizing pick jobs while optimizing efficiency--discloses: determining, in response to receiving the multiple picking tasks, a sorting indicator for each picking task of the multiple picking tasks based on task association information corresponding to the picking tasks, and sorting the multiple picking tasks based on sorting indicators, (See at least ¶0008 via "the at-risk pick jobs and the others of the pick jobs can be ordered based in part on an associated score, wherein the associated score can be based on one or more of the following associated with the at-risk pick jobs and the others of the pick jobs: a number of items; a location of items; and the associated due date." and ¶0029 via "…a score can be assigned to each pick job that the fulfillment center must complete and the score can determine the order in which pick jobs are assigned to autonomous vehicles for completion. The score can reflect one or more of the previously identified variables, including the locations of the items, congestion at certain locations within the fulfillment center, and the number of items associated with the pick job…". Also see ¶0063 via " For example, at-risk pick jobs 2, 3, and 4 have a higher score than pick job 6 because they involve more items to be collected.")
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Modified Li in view of utilizing the sorting indicators/associated score based ordering of Leonardo in order to increase the efficiency of the fulfillment, which is the same goal that Li aims to solve (See Li ¶0054): "One way that fulfillment management systems can organize jobs to optimize efficiency is to schedule pick jobs based on a priority ordering that takes into account the previously mentioned variables" [Leonardo ¶0029] and "more efficient operation of the fulfillment center will enable faster completion of pick jobs thereby improving the satisfaction of customers and merchants" [¶0032 Leonardo], and thus would have predictably increased the overall efficiency of the distribution of Modified Li.
However, although modified Li discloses packing as well as various stages, modified Li does not explicitly disclose the packing as an explicit stage or the maintenance stage.
Nevertheless, Lert, JR--who is directed towards a system and method for managing a plurality of automated mobile robots within an automated mobile robot--discloses: a packing stage (See at least ¶0015 via "In accordance with aspects of the present invention, when the mobile robot is designated and operates in the order fulfillment mode, the mobile robot further propels itself through a storage rack structure of the automated fulfillment section, placing totes into the storage rack structure, removing totes from the storage rack structure, and transporting totes throughout the storage rack structure" **Wherein the fulfillment mode corresponds to a packing stage)
or a maintenance stage (See at least ¶0036 via "Other examples of modes of operation can include an initialization mode, a standby mode, an idle mode, an active mode, an alarm mode, a disabled mode, a power off mode, a charging mode, a maintenance recall mode." **Wherein the charging mode or maintenance recall mode can correspond to a maintenance stage).
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Li in view of Lert, JR's various modes in order to account for the activities/status of each robot when assigning tasks: "provides a system and method to provide real-time task assignments for mode of operation for the plurality of interchangeable automated mobile robots" [Lert, JR ¶0005] while ensuring that available robots can be allocated tasks efficiently: "the allocation of operation modes for the automated mobile robots 122 can include any combination of modes based on demands of the automated store 200, number of available automated mobile robots 122, and other factors for optimization/efficiency" [Lert, JR ¶0072].
Regarding Claim 8, Li discloses:
An electronic device, comprising: one or more processors; and a memory configured to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors perform an operation for scheduling picking robots, the operation, applied to a scenario of multiple picking tasks assigned to multiple picking robots, comprising: (See at least ¶0023-¶0026 via "In one embodiment, the embodiment of the present disclosure provides a server. The server includes:…one or more processors; and…a memory, configured to store one or more programs…When executed by the one or more processors, the one or more programs cause the one or more processors to implement the method of any embodiment of the present disclosure." as well as Figure 20 and ¶0302 via "Components of server 412 may include, but not limited to, one or more processors 416, a storage device 428, and a bus 418 connecting different system components (including storage device 428 and processors 416)". Additionally see Figure 10A)
(Regarding the instructions/steps, see Claim 1 rejection as the steps are the same)
Regarding Claim 15, Li discloses:
A non-transitory storage medium containing computer-executable instructions, wherein the computer-executable instructions, when executed by a computer processor, perform an operation for scheduling picking robots, the operation, applied to a scenario of multiple picking tasks assigned to multiple picking robots, comprising: (See at least ¶0304 via "The server 412 includes a plurality of computer system readable media. These media can be any available medium that can be accessed by the server 412, including volatile medium and non-volatile medium, removable medium and non-removable medium" and ¶0321 via "a computer-readable storage medium configured to store computer programs for executing the methods in any of embodiments in the present disclosure when executed by a processor.")
