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 .
Status of Claims
This Office Action is in response to the Applicant’s Response filed on May 26, 2026.
Claim 14 is currently amended.
Claims 1-15 are pending and have been examined.
Response to Arguments
Regarding the outstanding 35 U.S.C. § 112(b) Rejection:
The outstanding 35 USC 112(b) rejection of claim 14 is withdrawn in view of Applicant’s amendment clarifying dependency of claim 14 from independent claim 9.
Regarding the outstanding 35 U.S.C. § 103 Rejections:
Applicant’s arguments filed on May 26, 2026 have been fully considered but they are not persuasive.
Applicant argues, “the Examiner therefore relies on Agrawal for the proposition that confidence values from different sources can be made ‘comparable,’ and that such comparability allegedly renders obvious Applicant’s selection of a positioning correction source based on confidence information.”
“Applicant respectfully submits that this reliance is misplaced. A careful review of Agrawal demonstrates that:
Agrawal is directed exclusively to perception-data annotation, not positioning or navigation.
Agrawal’s confidence scores are classification confidence scores, not confidence indicative of position information accuracy or quality.
Agrawal never uses confidence to select, correct, or update vehicle position, nor to select among positioning correction sources.”
“The core purpose of Agrawal is to detect sensor data frames that are useful to annotate and selectively store, flag or transmit those frames for human labelling, in order to improve perception algorithms. Agrawal repeatedly emphasizes that its heuristics are used to decide whether sensor data should be annotated (para. [0026]). Thus, Agrawal addresses a different technical problem from Applicant’s claims, which concern vehicle positioning in environments including underground sections and transitions, and the selection of a positioning correction source based on confidence in position information.”
“In Agrawal, a confidence score is assigned by a perception algorithm to a type of an object (e.g. pedestrian, car, building) based on sensor data at a particular location (par. [0029]). Agrawal explicitly states that ‘a confidence score [is] assigned to the type of the type of the object amongst a predefined set of types.’ (par. [0036]). Applicant submits that this confidence score is a classification confidence, i.e. an indication of how certain the algorithm is that an object belongs to a particular class. Such confidence scores are semantically and technically different from confidence level values indicative of position information accuracy or quality as required by Applicant’s claims.”
“The Office Action effectively assumes that because Agrawal compares confidence values, those values are inherently usable to generate comparable confidence level values indicative of position information accuracy or quality for positioning sources in Sakai or McFarland. However, Agrawal itself provides no such teaching. The only reason to look to Agrawal—and to reinterpret its perception-confidence comparisons as satisfying the claimed generation of comparable confidence level values indicative of position information accuracy or quality—appears to be knowledge of Applicant’s claimed solution. Accordingly, the rejection relies on impermissible hindsight.”
“Accordingly, amended claims 1, 9 and 15 and the claims dependent therefrom are not obviated by Sakai, McFarland and Agrawal.” See Remarks filed on May 26, 2026 on pages 6-7.
The Examiner respectfully disagrees.
Regarding points 1 and 2, both the claims at issue and the Agrawal reference are related to autonomous vehicle control and the calculations that are performed in order to control the autonomous vehicle. Both the claims at issue and the Agrawal reference relate to increasing the accuracy of determining positioning information within the environment of the autonomous vehicle. Further, both the claims at issue and the Agrawal reference relate to determining the confidence of positioning information of the environment of the autonomous vehicle. Therefore, the Examiner takes the position that the Agrawal reference is relevant to the claims at issue. Therefore, the Examiner respectfully disagrees with Applicant’s arguments.
Regarding point 3, Agrawal is not used for confidence to select, correct, or update vehicle position, nor to select among positioning correction sources. Rather Agrawal is only used for its teaching, “generate, on a basis of first confidence level information and second confidence level information, a comparable first confidence level value indicative of position information accuracy or quality from the first positioning source and a second confidence level value indictive of position information accuracy or quality from the second positioning source”. Therefore, the Examiner respectfully disagrees with Applicant’s argument.
Regarding the Applicant’s argument that this is impermissible hindsight, the Examiner disagrees with this argument because the Agrawal reference discloses, in [0006], that the reference pertains to detecting sensor data for autonomous vehicle perception and that the techniques set forth enable detecting sensor data that can be employed to improve a computer-implemented perception algorithm. The current reference relates to detecting sensor data for autonomous vehicle perception and it is reasonable for a person of ordinary skill in the art to look to other known methods of improving computer-implemented perception algorithms. Therefore, the Examiner respectfully disagrees with Applicant’s argument.
