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 .
DETAILED ACTION
Status of Claims
The following is a final office action in response to the communication filed on 07/28/2026.
Claims 1-9 are either amended directly or via a claim they depend from.
Claims 1-9 are rejected.
Response to Arguments
Applicant’s respectful arguments filed on 07/28/2026 have been fully considered and are
addressed as follows.
Regarding the Objections to the Claims for Informalities: The amendment to claim 5 has
rendered the objection moot. Accordingly, the objection has been withdrawn.
Regarding the Rejections under 35 § U.S.C. 112: The amendment to claim 1 clarifying that the control method is executed by a control device has rendered the rejection moot. Accordingly, the
rejection has been withdrawn.
Regarding the Rejections under 35 § U.S.C. 102/103: Applicant’s arguments/remarks made in
amendment (See Pages 5-9, filed 07/28/2026) regarding the rejections of the claims are respectfully deemed by the Examiner as not being persuasive to overcome the rejections of record. The particular arguments will now be addressed.
Regarding the argument, that Aisu, (Page 7, Lines 1-4) “fails to disclose storing a model representing a length of delay time defined for each passageway included in a route and updating the model using delay time actually generated in the passage,” Examiner respectfully disagrees.
Aisu teaches, (Paragraph [0058]) “FIG. 5B illustrates traveling IDs of the respective traveling paths, IDs of nodes at both ends of the traveling paths, and standard times required for traveling on the respective traveling paths. For example, a traveling ID of the traveling path between the nodes B and C is 1, nodes at both ends of the traveling path are B and C, and a standard time required for traveling on the traveling path is 180. Any time unit may be used,” and that, (Paragraph [0071]) “FIG. 7 illustrates an example of the travel timing schedule generated by the travel timing scheduler 105. An example of the travel timing schedule for three mobile objects (AGV 0, AGV 1, AGV 2) is indicated. The travel timing schedule includes an individual travel schedule for the AGV 0, an individual travel schedule for AGV 1, and an individual travel schedule for AGV 2.”
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Examiner is interpreting the wait times that are generated for a particular passageway between nodes, such a WAIT -52.0 for AGV0, as examples under broadest reasonable interpretations as delay times which are generated as the moving body passes through a passageway among a plurality of passageways among the one or more passageways. In this case, -52 is a unitless measure of time lost for an AGV’s traversal between nodes G and E. The wait time information for each travel passageway is updated when two or more AGVs intend to enter and occupy the same passageway. The context of Figure 7 is additionally an example under broadest reasonable interpretation as identification information of the passageway.
Aisu additionally teaches, (Paragraph [0183], Lines 3-9) “In a case where the mobile object 1 conflicts with the mobile object 2, there are two measures: a measure in which the mobile object 1 is caused to wait and a measure in which the mobile object 2 is caused to wait. In this case, the individual travel schedule of at least one of the mobile objects 1 and 2 among the individual travel schedules of the mobile objects 1 to H is changed for each measure,” wherein, (Paragraph [0187], Lines 1-5) “The travel timing scheduler 105 calculates (predicts) the evaluation value based on the model for each tentative travel timing schedule (the travel timing schedule in the transitioned state) using the evaluation value calculator 114 (calculation processing),” and therefore the model is updated to represent the length of delay time.
Regarding the argument that Aisu, (Page 7, Lines 5-9) “still fails to disclose storing a delay time model for each arc between the nodes and updating the model corresponding to the arc using a delay time actually generated in the arc.” Examiner respectfully disagrees with the thrust of the arguments due to the claim limitations not mentioning nodes or an arc, and therefore the teachings of Aisu are not limited to these features. Therefore, the rejections of claims 1-6 and 8-9 are maintained.
Regarding the argument that, “claim 7 is not disclosed, suggested, or otherwise rendered obvious by any combination of Aisu and Nishi,” Examiner agrees with this argument now that claim 1 has been amended to recite that the model to which claim 7 refers to is, (Claim 1, Lines 10-13) “a model representing a length of the delay time defined for a corresponding passageway identified by the identification information amongNishi is no longer the best prior art available to apply towards an obviousness type rejection to arrive at this feature. However a new rejection has been applied to the, Claim Rejections 35 § U.S.C. 103, section for Applicant’s consideration in response to the amendment.
