DETAILED ACTION
The following is a Non-Final, First Office Action on the Merits in response to communications filed June 27, 2024. Currently, claims 1–20 are pending.
Claim Objections
Claims 2–3 and 16–17 are objected to because of the following informalities:
Claims 2–3 and 16–17 recite “the assignment” in lines 1, 2, 1, and 2, respectively. However, claims 1 and 15, from which claims 2–3 and 16–17 depend, previously recite “generating … at least one assignment”. In view of claims 1 and 15, Examiner recommends amending claims 2–3 and 16–17 to recite “the at least one assignment” in order to avoid issues of clarity under 35 U.S.C. 112(b).
Appropriate correction is required.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1–20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites “the requests from the set of requests” in the element reciting “generating … a set of clusters”. There is insufficient antecedent basis for this limitation in the claim.
For purposes of examination, claim 1 is interpreted as reciting “[[the]] requests from the set of requests” in the element reciting “generating … a set of clusters”.
Claim 1 recites “the cluster” in the element reciting “processing … each cluster”. Although claim 1 previously recites “each cluster of the set of clusters”, there is insufficient antecedent basis for “the cluster” in the claim.
For purposes of examination, claim 1 is interpreted as reciting “[[the]] a cluster” in the element reciting “processing … each cluster”.
Claim 1 recites “the requests remaining in the cluster” and “the request remaining in the cluster” in the element reciting “processing the requests remaining in the cluster”. There is insufficient antecedent basis for these limitations in the claim.
For purposes of examination, claim 1 is interpreted as reciting “processing [[the]] requests remaining in the cluster … to identify a highest priority request from the requests remaining in the cluster”.
Finally, claim 1 recites “the item” in line 5 of the element reciting “generating … at least one of an estimated amount of time or an estimated distance”. There is insufficient antecedent basis for this limitation in the claim.
For purposes of examination, claim 1 is interpreted as reciting “[[the]] an item” in line 5 of the element reciting “generating … at least one of an estimated amount of time or an estimated distance”.
In view of the above, claim 1 is rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Claims 2–8, which depend from claim 1, inherit the deficiencies described above. As a result, claims 2–8 are similarly rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Claim 6 recites the term “certain” in the element reciting “a certain capability”. The term “certain” is a relative term which renders the claim indefinite. The term “certain” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
For purposes of examination, claim 6 is interpreted as reciting “a
Claim 9 recites “the requests from the set of requests” in the element reciting “generating … a cluster of requests”. There is insufficient antecedent basis for this limitation in the claim.
For purposes of examination, claim 9 is interpreted as reciting “[[the]] requests from the set of requests” in the element reciting “generating … a cluster of requests”.
Claim 9 recites “the requests remaining in the cluster” in the element reciting “processing the requests remaining in the cluster”. There is insufficient antecedent basis for this limitation in the claim.
For purposes of examination, claim 9 is interpreted as reciting “processing [[the]] requests remaining in the cluster”.
Claim 9 recites “the item” in line 6 of the element reciting “generating … at least one of an estimated amount of time or an estimated distance”. There is insufficient antecedent basis for this limitation in the claim.
For purposes of examination, claim 9 is interpreted as reciting “[[the]] an item” in line 6 of the element reciting “generating … at least one of an estimated amount of time or an estimated distance”.
In view of the above, claim 9 is rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Claims 10–14, which depend from claim 9, inherit the deficiencies described above. As a result, claims 10–14 are similarly rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Claim 11 recites “the current location” and “the resource” in line 3. There is insufficient antecedent basis for these limitations in the claim.
For purposes of examination, claim 11 is interpreted as reciting “[[the]] a current location” and “[[the]] a resource” in line 3.
Claim 12 recites “an estimated amount of time” and “an estimated distance” in lines 4–5 and 5, respectively. However, claims 9 and 12 previously recite an “estimated amount of time” and an “estimated distance”. As a result, the scope of claim 12 is indefinite because it is unclear whether Applicant intends for the recitations of “an estimated amount of time” and “an estimated distance” in lines 4–5 and 5, respectively, to reference the previous recitations or intends to introduce second, different estimates.
For purposes of examination, claim 12 is interpreted as reciting “[[an]] a previous estimated amount of time” and “[[an]] a previous estimated distance” in lines 4–5 and 5, respectively.
