DETAILED ACTION
Claims 1-9 are pending. Claims dated 10/14/2025 are being examined.
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 .
Response to Arguments
35 U.S.C. § 101:
Claim 1 was amended to recite “a fourth step of distributing and setting the plurality of robot routes to a plurality of the moving bodies so that each moving body of the plurality of moving bodies moves along a corresponding set route of the plurality of robot routes”. The Examiner maintains previously set forth 101 rejections to the claims as these additional steps amount to additional mental processes.
35 U.S.C. § 112(b):
The claims have been amended to remove the unclear limitations. Accordingly, the Examiner has withdrawn the previously set forth 112(b) rejections to the claims.
35 U.S.C. § 103:
Applicant’s arguments filed 10/14/2025 with respect to claims have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-9 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
101 Analysis – Step 1:
Independent claim 1 is directed to a method. Therefore, claim 1 is within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong I:
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the following groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
Independent claim 1 includes limitations that recite an abstract idea (emphasized below) and will be used as a representative claim for the remainder of the 101 rejections. Claim 1 recites:
(Claim 1) A route generation method causing a computer to execute:
a first step of acquiring an order in which a moving body passes through a plurality of destination points by a shortest route after departing from a departure point;
a second step of generating a route of the moving body for passing through the plurality of destination points by moving multiple times from the departure point, based on the order acquired in the first step;
a third step of dividing the route into a plurality of robot routes; and
a fourth step of distributing and setting the plurality of robot routes to a plurality of the moving bodies so that each moving body of the plurality of moving bodies moves along a corresponding set route of the plurality of robot routes.
The Examiner submits that the foregoing bolded limitation(s) constitute “mental processes” – concepts performed in the human mind (including an observation, evaluation, judgment, opinion) (see MPEP § 2106.04(a)(2), subsection III) because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind.
Specifically, the limitation: “a first step of acquiring an order for passing through the plurality of destination points by a shortest route” in the context of this claim encompasses mental observation. For example, a delivery driver can acquire an order by determining that going from house 1 to house 2 to house 3 leads to a shortest route.
The limitation: “a second step of generating a route of the moving body for passing through the plurality of destination points by moving multiple times from the departure point, based on the order acquired in the first step” in the context of this claim encompasses mental evaluation. For example, the delivery driver can generate a route based on the order and known map/street/road data. For example, a delivery driver can depart from a warehouse, and drive multiple times from the warehouse by going to house 1, going back to the warehouse to reload, then going to house 2, and lastly going to house 3.
The limitation: “a third step of dividing the route into a plurality of robot routes” in the context of this claim encompasses mental evaluation. For example, the delivery driver can determine that completing delivery at each house will be completed faster with two drivers, and can divide the route into two portions. The route can be divided into a first sub-route and a second sub-route.
The limitation: “a fourth step of distributing and setting the plurality of robot routes to a plurality of the moving bodies so that each moving body of the plurality of moving bodies moves along a corresponding set route of the plurality of robot routes” in the context of this claim encompasses mental evaluation. For example, the delivery driver can determine that he/she can drive the first sub-route, and a second delivery driver can drive the second sub-route.
Accordingly, the claim recites at least one abstract idea.
101 Analysis – Step 2A, Prong II:
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract idea(s) into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional” limitations” while the bolded portions continue to represent the “abstract idea”):
(Claim 1) A route generation method causing a computer to execute:
a first step of acquiring an order in which a moving body passes through a plurality of destination points by a shortest route after departing from a departure point;
a second step of generating a route of the moving body for passing through the plurality of destination points by moving multiple times from the departure point, based on the order acquired in the first step;
a third step of dividing the route into a plurality of robot routes; and
a fourth step of distributing and setting the plurality of robot routes to a plurality of the moving bodies so that each moving body of the plurality of moving bodies moves along a corresponding set route of the plurality of robot routes.
For the following reason(s), the Examiner submits that the above identified additional elements do not integrate the above-noted abstract idea into a practical application.