Claim Rejections - 35 USC § 102
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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1-6 and 8-9 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Aisu et al. (US 2021/0286373 A1, hereinafter Aisu)
Claim 1 Discloses:
“A control method in a control device that controls movement of a plurality of moving bodies,”
Aisu teaches, (Abstract, Lines 1-2) “A travel control device includes: a controller configured to control traveling of a plurality of mobile objects.”
“the control method comprising: moving the plurality of moving bodies”
Aisu teaches, (Paragraph [0039], Lines 1-4) “The travel planning system 1 efficiently controls operation of a number of mobile objects autonomously traveling at low speed in a travel network including a plurality of traveling paths.”
“in accordance with movement plans that have been predetermined,”
Aisu teaches, (Paragraph [0159], Lines 1-5) “The route planner 109 generates the route plan starting from the update position for each mobile object or extracts part of the route plan prepared in advance. The previous route plan is updated with the generated or extracted route plan (step 13).”
Aisu teaches, (Paragraph [0039], Lines 1-4) “The travel planning system 1 efficiently controls operation of a number of mobile objects autonomously traveling at low speed in a travel network including a plurality of traveling paths disposed in a narrow area.”
“where each of the plurality of moving bodies passes from a departure place to a destination;”
Aisu teaches, (Paragraph [0117], Lines 6-11) “for example, assumed that, in a case where the current route plan is the route plan in FIG. 6A, the current position of the mobile object is a designated area E (before the intersection portion indicated by the node E), and the next movement destination is a node C (before the intersection portion indicated by the node C).”
“acquiring, from each of the plurality of moving bodies, delay time information including an actual delay time that is a delay time of each of the plurality of moving bodies,”
Aisu teaches, (Paragraph [0121], Lines 7-9) “The evaluation value of each tentative travel timing schedule based on delay times of a plurality of mobile objects is acquired using the evaluation value calculator 114.”
Aisu additionally teaches, (Paragraph [0167]) “The replan determiner 108 judges whether at least one mobile object which cannot meet the travel plan (or the travel timing schedule) exists on the basis of the travel plan of each mobile object and the state of each mobile object (step 19).”
“the delay time being generated when the moving body passes through a passageway amongpassageways, and identification information of the passageway; updating, based on the identification information, a model representing a length of the delay time defined for a corresponding passageway identified by the identification information amongthe[[a]] corresponding passageway among the one or more passageways;”
Aisu teaches, (Paragraph [0134], Lines 4-12) “a delay time (a sum of adjusted times for solving conflict) in traveling from the current position of the mobile object in midstream of the completed travel timing schedule (estimated position after each mobile object travels in a range in which conflict in the tentative travel timing schedule has been solved) until the end of the travel timing schedule, is calculated, and a value obtained by summing up the delay times for the plurality of mobile objects is used.”
Aisu additionally teaches, (Paragraph [0129], Lines 1-4) “the current position may be a coordinate at which the mobile object is located, an ID of the designated area in which the mobile object is located, or an ID of the traveling path on which the mobile object is located,” and that, (Paragraph [0176]) “FIG. 13A is a diagram for explaining an example where conflict will occur in a case where two mobile objects (indicated as a mobile object 1 and a mobile object 2) travel in a travel network with a simple structure. It is assumed here that the route plane of the mobile object 1 and the route plan of the mobile object 2 defines that the mobile object 1 travels back and forth between the node C and the node E, and the mobile object 2 travels back and forth between the node F and the node D.” Under broadest reasonable interpretation, the segments between the nodes that make up the traveling paths are examples of passageways given the context of the invention.
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Aisu teaches, (Paragraph [0058]) “FIG. 5B illustrates traveling IDs of the respective traveling paths, IDs of nodes at both ends of the traveling paths, and standard times required for traveling on the respective traveling paths. For example, a traveling ID of the traveling path between the nodes B and C is 1, nodes at both ends of the traveling path are B and C, and a standard time required for traveling on the traveling path is 180. Any time unit may be used,” and that, (Paragraph [0071]) “FIG. 7 illustrates an example of the travel timing schedule generated by the travel timing scheduler 105. An example of the travel timing schedule for three mobile objects (AGV 0, AGV 1, AGV 2) is indicated. The travel timing schedule includes an individual travel schedule for the AGV 0, an individual travel schedule for AGV 1, and an individual travel schedule for AGV 2.”
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Examiner is interpreting the wait times that are generated for a particular passageway between nodes, such a WAIT -52.0 for AGV0, as examples under broadest reasonable interpretations as delay times which are generated as the moving body passes through a passageway among a plurality of passageways among the one or more passageways. In this case, -52 is a unitless measure of time lost for an AGV’s traversal between nodes G and E. The wait time information for each travel passageway is updated when two or more AGVs intend to enter and occupy the same passageway. The context of Figure 7 is additionally an example under broadest reasonable interpretation as identification information of the passageway.
