DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Summary
The Amendment filed on 27 January 2026 has been acknowledged.
Claims 1, 16 and 18 are amended.
Claim 2 is cancelled.
Claims 9 – 15, 17 and 19 are withdrawn as result of previous restriction/election.
Currently, claims 1, 3 – 8, 16 and 18 are pending and considered as set forth.
Response to Amendment
Applicant’s amendments to the claims are sufficient to overcome the 35 U.S.C. 101 rejections set forth in the previous office action.
Response to Arguments
The Examiner notes, said applicant’s claim amendment, necessitated the new grounds of rejection. Claims 1, 16 and 18 remain rejected under 35 U.S.C. 102(a)(1) as being unpatentable over Hicok et al., however after a reevaluation of the references, in view of said applicant’s claim amendment, a rearrangement of the rejection occurred.
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 following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 4 – 8, 16 and 18 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Hicok et al. (Hereinafter Hicok) (US 2019/0265703 A1).
As per claim 1, Hicok teaches a map data generation device (See at least paragraph 117; One aspect of an example non-limiting system uses optical sensing such as LIDAR and optical cameras to generate and/or update a dynamic map of the environment the vehicle is operating within.) comprising:
at least one processor or circuit configured to function (See at least paragraph 212; a processor configured to determine the virtual shuttle's performance) as:
an operation data reception unit configured to receive operation data indicating results of a movable apparatus autonomously moving in a space and performing a predetermined operation (See at least abstract; A system and method for an on-demand shuttle, bus, or taxi service able to operate on private and public roads provides situational awareness and confidence displays. The shuttle may include ISO 26262 Level 4 or Level 5 functionality and can vary the route dynamically on-demand, and/or follow a predefined route or virtual rail. The shuttle is able to stop at any predetermined station along the route. The system allows passengers to request rides and interact with the system via a variety of interfaces, including without limitation a mobile device, desktop computer, or kiosks.);
a map data generation unit configured to generate map data which is used when the movable apparatus autonomously moves in the space and performs the predetermined operation on the basis of the operation data (See at least paragraph 30 and 116 – 117; The shuttle may stop at any point along the route, including unplanned stops requested by an on-board traveler or pedestrians wishing to ride on the shuttle. In other embodiments, the shuttle dynamically develops a “virtual rail” by performing a high definition dynamic mapping process while surveying the environment. In one example implementation, the shuttle ecosystem described herein for use on a college or corporate campus provides a seamless traveling experience from any point A to any point B in a campus service area, which may include locations that are on a private campus, off campus, or a combination of both. … dynamic mapping based on LIDAR and other sensors may be desired in less structured environments such as these. Even in such unstructured or less structured driving environments, example non-limiting systems may develop a virtual rail, or such a virtual rail may be predefined for the vehicle. One aspect of an example non-limiting system uses optical sensing such as LIDAR and optical cameras to generate and/or update a dynamic map of the environment the vehicle is operating within. Such mapping may be performed locally on the vehicle, in the cloud, or a combination. One example non-limiting embodiment filters dynamic objects out of the data set so the resulting map consists of static objects that remain stationary within the environment. For example, mapping of a tree-lined campus avenue may result in mapping information related to the trees lining the avenue, but the map excludes the vehicles that are traveling on the avenue, pedestrians walking along the sidewalk, and other dynamic objects. Environments that may be desirable to map include campuses, parking lots, and other relatively unconstrained driving environments. Mapping such environments can be challenging due to the absence of landmarks such as street signs, lane markers, utility or light poles or other regular virtual structures, and the like.);
wherein the operation data reception unit receives the operation data indicating at least one of the number of times of stops during a predetermined period when the movable apparatus autonomously moves in the space and performs the predetermined operation, positions of stops during the predetermined period, times for stops during the predetermined period, the number of times of deviations from a predetermined path and detours during the predetermined period, positions of deviations from the predetermined path and detours during the predetermined period, and times for deviations from the predetermined path and detours during the predetermined period (See at least paragraph 29 – 30; The vehicle in some embodiments is not confined to this virtual rail (for example, it may deviate from it when conditions warrant) but to reduce complexity, the vehicle does not need to generate a new virtual rail “from scratch” every time it navigates across a parking lot it has previously navigated. Such a virtual rail may include definitions of bus stops; stop signs, speed bumps and other vehicle stopping or slowing points; intersections with other paths (which the vehicle may slow down for); and other landmarks at which the vehicle takes specific actions. In some embodiments, the vehicle may be trained on a virtual rail by a human driver and/or receive information concerning the virtual rail definition from another vehicle or other source. However, in some embodiments it is desirable for the vehicle to calibrate, explore/discover, and map its own virtual rail because different vehicles may have different sensor suites. In typical implementations, the vehicle is constantly using its sensor suite to survey its environment in order to update a predefined virtual rail (if necessary, to take environmental changes into the account) and also to detect dynamic objects such as parked cars, pedestrians, animals, etc. that only temporarily occupy the environment, but which nevertheless must be avoided or accommodated. The shuttle may stop at any point along the route, including unplanned stops requested by an on-board traveler or pedestrians wishing to ride on the shuttle);