(Regarding the instructions/steps, see Claim 1 rejection as the steps are the same)
Regarding Claims 7 and 14 respectively, Modified Li discloses the method for scheduling picking robots according to Claim 1 and the electronic device according to Claim 8.
Furthermore, Li discloses: before scheduling the picking robot to execute the picking tasks according to a working stage of the picking robot and the task sorting result, further comprising: (See at least ¶0074 via Step S140 as well as ¶0077 via " A robot whose navigation distance does not exceed a distance threshold is found at least partly based on the position information of the target workstation" and ¶0079 via "According to the robot scheduling algorithm, the robot scheduling system software of the warehouse server is used for determining the navigation path, and the robot which is currently in the idle state and has the shortest moving distance for carrying the inventory container is scheduled preferentially, which can reduce the navigation time of the robot for carrying the inventory container and further help to improve the picking efficiency")
acquiring location information of the picking robot in a warehouse, (See at least ¶0075 via "the navigation path is planned and sent to the target robot by combining the position of the scheduled robot and the position of the workstation, and the target robot carries the designated shelves according to the navigation path")
the warehouse comprising at least two working areas, the working areas comprising at least one of a waiting area,(See at least Figure 10A which illustrates 1-N Workstations 40. Additionally, see at least ¶0072 via "Each workstation can include a plurality of batch of tasks" which illustrates at least two working areas. Furthermore, see ¶0124 via "a picking station (i.e., target workstation) 40" which corresponds to the picking area. Additionally see ¶0128 via "At the picking station 40, a picking staff 41 or picking device, such as a robot arm, picks order items from the inventory container 31 and places them in an order tote (or picking box) 50 on a sorting wall 600 for packing, as shown in FIGS. 10D and 10E" which corresponds to a packing area, as part of the packing process is being performed at the working area. Additionally, see ¶0174 via "Correspondingly, the workstation may be provided with a picking area or a buffer area. The picking area refers to an area where the order item picking is performed in an inventory container carried by a robot in a queue. The buffer area refers to an area where the inventory container carried by the robot in the queue is waiting for the order item picking. Therefore, the server will control the target robot to park the target inventory container in the picking area and/or buffer area in the target workstation" **Wherein the buffer area corresponds to a waiting area).
However, Li does not explicitly disclose a replenishment area or a maintenance area, or the determination of the working stage based on a positional relationship between the location of the robot and the working areas.
Nevertheless, Lert, JR discloses: a replenishment area,(See at least Figure 2B via the replenishment section 206)
determining the working stage of the picking robot according to a relative positional relationship between the location information and the working areas (See at least ¶0051 via "The identification of the locations for all of the automated mobile robots 122 and totes 232 can further be utilized by the central controller 116 when allocating automated mobile robots 122 to different modes of operations. In particular, the central controller 116 can identify all of the automated mobile robots 122 that are located within a particular section and instruct those automated mobile robots 122 to perform a particular mode of operation within that section" as well as ¶0048 via "The responsibilities for each of the automated mobile robots 122 changes based on the area of the automated store 200 that the automated robots 122 are assigned as well as the task that they are assigned to perform within or between those areas" **Wherein the sections are a part of the working areas, the robots being located within a section is a positional relationship, and the robots operating in a particular mode within a section is the mode determination based on that relationship)
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Modified Li in view of Lert, JR's robots operating in specific modes based on the section they are in in order to provide robots that are able to adapt and perform any of the operation modes: "a single automated mobile robot 122 is capable of carrying out the tasks required by each of the modes of operation without modification" [Lert, JR ¶0049] which increases the efficiency of task performance "the present invention is directed to a system and method of operation of an automated store with a plurality of interchangeable robots configured with different modes of operation, assigned based on real-time demand, in a manner to optimize inventory usage throughout the entire automated store system. In particular, the present invention provides a system and method to provide real-time task assignments for mode of operation for the plurality of interchangeable automated mobile robots" [Lert, JR ¶0005].
