DETAILED ACTION
This office action is responsive to the amendment in the above identified application filed November 16, 2025. Claims 1, 2, 4-6, 8-14 and 16-23 are pending, all examined and rejected.
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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on September 23, 2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
Claims 1, 2, 4-6, 8-14, 16-19 and 21-23 are rejected under 35 U.S.C. 103 as being unpatentable over Xu, U.S. Patent #10,671,068, issued June 2, 2020
in view of Kim, U.S. PG Pub #2020/0004257 published January 2, 2020
With regard to Independent Claim 1,
Xu teaches a method comprising obtaining first information comprising environment information of a terminal in which a first apparatus is located. See e.g., Col. 5:29-33 (“Next, the specification describes a control system that may receive sensor data from different sensors and share sensor data across processing pipelines. An example control system, providing autonomous navigation for a vehicle is then described.”) See also Col. 7:30-32 (“External sensors may be sensors that can monitor one or more aspects of an external environment relative to vehicle…”). The examiner notes that a “vehicle” is a “terminal” and a “sensor” is a “first apparatus” located in the terminal under BRI consistent with the specification.
Xu further teaches receiving second information indicating at least one of region information or time information of the terminal. See e.g., Col. 7:32-39, (discussing various types of sensors, including GPS devices which provide “region information” of the terminal.)
Xu further teaches inputting the first and second information to [a] predefined algorithm to obtain first sensed information for the terminal and outputting the first sensed information. See e.g., Fig. 1 (showing raw sensor data from various sensors – which as explained above can include the claimed “first information” and “second sensors” being passed into processing pipelines (which include various algorithms). At step 182, the processed sensor data from one sensor’s pipeline can be shared with others. Thus, as the pipeline progresses along, the data that is ultimately output is based on both the claimed “first information” and “second information.”
Xu does not explicitly disclose “selecting, from among multiple predefined algorithms in a predefined algorithm set, a predefined algorithm based on the second information, wherein each of the multiple predefined algorithms corresponds to a different region or a different time.”
Kim teaches selecting, from among multiple predefined algorithms in a predefined algorithm set, a predefined algorithm based on the second information, wherein each of the multiple predefined algorithms corresponds to a different region or a different time. See e.g., [0011], (discussing acquiring location information (meta info) and then receive an object detection algorithm selected based on the meta info.) See also [0021], (algorithms can be selected based on time as well.) See also [0332], (specific example of algorithm selected based on region and time.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention having Xu and Kim before them to modify the fusion system and neural networks of Xu with the ability to select algorithms based on region and time as taught by Kim. One would be motivated to do so in order to provide specialized custom resources to improve object detection.
With regard to Dependent Claim 2,
As discussed above, Xu-Kim teaches all the limitations of Claim 1. Xu-Kim further teaches wherein obtaining the first information comprises detecting the environment information of the terminal or receiving the first information. See e.g., Xu, Col. 5:29-33 (“Next, the specification describes a control system that may receive sensor data from different sensors and share sensor data across processing pipelines. An example control system, providing autonomous navigation for a vehicle is then described.”) See also Col. 7:30-32 (“External sensors may be sensors that can monitor one or more aspects of an external environment relative to vehicle…”). The examiner notes that even though this claim is written in the alternative Xu teaches both alternatives as shown above.
With respect to Dependent Claim 4,
As discussed above, Xu-Kim teaches all the limitations of Claim 1. Xu-Kim further teaches wherein each of the multiple predefined algorithms is a neural network model. See e.g., Xu, Fig. 4, Col. 9:49-55, (discussing using a neural network in the processing pipelines, thus the information output would be based on a neural network model.)
With respect to Dependent Claim 5,
As discussed above, Xu-Kim teaches all the limitations of Claim 1. Xu-Kim further teaches wherein outputting the first sensed information comprises sending the first sensed information to a fusion unit. See e.g., Xu, Fig. 1, (first sensed information is sent to “final decision processing 170” which is a fusion unit.)
With regard to Independent Claim 6,
Claim 6 is similar in scope to Claim 1 and is rejection under a similar rationale.
With respect to Dependent Claim 8,
As discussed above, Xu-Kim teaches all the limitations of Claim 6. Xu-Kim further teaches wherein each of the multiple predefined algorithms in the predefined algorithm set further correspond to different sensors. See Xu, Fig. 1, showing various sensors with separate processing pipelines, see also Zhang [0088], discussing that the algorithms can be used on different data sets.
With regard to Dependent Claims 9 and 16,
These claims are similar in scope to Claim 4 and are rejected under a similar rationale.