Aisu additionally teaches, (Paragraph [0183], Lines 3-9) “In a case where the mobile object 1 conflicts with the mobile object 2, there are two measures: a measure in which the mobile object 1 is caused to wait and a measure in which the mobile object 2 is caused to wait. In this case, the individual travel schedule of at least one of the mobile objects 1 and 2 among the individual travel schedules of the mobile objects 1 to H is changed for each measure,” wherein, (Paragraph [0187], Lines 1-5) “The travel timing scheduler 105 calculates (predicts) the evaluation value based on the model for each tentative travel timing schedule (the travel timing schedule in the transitioned state) using the evaluation value calculator 114 (calculation processing),” and therefore the model is updated to represent the length of delay time.
“acquiring a current location of each of the plurality of moving bodies;”
Aisu teaches, (Paragraph [0065]) “The state storage 104 stores information indicating states of the respective mobile objects and specific information of the mobile objects inside,” and that, (Paragraph [0066], Lines 6-8) “The position information includes current positions (positions which are detected most recently) of the mobile objects.”
“and updating each of the movement plans based on the updated model, the destination, and the current location.”
Aisu teaches, (Paragraph [0113], Lines -14) “the travel plan of the mobile object is updated in accordance with a timing at which the mobile object arrives at the updated position. Therefore, the update position determiner 106 determines the update position of each mobile object. The mobile object operates in accordance with the travel plan before update (travel timing schedule before update) until the mobile object reaches the update position, and, after the mobile object reaches the update position, the mobile object operates in accordance with the updated travel plan (updated travel timing schedule),” and that, (Paragraph [0114], Lines 3-5) “the update position may be an arbitrary position (such as, for example, a current position of the mobile object,” as well as that, (Paragraph [0156], Lines 1-4) “In the processing illustrated in FIG. 11, the travel timing scheduler 105 generates or updates the model using the search log added to the search log storage 111 every time the travel timing schedule is updated.”
Aisu additionally teaches, (Paragraph [0170]) “In a case where the replan trigger is not generated (step 19: No), it is judged whether a mobile object which has finished the travel plan (or the travel timing schedule) exists. In a case where a mobile object which has finished the travel plan exists (step 20: Yes), the processing returns to step 11. In a case where a mobile object which has finished the travel plan does not exist (step 20: No), the processing returns to step 18. The processing from step 18 to step 20 is repeated until the replan trigger is generated or until a mobile object which has finished the travel plan occurs.”
Claim 2 Discloses:
“The control method according to claim 1, wherein the movement plans are updated when any one of the plurality of moving bodies reaches the destination.”
Aisu teaches, (Paragraph [0170], Lines 1-5) “In a case where the replan trigger is not generated (step 19: No), it is judged whether a mobile object which has finished the travel plan (or the travel timing schedule) exists. In a case where a mobile object which has finished the travel plan exists (step 20: Yes), the processing returns to step 11,” wherein steps 12 and 13 subsequently occur which comprise the updating of the route plans as seen in Fig. 11.
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Claim 3 Discloses:
“The control method according to claim 1, wherein the movement plans are updated when any one of the plurality of moving bodies has passed through any one of the one or more passageways.”
Aisu additionally teaches, (Paragraph [0114], Lines 3-5) “the update position may be an arbitrary position (such as, for example, a current position of the mobile object,” and that, (Paragraph [0129], Lines 1-4) “the current position may be a coordinate at which the mobile object is located, an ID of the designated area in which the mobile object is located, or an ID of the traveling path on which the mobile object is located.”
Claim 4 Discloses:
“The control method according to claim 1, wherein the movement plans are periodically updated during movement of the plurality of moving bodies.”
Aisu teaches, (Paragraph [0114]) “As an example of the update position, in a case where each mobile object can perform communication with the travel management device 200 in real time, the update position may be … a position at time after a certain margin is added to the current position in view of a time length required for calculation.”
Aisu additionally teaches, (Paragraph [0189], Lines 1-11) “The travel timing scheduler 105 judges whether a calculation period falls within a predetermined time limit or whether or not the number of times of repetition falls within a predetermined number of times (step 28). An arbitrary range in the flowchart can be set as a target for judging the number of times of repetition. For example, the number of times of repetition may be the number of times of repetition of processing from step 23 to 28. If the calculation period falls within the time limit or the number of times of repetition falls within the predetermined number of times (step 28: Yes), the processing returns to step 23.”