Regarding the additional limitations of “the route generation method causing a computer to execute”, the claimed computer is a generic computer component and acts merely as a tool to perform the aforementioned abstract ideas, and does not amount to significantly more than a judicial exception. See MPEP 2106.05(f), additional elements that invoke computers or other machinery merely as a tool to perform an existing process will generally not amount to significantly more than a judicial exception.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, that reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B:
Regarding Step 2B of the 2019 PEG, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application.
Further, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B to determine if they are more than what is well understood, routine, conventional activity in the field. All the additional limitations are well-understood, routine, and conventional activity as exemplified by the cited art for the 35 USC § 103 claim rejection of claim 1. Furthermore, generally applying an exception using a generic computer component/tool cannot provide an inventive concept. Hence, the claim is not patent eligible.
Dependent claims 2-9 do not recite any further limitations that cause the claims to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception that may also be reasonably performed in the human mind, specifically only reciting/elaborating on the generation of the order and route.
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 for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-4 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Saito et al. (JP-2021043505-A, as cited in the IDS dated 02/28/2024), in view of Tajammul et al. (US-20190195638-A1), in view of Williams et al. (US-20220364866-A1) and herein after will be referred to as Saito, Tajammul, and Williams respectively.
Regarding claim 1, Saito teaches a route generation method ([0040] the execution order of executing the services in the order of delivery destinations A, B, and C from the vehicle base is determined), the route generation method causing a computer to execute:
a first step of acquiring an order in which a moving body passes through a plurality of destination points by a shortest route after departing from a departure point ([0022] The execution order determination unit 14 has a function of determining the execution order of a plurality of services by calculating the execution order as a combinatorial optimization problem; [0025] Furthermore, the execution order determination unit 14 may execute the execution order determination process in a plurality of situations, for example, by changing parameters, and may store a plurality of patterns of execution order solutions. Here, one example of generating multiple solution patterns is to generate multiple patterns such as a pattern in which the travel time is set as a parameter to a short time; [0027] Furthermore, the execution location specific information may include surrounding cost information including the cost value of a U-turn at the execution location of each service. […] Such peripheral cost information is used to calculate the total cost value of each route and determine the route with the smallest cost value as the optimum route);
a second step of generating a route of the moving body for passing through the plurality of destination points by moving multiple times […], based on the order acquired in the first step ([0028] The optimum route determination unit 16 has a function of determining an optimum route including information on the optimum stopping position and/or the optimum stopping direction at each execution point, using the execution order and the execution point specific information; [0041] FIG. 12B illustrates a case where a conventional shortest route search process is performed in the situation of FIG. 12A; [0045] The optimum route determination process is carried out…).
Saito does not explicitly teach: moving multiple times from the departure point.
However, Tajammul teaches generating a route optimized with moving multiple times from the departure point (FIG. 5 return-to-depot; [0009] a user of the route planning platform can wish to compare metrics associated with different route plans, calculated for different route planning scenarios associated with the route planning information (e.g., such that the user can identify a most cost-effective route plan, a route plan with a shortest total driving time, a route plan with a number of violations that is below a threshold, and/or the like); [0056] Additionally, or alternatively, the scenario information can include information that identifies a configuration associated with the route planning scenario. The configuration can include a preference, a constraint, a setting, and/or the like, associated with generating a route plan for the route planning scenario […] As another example, the configuration can include an indication of whether vehicles are permitted to return to a start location during a route (e.g., such that the vehicles can be used for multiple routes)).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the present claimed invention to modify the moving multiple times as taught in Saito to incorporate the teachings of Tajammul to include moving multiple times from the departure point, with a reasonable expectation of success since doing so would have achieved the benefit of “allowing vehicles to return to their starting location during a route to reset their load capacity” (Tajammul FIG. 5) and so that “the vehicles can be used for multiple routes” (Tajammul [0056]).
Saito, in view of Tajammul does not explicitly teach: a third step of dividing the route into a plurality of robot routes; and a fourth step of distributing and setting the plurality of robot routes to a plurality of the moving bodies so that each moving body of the plurality of moving bodies moves along a corresponding set route of the plurality of robot routes.
