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 .
This is the first office action on the merits and is responsive to the papers filed on 9/4/2025. Claims 1-20 are currently pending.
Information Disclosure Statement
1. The Information Disclosure Statement (IDS) submitted on 6/10/2026 has been considered by the Examiner.
Specification
2. The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
3. Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Any claim not specifically mentioned, including Claims 2-19, have been included based on its dependency.
4. Claim 1 recites the limitation "a mobile device" in Lines 2 and 5. There is insufficient antecedent basis for this limitation in the claim. More specifically, it is unclear if the mobile devices in Lines 2 and 5 are the same. Under the broadest reasonable interpretation, the mobile devices are interpreted as the same. Claim 20 has the same limitations as Claim 1 except for is it a separate independent claim but is rejected for the same reasoning.
5. The term “recent” in Claim 1 is a relative term which renders the claim indefinite. The term “recent” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. Under the broadest reasonable interpretation, “recent” is interpreted as any previous state of the mobile device. Claim 20 has the same limitations as Claim 1 except for is it a separate independent claim but is rejected for the same reasoning.
Claim Rejections - 35 USC § 103
6. 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.
7. 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.
8. 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.
9. Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang (US 20250216847 A1) in view of Couleaud (US 20240426621 A1).
10. Regarding Claim 1, Zhang teaches a method for operating a mobile device, the method comprising: receiving, at the mobile device: an initial plurality of state tokens, wherein each of the initial plurality of state tokens corresponds to transformer model data reflecting at least one previous state of a mobile device (Zhang: [0034]);
And sensor data, from a set of one or more sensors that are appended to the mobile device (Zhang: [0053]);
Determining at least one sub-task for the mobile device by inputting the initial plurality of state tokens into a particular large language model (Zhang: [0031]);
Encoding the sensor data into a plurality of patch tokens, by inputting the sensor data into at least one vision transformer, wherein: each of the plurality of patch tokens reflects at least one recent state of the mobile device (Zhang: [0034] and [0038]);
And the at least one recent state corresponds to a period before the at least one previous state (Zhang: [0033] and [0034]);
Updating the initial plurality of state tokens into an updated plurality of state tokens by inputting the initial plurality of state tokens into at least one cross-attention transformer, wherein: each of the updated plurality of state tokens corresponds to transformer model data reflecting the at least one recent state of the mobile device; and the initial plurality of state tokens are updated based on the plurality of patch tokens and the at least one sub-task (Zhang: [0049] and [0050]);
Producing, by the mobile device, a set of navigation waypoints from the updated plurality of state tokens… (Zhang: [0047] and [0094]);
And controlling the mobile device according to the set of navigation waypoints (Zhang: [0027] and [0059]).
Zhang does not explicitly teach that each of the set of navigation waypoints represents a distinct destination for the mobile device. However, Zhang teaches that a sequence of waypoints is predicted for the AV in at least [0047] and [0094].
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date to produce a set of navigation waypoints representing a distinct destination for the mobile device as similarly shown in Zhang's [0047] and [0094] use of predicted waypoints. This provides the benefit of turning the waypoints into control commands for the vehicle to navigation to each waypoint destination.
Additionally, in the same field of endeavor, Couleaud teaches producing, by the mobile device, a set of navigation waypoints from the updated plurality of state tokens, wherein each of the set of navigation waypoints represents a distinct destination for the mobile device (Couleaud: [0043] and [0046]).
Zhang and Couleaud are considered to be analogous to the claim invention because they are in the same field of vehicle navigation and control. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Zhang to incorporate the teachings of Couleaud to produce a set of waypoints representing distinct destination for the mobile device because it provides the benefit of a selecting a route that passes through waypoints based on the user preferences as explicitly explained in [0008].
11. Regarding Claim 2, Zhang and Couleaud remains as applied above in Claim 1, and further, Zhang teaches the mobile device is an autonomous vehicle (Zhang: [0018]).
12. Regarding Claim 3, Zhang and Couleaud remains as applied above in Claim 1, and further, Zhang teaches the set of one or more sensors includes at least one camera (Zhang: [0053]).
13. Regarding Claim 4, Zhang and Couleaud remains as applied above in Claim 1, and further, Zhang teaches encoding the sensor data into the plurality of patch tokens further comprises adding learned ray embeddings, produced using at least one Multi-Layer Perceptron (MLP), into each of the plurality of patch tokens (Zhang: [0034]).
14. Regarding Claim 5, Zhang and Couleaud remains as applied above in Claim 1, and further, Zhang teaches producing the set of navigation waypoints comprises producing, using a primary query decoder and the updated plurality of state tokens, at least one proposed path for the mobile device (Zhang: [0039] and [0044]).
15. Regarding Claim 6, Zhang and Couleaud remains as applied above in Claim 5, and further, Zhang teaches the primary query decoder comprises at least one Diffusion Policy Decoder (Zhang: [0039]).