Claim 5 Discloses:
“The control method according to claim 1, wherein the movement plans each are updated to define one or more passageways where each of the plurality of moving bodies passes from a passageway next to a passageway including the current location to the destination so that the plurality of moving bodies does not collide with each other.”
Aisu teaches, (Paragraph [0039]) “The travel planning system 1 efficiently controls operation of a number of mobile objects autonomously traveling at low speed in a travel network including a plurality of traveling paths disposed in a narrow area as a whole so that conflict such as deadlock and a collision does not occur,” and that, (Paragraph [0171], Lines 1-8) “Details of step 15 in FIG. 11 will be described using FIG. 12, FIGS. 13A to 13C and FIGS. 14A to 14D. In the present step, the travel timing schedule is generated which ensures that a collision or deadlock among mobile object does not occur even in a case where a plurality of mobile objects which travel in reverse directions or travel at different speed on the same traveling path in the respective route plans exist,” as well as that, (Paragraph [0156], Lines 1-4) “In the processing illustrated in FIG. 11, the travel timing scheduler 105 generates or updates the model using the search log added to the search log storage 111 every time the travel timing schedule is updated.”
Claim 6 Discloses:
“The control method according to claim 1, wherein in the movement plans, a scheduled time at which each of the plurality of moving bodies enters each of the one or more passageways is defined.”
Aisu teaches, (Paragraph [0058]) “FIG. 5B illustrates traveling IDs of the respective traveling paths, IDs of nodes at both ends of the traveling paths, and standard times required for traveling on the respective traveling paths. For example, a traveling ID of the traveling path between the nodes B and C is 1, nodes at both ends of the traveling path are B and C, and a standard time required for traveling on the traveling path is 180. Any time unit may be used,” and that, (Paragraph [0071]) “FIG. 7 illustrates an example of the travel timing schedule generated by the travel timing scheduler 105. An example of the travel timing schedule for three mobile objects (AGV 0, AGV 1, AGV 2) is indicated. The travel timing schedule includes an individual travel schedule for the AGV 0, an individual travel schedule for AGV 1, and an individual travel schedule for AGV 2.”
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Claim 8 Discloses: (Currently Amended)
“A control device that controls movement of a plurality of moving bodies,”
Aisu teaches, (Abstract, Lines 1-2) “A travel control device includes: a controller configured to control traveling of a plurality of mobile objects.”
“the control device comprising: a processor,”
Aisu teaches, (Paragraph [0207], Lines 1-6) “FIG. 16 illustrates a hardware configuration of the travel planning device 100 according to any one of the first to third embodiments. The travel planning device 100 according to the present embodiment is configured with a computer device 600. The computer device 600 includes a CPU.”
“wherein the processor executes: moving the plurality of moving bodies”
Aisu teaches, (Paragraph [0039], Lines 1-4) “The travel planning system 1 efficiently controls operation of a number of mobile objects autonomously traveling at low speed in a travel network including a plurality of traveling paths.”
“in accordance with movement plans that have been predetermined,”
Aisu teaches, (Paragraph [0159], Lines 1-5) “The route planner 109 generates the route plan starting from the update position for each mobile object or extracts part of the route plan prepared in advance. The previous route plan is updated with the generated or extracted route plan (step 13).”
“the movement plans defining one or more passageways”
Aisu teaches, (Paragraph [0039], Lines 1-4) “The travel planning system 1 efficiently controls operation of a number of mobile objects autonomously traveling at low speed in a travel network including a plurality of traveling paths disposed in a narrow area.”
“where each of the plurality of moving bodies passes from a departure place to a destination;”
Aisu teaches, (Paragraph [0117], Lines 6-11) “for example, assumed that, in a case where the current route plan is the route plan in FIG. 6A, the current position of the mobile object is a designated area E (before the intersection portion indicated by the node E), and the next movement destination is a node C (before the intersection portion indicated by the node C).”
“acquiring, from each of the plurality of moving bodies, delay time information including an actual delay time that is a delay time of each of the plurality of moving bodies,”
Aisu teaches, (Paragraph [0121], Lines 7-9) “The evaluation value of each tentative travel timing schedule based on delay times of a plurality of mobile objects is acquired using the evaluation value calculator 114.”