However, Williams teaches a third step of dividing a route into a plurality of robot routes (FIG. 5 route is divided into 4 segments with Car 1 picking up cargo at Location 1 and delivering to Location 2, Car 2 picking up cargo at Location 2 and delivering to Location 3, and Car 3 picking up cargo at Location 3 and delivering to Location 4);
and a fourth step of distributing and setting the plurality of robot routes to a plurality of the moving bodies so that each moving body of the plurality of moving bodies moves along a corresponding set route of the plurality of robot routes ([0146] In the illustrated embodiment, task 500 may be associated with cargo including an object and/or cargo including a person. In the first portion (I) of task 500, Car 1 picks up the cargo at a Location 1, an original pick-up location associated with task 500. Car 1 delivers the cargo to a Location 2, and completes the first portion (I) of task 500. The second portion (II) of task 500 is initiated by Car 2, which picks up the cargo at Location 2 and delivers the cargo to a Location 3. The second portion (II) of task 500 is completed. The third portion (III) of task 500 is initiated by Car 3, which picks up the cargo at Location 3 and delivers the cargo to a Location 4, an original delivery location associated with task 500. The third portion (III) of task is completed, and task 500 is completed).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the present claimed invention to modify the route as taught in Saito, in view of Tajammul to incorporate the teachings of Williams to include a third step of dividing the route into a plurality of robot routes; and a fourth step of distributing and setting the plurality of robot routes to a plurality of the moving bodies so that each moving body of the plurality of moving bodies moves along a corresponding set route of the plurality of robot routes, with a reasonable expectation of success since doing so would have achieved the benefit of, rather than optimizing delivery routing for only one vehicle, “optimizing delivery routing for a plurality of vehicles” (Williams [0004]).
Regarding claim 2, Saito, as modified, teaches the route generation method according to claim 1.
Saito also teaches wherein the route is a route for passing through the plurality of destination points in an order identical to the order acquired in the first step ([0025] Furthermore, the execution order determination unit 14 may execute the execution order determination process in a plurality of situations, for example, by changing parameters, and may store a plurality of patterns of execution order solutions. Here, one example of generating multiple solution patterns is to generate multiple patterns such as a pattern in which the travel time is set as a parameter to a short time; [0028] The optimum route determination unit 16 has a function of determining an optimum route including information on the optimum stopping position and/or the optimum stopping direction at each execution point, using the execution order and the execution point specific information).
Regarding claim 3, Saito, as modified, teaches the route generation method according to claim 1.
Saito also teaches wherein in the first step, the computer generates the order based on information indicating positions of the plurality of destination points ([0025] Furthermore, the execution order determination unit 14 may execute the execution order determination process in a plurality of situations, for example, by changing parameters, and may store a plurality of patterns of execution order solutions. Here, one example of generating multiple solution patterns is to generate multiple patterns such as a pattern in which the travel time is set as a parameter to a short time; [0027] Furthermore, the execution location specific information may include surrounding cost information including the cost value of a U-turn at the execution location of each service. […] Such peripheral cost information is used to calculate the total cost value of each route and determine the route with the smallest cost value as the optimum route).
Regarding claim 4, Saito teaches the route generation method according to claim 1.
Saito, as modified, also teaches wherein the route is a route along which the moving body delivers articles at the departure point to the plurality of destination points ([0040] the execution order is determined such that services are executed from the vehicle base to delivery destinations A, B, and C in that order; [0048] This can be applied not only to delivery services, but also to any industry that involves traveling to multiple locations with one or more vehicles, such as wholesale to stores, vending machine maintenance, home medical/care visits, and shared taxis).
Regarding claim 7, Saito, as modified, teaches the route generation method according to claim 1.
Saito also teaches wherein in the second step, the computer generates the route, based on information indicating a distance between points including the departure point and the plurality of destination points, and ([0027] Furthermore, the execution location specific information may include surrounding cost information including the cost value of a U-turn at the execution location of each service. Here, the peripheral cost information refers to information required to calculate cost information of the execution point of the service. An example of the surrounding cost information is the cost value of a U-turn. When the arrival direction and departure direction for a stop position candidate around the execution point are different, a U-turn needs to be made at the stop position candidate. If the location allows easy U-turning, the cost value is set small, whereas if the location allows difficult U-turning, the cost value is set large. Such peripheral cost information is used to calculate the total cost value of each route and determine the route with the smallest cost value as the optimum route. For example, a U-turn would be necessary if the method was based solely on the shortest travel distance, but if the U-turn is in a very difficult location, it may take a long time to make the turn even though it is the shortest distance. In this way, by using the surrounding cost information, it becomes possible to determine the optimal route using information other than distance)
information indicating a speed of the moving body between the points ([0027] Moreover, the surrounding cost information may be information that sets a cost value for a road to be used as a route. That is, it is conceivable that the cost value can be used to adjust the selection of roads, such as by setting a high cost value for roads that are narrow and slow to travel due to low speeds).