However, modified Li does not explicitly disclose the maintenance area. Nevertheless, Lert, JR discloses "a charging mode, a maintenance recall mode" [Lert, JR ¶0036] as well as other sections/areas (See at least Figure 2B). Thus, one of ordinary skill in the art would recognize that it is obvious to include additional areas (for example, an area for the robot to charge) based on the robot already having those modes, which corresponds to a maintenance area.
Claims 2, 9, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Li et. al. (US 20200302391 A1), Leonardo et. al. (US 20230022085 A1), and Lert, JR et. al. (US 20180194556 A1) in view of Zhang et. al. (CN 115471040 A, Translation Previously Attached in Non-Final dated 04/16/2026).
Regarding Claims 2, 9, and 16 respectively, Modified Li discloses the method for scheduling picking robots according to Claim 1, the electronic device according to Claim 8, and the storage medium according to Claim 15.
However, Modified Li does not explicitly disclose the number of packages being packed.
Nevertheless, Zhang--who is directed towards a target object (such as robot) allocation method and device--discloses: wherein the packing information comprises at least a number of packages being packed (See at least ¶n0032 via "The order information includes order type, order quantity, order package quantity, etc…For example, taking e-commerce warehouse operations as an example, the warehouse's daily forecast orders can be 15 orders. The order splitting coefficient for each order is 2. Then, these 15 orders can be split into 30 packages. Among them, the 30 packages include 100 boxes of milk, 50 pens, 150 dolls, and other items.")
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Modified Li in view of Zhang's number of packages in order to provide more information for the system to efficiently allocate automated equipment for tasks: "…utilize data-driven and intelligent algorithms to optimize the management of operational processes such as picking list assembly, AGV (Automated Guided Vehicle) scheduling, and site task allocation, making the production process more transparent and controllable" [Zhang ¶n0024] by more effectively determining the workload for each job/task: "…Determine the predicted orders for the day, and based on the predicted orders for the day, determine the workload of each job in the job set within a given time period" [Zhang ¶n0031].
Claims 3, 10, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Li et. al. (US 20200302391 A1), Leonardo et. al. (US 20230022085 A1), Lert, JR et. al. (US 20180194556 A1), and Zhang et. al. (CN 115471040 A, Translation Previously Attached in Non-Final dated 04/16/2026) in view of Perry et. al. (US 20140040075 A1) and Singh et. al. (US 20210387805 A1).
Regarding Claims 3, 10, and 17 respectively, Modified Li discloses the method for scheduling picking robots according to Claim 2, the electronic device according to Claim 9, and the storage medium according to Claim 16.
Furthermore, Li disclose: wherein sorting the multiple picking tasks based on task association information corresponding to the picking tasks comprises: (See at least Figure 2 and ¶0057-¶0059 via "In step S10, at least one pending order is received, and the at least one pending order is placed in an order pool…In step S20, part or all of the pending orders in the order pool are divided into at least one batch of task…In step S30, for any of the at least one batch of task, the batch of task is allocated to a corresponding target workstation" as well as ¶0072 via "the batch of task can be disbursed to the appropriate target workstations…Exemplarily, a warehouse management system on a warehouse server disburses the batch of tasks to corresponding target workstations according to parameters of order items in pending orders in each batch of task, such as name of the order item, manufacturer, information of the inventory container where the order item is located, the number of order items in each order, and the like" *Wherein the pool of orders corresponds to the multiple picking tasks, and the division into the batch(es) of task(s) + assigning to workstations corresponds to the sorting/sorting result.)
sorting the multiple picking tasks according to the total quantity of items, (See at least ¶0072 via "the batch of task can be disbursed to the appropriate target workstations…Exemplarily, a warehouse management system on a warehouse server disburses the batch of tasks to corresponding target workstations according to parameters of order items in pending orders in each batch of task, such as … the number of order items in each order, and the like" ).