Aisu additionally teaches, (Paragraph [0167]) “The replan determiner 108 judges whether at least one mobile object which cannot meet the travel plan (or the travel timing schedule) exists on the basis of the travel plan of each mobile object and the state of each mobile object (step 19).”
“the delay time being generated when the moving body passes through a passageway amongpassageways, and identification information of the passageway; updating, based on the identification information, a model representing a length of the delay time defined for a corresponding passageway identified by the identification information amongthe corresponding passageway among the one or more passageways;”
Aisu teaches, (Paragraph [0134], Lines 4-12) “a delay time (a sum of adjusted times for solving conflict) in traveling from the current position of the mobile object in midstream of the completed travel timing schedule (estimated position after each mobile object travels in a range in which conflict in the tentative travel timing schedule has been solved) until the end of the travel timing schedule, is calculated, and a value obtained by summing up the delay times for the plurality of mobile objects is used.”
Aisu additionally teaches, (Paragraph [0129], Lines 1-4) “the current position may be a coordinate at which the mobile object is located, an ID of the designated area in which the mobile object is located, or an ID of the traveling path on which the mobile object is located,” and that, (Paragraph [0176]) “FIG. 13A is a diagram for explaining an example where conflict will occur in a case where two mobile objects (indicated as a mobile object 1 and a mobile object 2) travel in a travel network with a simple structure. It is assumed here that the route plane of the mobile object 1 and the route plan of the mobile object 2 defines that the mobile object 1 travels back and forth between the node C and the node E, and the mobile object 2 travels back and forth between the node F and the node D.” Under broadest reasonable interpretation, the segments between the nodes that make up the traveling paths are examples of passageways given the context of the invention.
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Aisu teaches, (Paragraph [0058]) “FIG. 5B illustrates traveling IDs of the respective traveling paths, IDs of nodes at both ends of the traveling paths, and standard times required for traveling on the respective traveling paths. For example, a traveling ID of the traveling path between the nodes B and C is 1, nodes at both ends of the traveling path are B and C, and a standard time required for traveling on the traveling path is 180. Any time unit may be used,” and that, (Paragraph [0071]) “FIG. 7 illustrates an example of the travel timing schedule generated by the travel timing scheduler 105. An example of the travel timing schedule for three mobile objects (AGV 0, AGV 1, AGV 2) is indicated. The travel timing schedule includes an individual travel schedule for the AGV 0, an individual travel schedule for AGV 1, and an individual travel schedule for AGV 2.”
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Examiner is interpreting the wait times that are generated for a particular passageway between nodes, such a WAIT -52.0 for AGV0, as examples under broadest reasonable interpretations as delay times which are generated as the moving body passes through a passageway among a plurality of passageways among the one or more passageways. In this case, -52 is a unitless measure of time lost for an AGV’s traversal between nodes G and E. The wait time information for each travel passageway is updated when two or more AGVs intend to enter and occupy the same passageway. The context of Figure 7 is additionally an example under broadest reasonable interpretation as identification information of the passageway.
Aisu additionally teaches, (Paragraph [0183], Lines 3-9) “In a case where the mobile object 1 conflicts with the mobile object 2, there are two measures: a measure in which the mobile object 1 is caused to wait and a measure in which the mobile object 2 is caused to wait. In this case, the individual travel schedule of at least one of the mobile objects 1 and 2 among the individual travel schedules of the mobile objects 1 to H is changed for each measure,” wherein, (Paragraph [0187], Lines 1-5) “The travel timing scheduler 105 calculates (predicts) the evaluation value based on the model for each tentative travel timing schedule (the travel timing schedule in the transitioned state) using the evaluation value calculator 114 (calculation processing),” and therefore the model is updated to represent the length of delay time.
“acquiring a current location of each of the plurality of moving bodies;”
Aisu teaches, (Paragraph [0065]) “The state storage 104 stores information indicating states of the respective mobile objects and specific information of the mobile objects inside,” and that, (Paragraph [0066], Lines 6-8) “The position information includes current positions (positions which are detected most recently) of the mobile objects.”