Therefore, the Examiner respectfully disagrees with Applicant’s arguments. The outstanding 35 USC 103 rejections are maintained.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-15 are rejected under 35 U.S.C. 103 as being unpatentable over Sakai, et al., Publication US 2018/0074201 A1, in view of McFarland, et al., Publication US 2018/0292543 A1, and Agrawal, Publication US 2022/0051489 A1 (hereinafter referred to as “Sakai”, “McFarland”, and “Agrawal”, respectively.)
As per claim 1 (representative of claims 9 and 15), Sakai discloses an apparatus for controlling a vehicle … the apparatus [see at least Sakai [0004] "In a case where a work machine travels in a mining site of a mine, it can be considered that the work machine travels referring to map data of the mine. The mining site is vast. … During travel in the mine, the work machine is just to refer only to map data around the work machine."] comprising:
at least one processor [see at least Sakai [0052] "The computer 11 includes … an arithmetic processing device having a microprocessor such as a central processing unit (CPU) to execute a control program,…"],
at least one memory including computer program code, the at least one memory and the computer program code being configured to, with the at least one processor [see at least Sakai [0052] "The computer 11 includes … an external storage device such as a read only memory (ROM) to store the control program, a main storage device (internal storage device) such as a random access memory (RAM) used as a work area of the CPU, and an external storage device (auxiliary storage device) such as a nonvolatile memory in which data is registered by the CPU."], cause the apparatus at least to:
define first confidence level information for position information by a satellite based first positioning source of a vehicle at a worksite including an underground tunnel system [see at least Sakai [0094] "The determination unit 33A determines whether the error of the GPS position detected by the GPS receiver 31 is equal to or smaller than a predetermined error. The determination unit 33A determines whether the solution of the GPS position is the Fix solution"; [0037] "The mining machine 4 is a collective term of machinery used in various operations in a mine."];
define second confidence level information for position information by a second positioning source configured to position the vehicle based on environment scanning [see at least Sakai [0122] "... the scan matching navigation position calculation unit 33B discards the calculated position and orientation of the dump truck 2 and performs similar calculation again when the calculated position and orientation of the dump truck 2 … when the reliability is lower than predetermined reliability..."; Fig. 18];
generate on a basis of the first confidence level information and the second confidence level information, a … first confidence level value … [see at least Sakai [0044] “…The positioning status includes a Fix solution (accuracy of approximately ±1 to 2 centimeters), a Float solution (accuracy of approximately ±10 centimeters to several meters), a Single solution (accuracy of approximately ±several meters), and non-positioning (positioning calculation cannot be performed).“; [0076] “When detecting any one of the Fix solution, Float solution, and Single solution indicating the accuracy of the detected GPS position, the GPS receiver 31 outputs a positioning signal indicating that positioning calculation of the GPS position is performed together with the accuracy of the detected GPS position.” [0094] “The determination unit 33A determines whether the error of the GPS position detected by the GPS receiver 31 is equal to or smaller than a predetermined error…”] and
a second confidence level value …, respectively [see at least Sakai [0122] “The scan matching navigation position calculation unit 33B performs various diagnoses on the calculated position and orientation of the dump truck 2 (step ST644). Specifically, the scan matching navigation position calculation unit 33B discards the calculated position and orientation of the dump truck 2 and performs similar calculation again when … calculated from the detection results of the laser sensor 24B fewer than the predetermined number, when the reliability is lower than predetermined reliability…], respectively [see at least Sakai [0129] "… the diagnosis unit 33E diagnoses the detection data of the GPS receiver 31 using the position data of the dump truck 2 calculated by the scan matching navigation position calculation unit 33B. The diagnosis unit 33E compares the position of the dump truck 2 derived from the detection data of the GPS detector 31 with the position of the dump truck 2 calculated by the scan matching navigation position calculation unit 33B and diagnoses the detection data of the GPS detector 31. "];
select a positioning correction source for the vehicle on the basis of the first confidence level value and the second confidence level value [see at least Sakai [0094] “…in this case, the GPS travel mode is selected as the travel mode by the travel controller 20…in this case, the scan matching navigation travel mode is selected as the travel mode in the travel controller 20…”; [0106] "Next, after the GPS receiver 31 detects the GPS position, the determination unit 33A of the scan matching navigation position measurement controller 33 executes step ST2 of determining whether the error of the GPS position of the dump truck 2 detected by the GPS receiver 31 is equal to or smaller than a predetermined error.."; [0109] "...When extracting the detection result regarding the bank BK, the observation point availability determination unit 39 first removes various noises of the detection result the coordinates of which are converted by the observation point coordinate conversion unit 38"]; and