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Saito, in view of Tajammul, in view of Williams, in further view of Ito et al. (WO-2019181895-A1, as cited in the IDS dated 02/28/2024), and herein after will be referred to as Ito.
Regarding claim 4, Saito, as modified, teaches the route generation method according to claim 4.
Saito does not explicitly teach wherein in the second step, the computer generates the route, based on a quantity of the articles capable of being loaded onto the moving body at the departure point, and a quantity of the articles to be delivered to each of the plurality of destination points.
However, Ito teaches wherein in the second step, the computer generates the route, based on a quantity of the articles capable of being loaded onto the moving body at the departure point, and a quantity of the articles to be delivered to each of the plurality of destination points ([0029] The order DB 70 accumulates information (order information Io) relating to orders received via each customer terminal 20. The inventory DB 72 accumulates information regarding inventory (inventory information Is). The mobile object DB 74 accumulates individual information Ii regarding the drones 30 and delivery vehicles 32 used for delivery. The individual information Ii includes, for example, the identification information (identification ID) of the moving object, the type (drone, vehicle, etc.), the maximum load weight, and the maximum dimensions of the loadable cargo. Furthermore, the individual information Ii may include one or more of fuel efficiency, maximum speed, years of operation, total travel distance, number of loadable items, maximum number of people available, and the current location of the moving object; [0115] In addition, the service server 22 calculates the total T of the travel cost C (travel evaluation value) from the starting point Pst to the destination Ptar for each route option RTop based on the unit division information Isu and individual information Ii from the starting point Pst to the destination Ptar (S94). Furthermore, the service server 22 selects a target moving object 26tar that is actually moving among the moving objects 26 and a movement route RTm to be used by the target moving object 26tar among the route options RTop, based on the total T of the movement costs C (S95, S96).).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the present claimed invention to modify the generation of the route as taught in Saito, as modified, to incorporate the teachings of Ito to include wherein in the second step, the computer generates the route, based on a quantity of the articles capable of being loaded onto the moving body at the departure point, and a quantity of the articles to be delivered to each of the plurality of destination points, with a reasonable expectation of success since doing so would have achieved the benefit of taking into consideration the amount of load that a mobile body carries, which by extension allows for a more optimized route.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Saito, in view of Tajammul, in view of Williams, in further view of Ur (US-20200286033-A1), and herein after will be referred to as Ur.
Regarding claim 6, Saito, as modified, teaches the route generation method according to claim 1.
Saito, as modified, does not explicitly teach wherein in the second step, the computer generates the route, based on information indicating a distance by which the moving body is continuously movable from a charging point at which the moving body is charged, and information indicating positions of the departure point, the plurality of destination points, and the charging point.
