Office Action Predictor
Last updated: April 15, 2026
Application No. 18/380,542

POSITION ESTIMATING DEVICE, FORKLIFT, POSITION ESTIMATING METHOD, AND NON-TRANSITORY COMPUTER READABLE STORAGE MEDIUM STORING PROGRAM

Final Rejection §103
Filed
Oct 16, 2023
Examiner
CASCAIS, JUSTIN PHILIP
Art Unit
2674
Tech Center
2600 — Communications
Assignee
Mitsubishi Logisnext Co., LTD.
OA Round
2 (Final)
70%
Grant Probability
Favorable
3-4
OA Rounds
2y 10m
To Grant
86%
With Interview

Examiner Intelligence

Grants 70% — above average
70%
Career Allow Rate
31 granted / 44 resolved
+8.5% vs TC avg
Strong +15% interview lift
Without
With
+15.2%
Interview Lift
resolved cases with interview
Typical timeline
2y 10m
Avg Prosecution
23 currently pending
Career history
67
Total Applications
across all art units

Statute-Specific Performance

§101
14.9%
-25.1% vs TC avg
§103
57.6%
+17.6% vs TC avg
§102
21.0%
-19.0% vs TC avg
§112
6.5%
-33.5% vs TC avg
Black line = Tech Center average estimate • Based on career data from 44 resolved cases