Claim 12 further recites “the resource” in line 5. Although claim 12 previously recites “at least one resource”, there is insufficient antecedent basis for “the resource” in the claim.
For purposes of examination, claim 12 is interpreted as reciting “the at least one resource” in line 5.
Claim 14 recites “the request” in line 4. Although the claim previously recites “each request”, there is insufficient antecedent basis for “the request” in the claim.
For purposes of examination, claim 14 is interpreted as reciting “[[the]] a request” in line 4.
Claim 15 recites “the requests remaining in the set of requests” in the element reciting “processing the requests remaining in the set of requests”. There is insufficient antecedent basis for this limitation in the claim.
For purposes of examination, claim 15 is interpreted as reciting “processing [[the]] requests remaining in the set of requests”.
Claim 15 recites “the item” in line 5 of the element reciting “generating … at least one of an estimated amount of time or an estimated distance”. There is insufficient antecedent basis for this limitation in the claim.
For purposes of examination, claim 15 is interpreted as reciting “[[the]] an item” in line 5 of the element reciting “generating … at least one of an estimated amount of time or an estimated distance”.
In view of the above, claim 15 is rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Claims 16–20, which depend from claim 15, inherit the deficiencies described above. As a result, claims 16–20 are similarly rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
In view of the above, Examiner respectfully requests that Applicant thoroughly review the claims for compliance with the requirements set forth under 35 U.S.C. 112(b).
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 15–20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. Claims 15–20 are directed to a computer-readable medium, and the broadest reasonable interpretation of a computer-readable medium includes a signal. Although paragraphs 106–108 of Applicant’s Specification describe computer-readable storage mediums, Applicant’s Specification omits any specific definition of the claimed “computer-readable medium.” The broadest reasonable interpretation of the claims includes transitory signals, and transitory signals are non-statutory subject matter. Accordingly, claims 15–20 are rejected under 35 U.S.C. 101 because it is directed to non-statutory subject matter.
Claims 1–20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. Specifically, claims 1–20 are directed to an abstract idea without additional elements amounting to significantly more than the abstract idea.
With respect to Step 2A Prong One of the framework, claim 1 recites an abstract idea. Claim 1 includes elements for “obtaining (1) a set of requests that involve moving items between a plurality of locations found at a facility and (2) a priority for each request of the set of requests”; obtaining geographical data for the facility …”; “obtaining state data for the facility …; “generating a movement plan that identifies a specific resource from the plurality of resources to execute each request found in the set of requests by: generating, based at least in part on the priority, a set of clusters …”; “processing each cluster of the set of clusters by conducting iterations on the cluster, wherein each iteration involves: processing the requests remaining in the cluster …”; “generating, based at least in part on the geographical data and the state data, at least one of an estimated amount of time or an estimated distance for each resource in the plurality of resources that is eligible to execute the highest priority request …”; “identifying, based at least in part on at least one of the estimated amount of time or the estimated distance for each resource in the plurality of resources that is eligible to execute the highest priority request, the specific resource to execute the highest priority request”; “generating based at least in part on the movement plan, at least one assignment for having the specific resource identified for at least one request in the set of requests execute the at least one request”; and “communicating the at least one assignment to initiate the specific resource executing the at least one request to move the item from the first location to the second location.”
The limitations above recite an abstract idea. More particularly, the elements above recite certain methods of organizing human activity related to managing personal behavior or relationships or interactions between people because the elements describe a process for assigning tasks to resources. Further, the elements recite mental processes because the elements embody observations or evaluations that can be practically performed in the mind or by a human using pen and paper. As a result, claim 1 recites an abstract idea under Step 2A Prong One.
Claims 9 and 15 include substantially similar limitations to those included with respect to claim 1. Although claim 9 further recites an element for “determining to evaluate a movement plan,” the element recites certain methods of organizing human activity and/or mental processes for the same reasons as stated above. As a result, claims 9 and 15 recite an abstract idea under Step 2A Prong One for the same reasons as stated above with respect to claim 1.
Claims 2–8, 10–14, and 16–20 further describe the process for assigning tasks to resources and further recite certain methods of organizing human activity and/or mental processes for the same reasons as stated above. As a result, claims 2–8, 10–14, and 16–20 recite an abstract idea under Step 2A Prong One.