However, Ur teaches wherein in the second step, the computer generates the route, based on information indicating a distance by which the moving body is continuously movable from a charging point at which the moving body is charged, and information indicating positions of the departure point, the plurality of destination points, and the charging point ([0084] In some exemplary embodiments, the route may be determined based on additional limitations, such as an initial energy level of a power source of the drone, expected power consumption of the drone at each leg, based on expected charging of the power source at each leg, or the like. The route may be planned so as to be feasible for the drone in view of energy available to the drone. As an example, in case the power in the drone is not sufficient to fly in the leg from A to B, the leg may be divided into sub-legs, A to E, E to F, and F to D. The drone may be planned to fly from A to E, land on a second vehicle from E to F, while saving energy or re-charging; and then fly from E to B where the drone can catch the vehicle and ride thereon; [0120] As energy and power may be a limiting factor on drones operating distance and duration, Route 200 may be further determined based on the energy element of the drone. Route 200 may be planned so as to be feasible for the drone in view of energy available to the drone. In some exemplary embodiments, Route 200 may be further determined based on an initial energy level of a power source of the drone. A maximal length and a duration of legs in Route 200 may be determined on the initial energy level and the distance the drone can fly with such level. Additionally or alternatively, Route 200 may be further determined based on expected power consumption of the drone at each leg. As an example, during legs that the drone is configured to ride on a vehicle, the drone may be shut down, or recharged, accordingly, there may be no limitation on such legs. As opposed to legs that the drone is planned to fly, the duration and distance of such legs may be determined based on the expected power consumption of the drone in these legs. Different elements may affect the expected power consumption of the drone of each leg, such as the weight of the package, expected air resistance in the area the drone is planned to fly in, expected whether, or the like. Additionally or alternatively, Route 200 may be further determined based on expected charging of the power source at each leg. As an example, the duration of a leg of the first portion may be determined based on the expected charging of the power source at the preceding leg where the drone is landing on a vehicle and charging thereon).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the present claimed invention to modify the route generation as taught in Saito, as modified, to incorporate the teachings of Ur to include wherein in the second step, the computer generates the route, based on information indicating a distance by which the moving body is continuously movable from a charging point at which the moving body is charged, and information indicating positions of the departure point, the plurality of destination points, and the charging point, with a reasonable expectation of success since doing so would have achieved the benefit of a feasible route (Ur [0084]), ensuring the power does not run out while traversing the route.
Claims 8-9 are rejected under 35 U.S.C. 103 as being unpatentable over Saito, in view of Tajammul, in view of Williams, in further view of Harasaki (US-20160232786-A1, as cited in the IDS dated 02/28/2024), and herein after will be referred to as Harasaki.
Regarding claim 8, Saito, as modified, teaches the route generation method according to claim 1.
Saito, as modified, does not explicitly teach: wherein the moving body includes a plurality of moving bodies, and the route is each route of the plurality of moving bodies along which the plurality of moving bodies share and pass through the plurality of destination points.
However, Harasaki teaches wherein the moving body includes a plurality of moving bodies (FIG. vehicles 5A, 5B), and the route is each route of the plurality of moving bodies along which the plurality of moving bodies share and pass through the plurality of destination points (FIG. 1 shared traveling routes R1-R4 passing through points P1-P4).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the present claimed invention to modify Saito, as modified, to incorporate the teachings of Harasaki to include wherein the moving body includes a plurality of moving bodies, and the route is each route of the plurality of moving bodies along which the plurality of moving bodies share and pass through the plurality of destination points, with a reasonable expectation of success since doing so would have achieved the benefit of considering for other vehicles (Harasaki [0008]), and to achieve the benefit of less collision risk as a one-way traffic/route is well-known to have less collision risk than two-way traffic/route(s).
Regarding claim 9, Saito, as modified, teaches the route generation method according to claim 8.
Saito, as modified, does not explicitly teach: wherein each route of the plurality of moving bodies is a route along which the plurality of moving bodies do not pass through a same point in different directions.
However, Harasaki teaches wherein each route of the plurality of moving bodies is a route along which the plurality of moving bodies do not pass through a same point in different directions (FIG. 4 one-way traveling route; [0073] Hereinafter, assuming that the loop travelling routes R11, R12 and retraction route R13 are set such that the travelling vehicle 5 travels in a one-way clockwise manner).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the present claimed invention to modify Saito, as modified, to incorporate the teachings of Harasaki to include wherein each route of the plurality of moving bodies is a route along which the plurality of moving bodies do not pass through a same point in different directions, with a reasonable expectation of success since doing so would have achieved the benefit of considering for other vehicles (Harasaki [0008]), and to achieve the benefit of less collision risk as a one-way traffic/route is well-known to have less collision risk than two-way traffic/route(s).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20210025715 A1: Benjamin FIG. 3A shows generation of a route from departure point R1 to C1, back to R1, to C2 then C3
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 extension fee 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 date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAVIN SEOL whose telephone number is (571) 272-6488. The examiner can normally be reached on Monday-Friday 9:00 a.m. to 5:00 p.m.
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/DAVIN SEOL/Examiner, Art Unit 3662
/JELANI A SMITH/Supervisory Patent Examiner, Art Unit 3662