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 .
Status of Claims
Applicant's submission filed on 11/25/25 has been entered. Claims 4, 10, 14-20 are cancelled. Claims 21-23 are new. Claims 1-3, 5-9, 11-13, 21-23 are presented for examination.
Claim Rejections - 35 USC § 101
The Examiner is in agreement with Applicant’s remarks dated 11/25/25, regarding patent eligibility. The amendments, in view of the remarks, render the claims eligible. Therefore, the rejection under 35 U.S.C. 101 is withdrawn.
Claim Rejections - 35 USC § 103
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, 8, 9, 11, 21, 22, 23 are rejected under 35 U.S.C. 103 as being unpatentable over FRANEY et al. (US 20220237530 A1), in view of GRUNDBERG (WO 2016190805 A1), in view of Ebrahimi et al. (US11340079).
Re-claims 1, 21, FRANEY (‘530) teaches --- A computer system for generating paths to items in a retail store, the method comprising:
(see e.g. [0013] A system can generate a pick path indicating a plurality of locations (e.g., within a store or warehouse) for a device (e.g., enhanced cart, robotic device to find and select one or more products included in a listing (e.g., pick list, customer's list, grocery list, shopping list).
--receiving a request from a mobile computing device, the request indicative of a plurality of items and a current location of the mobile computing device;
(see e.g. [0059] The pick path 310 can be generated, for example, in response to a request (e.g., listing) from a customer for one or more products available at a warehouse)
[0014] The system can choose from options for available products based in part on a distance from a current location of the device, the original product location, or a location of each available product to one or more product locations indicated in the path.
Note: The Examiner notes FRANEY et al. {‘530) does not explicitly teach the current location of the client device is included in the request. However, it is considered an obvious variation of FRANEY et al. (‘530), since FRANEY et al. {‘530) teach determining the current location of the client device, which is used to determine the pick pack leading to the item location.
--identifying, for each respective item of the plurality of items, one or more locations within the retail store corresponding to the respective item based on inventory data, wherein each of the one or more locations comprises a physical location within the retail store;
[0103] A system can generate a pick path indicating a plurality of locations (e.g., within a store or warehouse) for a device (e.g., enhanced cart, robotic device) to find and select one or more products included in a listing (e.g., pick list, customer's list, grocery list, shopping list). The path can include a plurality of tasks or units of work, and each task can identify at least one product and a location for the respective product. The products can be located, for example, at a warehouse, fulfillment centre, retail location, or other forms of facilities or shopping centers.
--selecting, for each respective item of the plurality of items, a best location of the one or more locations corresponding to the respective item based on a priority associated with each location of the one or more locations;
(see e.g. [0035] In some embodiments, the device 126 can receive instructions 142 to provide a path 144 to a picker 128, user, customer 172 or buyer. The instructions 142 can indicate the path 144 (e.g., route, pick path), location data 146 identifying one or more locations (e.g., pick locations) and/or one or more products.
[0050] The pick path 208 can include or correspond to an original or initial path 208 generated based on the locations 240 of the originally requested products 244 within the warehouse 204. The pick path 208 can provide a route through the warehouse 204 for a device 260 to follow to select or retrieve the corresponding products 244. In some embodiments, the pick path 208 can correspond to a minimal or smallest total distance for the device 260 to travel through the warehouse 204 to select and/or retrieve the products 244 from the different locations 204 within the warehouse 204.
--determining a route that starts at the current location of the mobile computing device and includes the best location for each respective item of the plurality of items; and
(see e.g. [0014] The system can choose from options for available products based in part on a distance from a current location of the device, the original product location, or a location of each available product to one or more product locations indicated in the path.
[0051] The pick path 208 can include a starting point 212 and an end point 214 with each of the pick locations 240 at different points along the path 208.)
--transmitting the route to the mobile computing device for display by its graphical mapping application.