Furthermore Li does not disclose, but Zhang discloses: the number of packages (See at least ¶n0032 via "The order information includes order type, order quantity, order package quantity, etc…For example, taking e-commerce warehouse operations as an example, the warehouse's daily forecast orders can be 15 orders. The order splitting coefficient for each order is 2. Then, these 15 orders can be split into 30 packages. Among them, the 30 packages include 100 boxes of milk, 50 pens, 150 dolls, and other items.") and
(See at least ¶n0020 via "SKU (Stock Keeping Unit): It is a coding and classification method for products after they are put into storage, and it is also the smallest unit of inventory control." and ¶n0032 via "the 30 packages include 100 boxes of milk, 50 pens, 150 dolls, and other items" )
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Modified Li in view of Zhang's number of packages and SKU data in order to provide more information for the system to efficiently allocate automated equipment for tasks: "…utilize data-driven and intelligent algorithms to optimize the management of operational processes such as picking list assembly, AGV (Automated Guided Vehicle) scheduling, and site task allocation, making the production process more transparent and controllable" [Zhang ¶n0024] by more effectively determining the workload for each job/task: "…Determine the predicted orders for the day, and based on the predicted orders for the day, determine the workload of each job in the job set within a given time period" [Zhang ¶n0031].
However, modified Li does not explicitly disclose the number of categories, however, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to consider the number of categories or types of items as Zhang already accounts for a plurality of different types of items: "the 30 packages include 100 boxes of milk, 50 pens, 150 dolls, and other items" [Zhang ¶n0032].
However, Modified Li does not explicitly disclose the ratios.
Nevertheless, Perry--who is directed towards selection and organization of customer orders in preparation for distribution operations order fulfillment--discloses: determining a first ratio based on the total quantity of items and the number of packages,… (See at least ¶0029 via " Embodiments disclosed herein may be particularly useful in processing orders each containing two or more distinct items." as well as ¶0008 via "The order profile characteristics of eCommerce orders can include a substantial volume of single unit orders and the decreasing volume of orders for subsequent order unit counts. For example: single unit order may comprise 30% of the overall order volume, while 2 unit orders comprise just 25% of the orders and 3 unit orders comprise 18% of the orders and so on" and Claim 4 via "…wherein the instructions are further translatable by the at least one processor to determine a number of virtual order footprints based on a number of available resources, an average number of items per order, or a combination thereof").
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Modified Li in view of the concept of the first ratio as disclosed by Perry in order to consider and address issues that relate to orders/packages with varying quantities of items: "Today, direct to consumer (DTC) or eCommerce (eCom) operations that are required to deliver substantial volume of "multi-unit orders" or "multies" (i.e., orders with more than 1 item per shipment package) yet few items per order continue to face challenges that tax conventional distribution processes that have evolved from high unit volume orders found in retail distribution. These challenges include: very large variations in daily workload, a more or less constant arrival of new orders, staffing constraints, shrunken order delivery requirements, ever growing variety of offered products, small order item counts, limited predictability of immediate inbound orders, and the control of shipment costs." [Perry ¶0003].
However, Modified Li does not explicitly disclose the second ratio.
Nevertheless, Singh--who is directed towards warehouse order picking optimization systems and methods--discloses: and determining a second ratio based on the total quantity of items and the number of categories; (See at least ¶0034 via "an exemplary order allocation optimization process may utilize two data inputs: an active inventory file, which indicates the quantity of items by location according to SKU; and an order file, which indicates the quantity of SKUs required by each order" **wherein the quantity of SKUs required corresponds to the second ratio)
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Modified Li in view of the concept of the second ratio as disclosed by Singh in order to consider the types of items being picked across orders to improve picking efficiency and minimize unnecessary back and forth travel: "For warehouses where pickers pick multiple orders at a time, order grouping optimization attempts to minimize the picker travel distance by generating pick assignments (each of which contains multiple orders) whose items are located as close as possible to each other." [Singh ¶0065].