16. Regarding Claim 7, Zhang and Couleaud remains as applied above in Claim 5, and further, Couleaud teaches decoding a natural language query into a decoded query using a secondary query decoder, wherein the natural language query is received through a user interface (Couleaud: [0008] and [0040]).
17. Regarding Claim 8, Zhang and Couleaud remains as applied above in Claim 7, and further, Couleaud teaches projecting an answer to the decoded query on the user interface, wherein the answer to the decoded query is based on the updated plurality of state tokens and the sensor data (Couleaud: [0008] and [0058]).
18. Regarding Claim 9, Zhang and Couleaud remains as applied above in Claim 7, and further, Couleaud teaches the secondary query decoder…operates more slowly than the primary query decoder (Couleaud: [0008] and [0060] Note that the second query decoder operating more slowly than the primary decoder is equivalent to receiving multiple user inputs to determine waypoints because sensor data is determined in real-time. Under the broadest reasonable interpretation, the operation is interpreted as the start time data is input to the output. One of ordinary skill in the art would recognize that it takes time to speak a sentence as multiple inputs compared to sensor data which is continuously updated.).
Zhang in view of Couleaud discloses the claimed invention except for an additional large language model. It would have been obvious to one having ordinary skill in the art at the time the invention was made to include an additional large language model, since it has been held that mere duplication of the essential working parts of a device involves only routine skill in the art, St. Regis Paper Co. v. Bemis Co., 193 USPQ 8.
19. Regarding Claim 10, Zhang and Couleaud remains as applied above in Claim 7, and further, Zhang teaches the particular large language model, the at least one vision transformer, the at least one cross-attention transformer, the primary query decoder, and the secondary query decoder are components of a foundation model (Zhang: [0017] Note that the GPT model is a foundation model and includes all the components.).
20. Regarding Claim 11, Zhang and Couleaud remains as applied above in Claim 6, and further, Zhang teaches the at least one proposed path is produced using a specific cross-attention transformer included in the primary query decoder, according to keys and values derived from the updated plurality of state tokens (Zhang: [0049] and [0050]).
21. Regarding Claim 12, Zhang and Couleaud remains as applied above in Claim 7, and further, Zhang teaches the primary decoder operates on the mobile device (Zhang: [0033] Note that the Fig. 1 includes the trajectory GPT model as part of the autonomous vehicle [operates on mobile device].).
Zhang fails to teach the secondary decoder operates on a remote server that is communicatively coupled to the mobile device.
However, in the same field of endeavor, Couleaud teaches the secondary decoder operates on a remote server that is communicatively coupled to the mobile device (Couleaud: [0120]).
Zhang and Couleaud are considered to be analogous to the claim invention because they are in the same field of vehicle navigation and control. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Zhang to incorporate the teachings of Couleaud for the second decoder to operate on a remote server because it provides the benefit of retrieving data on demand and to process instructions in accordance with the input to generate a display as explicitly explained in [0120] of Couleaud.
22. Regarding Claim 13, Zhang and Couleaud remains as applied above in Claim 5, and further, Zhang teaches a given path of the at least one proposed path is selected from the group consisting of: a planned spatial path comprising a set of spatially-separated points with consistent spacing (Zhang: [0039] and [0044] Note that one of ordinary skill in the art would recognize that a candidate trajectory comprises a plurality of waypoints from the start point to the destination point. This is equivalent to a set of spatially separated points with consistent spacing.);
A planned temporal path comprising a set of temporally-separated points with consistent spacing, derived according to a linear speed of the mobile device (Zhang: [0028]);
And a left boundary and a right boundary for the mobile device (Zhang: [0018] and [0061]).
23. Regarding Claim 14, Zhang and Couleaud remains as applied above in Claim 1, and further, Zhang teaches the plurality of patch tokens comprises encodings of at least one of: an estimate of a kinematic state of the mobile device, wherein the estimate comprises a linear speed of the mobile device and an angular speed of the mobile device; a set of dimensions for the mobile device; or a set of route instructions that are pre-determined for the mobile device (Zhang: [0033] and [0042]).
24. Regarding Claim 15, Zhang and Couleaud remains as applied above in Claim 1, and further, Zhang teaches updating the initial plurality of state tokens comprises inputting the plurality of patch tokens and the at least one sub-task into a state aggregator (Zhang: [0049] and [0050]).
25. Regarding Claim 16, Zhang and Couleaud remains as applied above in Claim 15, and further, Zhang teaches producing a set of queries from the initial plurality of state tokens; generating answers to the set of queries, using a cross-attention transformer included in the state aggregator, according to keys and values derived from the plurality of patch tokens and the at least one sub-task; and applying the answers to updating the initial plurality of state tokens (Zhang: [0050]).
26. Regarding Claim 17, Zhang and Couleaud remains as applied above in Claim 16, and further, Zhang teaches inputting the updated plurality of state tokens into at least one of a feed-forward network or a self-attention network (Zhang: [0042], [0043], and [0050]).