(see e.g. [0013] In some embodiments, the system can transmit instructions for the path such that tasks are displayed in sequential order through an interface of the device for a user (e.g., picker) using the device to collect one or more products.).
FRANEY et al. do not teach the following limitations as claimed.
However, GRUNDBERG teaches ---
--a local positioning system comprising a plurality of beacons installed in the retail store
a plurality of mobile computing devices, each mobile computing device being configured to (i) determine its respective current location within the retail store using the local positioning system, based on a relative position between the mobile computing device and one or more beacons of the plurality of beacons, and
(see e.g. page 14, lines 28-33 --The positioning of the terminal may be carried out by using any type of positioning, motion detection and identification of the location allowed by the terminal, e.g. GPS, GLONASS, triangulation, optical, IR, pedometer, compass, gyro sensors etc. or a combination thereof. In a store for example, RF beacons may be used for data exchange and positioning. Wi-Fi or Bluetooth access points/transceivers may also be used for identification and positioning of the terminal location.)
(see e.g. page 13, lines 8-9 --Terminal 104 may display information associated with route viewed by a user of terminal 104 in a graphical format.
(see e.g. page 12, lines 22-26 --If one has access to a limited map, one can also use this limited data to influence the outcome of the graph. For example, if a rough/schematic map is available displaying the placement of certain grocery categories in the store or if there are dedicated locations for items from different grocery categories but with similar special properties such as raw, ecological, fair trade etc.)
wherein determining the route comprises:
for each pair of best locations for the plurality of items, (i) identifying a pair of nodes in the graph representation that correspond to the pair of best locations, and (ii) executing a pathfinding algorithm to identify a path between the pair of nodes in the graph representation having a smallest cost;
(see e.g. page 2, lines 28-32 --The method may further comprise: for each area, building an undirected graph in which each location for an item is realized as node, and each pair of nodes that probably is closest to each other has an edge between them with a length that varies with the probability that they are closest to each other;
page 4, lines 10-14 -In one embodiment, if edges are disregarded, the graph is partitioned, for each pair of nodes, where nodes are in different partitions, calculating a distance between the nodes in the following manner: nAyB
y=o y=o
wherein y is the number of items picked between A and B, and n is the number of occurrences of a location.
Page 12, lines 15-18 --Between the nodes having the shortest distance, edges are then formed having length equal to the calculated distance. One can choose to form edges between just a couple of nodes or several pairs. Of course, there are several other possible methods to connect the partitions.
Page 12, lines 1-4 --For each pair of locations calculate a distance between them as the inverse of the probability. The distances between the locations then form the length of the edges in an undirected graph where the locations are nodes.
Page 10, lines15-16; 24-25 The solution of the TSP-problem, produced by using, e.g. a k- opt-algorithm, may then be used to optimize the sorting of the items in the list.
The algorithm for building the graph of locations in an area is based on analysis of previous outcomes of pick lists in one area.)
*****NOTE: According to Google: A k-opt algorithm is a heuristic method for the Traveling Salesman Problem (TSP) that iteratively improves a tour by replacing up to k edges with a different set of k edges, leading to a shorter overall tour. )
GRUNDBERG also teaches
--transmitting the route to the client mobile computing device for display by its graphical mapping application.
(see e.g. claim 1 -- • providing a user terminal with resulted route;
page 13, lines 8-9 Terminal 104 may display information associated with route viewed by a user of terminal 104 in a graphical format.)
claim 21. The computer system of claim 1, wherein the plurality of beacons comprise radio beacons.
(see e.g. page 14, lines 28-33 -- RF beacons may be used for data exchange and positioning.)
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify FRANEY (‘530), and include the steps cited above, as taught by GRUNDBERG, in order to provide a dynamic system for optimizing route/list (see e.g. page 2, line 4).
FRANEY et al., in view of GRUNDBERG, do not teach the following limitations as claimed.