Claims 4, 11, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Li et. al. (US 20200302391 A1), Leonardo et. al. (US 20230022085 A1), and Lert, JR et. al. (US 20180194556 A1) in view of Li Xuejun. (CN113762664A, Translation Previously Attached in Non-Final dated 04/16/2026) and Gruenstein et. al. (US 20240131712 A1).
Regarding Claims 4, and 11, respectively, Modified Li discloses the method for scheduling picking robots according to Claim 1 and the electronic device according to Claim 8.
Furthermore, Li discloses: after sorting the multiple picking tasks based on task association information corresponding to the picking tasks to obtain a task sorting result, further comprising: (See at least Figure 2 and ¶0057-¶0059 via "In step S10, at least one pending order is received, and the at least one pending order is placed in an order pool…In step S20, part or all of the pending orders in the order pool are divided into at least one batch of task…In step S30, for any of the at least one batch of task, the batch of task is allocated to a corresponding target workstation" as well as ¶0072 via "the batch of task can be disbursed to the appropriate target workstations…Exemplarily, a warehouse management system on a warehouse server disburses the batch of tasks to corresponding target workstations according to parameters of order items in pending orders in each batch of task, such as name of the order item, manufacturer, information of the inventory container where the order item is located, the number of order items in each order, and the like" *Wherein the pool of orders corresponds to the multiple picking tasks, and the division into the batch(es) of task(s) + assigning to workstations corresponds to the sorting/sorting result.).
However, although Modified Li discloses the consideration of due dates/times, Modified Li does not explicitly disclose the latest start time or user manual picking takeover.
Nevertheless, Li Xuejun--who is directed towards goods picking task allocation methods--discloses: and in response to the latest start time for the picking tasks being reached (See at least ¶n0077 via "In some implementations, the priority of each picking task can be determined based on the current time and the latest outbound time of each picking task in the set. Each picking task has a "latest outbound time" attribute. In order to ensure that each picking task can be completed within the specified time, picking tasks that are closer to the latest outbound time need to be prioritized. It is understandable that the latest outbound time can be interpreted as the picking task not being able to be outbound later than this time. The picking task needs to be outbound before the latest outbound time, otherwise it will affect the delivery time." and ¶n0078 via "In step 302, the time difference m<sub>i</sub>0 between the current time and the latest departure time of the i-th picking task in the set can be calculated first, where i represents the number of each picking task in the set, i≥1 and i is an integer; for example: the latest departure time of the first picking task is 2020-05-13 12:00:00, the current time is 2020-05-13 10:00:00, then m<sub>1</sub> = 120 minutes…For example, the time difference m<sub>i</sub>≤0 can be compared with the emergency task time threshold P to determine the selection cost. The lower the selection cost, the higher the priority of the picking task. The emergency task time threshold P is a conditional parameter for judging whether the picking task is urgent. The value of the emergency task time threshold P can be set according to the actual outbound efficiency of the warehouse. The range of the emergency task time threshold P is P > 0." **Wherein the latest start time corresponds to the emergency task time threshold P)
and the picking tasks being not assigned to the picking robot, (See at least ¶n0068 via "2) Query the set of idle picking robots. If the number of idle picking robots is m; if m = 0, then proceed to step 3); if m ≥ n, then assign all picking tasks to n idle picking robots and end the current assignment process; if m < n, then assign m picking tasks to all idle picking robots and proceed to step 3).")
generating task prompt information corresponding to the picking tasks, and (See at least ¶n0076 via "the priority of each picking task can be understood as the execution order of each picking task. The higher the priority of a picking task, the earlier it will be executed. For example: There is currently only one available human picker, and there are two picking tasks, a and b. If picking task a has a higher priority, picking task a will be assigned first.")
(See at least ¶n0069 via "3) Query the set of available pickers, and let the number of available pickers be k; if k = 0, then end the process. If k ≥ n-m, then all picking tasks are assigned to n-m available pickers; if k < n-m, then k picking tasks are assigned to all available pickers, and the process ends." as well as ¶n0155 via "When picking robot resources are available, picking tasks should be prioritized for picking robots. When picking robot resources are unavailable, picking tasks that are more suitable for human picking should be prioritized for human pickers. This reduces the intensity of human labor, increases the utilization rate of robots, and improves work efficiency.")