With respect to Step 2A Prong Two of the framework, claim 1 does not include additional elements that integrate the abstract idea into a practical application. Claim 1 includes an additional element that does not recite an abstract idea under Step 2A Prong One. The additional element include computing hardware. When considered in view of the claim as a whole, the additional element does not integrate the abstract idea into a practical application because the additional computer element is a generic computing component that is merely used as a tool to perform the recited abstract idea. As a result, claim 1 does not include any additional elements that integrate the abstract idea into a practical application under Step 2A Prong Two.
As noted above, claims 9 and 15 include substantially similar limitations to those included with respect to claim 1. Although claim 9 further includes a computer-readable medium and a processing device and claim 15 includes a computer-readable medium, the additional elements, when considered in view of the claim as a whole, do not integrate the abstract idea into a practical application because the additional computer elements are generic computing components that are merely used as a tool to perform the recited abstract idea. As a result, claims 9 and 15 do not include any additional elements that integrate the abstract idea into a practical application under Step 2A Prong Two.
Claims 2–3, 14, and 16–17 include additional elements that do not recite an abstract idea under Step 2A Prong One. The additional elements include “sending an electronic communication over a wireless network” (claims 2 and 16), “sending an electronic instruction to the autonomous equipment” (claims 3 and 17), and a machine-learning model (claim 14). When considered in view of the claims as a whole, the additional elements do not integrate the abstract idea into a practical application because the additional elements do no more than generally link the use of the recited abstract idea to a particular technological environment. As a result, claims 2–3, 14, and 16–17 do not include additional elements that integrate the abstract idea into a practical application under Step 2A Prong Two.
Claims 4–8, 10–13, and 18–20 do not include any additional elements beyond those included with respect to the claims from which claims 4–8, 10–13, and 18–20 depend. As a result, claims 4–8, 10–13, and 18–20 do not include any additional elements that integrate the abstract idea into a practical application under Step 2A Prong Two for the same reasons as stated above.
With respect to Step 2B of the framework, claim 1 does not include additional elements amounting to significantly more than the abstract idea. As noted above, claim 1 includes an additional element that does not recite an abstract idea under Step 2A Prong One. The additional element includes computing hardware. The additional element does not amount to significantly more than the recited abstract idea because the additional computer element is a generic computing component that is merely used as a tool to perform the recited abstract idea. As a result, claim 1 does not include any additional elements that amount to significantly more than the recited abstract idea under Step 2B.
As noted above, claims 9 and 15 include substantially similar limitations to those included with respect to claim 1. Although claim 9 further includes a computer-readable medium and a processing device and claim 15 includes a computer-readable medium, the additional elements do not amount to significantly more than the recited abstract idea because the additional computer elements are generic computing components that are merely used as a tool to perform the recited abstract idea. Further, looking at the additional elements as an ordered combination adds nothing that is not already present when considering the additional elements individually. As a result, claims 9 and 15 do not include any additional elements that amount to significantly more than the recited abstract idea under Step 2B.
Claims 2–3, 14, and 16–17 include additional elements that do not recite an abstract idea under Step 2A Prong One. The additional elements include “sending an electronic communication over a wireless network” (claims 2 and 16), “sending an electronic instruction to the autonomous equipment” (claims 3 and 17), and a machine-learning model (claim 14). The additional elements do not amount to significantly more than the recited abstract idea because the additional elements do no more than generally link the use of the recited abstract idea to a particular technological environment. Further, looking at the additional elements as an ordered combination adds nothing that is not already present when considering the additional elements individually. As a result, claims 2–3, 14, and 16–17 do not include additional elements that amount to significantly more than the recited abstract idea under Step 2B.
Claims 4–8, 10–13, and 18–20 do not include any additional elements beyond those included with respect to the claims from which claims 4–8, 10–13, and 18–20 depend. As a result, claims 4–8, 10–13, and 18–20 do not include any additional elements that amount to significantly more than the recited abstract idea under Step 2B for the same reasons as stated above.
Therefore, the claims are directed to an abstract idea without additional elements amounting to significantly more than the abstract idea. Accordingly, claims 1–20 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
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 1–6, 8–11, 13, and 15–20 are rejected under 35 U.S.C. 103 as being unpatentable over Mountz et al. (U.S. 9,551,987) in view of SARKAR et al. (U.S. 2019/0212753).