However, Ebrahimi et al. teach --
a mapping system of the retail store, comprising one or more data processing apparatuses including one or more processors, memory, and storage devices storing instructions that, when executed, cause the one or more processors to perform operations comprising:
based on predetermined map data associated with the retail store, generating a matrix representation of the retail store that defines accessible areas and obstacles within the retail store; based on the matrix representation of the retail store, generating a graph representation of the retail store, wherein each vertex of the graph represents and obstacle corner, and each edge represents an immediate connection between a pair of obstacle corners;
(see e.g. col. 33, lines 54-63--In some embodiments, the processor represents the environment using a coordinate map including a collection of cells, and zones may have the form of any connected component on the coordinate map. In such embodiments, the coordinate map of the environment is represented using a matrix wherein each entry corresponds to a coordinate cell of the environment and zones may be represented using a matrix corresponding to a portion of the coordinate cells of the environment.
col. 23, lines 35-41 --In some embodiments, the processor uses the constructed map to autonomously navigate the environment during operation, e.g., accessing the map to determine that a candidate movement path is blocked by an obstacle denoted in the map, to select a movement path with a movement path-finding algorithm from a current point to a target point, or the like. )
(see e.g. -col. 34, lines 57-64 -- To do so, in some embodiments, the environment is represented by a grid map and divided into zones by the processor. In some embodiments, the processor converts the grid map into a routing graph G consisting of nodes N connected by edges E. The processor represents a zone A using a set of nodes of the routing graph wherein A⊂N. The nodes are connected and represent an area on the grid map. ----For instance, some embodiments may determine a Euclidean Steiner tree with Steiner vertices that define zone corners and correspond to obstacles. )
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify FRANEY (‘530), in view of GRUNDBERG, and include the steps cited above, as taught by Ebrahimi et al., because by generating a map for a user/robot of their immediate surroundings as they operate to navigate from a current location to a final destination, obstacles are avoided, while travelling to the final destination (see e.g. Ebrahimi et al.).
Re-claims 8, 9, FRANEY et al. (‘530) do not teach the limitations as claimed.
However, GRUNDBERG teaches --the computer system of claim 1, wherein determining the route that includes the best location for each respective item of the plurality of items comprises:
--determining an approximately shortest route by inputting all of the paths between the pairs of best locations to a heuristic algorithm.
(see e.g. Page 12, lines 1-4 ---For each pair of locations calculate a distance between them as the inverse of the probability. The distances between the locations then form the length of the edges in an undirected graph where the locations are nodes.
Page 10, lines15-16; 24-25 The solution of the TSP-problem, produced by using, e.g. a k- opt-algorithm, may then be used to optimize the sorting of the items in the list.
The algorithm for building the graph of locations in an area is based on analysis of previous outcomes of pick lists in one area.
NOTE: According to Google: A k-opt algorithm is a heuristic method for the Traveling Salesman Problem (TSP) that iteratively improves a tour by replacing up to k edges with a different set of k edges, leading to a shorter overall tour.
(9) The computer system of claim 8, wherein: -- the pathfinding algorithm is an A* pathfinding algorithm; and --the heuristic algorithm is a traveling salesman problem algorithm.
(see e.g. page 3 , lines 1-2-- In ONE embodiment the optimization problem is a Travelling Salesman Problem (TSP).
Page 10, lines 12-17--When sorting by a pick list, solve a Traveling Salesman Problem (TSP) (or the like) in the aforementioned graph with an algorithm that takes into account both using probabilities and providing a solution, individually tailored for the user under the preceding step. The solution of the TSP-problem, produced by using, e.g. a k- opt-algorithm, may then be used to optimize the sorting of the items in the list.
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify FRANEY (‘530), and include the steps cited above, as taught by GRUNDBERG, in order to provide a dynamic system for optimizing route/list (see e.g. page 2, line 4).
Re-claim 11, FRANEY et al., in view of GRUNDBERG, do not teach the limitations as claimed.