wherein the operation data reception unit receives, as the operation data, information obtained after filtering such that stops or detours whose cause is detection of a person, an animal, or another movable apparatus is excluded from said number, position and time (See at least paragraph 117 and 121; system uses optical sensing such as LIDAR and optical cameras to generate and/or update a dynamic map of the environment the vehicle is operating within. Such mapping may be performed locally on the vehicle, in the cloud, or a combination. One example non-limiting embodiment filters dynamic objects out of the data set so the resulting map consists of static objects that remain stationary within the environment. … the vehicle performs LIDAR based mapping continually in order to update its map with the most recent information based on the most recent conditions while filtering out dynamic objects (anything that changes relatively rapidly) and instead using dynamic object detection to detect such changing objects. The mapping algorithm in some embodiments may thus provide a sort of hysteresis in which features that remain constant or recurring for more than a certain time period are included in the map, and features that change more rapidly are excluded. Dynamic remapping and surveying may continually revisit map features to determine whether anything new needs to be added (e.g., a newly installed stop sign, or on many college campuses, a new building) or deleted (e.g., a now-removed speed bump)), and
using the generated map to control autonomous movement of a movable apparatus (See at least paragraph 121; In case a new feature is added to the map (e.g., a new bus stop), the vehicle may decide autonomously what (if anything) to do with respect to it or wait for dispatch to notify it of a different or new action to take. Furthermore, the map can be structured for lower speed applications since in many contexts a shuttle will not exceed 20 or 25 mph. A map designed for higher speed autonomous vehicles may not require as much accuracy (for example, there are no speed bumps on a limited access highway except potentially at toll plazas)).
As per claim 4, Hicok teaches limitations of:
wherein the predetermined period has a length equal to or longer than a time during which the movable apparatus autonomously moves in the space and ends performance of the predetermined operation (See at least paragraph 29).
As per claim 5, Hicok teaches limitations of:
wherein the operation data reception unit receives the operation data indicating at least a part of results of the movable apparatus autonomously moving in the space and performing the predetermined operation (See at least abstract, and paragraph 29, and 123 – 124).
As per claim 6, Hicok teaches limitations of:
wherein the map data generation unit further generates, on the basis of the map data, at least one of path data indicating a path for autonomous movement in the space when the movable apparatus autonomously moves in the space and performs the predetermined operation, and region data indicating a region in which the predetermined operation is to be performed in the space when the movable apparatus autonomously moves in the space and performs the predetermined operation (See at least paragraph 29 – 30 and 116 – 117).
As per claim 7, Hicok teaches limitations of:
wherein the at least one processor or circuit is further configured to function as:
an object recognition data reception unit configured to receive object recognition data indicating results of object recognition processing of recognizing an object different from the movable apparatus, and the map data generation unit generates the map data on the basis of the object recognition data (See at least paragraph 119 – 120 and 123).
As per claim 8, Hicok teaches limitations of:
wherein the at least one processor or circuit is further configured to function as:
an evaluation data reception unit configured to receive evaluation data indicating evaluation of a user with respect to results of the movable apparatus autonomously moving in the space and performing the predetermined operation, and the map data generation unit generates the map data on the basis of the evaluation data (See at least paragraph 194).
Regarding claims 16 and 18:
Claims 16 and 18 are rejected using the same rationale, mutatis mutandis, applied to claim 1 above, respectively.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
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.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Hicok in view of Ebrahimi Afrouzi et al. (Hereinafter Ebrahimi) (US 2022/0026920 A1).
As per claim 3, Hicok does explicitly teach limitations of:
wherein the predetermined period has a length shorter than a time during which the movable apparatus autonomously moves in the space and ends performance of the predetermined operation.
Ebrahimi teaches the limtiations of:
wherein the predetermined period has a length shorter than a time during which the movable apparatus autonomously moves in the space and ends performance of the predetermined operation (See at least paragraph 1043).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify creating the dynamic environment mapping of the route of the autonomous vehicle of Hicok, to include run time is reduced and shorter by reducing cost of functioning the autonomous vehicle as taught by Ebrahimi in order to increase efficiency and minimize the length it has to travel for shorter operational time (See paragraph 1043).
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 IG T AN whose telephone number is (571)270-5110. The examiner can normally be reached M - F: 10:00AM- 4:00PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Aniss Chad can be reached at (571) 270-3832. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/IG T AN/Primary Examiner, Art Unit 3662
IG T AN
Primary Examiner
Art Unit 3662