Claims 1, 9, and 15: Mountz discloses a method comprising:
obtaining, by computing hardware (See FIG. 2), (1) a set of requests that involve moving items between a plurality of locations found at a facility (See col. 5, l. 59–col. 6, l. 4, wherein inventory requests for moving inventory are received by the management system, and col. 4, ll. 47–64, wherein requests are associated with inventory items and associated inventory containers, such that each item/container represents a subtask request; see also col. 6, ll. 44–58) and (2) a priority for each request of the set of requests (See FIG. 10 and col. 21, ll. 3–45, wherein inventory containers and associated inventory items are assigned priority scores);
obtaining, by the computing hardware, geographical data for the facility, wherein the geographical data comprises at least one of a set of amounts of time or a set of distances involved in moving the items between the plurality of locations (See col. 23, ll. 17–31, wherein travel times and distances between containers and stations are obtained; see also col. 5, ll. 26–58 and col. 6, ll. 19–43, wherein locations are monitored for mobile drive units, inventory holders, and work stations within the workspace) and a set of constraints on moving the items between the plurality of locations (See col. 6, ll. 23–28 and 39–43, wherein mobile drive unit availability constraints are considered; see also, col. 19, ll. 26–59, wherein constraint criteria is utilized by a selection module in resource scheduling and col. 8, ll. 36–60, wherein path and collision-avoidance reservations are further disclosed as movement constraints);
obtaining, by the computing hardware, state data for the facility, wherein the state data comprises current locations of a plurality of resources available to execute the set of requests (See col. 5, ll. 26–58 and col. 6, ll. 19–43, wherein locations are monitored for mobile drive units, inventory holders, and work stations within the workspace; see also col. 3, ll. 59–64, col. 14, ll. 9–24, and col. 10, l. 53–col. 11, l. 2);
generating, by the computing hardware, a movement plan that identifies a specific resource from the plurality of resources to execute each request found in the set of requests (See col. 6, ll. 8–43, in view of col. 6, l. 65–col. 7, l. 14, wherein a movement plan is generated by assigning tasks and pathways to selected mobile drive units; see also col. 6, ll. 44–58 and col. 8, ll. 20–35) by:
generating, based at least in part on the priority, a set of tasks, wherein each task of the set of tasks comprises the requests from the set of requests with the priority being same or similar (See col. 21, ll. 3–45, wherein inventory holder retrieval tasks are generated using dynamic priority scores, and wherein the inventory holder retrieval task priority scores are iteratively modified to assign similar inventory holder retrieval tasks a same priority); and
processing, by the computing hardware, each task of the set of tasks by conducting iterations on the tasks (See col. 21, ll. 3–45, wherein inventory holder retrieval tasks are generated using dynamic priority scores, and wherein the inventory holder retrieval task priority scores are iteratively modified to assign similar inventory holder retrieval tasks a same priority), wherein each iteration involves:
processing the requests remaining in the tasks that have yet to be assigned the specific resource using a rules-based engine to identify a highest priority request from the request remaining in the tasks that have yet to be assigned the specific resource (See col. 21, ll. 3–45, wherein inventory holder retrieval tasks are generated using dynamic priority scores, and wherein the inventory holder retrieval task priority scores are iteratively modified to assign similar inventory holder retrieval tasks a same priority; see also col. 6, ll. 8–43, in view of col. 6, l. 65–col. 7, l. 14, wherein a movement plan is generated by assigning tasks and pathways to selected mobile drive units and col. 7, ll. 15–24, wherein rule-based decision making is disclosed);
generating, based at least in part on the geographical data and the state data, at least one of an estimated amount of time or an estimated distance for each resource in the plurality of resources that is eligible to execute the highest priority request, wherein the estimated amount of time or the estimated distance concerns executing the highest priority request to move the item involved in the highest priority request from a first location of the plurality of locations to a second location of the plurality of locations (See col. 23, ll. 17–31, wherein task performance times and distances are estimated based on the current workspace configuration, and col. 6, ll. 23–28 and 39–43, wherein mobile drive unit availability is considered; see also col. 21, ll. 3–45, col. 5, ll. 26–58, and col. 6, ll. 19–43, as cited above, wherein task priority and workspace component location monitoring are disclosed); and
identifying, based at least in part on at least one of the estimated amount of time or the estimated distance for each resource in the plurality of resources that is eligible to execute the highest priority request, the specific resource to execute the highest priority request (See col. 6, ll. 8–43, wherein mobile drive units are assigned to tasks; see also col. 21, ll. 3–45 and col. 23, ll. 17–31, as cited above, wherein tasks are assigned according to time and distance estimates and task priority);
generating, by the computing hardware and based at least in part on the movement plan, at least one assignment for having the specific resource identified for at least one request in the set of requests execute the at least one request (See col. 6, ll. 8–43, wherein mobile drive units are assigned to tasks); and
communicating, by the computing hardware, the at least one assignment to initiate the specific resource executing the at least one request to move the item from the first location to the second location (See col. 6, ll. 8–43, wherein mobile drive units are assigned to tasks, and wherein tasks are transmitted by the management system to appropriate components). Although Mountz implicitly generates at least one of an estimated amount of time or an estimated distance for each resource (See col. 21, ll. 3–45 and col. 23, ll. 17–31, in view of col. 7, ll. 32–38, wherein tasks assignments are optimized by considering time and distance estimates of each inventory containers and monitoring the current state of all components within the system, such that resource time and distance estimates are implicitly considered), Mountz does not expressly disclose the remaining claim elements.