However, Ebrahimi et al. teach --The computer system of claim 1, wherein generating the graph representation of the retail store comprises assigning to each edge of the graph a weight indicative of a walkable distance between the pair of obstacle corners.
(see e.g. col. 70, lines 5-17--In some embodiments, the processor assigns each edge a weight corresponding to the length of the edge. In some embodiments, the processor computes the next driving action of a robotic device navigating from a first location to a second location by determining the shortest path in the directed, weighted graph. In other embodiments, the weight assigned to an edge depends on one or more other variables such as, traffic within close proximity of the edge, obstacle density within close proximity of the edge, road conditions, number of available charged robotic devices within close proximity of the edge, number of robotic devices with whom linking is possible within close proximity of the edge, etc.)
The Examiner notes Ebrahimi et al. teach minimizing travel distance between zones. The travel distance may be applied to a distance covered by a robot or human (walking distance). Thus, the simple substitution of one known element for another producing a predictable result renders the claim obvious. (see e.g. KSR Rationale B).
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify FRANEY (‘530), in view of GRUNDBERG, and include the steps cited above, as taught by Ebrahimi et al., because by generating a map for a user/robot of their immediate surroundings as they operate to navigate from a current location to a final destination, obstacles are avoided, while travelling to the final destination (see e.g. Ebrahimi et al.).
Re-claim 22, “The computer system of claim 1, wherein the plurality of beacons comprise visible light beacons. “ , FRANEY et al. (‘530) teach “The path 144 can include a plurality of data structures corresponding to each location and include coordinates (e.g., global positioning systems (GPS) data), beacon signal data or other forms of signal data to identify a particular location within a warehouse or environment.”. Therefore, it is considered an obvious variation of FRANEY et al. (‘530) since FRANEY et al. (‘530) anticipates other forms of signal data to identify a particular location within a warehouse or environment.
Re-claim 23, FRANEY et al. (‘530), in view of GRUNDBERG, do not teach the limitations as claimed.
However, Ebrahimi et al. teach --The computer system of claim 1, wherein the matrix representation is embodied as a grid of cells, with each cell in the grid of cells representing a physical location within the retail store, and with a value of each cell indicating whether the physical location is part of an obstacle or is a walkable space.
(see e.g. col. 8, lines 47-52-- As a further example, consider the environment of robotic excavators K and L represented by a grid world and described by a m×n matrix G comprising all state spaces available to the robotic excavators. In a two-dimensional world, each entry of the matrix may represent a cell of the grid world and have a value (x,y).
see e.g. col 15, lines 48-53 ---In another embodiment, the environment is represented by a matrix, wherein every cell within the matrix is a coordinate representing an area within the environment. Other suitable forms of representing the environment are used in other cases.
col 33, lines 64- 67 --In some embodiments, the processor represents the environment using a coordinate map including a collection of cells, and zones may have the form of any connected component on the coordinate map. In such embodiments, the coordinate map of the environment is represented using a matrix wherein each entry corresponds to a coordinate cell of the environment and zones may be represented using a matrix corresponding to a portion of the coordinate cells of the environment. In some embodiments, each cell of the environment can only belong to a single zone, overlap between zones is avoided by construction. Entries in the matrices of zones may have a value of zero if the corresponding cell of the environment is empty or may have a value of one if the cell is occupied by, for example, a wall or building or static object.
col 34, lines 45-50 --In some embodiments, the processor determines optimal division of zones of an environment by modeling zones as emulsions of liquid, such as bubbles. For instance, some embodiments may determine a Euclidean Steiner tree with Steiner vertices that define zone corners and correspond to obstacles
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify FRANEY (‘530), in view of GRUNDBERG, and include the steps cited above, as taught by Ebrahimi et al., in order to avoid obstacles while travelling to the final destination (see e.g. col. 1, line 60).