Office Action

§103
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 . Amendment Applicant submitted amendments on 12/24/2025. The Examiner acknowledges the amendment and has reviewed the claims accordingly. Priority Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55. Information Disclosure Statement The IDS(s) dated 11/27/2024, 4/18/2024, and 10/16/2023 that have been previously considered remain placed in the application file. Overview Claims 1 and 6-10 are pending in this application and have been considered below. Claims 2-5 are canceled by the applicant. Claims 1 and 6, and 8-10 are rejected. Claim 7 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Applicant Arguments In regards to Argument 1, Applicant states claim 1 has been amended to recite language to overcome the rejection under 35 U.S.C. § 101. These additional limitations, as well as the specification at paragraph [0018], [0025], and [0026], discuss how controlling the processing speed based on the vehicle's speed or other factors related to movement provides unconventional advantages. The Applicant suggests that by including these limitations, claim 1 is clearly directed to a practical application which includes the advantages of decreased image processing power consumption while ensuring accuracy and that controlling an execution timing of processing circuitry is not a mental process and cannot be performed by the human mind. Additionally, these limitations also provide a real world “affect” on the power usage and processing load and are not merely generic computations (See Remarks, page 5-6 under “Rejection under 35 U.S.C. § 101”). In regards to Argument 2, Applicant states the cited art does not disclose or suggest "the processing circuitry is configured to control the execution timing of the image processing by causing estimating the position of the vehicle every time when the vehicle travels a predetermined distance or rotates at a predetermined angle" and "the image processing including collating a marker included in the image with map data with information of the marker," as recited in claim 1. Specifically, the cited art does not disclose or suggest that a position is estimated by collating a marker included in the image with map data with information of the marker, nor does it disclose estimating the position of the vehicle every time when the vehicle travels a predetermined distance or rotates at a predetermined angle (See Remarks, page 7-8 under “Rejection under 35 U.S.C. § 103”). Examiner’s Response In regards to Argument 1, with respect to Claim(s) 1 and 6-10, the Examiner has fully considered the Argument and has found it persuasive. In response to Argument 2, it has been considered but is moot in view of new ground(s) of rejection based on the amendments. A new reference, Shieh, has been introduced which in Abstract and ¶3, 7, and 19-21 discloses “the processing circuitry is configured to control the execution timing of the image processing by causing estimating the position of the vehicle every time when the vehicle travels a predetermined distance or rotates at a predetermined angle" and "the image processing including collating a marker included in the image with map data with information of the marker”. Shieh introduces a similar process as described in the amended claim where the reference’s keyframe selection avoids processing every frame and uses the distance and angle thresholds to trigger estimation. Kaino teaches a position estimating device for a vehicle with cameras ([2, 51]). The system estimates position by image processing, including collating a “marker” (feature points/landmarks, e.g., edges or objects) in the image with map data with information of the marker ([51, 90, 95]; matches extracted feature points to pre-registered 3D landmarks in stored maps via SLAM and collates image features with map coordinates for position estimation). The system controls processing load by controlling execution timing and/or images processed (Abstract, [3, 31, 85-91, 166], Fig. 7). Additionally, Shiroshima suggests movement-based feature updates ([24, 52-53]). After reviewing the amendments, the Examiner interprets that Kaino in view of Shiroshima, further in view of Shieh teaches on the amended claims that were presented. The details of the rejection are listed below. 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(s) 1, 6, and 8-10 is/are rejected under 35 U.S.C. 103 as obvious over Kaino et al (US 20210027486 A1, hereafter referred to as Kaino) in view of Shiroshima et al (WO 2024009377 A1, hereafter referred to as Shiroshima), further in view of Shieh et al (US 20190080190 A1, hereafter referred to as Shieh). Claim 1 Regarding Claim 1, Kaino teaches a position estimating device that estimates a position of a vehicle equipped with a camera, the position estimating device comprising: Processing circuitry configured to estimate the position of the vehicle by image processing of an image captured by the camera (Kaino in ¶51 discloses "The self-localization unit 132 performs estimation processing of the location, posture, and the like of the vehicle".), the image processing including collating a marker included in the image with map data with information of the marker (Kaino in ¶51, 90, 95 discloses matching extracted feature points to pre-registered 3D landmarks in stored maps via SLAM and collates image features with map coordinates for position estimation). Kaino does not explicitly teach all of control a processing load of the image processing by controlling an execution timing of the image processing performed by the position estimating unit and/or the image to be subjected to the image processing, wherein the processing circuitry is configured to control the execution timing of the image processing by causing estimating the position of the vehicle every time when the vehicle travels a predetermined distance or rotates at a predetermined angle. However, Shiroshima teaches control a processing load of the image processing by controlling an execution timing of the image processing performed by the position estimating unit and/or the image to be subjected to the image processing (Shiroshima in ¶24 discloses "the detection unit 11 changes the number of new feature points to be detected from the target image for estimating the position and orientation of the image capturing device, depending on the number of corresponding feature points" – emphasizes reducing load in feature extraction by varying the number of features processed per image, which controls the data subjected to estimation. This affects timing by scaling per-frame computations in real-time cycles. See also ¶52-53.). Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kaino by adding the load control teachings that is taught by Shiroshima, since both reference are analogous art in the field of vehicle imaging and self-localization systems; thus, one of ordinary skilled in the art would be motivated to combine the references since Kaino’s position estimation via image processing with Shiroshima’s dynamic adjustment of feature detection load yields the predictable result of efficient real-time processing under varying computational restraints. Kaino in view of Shiroshima does not explicitly teach all of the processing circuitry is configured to control the execution timing of the image processing by causing estimating the position of the vehicle every time when the vehicle travels a predetermined distance or rotates at a predetermined angle. However, Shieh teaches the processing circuitry is configured to control the execution timing of the image processing by causing estimating the position of the vehicle every time when the vehicle travels a predetermined distance or rotates at a predetermined angle (Shieh in Abstract and ¶3, 7, and 19-21 discloses keyframe selection avoids processing every frame by using distance and angle thresholds to trigger estimation). Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kaino in view of Shiroshima by controlling the execution timing of the image processing by causing estimating the position of the vehicle every time when the vehicle travels a predetermined distance or rotates at a predetermined angle that is taught by Shieh, since both reference are analogous art in the field of vehicle imaging and self-localization systems; thus, one of ordinary skilled in the art would be motivated to combine the references since Kaino in view of Shiroshima’s position estimation with dynamic adjustment of feature detection load with Shieh’s keyframe selection that avoids processing every frame by using distance and angle thresholds to trigger estimation yields the predictable result of efficient real-time processing. Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention. Claim 6 Regarding Claim 6, Kaino in view of Shiroshima, further in view of Shieh teaches the position estimating device according to claim 1, wherein when a plurality of the cameras is provided, processing circuitry is configured to change, according to a speed or an angular speed of the vehicle, the number of images to be subjected to the image processing of a plurality of the images captured by the plurality of the cameras (Kaino in ¶31 discloses "the data acquisition unit 102 includes various sensors for detecting the state and the like of the vehicle 10. Specifically, for example, the data acquisition unit 102 includes a gyro sensor, an acceleration sensor, an inertial measurement unit (IMU), and a sensor or the like for detecting an accelerator pedal operation amount, a brake pedal operation amount, a steering wheel steering angle, the number of revolutions of the engine, the number of revolutions of the motor, the rotation speed of the wheels, or the like"; ¶132 discloses "since the peripheral camera 253 used for imaging and the peripheral camera 253 not used for imaging are selected, the power consumed by the peripheral camera 253 can be reduced, the number of images to be processed can be reduced, and the processing load on image processing (self-localization processing) can be reduced."). Claim 8 Regarding Claim 8, Kaino in view of Shiroshima, further in view of Shieh teaches a forklift, comprising: a camera (Kaino in ¶2 discloses "a camera"); and a position estimating device described in claim 1 (Kaino and Shiroshima discloses Claim 1. See rejection of Claim 1.). Claim 9 Regarding Claim 9, Kaino teaches A position estimating method of estimating a position of a vehicle equipped with a camera, the position estimating method comprising: estimating the position of the vehicle by the image processing of the image based on control of the load (Kaino in ¶51 discloses "The self-localization unit 132 performs estimation processing of the location, posture, and the like of the vehicle".). Kaino does not explicitly teach all of controlling, when position estimation is performed by image processing of an image captured by the camera, a load of the image processing by controlling an execution timing of the image processing and/or the image to be subjected to the image processing. However, Shiroshima teaches controlling, when position estimation is performed by image processing of an image captured by the camera, a load of the image processing by controlling an execution timing of the image processing and/or the image to be subjected to the image processing (Shiroshima in ¶24 discloses "the detection unit 11 changes the number of new feature points to be detected from the target image for estimating the position and orientation of the image capturing device, depending on the number of corresponding feature points". See also ¶52-53.). Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kaino by adding the load control teachings that is taught by Shiroshima, since both reference are analogous art in the field of vehicle imaging and self-localization systems; thus, one of ordinary skilled in the art would be motivated to combine the references since Kaino’s position estimation via image processing with Shiroshima’s dynamic adjustment of feature detection load yields the predictable result of efficient real-time processing under varying computational restraints. Kaino in view of Shiroshima does not explicitly teach all of the controlling the execution timing of the image processing by causing estimating the position of the vehicle every time when the vehicle travels a predetermined distance or rotates at a predetermined angle. However, Shieh teaches the controlling the execution timing of the image processing by causing estimating the position of the vehicle every time when the vehicle travels a predetermined distance or rotates at a predetermined angle (Shieh in Abstract and ¶3, 7, and 19-21 discloses keyframe selection avoids processing every frame by using distance and angle thresholds to trigger estimation). Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kaino in view of Shiroshima by controlling the execution timing of the image processing by causing estimating the position of the vehicle every time when the vehicle travels a predetermined distance or rotates at a predetermined angle that is taught by Shieh, since both reference are analogous art in the field of vehicle imaging and self-localization systems; thus, one of ordinary skilled in the art would be motivated to combine the references since Kaino in view of Shiroshima’s position estimation with dynamic adjustment of feature detection load with Shieh’s keyframe selection that avoids processing every frame by using distance and angle thresholds to trigger estimation yields the predictable result of efficient real-time processing. Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention. Claim 10 Regarding Claim 10, Kaino teaches a non-transitory computer readable storage medium storing a program for causing a computer that estimates a position of a vehicle equipped with a camera to function as: a unit configured to estimate the position of the vehicle by image processing of an image captured by the camera (Kaino in ¶51 discloses "The self-localization unit 132 performs estimation processing of the location, posture, and the like of the vehicle".). Kaino does not explicitly teach all of a unit configured to control a processing load of the image processing by controlling an execution timing of the image processing performed by the unit configured to estimate the position and/or the image to be subjected to the image processing. However, Shiroshima teaches a unit configured to control a processing load of the image processing by controlling an execution timing of the image processing performed by the unit configured to estimate the position and/or the image to be subjected to the image processing (Shiroshima in ¶24 discloses "the detection unit 11 changes the number of new feature points to be detected from the target image for estimating the position and orientation of the image capturing device, depending on the number of corresponding feature points". See also ¶52-53.). Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kaino by adding the load control teachings that is taught by Shiroshima, since both reference are analogous art in the field of vehicle imaging and self-localization systems; thus, one of ordinary skilled in the art would be motivated to combine the references since Kaino’s position estimation via image processing with Shiroshima’s dynamic adjustment of feature detection load yields the predictable result of efficient real-time processing under varying computational restraints. Kaino in view of Shiroshima does not explicitly teach all of the controlling the execution timing of the image processing by causing estimating the position of the vehicle every time when the vehicle travels a predetermined distance or rotates at a predetermined angle. However, Shieh teaches the controlling the execution timing of the image processing by causing estimating the position of the vehicle every time when the vehicle travels a predetermined distance or rotates at a predetermined angle (Shieh in Abstract and ¶3, 7, and 19-21 discloses keyframe selection avoids processing every frame by using distance and angle thresholds to trigger estimation). Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kaino in view of Shiroshima by controlling the execution timing of the image processing by causing estimating the position of the vehicle every time when the vehicle travels a predetermined distance or rotates at a predetermined angle that is taught by Shieh, since both reference are analogous art in the field of vehicle imaging and self-localization systems; thus, one of ordinary skilled in the art would be motivated to combine the references since Kaino in view of Shiroshima’s position estimation with dynamic adjustment of feature detection load with Shieh’s keyframe selection that avoids processing every frame by using distance and angle thresholds to trigger estimation yields the predictable result of efficient real-time processing. Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention. Allowable Subject Matter Claim 7 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. 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 JUSTIN P CASCAIS whose telephone number is (703)756-5576. The examiner can normally be reached Monday-Friday 8:00-4:00. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Mr. O’Neal Mistry can be reached on (313) 446-4912. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /J.P.C./Examiner, Art Unit 2674 /Ross Varndell/Primary Examiner, Art Unit 2674 Date: 1/5/2025
Read full office action

Prosecution Timeline

Oct 16, 2023
Application Filed
Sep 16, 2025
Non-Final Rejection — §103
Nov 18, 2025
Interview Requested
Nov 26, 2025
Examiner Interview Summary
Dec 24, 2025
Response Filed
Jan 06, 2026
Final Rejection — §103
Apr 06, 2026
Response after Non-Final Action

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
70%
Grant Probability
86%
With Interview (+15.2%)
2y 10m
Median Time to Grant
Moderate
PTA Risk
Based on 44 resolved cases by this examiner. Grant probability derived from career allow rate.

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