“and updating
Aisu teaches, (Paragraph [0113], Lines -14) “the travel plan of the mobile object is updated in accordance with a timing at which the mobile object arrives at the updated position. Therefore, the update position determiner 106 determines the update position of each mobile object. The mobile object operates in accordance with the travel plan before update (travel timing schedule before update) until the mobile object reaches the update position, and, after the mobile object reaches the update position, the mobile object operates in accordance with the updated travel plan (updated travel timing schedule),” and that, (Paragraph [0114], Lines 3-5) “the update position may be an arbitrary position (such as, for example, a current position of the mobile object,” as well as that, (Paragraph [0156], Lines 1-4) “In the processing illustrated in FIG. 11, the travel timing scheduler 105 generates or updates the model using the search log added to the search log storage 111 every time the travel timing schedule is updated.”
Aisu additionally teaches, (Paragraph [0170]) “In a case where the replan trigger is not generated (step 19: No), it is judged whether a mobile object which has finished the travel plan (or the travel timing schedule) exists. In a case where a mobile object which has finished the travel plan exists (step 20: Yes), the processing returns to step 11. In a case where a mobile object which has finished the travel plan does not exist (step 20: No), the processing returns to step 18. The processing from step 18 to step 20 is repeated until the replan trigger is generated or until a mobile object which has finished the travel plan occurs.”
Claim 9 Discloses: (Currently Amended)
“A non-transitory computer readable storage medium storing a program of a control device that controls movement of a plurality of moving bodies, the program causing the control device to perform operations”
Aisu teaches, (Abstract, Lines 1-2) “A travel control device includes: a controller configured to control traveling of a plurality of mobile objects,” wherein, (Claim 7, Lines 1-4) “A non-transitory computer readable medium having a computer program stored therein which when executed by a computer, causes the computer to perform processes.”
“comprising: moving the plurality of moving bodies”
Aisu teaches, (Paragraph [0039], Lines 1-4) “The travel planning system 1 efficiently controls operation of a number of mobile objects autonomously traveling at low speed in a travel network including a plurality of traveling paths.”
“in accordance with movement plans that have been predetermined,”
Aisu teaches, (Paragraph [0159], Lines 1-5) “The route planner 109 generates the route plan starting from the update position for each mobile object or extracts part of the route plan prepared in advance. The previous route plan is updated with the generated or extracted route plan (step 13).”
“the movement plans defining one or more passageways”
Aisu teaches, (Paragraph [0039], Lines 1-4) “The travel planning system 1 efficiently controls operation of a number of mobile objects autonomously traveling at low speed in a travel network including a plurality of traveling paths disposed in a narrow area.”
“where each of the plurality of moving bodies passes from a departure place to a destination;”
Aisu teaches, (Paragraph [0117], Lines 6-11) “for example, assumed that, in a case where the current route plan is the route plan in FIG. 6A, the current position of the mobile object is a designated area E (before the intersection portion indicated by the node E), and the next movement destination is a node C (before the intersection portion indicated by the node C).”
“acquiring, from each of the plurality of moving bodies, delay time information including an actual delay time that is a delay time of each of the plurality of moving bodies,”
Aisu teaches, (Paragraph [0121], Lines 7-9) “The evaluation value of each tentative travel timing schedule based on delay times of a plurality of mobile objects is acquired using the evaluation value calculator 114.”
Aisu additionally teaches, (Paragraph [0167]) “The replan determiner 108 judges whether at least one mobile object which cannot meet the travel plan (or the travel timing schedule) exists on the basis of the travel plan of each mobile object and the state of each mobile object (step 19).”
“the delay time being generated when the moving body passes through a passageway amongpassageways, and identification information of the passageway; updating, based on the identification information, a model representing a length of the delay time defined for a corresponding passageway identified by the identification information amongthe[[a]] corresponding passageway among the one or more passageways;”
Aisu teaches, (Paragraph [0134], Lines 4-12) “a delay time (a sum of adjusted times for solving conflict) in traveling from the current position of the mobile object in midstream of the completed travel timing schedule (estimated position after each mobile object travels in a range in which conflict in the tentative travel timing schedule has been solved) until the end of the travel timing schedule, is calculated, and a value obtained by summing up the delay times for the plurality of mobile objects is used.”
Aisu additionally teaches, (Paragraph [0129], Lines 1-4) “the current position may be a coordinate at which the mobile object is located, an ID of the designated area in which the mobile object is located, or an ID of the traveling path on which the mobile object is located,” and that, (Paragraph [0176]) “FIG. 13A is a diagram for explaining an example where conflict will occur in a case where two mobile objects (indicated as a mobile object 1 and a mobile object 2) travel in a travel network with a simple structure. It is assumed here that the route plane of the mobile object 1 and the route plan of the mobile object 2 defines that the mobile object 1 travels back and forth between the node C and the node E, and the mobile object 2 travels back and forth between the node F and the node D.” Under broadest reasonable interpretation, the segments between the nodes that make up the traveling paths are examples of passageways given the context of the invention.