Sarkar discloses generating a set of clusters, wherein each cluster of the set of clusters comprises the requests from the set of requests (See FIG. 3, wherein task nodes are clustered, and paragraph 26, wherein the system operates in a warehouse scenario);
processing each cluster of the set of clusters by conducting iterations on the cluster (See FIG. 3 and paragraph 45, in view of paragraph 26, wherein the clusters are processed iteratively to optimize task assignments for an associated resource); and
generating at least one of an estimated amount of time or an estimated distance for each resource (See FIG. 3 and paragraph 5, in view of paragraphs 26–27, wherein each route is optimized to minimize a distance of travel for the associated vehicle, and wherein distance estimates simultaneously minimize time; see also paragraph 52, wherein distance is considered with respect to each resource in the system).
Mountz discloses a system directed to managing inventory requests within a warehouse system. Sarkar discloses a system directed to optimizing resource paths for warehouse tasks. Each reference discloses a system directed to managing inventory tasks in a warehouse. The technique of utilizing clusters is applicable to the system of Mountz as they each share characteristics and capabilities; namely, they are directed to managing inventory tasks in a warehouse.
One of ordinary skill in the art would have recognized that applying the known technique of Sarkar would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Sarkar to the teachings of Mountz would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate inventory task management into similar systems. Further, applying request clusters to Mountz would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow more detailed analysis and more reliable results.
With respect to claim 9, Mountz further discloses a computer-readable medium storing instructions (See FIG. 2 and col. 8, ll. 8–19);
a processing device communicatively coupled to the computer-readable medium, wherein the processing device is configured to execute the instructions and thereby perform operations comprising (See FIG. 2 and col. 7, l. 66–col. 8, l. 19);
determining to evaluate a movement plan for the facility that involves the set of requests to move the items between the plurality of locations (See col. 5, l. 59–col. 6, l. 18, wherein a movement plan is evaluated with respect to a plurality of inventory requests; see also Abstract).
With respect to claim 15, Mountz further discloses a computer-readable medium storing computer-executable instructions that, when executed by computing hardware, configure the computing hardware to perform operations (See FIG. 2 and col. 7, l. 66–col. 8, l. 19).
Claims 2 and 16: Mountz discloses the method of claim 1, wherein communicating the assignment involves sending an electronic communication over a wireless network to the specific resource (See col. 6, ll. 8–18, wherein task assignments are transmitted to mobile drive units; see also col. 3, l. 59–col. 4, l. 6, wherein wireless transmission capabilities are disclosed).
Claims 3 and 17: Mountz discloses the method of claim 1, wherein the specific resource is autonomous equipment (See col. 3, ll. 30–38, wherein mobile drive units are automated devices), and communicating the assignment involves sending an electronic instruction to the autonomous equipment to have the autonomous equipment move the item from the first location to the second location without human intervention (See col. 6, ll. 8–18, wherein task assignments are transmitted to mobile drive units).
Claims 4 and 18: Mountz discloses the method of claim 1, wherein the specific resource has at least one of the estimated amount of time or the estimated distance that is shorter than at least one of the estimated amount of time or the estimated distance for each other resource in the plurality of resources that is eligible to execute the highest priority request (See col. 23, ll. 17–31, in view of col. 21, ll. 3–45, wherein tasks are assigned according to time and distance estimates and task priority).