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Modified Li to account for time deadlines for tasks such as in Li Xuejun in order to ensure that tasks/picks with a higher priority can be manually completed prior to the deadline to avoid delayed outbound delivery: " allocating picking tasks according to their priority, ensuring that urgent tasks can be processed first and reducing the risk of delayed outbound delivery." [Li Xuejun ¶n0052].
However, Modified Li does not explicitly disclose the displaying of the task prompt information to inform the user.
Nevertheless, Gruenstein--who is directed towards a robotic system--discloses: displaying the task prompt information, … inform a user (See at least Figure 3 and ¶0089 via " FIG. 3 illustrates an exemplary user interface 300 provided to a human worker, in accordance with some embodiments. The user interface 300 prompts the human worker to solve a task 310 (“Son Shapes Into Bins”)." [Sort shapes into bins] )
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Modified Li in view of Gruenstein's displaying to inform a user in order to provide a method to communicate information to a user when the user needs to perform a task, such as by showing both text and images on the display/interface: "the user interface 300 includes an image 312 depicting the objects to be sorted, and an image 314 depicting the bins that the objects need to be sorted into" [Gruenstein ¶0089].
Regarding Claim 18, Modified Li discloses the storage medium according to Claim 15.
Furthermore, Li discloses: after sorting the multiple picking tasks based on task association information corresponding to the picking tasks to obtain a task sorting result, the operation further comprising: (See at least Figure 2 and ¶0057-¶0059 via "In step S10, at least one pending order is received, and the at least one pending order is placed in an order pool…In step S20, part or all of the pending orders in the order pool are divided into at least one batch of task…In step S30, for any of the at least one batch of task, the batch of task is allocated to a corresponding target workstation" as well as ¶0072 via "the batch of task can be disbursed to the appropriate target workstations…Exemplarily, a warehouse management system on a warehouse server disburses the batch of tasks to corresponding target workstations according to parameters of order items in pending orders in each batch of task, such as name of the order item, manufacturer, information of the inventory container where the order item is located, the number of order items in each order, and the like" *Wherein the pool of orders corresponds to the multiple picking tasks, and the division into the batch(es) of task(s) + assigning to workstations corresponds to the sorting/sorting result.).
However, although Modified Li discloses the consideration of due dates/times, Modified Li does not explicitly disclose the latest start time or user manual picking takeover.
Nevertheless, Li Xuejun--who is directed towards goods picking task allocation methods--discloses: determining a latest start time for the picking robot to begin executing the picking tasks; and (See at least ¶n0077 via "In some implementations, the priority of each picking task can be determined based on the current time and the latest outbound time of each picking task in the set. Each picking task has a "latest outbound time" attribute. In order to ensure that each picking task can be completed within the specified time, picking tasks that are closer to the latest outbound time need to be prioritized. It is understandable that the latest outbound time can be interpreted as the picking task not being able to be outbound later than this time. The picking task needs to be outbound before the latest outbound time, otherwise it will affect the delivery time." and ¶n0078 via "In step 302, the time difference m<sub>i</sub>0 between the current time and the latest departure time of the i-th picking task in the set can be calculated first, where i represents the number of each picking task in the set, i≥1 and i is an integer; for example: the latest departure time of the first picking task is 2020-05-13 12:00:00, the current time is 2020-05-13 10:00:00, then m<sub>1</sub> = 120 minutes…For example, the time difference m<sub>i</sub>≤0 can be compared with the emergency task time threshold P to determine the selection cost. The lower the selection cost, the higher the priority of the picking task. The emergency task time threshold P is a conditional parameter for judging whether the picking task is urgent. The value of the emergency task time threshold P can be set according to the actual outbound efficiency of the warehouse. The range of the emergency task time threshold P is P > 0." **Wherein determining the latest start time corresponds to the current time and the emergency task time threshold P)
being not assigned to the picking robot, (See at least ¶n0068 via "2) Query the set of idle picking robots. If the number of idle picking robots is m; if m = 0, then proceed to step 3); if m ≥ n, then assign all picking tasks to n idle picking robots and end the current assignment process; if m < n, then assign m picking tasks to all idle picking robots and proceed to step 3).")