Claims 2, 3 are rejected under 35 U.S.C. 103 as being unpatentable over FRANEY et al. (US 20220237530 A1), in view of GRUNDBERG (WO 2016190805 A1), in view of Ebrahimi et al. (US11340079), in further view of Field-Darragh et al. (US 20140279294 A1)
Re-claims 2, 3, FRANEY et al. (‘530), in view of GRUNDBERG, in further view of Ebrahimi, do not teach the limitations as claimed.
However, Field-Darragh et al. teach --The computer system of claim 1, wherein selecting the best location based on the priority comprises determining whether each location is located within a back room of the retail store or a sales floor of the retail store.
(see e.g. [0051] The item or items may be located in a warehouse or in a physical store.
[0014] What is desired are a system and methods for enabling efficient fulfillment of an order placed by a customer either on-line or in-store, where the item may be located in one of one or more physical stores or warehouses.
[0016] In some embodiments, the inventive system and methods include elements that enable a determination of the location of a specific item within a physical space (such as a store). The location may be determined relative to another item or structure whose location is known, thereby providing a reference location.)
3. The computer system of claim 2, wherein selecting the best location based on priority further comprises determining relative accessibility of each location.
(see e.g. TABLE-US-00002 Some locations will be easier to pick from and therefore we can increase our confidence that we will be able to successfully fulfill an item Item arrives at a location which reduces its Confidence - X confidence score Some locations will be harder to pick from and therefore we decrease our confidence that we will be able to successfully fulfill an item
[0236] If desired, may display just the areas with the highest confidence score. For a customer facing implementation (as opposed to a store employee/picker) may display just the locations that are customer accessible.
[0059] This embodiment of the invention might also be of value in a warehouse where items are stored in areas that are difficult to reach or scan. In such a case, being able to scan a single tag instead of multiple tags would reduce the data collection time and effort.)
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify FRANEY et al. (‘530), in view of GRUNDBERG, in further view of Ebrahimi, and include the steps cited above, as taught by Field-Darragh et al., this way the workload placed on each picker at any time may be adjusted or re-balanced in accordance with one or more factors related to the current environment of the store or warehouse (see e.g.[0191] ).
Claims 5, 6, 7 are rejected under 35 U.S.C. 103 as being unpatentable over FRANEY et al. (US 20220237530 A1), in view of GRUNDBERG (WO 2016190805 A1), in view of Ebrahimi et al. (US11340079), in further view of FRANEY et al. (2022/0371626 A1) .
Re-claim 5, FRANEY et al. (‘530) teaches that the substitute product at the alternate location is the desired product.
(see e.g. [0014] The notification can indicate that the product is missing, unavailable at the indicated location, a damaged item (e.g., item on shelf is damaged and not available to fulfill an order) and/or that no inventory exists for the desired product at one or more alternate locations. ----The substitute product can include a product in the same product class, a requested product but in a different storage location)
FRANEY et al. (‘530), in view of GRUNDBERG, in further view of Ebrahimi, do not teach the limitations as claimed.
However, FRANEY et al. (‘626) explicitly teaches --The computer system of claim 1, the operations further comprising:
- receiving an update from the mobile computing device in response to transmitting the route, the update indicative of a first item of the plurality of items being unavailable at a first location and an updated location of the mobile computing device;
(see e.g. [0073] [0074] The analytics server may receive the input from a picker or the autonomous vehicle. The picker may identify a product short such that the analytics server receives an input from the picker indicating the shorted product. The picker can input the short into a handheld computer, wrist computer or wearable computer, or other electronic device in communication with the autonomous vehicle and/or the server. The picker may input into the autonomous vehicle that a product was not obtained, and the autonomous vehicle may transmit a notification or other data indicating that the product was a short.