With regard to Dependent Claim 10,
As discussed above, Xu-Kim teaches all the limitations of Claim 6. Xu-Kim further teaches wherein the first information is from a sensor. See e.g., Xu, Col. 5:29-33 (“Next, the specification describes a control system that may receive sensor data from different sensors and share sensor data across processing pipelines. An example control system, providing autonomous navigation for a vehicle is then described.”) See also Col. 7:30-32 (“External sensors may be sensors that can monitor one or more aspects of an external environment relative to vehicle…”).
With regard to Dependent Claim 11,
As discussed above, Xu teaches all the limitations of Claim 6. Xu further teaches wherein the region information comprises one or more of … a region. See e.g., Col. 4:25-32, (discussing image data being buffered into regions.) See also Col. 8:48-65, (discussing similar.) Also note the various citations to GPS and similar navigational systems which provide position information which naturally is a “region.”
With regard to Dependent Claim 12,
As discussed above, Xu-Kim teaches all the limitations of Claim 6. Xu-Kim further teaches wherein the first apparatus comprises a camera apparatus, a lidar…. See Xu, Col. 7:26-46 (describing several sensor types including cameras, lidar,
With regard to Independent Claim 13,
Claim 13 is similar in scope to Claim 1 and is rejected under a similar rationale.
With regard to Dependent Claim 14,
As discussed above, Xu-Kim teaches all the limitations of Claim 13. Xu-Kim further teaches wherein the instructions further cause the apparatus to detect the environment information of the terminal. See also Xu, Col. 7:30-32 (“External sensors may be sensors that can monitor one or more aspects of an external environment relative to vehicle…”). The examiner notes that a “vehicle” is a “terminal” and a “sensor” is a “first apparatus” located in the terminal under BRI consistent with the specification.
With regard to Dependent Claim 17,
Claim 17 is similar in scope to Claim 5 and is rejected under a similar rationale.
With regard to Dependent Claim 18,
As discussed above, Xu-Kim teaches all the limitations of Claim 13. Xu-Kim further teaches wherein the instructions further cause the apparatus to receive the first information. See also Xu, Col. 7:30-32 (“External sensors may be sensors that can monitor one or more aspects of an external environment relative to vehicle…”). The examiner notes that a “vehicle” is a “terminal” and a “sensor” is a “first apparatus” located in the terminal under BRI consistent with the specification.
With regard to Dependent Claim 19,
As discussed above, Xu-Kim teaches all the limitations of Claim 13. Xu-Kim further teaches wherein the second information indicates the region information and the time information. See e.g., Kim, [0011, 0012] (information can include location and time.)
With regard to Dependent Claim 21,
As discussed above, Xu-Kim teaches all the limitations of Claim 1. Xu-Kim further teaches wherein selecting the predefined algorithm comprises comparing the at least one of region information or time information to the corresponding region or time of each of the multiple predefined algorithms and selecting the predefined algorithm based on a match between the at least one of region information or time information and the corresponding region or time of each of the multiple predefined algorithms. See e.g., [0011], (discussing acquiring location information (meta info) and then receive an object detection algorithm selected based on the meta info.) See also [0021], (algorithms can be selected based on time as well.) See also [0332], (specific example of algorithm selected based on region and time, note specifically the matching which also requires a comparing step.)
With regard to Dependent Claims 22 and 23,
These claims are similar in scope to Claim 21 and are rejected under a similar rationale.
Claim 20 is rejected under 35 U.S.C. 103 as being unpatentable over Xu in view of Kim further in view of Drayna, U.S. PG Publication #2019/0191424, filed December 23, 2019
With regard to Dependent Claim 20,
As discussed above, Xu-Kim teaches all the limitations of Claim 13. Xu-Kim further teaches construct a neural network model …. output the sensed information based on the neural network model. See e.g., Xu, Fig. 4, Col. 9:49-55, (discussing using a neural network in the processing pipelines, thus the information output would be based on a neural network model.)
Xu does not teach constructing the neural network model using the region information and the time information.
In an analogous art, Drayna discloses construct a neural network model using the region information and the time information. See e.g., [0020], input data for neural network can be based on movement data along travel route, time of day, season, etc. See also [0067], (discussing training data may be generated using GNSS – global navigation satellite system, which see [0030] includes a GPS ).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the fusion system and neural networks of Xu with the ability to be trained (“based on”) specifically on region and time information as discussed by Drayna. One would be motivated to do so to better allow determination and recognition of operational surfaces on which the vehicles are operated. See generally Drayna, [0020].
Response to Arguments
In view of the amendments to claim 8 the objection thereof is withdrawn.
Applicant’s remarks regarding the prior art rejections are moot in view of the new grounds of rejection necessitated by applicant’s amendment.
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.
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/MATTHEW ELL/Supervisory Patent Examiner, Art Unit 2141