generating task prompt information corresponding to the picking tasks, and (See at least ¶n0069 via "3) Query the set of available pickers, and let the number of available pickers be k; if k = 0, then end the process. If k ≥ n-m, then all picking tasks are assigned to n-m available pickers; if k < n-m, then k picking tasks are assigned to all available pickers, and the process ends." as well as ¶n0155 via "When picking robot resources are available, picking tasks should be prioritized for picking robots. When picking robot resources are unavailable, picking tasks that are more suitable for human picking should be prioritized for human pickers. This reduces the intensity of human labor, increases the utilization rate of robots, and improves work efficiency.")
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Modified Li to account for time deadlines for tasks such as in Li Xuejun in order to ensure that tasks/picks with a higher priority can be manually completed prior to the deadline to avoid delayed outbound delivery: " allocating picking tasks according to their priority, ensuring that urgent tasks can be processed first and reducing the risk of delayed outbound delivery." [Li Xuejun ¶n0052].
However, Modified Li does not explicitly disclose the displaying of the task prompt information to inform the user.
Nevertheless, Gruenstein--who is directed towards a robotic system--discloses: displaying the task prompt information, … inform a user (See at least Figure 3 and ¶0089 via " FIG. 3 illustrates an exemplary user interface 300 provided to a human worker, in accordance with some embodiments. The user interface 300 prompts the human worker to solve a task 310 (“Son Shapes Into Bins”)." [Sort shapes into bins]).
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Modified Li in view of Gruenstein's displaying to inform a user in order to provide a method to communicate information to a user when the user needs to perform a task, such as by showing both text and images on the display/interface: "the user interface 300 includes an image 312 depicting the objects to be sorted, and an image 314 depicting the bins that the objects need to be sorted into" [Gruenstein ¶0089].
Claims 5, 12, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Li et. al. (US 20200302391 A1), Leonardo et. al. (US 20230022085 A1), and Lert, JR et. al. (US 20180194556 A1), Li Xuejun. (CN113762664A, Translation Previously Attached in Non-Final dated 04/16/2026), and Gruenstein et. al. (US 20240131712 A1) in view of Norman (US 20160103713 A1).
Regarding Claims 5, 12, and 19 respectively, Modified Li discloses the method for scheduling picking robots according to Claim 4, the electronic device according to Claim 11, and the storage medium according to Claim 18.
Furthermore, Li Xuejun discloses: a latest start time (See at least ¶n0077, ¶n0078 via "…For example, the time difference m<sub>i</sub>≤0 can be compared with the emergency task time threshold P to determine the selection cost. The lower the selection cost, the higher the priority of the picking task. The emergency task time threshold P is a conditional parameter for judging whether the picking task is urgent. The value of the emergency task time threshold P can be set according to the actual outbound efficiency of the warehouse. The range of the emergency task time threshold P is P > 0." **Wherein determining the latest start time corresponds to the current time and the emergency task time threshold P).
However, Li Xuejun does not explicitly disclose the specific determination of the latest start time from the latest completion time and the picking execution time.
Nevertheless, Norman--who is directed towards a method for sequencing a plurality of tasks performed by a processing system--discloses: wherein determining a latest start time for the picking robot to begin executing the picking tasks comprises: determining a latest completion time for the picking tasks and a picking execution time for the picking robot; and determining the latest start time for the picking robot to begin executing the picking tasks based on the latest completion time and the picking execution time (See at least ¶0041 via " Each task in the plurality of tasks is assigned an earliest start time (EST) and a latest start time (LST). An EST is the earliest time a task may be scheduled on a station. Similarly, an LST is the latest time that a task may be scheduled on a station. Accordingly, each task in the plurality of tasks also has an earliest end time (EET) and a latest end time (LET) corresponding to the earliest start time (EST) and the latest start time (LST), respectively…The LET is the latest time that a task could be completed. The LET typically is the LST plus the duration of the task being processed." **Wherein if the Latest End Time = Latest Start Time + Duration of the task, then the Latest Start Time = Latest End Time - Duration of the Task)
Therefore, it would have been obvious to one ordinary skill in the art prior to the effective filing date of the given invention to modify Modified Li in view of Norman's Latest Start Time, Latest End Time, and Task Duration in order to effectively sequence tasks, for example, in a case where two tasks can not be performed at the same time and the second must start after the first is completed: "If a queue time limit exists between the first task and the second task, then the LST.sub.2 is the LET.sub.1 plus the duration of the queue time limit. If a queue time limit does not exist between the first task and the second task, then the LST.sub.2 may be any time after the LET.sub.1." [Norman ¶0041].