[0039] The autonomous vehicle 106 can execute the instructions and traverse the pick path 128 selecting and retrieving the corresponding products 144 from the respective locations 113. In some embodiments, a second product 144 may be unavailable at the second location 113. For example, the autonomous vehicle 106 can determine that the second product 144 included in pick path 128 is not at the indicated second location 113 (e.g., the product shorted). A product may short if the product is sold out, stock depleted, damaged, or otherwise not available for a customer at an expected product location (e.g., the second location 113). If the product is shorted, the autonomous vehicle 106 (or picker) may transmit a notification or otherwise inform a server (e.g., the analytics server 122) of the shorted product. The warehouse 102 may store the product at other locations 113 such that the autonomous vehicle 106 can attempt to cure the shorted order at an alternate location 113.
[0081] The analytics server may determine the one alternate pick location based on the alternate pick location closest to the current location of the autonomous vehicle or some other factor.)
-- identifying, for the first item, one or more remaining locations within the retail store corresponding to the first item in response to receiving the update, wherein the one or more remaining locations do not include the first location;
(see e.g. [0044] The analytics server 122 can generate instructions to revise the pick path 128 to include the alternate pick locations for the products 144 in the revised pick path 128. While the autonomous vehicle 106 travels along the pick path 128 collecting the remaining products 144, the analytics server 122 can dynamically revise the pick path 128 to incorporate the alternate pick location based on the completion scores, the priorities of the orders, and/or the time associated with re-routing the autonomous vehicle 106. The analytics server 122 can transmit instructions for the revised path 128 to the autonomous vehicle 106. In some embodiments, the autonomous vehicle 106 can dynamically update, using the instructions, the display of the revised pick path 128 to include the alternate pick location, for example, for a picker 112 traversing the pick path 128 with the autonomous vehicle 106. The revised pick path 128 can include the alternate pick location as a next location 113 in the revised pick path 128 or as a future location 113 in the revised pick path 128. )
The Examiner notes the alternate location obviously does not include the first location since the notification of the product shorted is sent while the picker is at the first location and the picker has to travel to the alternate location.
--selecting a best location of the one or more remaining locations based on the priority associated with each location of the one or more remaining locations;
(see e.g. [0081] For example, the analytics server may compute the second completion score for one alternate pick location out of the four alternate pick locations received. The analytics server may determine the one alternate pick location based on the alternate pick location closest to the current location of the autonomous vehicle or some other factor.
[0082] The analytics server may compute the second completion score according to the same factors (e.g., number of picks left for the order, the amount of inventory existing at a particular location in a warehouse and an amount of inventory required for the order, the status of other containers associated with the order).
[0083]-[0084] The analytics server may also compute a completion score associated with each alternate pick location. For example, the completion score associated with an alternate pick location may be based on the amount of inventory existing at the alternate pick location in the warehouse and an amount of inventory required for the order.
--determining an updated route that starts at the updated location of the mobile computing device and includes the best location of the one or more remaining locations; and
(see e.g. [0091] the analytics server may, for example, transmit instructions for re-routing the autonomous vehicle using a revised pick path that includes the alternate pick location.)
--transmitting the updated route to the mobile computing device for display by its graphical mapping application.
(see e.g. [091] In operation 312, in response to the first completion score being less than the second completion score, the analytics server may, for example, transmit instructions for re-routing the autonomous vehicle using a revised pick path that includes the alternate pick location.
[0105] transmitting, by the computer to the autonomous vehicle, instructions configured to re-route the autonomous vehicle using the revised pick path.)
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to FRANEY et al. (‘530), in view of GRUNDBERG, in further view of Ebrahimi, and include the steps cited above, as taught by FRANEY et al. (‘626), in order to attempt to fulfill the shorted product (see e.g.[0089] ).
Re-claim 6, FRANEY et al. (‘530) teaches -- the computer system of claim 5, the operations further comprising: determining whether the updated location of the mobile computing device is within a predetermined distance of the first location; wherein transmitting the updated route comprises transmitting the updated route in response to determining that the updated location is within the predetermined distance.