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Aisu teaches, (Paragraph [0058]) “FIG. 5B illustrates traveling IDs of the respective traveling paths, IDs of nodes at both ends of the traveling paths, and standard times required for traveling on the respective traveling paths. For example, a traveling ID of the traveling path between the nodes B and C is 1, nodes at both ends of the traveling path are B and C, and a standard time required for traveling on the traveling path is 180. Any time unit may be used,” and that, (Paragraph [0071]) “FIG. 7 illustrates an example of the travel timing schedule generated by the travel timing scheduler 105. An example of the travel timing schedule for three mobile objects (AGV 0, AGV 1, AGV 2) is indicated. The travel timing schedule includes an individual travel schedule for the AGV 0, an individual travel schedule for AGV 1, and an individual travel schedule for AGV 2.”
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Greyscale
Examiner is interpreting the wait times that are generated for a particular passageway between nodes, such a WAIT -52.0 for AGV0, as examples under broadest reasonable interpretations as delay times which are generated as the moving body passes through a passageway among a plurality of passageways among the one or more passageways. In this case, -52 is a unitless measure of time lost for an AGV’s traversal between nodes G and E. The wait time information for each travel passageway is updated when two or more AGVs intend to enter and occupy the same passageway. The context of Figure 7 is additionally an example under broadest reasonable interpretation as identification information of the passageway.
Aisu additionally teaches, (Paragraph [0183], Lines 3-9) “In a case where the mobile object 1 conflicts with the mobile object 2, there are two measures: a measure in which the mobile object 1 is caused to wait and a measure in which the mobile object 2 is caused to wait. In this case, the individual travel schedule of at least one of the mobile objects 1 and 2 among the individual travel schedules of the mobile objects 1 to H is changed for each measure,” wherein, (Paragraph [0187], Lines 1-5) “The travel timing scheduler 105 calculates (predicts) the evaluation value based on the model for each tentative travel timing schedule (the travel timing schedule in the transitioned state) using the evaluation value calculator 114 (calculation processing),” and therefore the model is updated to represent the length of delay time.
“acquiring a current location of each of the plurality of moving bodies;”
Aisu teaches, (Paragraph [0065]) “The state storage 104 stores information indicating states of the respective mobile objects and specific information of the mobile objects inside,” and that, (Paragraph [0066], Lines 6-8) “The position information includes current positions (positions which are detected most recently) of the mobile objects.”
“and updating each of the movement plans based on the updated model, the destination, and the current location.”
Aisu teaches, (Paragraph [0113], Lines -14) “the travel plan of the mobile object is updated in accordance with a timing at which the mobile object arrives at the updated position. Therefore, the update position determiner 106 determines the update position of each mobile object. The mobile object operates in accordance with the travel plan before update (travel timing schedule before update) until the mobile object reaches the update position, and, after the mobile object reaches the update position, the mobile object operates in accordance with the updated travel plan (updated travel timing schedule),” and that, (Paragraph [0114], Lines 3-5) “the update position may be an arbitrary position (such as, for example, a current position of the mobile object,” as well as that, (Paragraph [0156], Lines 1-4) “In the processing illustrated in FIG. 11, the travel timing scheduler 105 generates or updates the model using the search log added to the search log storage 111 every time the travel timing schedule is updated.”
Aisu additionally teaches, (Paragraph [0170]) “In a case where the replan trigger is not generated (step 19: No), it is judged whether a mobile object which has finished the travel plan (or the travel timing schedule) exists. In a case where a mobile object which has finished the travel plan exists (step 20: Yes), the processing returns to step 11. In a case where a mobile object which has finished the travel plan does not exist (step 20: No), the processing returns to step 18. The processing from step 18 to step 20 is repeated until the replan trigger is generated or until a mobile object which has finished the travel plan occurs.”
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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Aisu in view of Jin et al. (US 2018/0336781 A1, hereinafter Jin)
Claim 7 Discloses:
“The control method according to claim 1, wherein the model is a probability distribution of the delay time.”
Aisu does not explicitly teach an embodiment wherein the model is a probability distribution of the delay time.