Claims 6, 13, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Li et. al. (US 20200302391 A1), Leonardo et. al. (US 20230022085 A1), and Lert, JR et. al. (US 20180194556 A1) in view of Raizer et. al. (US 20200324970 A1).
Regarding Claims 6, 13, and 20 respectively, Modified Li discloses the method for scheduling picking robots according to Claim 1, the electronic device according to Claim 8, and the storage medium according to Claim 15.
Furthermore, Li discloses: wherein scheduling the picking robot to execute the picking tasks according to a working stage of the picking robot and the task sorting result comprises: (See at least Figure 2 and ¶0057-¶0059 via "In step S10, at least one pending order is received, and the at least one pending order is placed in an order pool…In step S20, part or all of the pending orders in the order pool are divided into at least one batch of task…In step S30, for any of the at least one batch of task, the batch of task is allocated to a corresponding target workstation" as well as ¶0072 via "the batch of task can be disbursed to the appropriate target workstations…Exemplarily, a warehouse management system on a warehouse server disburses the batch of tasks to corresponding target workstations according to parameters of order items in pending orders in each batch of task, such as name of the order item, manufacturer, information of the inventory container where the order item is located, the number of order items in each order, and the like" *Wherein the pool of orders corresponds to the multiple picking tasks, and the division into the batch(es) of task(s) + assigning to workstations corresponds to the sorting/sorting result.).
scheduling the picking robot to execute the picking tasks according to the (See at least ¶0074 via Step S140 as well as ¶0077 via " A robot whose navigation distance does not exceed a distance threshold is found at least partly based on the position information of the target workstation" and ¶0079 via "According to the robot scheduling algorithm, the robot scheduling system software of the warehouse server is used for determining the navigation path, and the robot which is currently in the idle state and has the shortest moving distance for carrying the inventory container is scheduled preferentially, which can reduce the navigation time of the robot for carrying the inventory container and further help to improve the picking efficiency")
However, although Modified Li discloses the consideration of energy costs (See Leonardo ¶0045), Modified Li does not explicitly disclose the energy storage information.
Nevertheless, Raizer--who is directed towards energy consumption prediction--discloses: in the presence of the multiple picking robots, individually determining energy storage information for each picking robot, the energy storage information comprising at least one of battery information or information of containers being carried; and (See at least ¶0132 via "Information of the current battery state, i.e. charge status and age, of the battery/batteries on board each robot is stored in a current power state database 224 in RTTM 146. The current power state database 224 is continuously or frequently updated by the onboard computers of the individual robots in the warehouse. A current state algorithm 226 draws data from the current power state database 224 and compares the current power states of all of the robots to determine which of the available robots, i.e. which of the robots that isn't presently engaged in performing another task, at a battery charging station, or undergoing maintenance, is most suitable to carry out the task based on the available power in its batteries. The identity of the preferred robot for carrying out the transaction 228 is sent to the task assignment algorithm 230.").
Therefore it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the given invention to modify Modified Li in view of Raizer's consideration for scheduling/allocating robots based on their battery status in order to more efficiently allocate robots to tasks based on the consideration of how charged they are in comparison to each other: "Task assignment algorithm 232 is designed to take an overall view of the entire system with its main objective to operate the system with maximum efficiency and minimum cost" [Raizer ¶0136].
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/K.R.D./Examiner, Art Unit 3657 /ABBY LIN/Supervisory Patent Examiner, Art Unit 3657
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