As noted above, although Mountz implicitly considers at least one of an estimated amount of time or an estimated distance for each resource (See col. 21, ll. 3–45 and col. 23, ll. 17–31, in view of col. 7, ll. 32–38, wherein tasks assignments are optimized by considering time and distance estimates of each inventory containers and monitoring the current state of all components within the system, such that resource time and distance estimates are implicitly considered), Sarkar expressly discloses the remaining claim elements.
Sarkar discloses at least one of the estimated amount of time or the estimated distance for the specific resource (See FIG. 3 and paragraph 5, in view of paragraphs 26–27, wherein each route is optimized to minimize a distance of travel for the associated vehicle, and wherein distance estimates simultaneously minimize time; see also paragraph 52, wherein distance is considered with respect to each resource in the system).
One of ordinary skill in the art would have recognized that applying the known technique of Sarkar would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 1.
Claims 5 and 19: Mountz discloses the method of claim 1, wherein the set of constraints identifies each of the plurality of resources that is eligible to execute the highest priority request (See col. 6, ll. 23–28 and 39–43, wherein mobile drive unit eligibility is determined with respect to availability).
Claim 6: Mountz discloses the method of claim 5, wherein the plurality of resources comprises equipment configured to haul the items between the plurality of locations, and the set of constraints identifies each of the plurality of resources that is eligible to execute the highest priority request as able to at least one of travel to or have a certain capability needed for at least one of the first location or the second location (See col. 6, ll. 23–28 and 39–43, wherein mobile drive unit eligibility is determined with respect to availability).
Claims 8 and 20: Mountz discloses the method of claim 1, wherein at least one constraint of the set of constraints is based at least in part on a time of day (See col. 6, ll. 8–18, wherein assignments may be limited according to a start-up time).
Claim 10: Mountz discloses the system of claim 9, wherein determining to evaluate the movement plan for the facility comprises determining a triggering event has occurred with respect to the facility (See col. 5, l. 59–col. 6, l. 18, wherein a movement plan is evaluated with respect to a plurality of inventory requests, and wherein consideration may be triggered in response to the occurrence of particular events).
Claim 11: Mountz discloses the system of claim 9, wherein at least one of the estimated amount of time or the estimated distance for each resource of the plurality of resources is based at least in part on at least one of the current location of the resource, a distance of a route between the first location and the second location, an amount of time to travel the route, an obstacle involved with the route, or a constraint on the resource in executing the highest priority request (See col. 23, ll. 17–31, in view of col. 7, ll. 32–38, wherein tasks assignments are optimized by considering time and distance estimates and monitoring the current state of all components within the system; see also col. 8, ll. 36–60, wherein routing pathways are associated with each task assignment).
As noted above, although Mountz implicitly considers at least one of an estimated amount of time or an estimated distance for each resource (See col. 21, ll. 3–45 and col. 23, ll. 17–31, in view of col. 7, ll. 32–38, wherein tasks assignments are optimized by considering time and distance estimates of each inventory containers and monitoring the current state of all components within the system, such that resource time and distance estimates are implicitly considered), Sarkar expressly discloses the remaining claim elements.
Sarkar discloses at least one of the estimated amount of time or the estimated distance for the specific resource (See FIG. 3 and paragraph 5, in view of paragraphs 26–27, wherein each route is optimized to minimize a distance of travel for the associated vehicle, and wherein distance estimates simultaneously minimize time; see also paragraph 52, wherein distance is considered with respect to each resource in the system).
One of ordinary skill in the art would have recognized that applying the known technique of Sarkar would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 1.
Claim 13: Mountz discloses the system of claim 9, wherein processing the requests remaining in the tasks that have yet to be assigned the specific resource to identify the highest priority request is performed considering at least one of a type of request involved for each request in the tasks or a type of item involved in each request in the tasks (See col. 21, ll. 3–45, in view of col. 19, ll. 48–60, wherein request tasks are prioritized in the context of item types and inventory holder fitness; see also col. 2, ll. 64–65 and col. 4, ll. 20–28). Mountz does not expressly disclose the remaining claim elements.
Sarkar discloses the cluster (See FIG. 3, wherein task nodes are clustered).
One of ordinary skill in the art would have recognized that applying the known technique of Sarkar would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 1.
Claims 7, 12, and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Mountz et al. (U.S. 9,551,987) in view of SARKAR et al. (U.S. 2019/0212753), and in further view of Darmour et al. (U.S. 2021/0334682).