Aisu does teach a model which determines the delay time of traveling mobile objects. Aisu teaches, (Paragraph [0203], Lines 1-2) “the evaluation value is calculated (predicted) using the model in step S26 in the description of the flowchart in FIG. 12,” wherein, (Paragraph [0203], Lines 7-9) “a delay time (set as a delay time X) to adjust time for solving conflict in the tentative travel timing schedule.”
However, it would be obvious to a person of ordinary skill in the art to apply an explicit probability distribution model such as the one described in Jin to determine the delay time per route segment.
Jin is relevant to the Applicant’s disclosure due to teaching a system designed to reduce, (Abstract, Lines 15-16) “Traffic conflicts between motor vehicles, pedestrians and non-motor vehicles,” which is additionally capable of, “obtaining prediction values of traffic flows of one or more road sections in the road network and prediction values of road traffic at intersections of the one or more road sections according to the traffic condition prediction result,” wherein, (Paragraphs [0045-0047]) “In implementations, determining the control scheme by calculating the minimum value of the linear objective function includes: selecting a probability density function according to a negative exponential distribution fulfilled in a time interval between arrivals of motor vehicles at areas where the motor vehicles conflict with pedestrians; and calculating an average pedestrian delay time according to the negative exponential distribution and the probability density function.”
Jin additionally teaches, (Paragraph [0048]) “the total delay time is equal to a sum of the following three parts,” the first part being, (Paragraph [0049]) “the delay time for motor vehicles in the road flow direction being equal to a sum of vehicle delay times for motor vehicles on all branches, wherein a vehicle delay time for motor vehicles on each branch is equal to a product of an average delay time for each motor vehicle on the respective branch and an instantaneous vehicle flow of the respective branch in the road flow direction; and the average delay time for each motor vehicle on the respective branch is equal to a sum of an average signal delay time of the respective branch in the road flow direction and an average motor vehicle delay time caused by a conflicting area between motor vehicles and pedestrians.”
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to combine the vehicle control system of Aisu which calculates a delay time for a plurality of passageways in order to avoid conflicts, with the methodology of implementing a probability distribution model as taught by Jin, which solves a similar vehicle conflict/delay time per route segment problem with said probability distribution function, in order to yield predictable results.
Combining the references would yield the benefits of identifying potential vehicle delays/collisions by accounting for the probability that inconsistent time based delays occur during the route plan on particular segments, and making adjustments accordingly. As Jin describes, “when motor vehicle delay data and pedestrian waiting time length data for a road section have been obtained, the influences of traffic control effects on traffic subjects can be actually assessed according to these two types of data, thus determining a control direction for improving the traffic condition. The actual traffic condition assessment result is equivalent to a negative feedback in a feedback system in the present embodiment. The actual effects of a control scheme can be assessed according to the actual traffic condition assessment result, and a corresponding adjustment is thereby made.”
RELEVANT, BUT NOT CITED PRIOR ART
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Nguyenquang et al. (US 20220075381 A1) teaches, (Abstract) “An automatic vehicle dispatching system is applied to a factory where manufacturing operation devices reside, and includes an optimization server, a management server, and AGVs. The management server controls transfer of the AGVs and transmits a current transport request received from one of the manufacturing operation devices to the optimization server. The optimization server predicts a future transport request to be issued by each of other manufacturing operation devices using predicted transport request interval patterns, and generates allocation models by allocating AGVs to each transport request in different patterns. The optimization server predicts required transfer times for the allocated AGVs and adds up the required transfer times for each allocation model. The optimization server selects one allocation model having a smallest sum of the required transfer times, generates a transfer instruction for the current transport request based on the selected allocation model, and transmits the instruction to the management server.”
Nguyenquang et al. (US 20220380128 A1) teaches, (Abstract) “A conveyance system according to this disclosure includes a movement request acceptor which accepts a movement request to an automatic conveying device; and a section travel-route setter which sets a section travel route with a predetermined length constituting a part of a travel route from a current position of a first automatic conveying device to a destination position so that the section travel route of the first automatic conveying device does not overlap the section travel route set for another second automatic conveying device on the basis of the movement request accepted by the movement request acceptor, in which the section travel-route setter repeatedly executes processing of setting a second section travel route with an end position of a first section travel route as a start position of the subsequent second section travel route while the automatic conveying device is traveling on the first section travel route.”
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALEXANDER V. GENTILE whose telephone number is (703)756-1501. The examiner can normally be reached Monday - Friday 9-5.
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/ALEXANDER V GENTILE/Examiner, Art Unit 3664
/KITO R ROBINSON/Supervisory Patent Examiner, Art Unit 3664
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