(see e.g. [0014] While a device is along the path collecting the products, the system can dynamically revise the path to incorporate the selected, available product based on the distance of the selected, available product from the original path. --. The system can transmit instructions for the revised path to include the location for the available product. In some embodiments, the system can dynamically update (e.g., as the device is actively executing the instructions for the path) the path to include the location for the available product. The revised path may include the available product as the next task in the path or as a future task in the path.)
Re-claim 7, FRANEY et al. (‘530) teaches --The computer system of claim 5, the operations further comprising: determining, for the first item, that no remaining locations within the retail store correspond to the first item in response to receiving the update; and
(see e.g. [0052] The device 260 can generate and provide the notification 202 indicating that the product 244 is unavailable or otherwise unable to be selected at the warehouse 204 or update a status of the respective product 244 in an inventory database maintained at the device 260 using the notification 202. The notification 202 can indicate that the product 244 is missing, unavailable at the indicated location 240, and/or that no inventory exists for the desired product 244 at one or more alternate locations 240.
-requesting an inventory audit in response to determining that no remaining locations correspond to the first item.
(see e.g. [0069] [0070] In some embodiments, the device can receive the notification from an inventory database or inventory management system indicating an interruption (e.g., unable to satisfy a task due to missing product) associated with at least one product included in the listing. The inventory database may determine that the product was recently taken from the location (e.g., collected by a different device, picker, or customer), purchased or otherwise removed from the location prior to the device reaching the location of the product. )
Claims 12, 13 are rejected under 35 U.S.C. 103 as being unpatentable over FRANEY et al. (US 20220237530 A1), in view of GRUNDBERG (WO 2016190805 A1), in view of Ebrahimi et al. (US11340079), in further view of Li (CN114519448A).
Re-claims 12, 13, FRANEY et al. (‘530), in view of GRUNDBERG, in view of Ebrahimi et al., do not teach the limitations as claimed.
However, Li teaches --The computer system of claim 1, wherein generating the graph representation of the retail store comprises assigning to each edge of the graph a weight indicative of an estimated walking time between the pair of obstacle corners,
13. The computer system of claim 1, wherein generating the graph representation of the retail store comprises assigning to each edge of the graph a weight indicative of an estimated walking time based on average walking speed associated with an area associated with the edge of the graph.
(see e.g. Let us consider a traversal technique from a start node to an end node. In this technique, two immediate neighbors of the starting node, node a and node B, are considered and their edge weights may indicate the time that it may take for the robot to traverse from one node to another. For example, the edge weight of the start node to node a may be 1, and the edge weight of the start node to node B may be 2. Thus, the greater the value of the edge weight, this may indicate the longer it takes for the robot to traverse from one node to another. Thus, the robot may arrive at node B from the start node for a longer time than at node a, as depicted in fig. 3 (F).
--Considering a robot, it takes a certain amount of time to move from one node to another. Time may be calculated based on how long an edge is and how fast the robot moves from the starting node to the ending node.--
-- The options available to the system are to move the robot faster or slower or to move the robot or detour around to avoid obstacles.
Li does not explicitly teach a back room and a retail store , but teaches “the greater the value of the edge weight, this may indicate the longer it takes for the robot to traverse from one node to another”.
Therefore, the following limitation is considered an obvious variation of Li.: wherein edges within a back room area of the retail store have a slower estimated walking rate than edges within a sales floor area of the retail store.
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify FRANEY (‘530), in view of GRUNDBERG, in view of Ebrahimi et al., and include the steps cited above, as taught by Li , in order to plan an optimal route by moving around to avoid obstacles (see e.g. Li).
Response to Arguments
Applicant's arguments filed 11/25/25 have been fully considered but they are not persuasive. Applicant argued that the claims are allowable as amended. However, the Examiner disagrees based on the rejection above..
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Chachek et al. (US 20200302510 A1) -- System, Device, And Method Of Augmented Reality Based Mapping Of A Venue And Navigation Within A Venue.
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
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/LUNA CHAMPAGNE/Primary Examiner, Art Unit 3627
March 11, 2026