Claim 7: As indicated above, Mountz and Sarkar disclose the elements of claims 1 and 5.
Mountz further discloses the method of claim 5, wherein the plurality of resources comprises personnel operating equipment configured to haul the items between the plurality of locations (See col. 5, ll. 19–25, wherein human operators may perform transfer tasks) and the set of constraints identifies each of the plurality of resources that is eligible to execute the highest priority request (See col. 6, ll. 23–28 and 39–43, wherein mobile drive unit eligibility is determined with respect to availability). Mountz and Sarkar do not expressly disclose the remaining claim elements.
Darmour discloses the set of constraints identifies each of the plurality of resources that is eligible to execute the highest priority request as licensed to travel to at least one of the first location or the second location (See paragraphs 95 and 112, wherein tasks associated with a location are assigned to a given resource according to licensing constraints; see also paragraphs 53, 69, and 78).
As disclosed above, Mountz discloses a system directed to managing inventory requests within a warehouse system, and Sarkar discloses a system directed to optimizing resource paths for warehouse tasks. Darmour discloses a system directed to managing inventory and transfer tasks. Each reference discloses a system directed to managing inventory tasks. The technique of utilizing licensing requirements is applicable to the systems of Mountz and Sarkar as they each share characteristics and capabilities; namely, they are directed to managing inventory tasks.
One of ordinary skill in the art would have recognized that applying the known technique of Darmour would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Darmour to the teachings of Mountz and Sarkar would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate inventory task management into similar systems. Further, applying licensing requirements to Mountz and Sarkar would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow more detailed analysis and more reliable results.
Claim 12: Although Mountz and Sarkar disclose at least one of the estimated amount of time or the estimated distance for at least one resource of the plurality of resources (See citations above), Mountz and Sarkar do not expressly disclose the remaining elements of claim 12.
Darmour discloses wherein at least one of the estimated amount of time or the estimated distance for at least one resource of the plurality of resources is based at least in part on at least one of an actual time that the at least one resource took or an actual distance that the at least one resource traveled in performing a previous request with respect to at least one of an estimated amount of time or an estimated distance generated for the resource to perform the previous request (See paragraphs 108–109 and 113, wherein task performer attributes are scored using average and/or weighted distance and speed metrics; see also paragraphs 23 and 75, wherein historical task characteristics, including duration data and locational/navigational data, are used to train a learning model to generate task assignments and routes).
One of ordinary skill in the art would have recognized that applying the known technique of Darmour would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 7.
Claim 14: Mountz discloses the system of claim 9, wherein processing the requests remaining in the tasks that have yet to be assigned the specific resource to identify the highest priority request involves processing characteristics of each request remaining in the tasks to generate a representation on an importance of having the request executed to move the item associated with the request from the first location to the second location, and selecting the request remaining in the tasks with the representation having a highest importance as the highest priority request (See col. 21, ll. 3–45, wherein inventory holder retrieval tasks are generated using dynamic priority scores, and wherein the inventory holder retrieval task priority scores are determined according to retrieval task characteristics). Mountz does not expressly disclose the remaining claim elements.
Sarkar discloses the cluster (See FIG. 3, wherein task nodes are clustered).
One of ordinary skill in the art would have recognized that applying the known technique of Sarkar would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 1. Mountz and Sarkar do not expressly disclose the remaining claim elements.
Darmour discloses using a machine-learning model to generate a representation on an importance of having the request executed to move the item associated with the request from the first location to the second location (See paragraphs 49 and 54–55, in view of paragraph 70, wherein a machine-learning model learns task attributes, including urgency, and wherein tasks include transport tasks).
One of ordinary skill in the art would have recognized that applying the known technique of Darmour would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 7.
Conclusion
The following prior art is made of record and not relied upon but is considered pertinent to applicant's disclosure:
Francis (U.S. 2024/0303594) discloses a system directed to optimizing order fulfillment assignments and routing using store sections;
GRAVELLE et al. (U.S. 2023/0133964) discloses a system directed to optimizing automated retrieval using bin priority; and
Putrevu et al. (U.S. 2022/0292580) discloses a system directed to optimizing order fulfillment and task allocation using order grouping.
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/WILLIAM S BROCKINGTON III/ Primary Examiner, Art Unit 3623
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