27. Regarding Claim 18, Zhang and Couleaud remains as applied above in Claim 17, and further, Zhang teaches the at least one of the feed-forward network or the self-attention network is incorporated into the state aggregator (Zhang: [0042], [0043], and [0050]).
28. Regarding Claim 19, Zhang and Couleaud remains as applied above in Claim 1, and further, Zhang teaches a quantity of the initial plurality of state tokens remains constant when updated into the updated plurality of state tokens (Zhang: [0049] and [0050]).
29. Regarding Claim 20, Zhang teaches a method for operating a mobile device, the method comprising: receiving, at the mobile device: an initial plurality of state tokens, wherein each of the initial plurality of state tokens corresponds to transformer model data reflecting at least one previous state of a mobile device (Zhang: [0034]);
And sensor data, from a set of one or more sensors that are appended to the mobile device (Zhang: [0053]);
Determining at least one sub-task for the mobile device by inputting the initial plurality of state tokens into a particular large language model (Zhang: [0031]);
Encoding the sensor data into a plurality of patch tokens, by inputting the sensor data into at least one vision transformer, wherein: each of the plurality of patch tokens reflects at least one recent state of the mobile device (Zhang: [0034] and [0038]);
And the at least one recent state corresponds to a period before the at least one previous state (Zhang: [0033] and [0034]);
Updating the initial plurality of state tokens into an updated plurality of state tokens by inputting the initial plurality of state tokens into at least one cross-attention transformer, wherein: each of the updated plurality of state tokens corresponds to transformer model data reflecting the at least one recent state of the mobile device (Zhang: [0049] and [0050]);
A quantity of the initial plurality of state tokens remains constant when updated into the updated plurality of state tokens (Zhang: [0049] and [0050]);
And the initial plurality of state tokens are updated based on the plurality of patch tokens and the at least one sub-task (Zhang: [0049] and [0050]);
Producing, by the mobile device, a set of navigation waypoints from the updated plurality of state tokens, wherein: producing the set of navigation waypoints comprises producing at least one proposed path for the mobile device (Zhang: [0047] and [0094]),
Wherein the at least one proposed path is produced using a specific cross-attention transformer included in a primary query decoder, according to keys and values derived from the updated plurality of state tokens (Zhang: [0049] and [0050]);
Controlling the mobile device according to the set of navigation waypoints (Zhang: [0027] and [0059]);
And the particular large language model, the at least one vision transformer, the at least one cross-attention transformer, the primary query decoder… are components of a foundation model (Zhang: [0017] Note that the GPT model is a foundation model and includes all the components.).
Zhang does not explicitly teach that each of the set of navigation waypoints represents a distinct destination for the mobile device. However, Zhang teaches that a sequence of waypoints is predicted for the AV in at least [0047] and [0094].
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date to produce a set of navigation waypoints representing a distinct destination for the mobile device as similarly shown in Zhang's [0047] and [0094] use of predicted waypoints. This provides the benefit of turning the waypoints into control commands for the vehicle to navigation to each waypoint destination.
Zhang fails to explicitly teach and when a natural language query, corresponding to the mobile device, is received through a user interface of the mobile device: decoding the natural language query into a decoded query using a secondary query decoder, wherein: the secondary query decoder: comprises an additional large language model; and operates more slowly than the primary query decoder… and projecting an answer to the decoded query on the user interface, wherein the answer to the decoded query is based on the updated plurality of state tokens and the sensor data.
However, in the same field of endeavor, Couleaud teaches each of the set of navigation waypoints represents a distinct destination for the mobile device (Couleaud: [0043] and [0046]);
And when a natural language query, corresponding to the mobile device, is received through a user interface of the mobile device: decoding the natural language query into a decoded query using a secondary query decoder (Couleaud: [0008] and [0040]);
Wherein: the secondary query decoder… operates more slowly than the primary query decoder (Couleaud: [0008] and [0060] Note that the second query decoder operating more slowly than the primary decoder is equivalent to receiving multiple user inputs to determine waypoints because sensor data is determined in real-time. Under the broadest reasonable interpretation, the operation is interpreted as the start time data is input to the output. One of ordinary skill in the art would recognize that it takes time to speak a sentence as multiple inputs compared to sensor data which is continuously updated.);
And projecting an answer to the decoded query on the user interface, wherein the answer to the decoded query is based on the updated plurality of state tokens and the sensor data (Couleaud: [0008] and [0058]).
Zhang in view of Couleaud discloses the claimed invention except for an additional large language model. It would have been obvious to one having ordinary skill in the art at the time the invention was made to include an additional large language model, since it has been held that mere duplication of the essential working parts of a device involves only routine skill in the art, St. Regis Paper Co. v. Bemis Co., 193 USPQ 8.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL T SILVA whose telephone number is (571)272-6506. The examiner can normally be reached Mon-Tues: 7AM - 4:30PM ET; Wed-Thurs: 7AM-6PM ET; Fri: OFF.
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/MICHAEL T SILVA/Examiner, Art Unit 3663
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