control the vehicle … using the selected positioning correction source for correcting dead-reckoning based positioning [see at least Sakai [0086] “In the GPS travel mode, the travel controller 20 allows the dump truck 2 to travel while preventing the error accumulated by the dead-reckoning navigation from becoming too large by correcting the position (estimated position) of the dump truck 2 calculated (estimated) by the dead-reckoning navigation using the GPS position data detected by the GPS receiver 31 … In the scan matching navigation travel mode also, the travel controller allows the dump truck 2 to travel while preventing the error accumulated by the dead-reckoning navigation from becoming too large by correcting the position (estimated position) and orientation (estimated orientation) of the dump truck 2 calculated (estimated) by the dead-reckoning navigation using scan matching navigation position data and orientation calculated by the scan matching navigation position calculation unit 33B …”; [0113] "When the determination unit 33A of the scan matching navigation position measurement controller 33 determines that the solution of the GPS position detected by the GPS receiver 31 is not the Fix solution, that is, determines that the error of the GPS position of the dump truck 2 detected by the GPS receiver 31 is larger than a predetermined error (step St2: No)...the travel controller 20 shifts to the scan matching navigation travel mode..."; [0114] "…even in the scan matching navigation travel mode, when the frequency of the dead-reckoning navigation and the calculation frequency of the position and orientation by the scan matching navigation position calculation unit 33B are in the state as illustrated in FIG. 11, after the dead-reckoning navigation is performed several times, ... "].
Sakai fails to disclose … transitioning between an underground section and a surface section of a worksite comprising an underground tunnel system … and … control the vehicle transitioning between the underground section and the surface section. However, McFarland teaches these limitations [see at least McFarland [0032] "The block 108 may be configured to generate a number of motion and/or inertial measurements that may be used by the block 102 to calculate the vehicle position using dead reckoning (DR) when satellite signals from the antenna 106 are lost or otherwise unavailable (e.g., in a tunnel... ."]
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus as disclosed in Sakai to use … transitioning between an underground section and a surface section of a worksite comprising an underground tunnel system … and … control the vehicle transitioning between the underground section and the surface section as disclosed in McFarland with a reasonable expectation of success for the benefit of improved vehicle positioning in long tunnels that extend for many miles. [See at least McFarland [0021].]
The combination of Sakai and McFarland fails to disclose … generate on a basis of ... first confidence level information and … second confidence level information, a comparable first confidence level value indicative of position information accuracy or quality from the first positioning source and a second confidence level value indicative of position information accuracy or quality from the second positioning source... . However, Agrawal teaches this limitation [See at least Agrawal [0042] "...the heuristic 300 implemented by the annotation management system 130 can include comparing ... confidence scores generated by the differing perception algorithms based on sensor data from differing modalities of sensor systems."; [0043] " ... the heuristic 300 can include comparing the first label assigned to the object 304 at the particular location in the environment 302 by the perception algorithm 1 212... ."]
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus as disclosed in the combination of Sakai and McFarland to use … generate on a basis of ... first confidence level information and … second confidence level information, a comparable first confidence level value indicative of position information accuracy or quality from the first positioning source and a second confidence level value indicative of position information accuracy or quality from the second positioning source... as disclosed in Agrawal with a reasonable expectation of success for the benefit of improving a computer-implemented perception algorithm using sensor data . [See at least Agrawal [0006].]
As per claim 2 (representative of claim 10), the combination of Sakai, McFarland, and Agrawal, as shown in the rejection above, discloses all of the limitations of claim 1.
Sakai discloses the apparatus, wherein the at least one memory and the computer program code are further configured to, with the at least one processor, cause the apparatus to define the first confidence level value on a basis of processing position estimate information from the first positioning source [see at least Sakai [0044] “…The positioning status includes a Fix solution (accuracy of approximately ±1 to 2 centimeters), a Float solution (accuracy of approximately ±10 centimeters to several meters), a Single solution (accuracy of approximately ±several meters), and non-positioning (positioning calculation cannot be performed).“; [0076] & [0094] “The determination unit 33A determines whether the error of the GPS position detected by the GPS receiver 31 is equal to or smaller than a predetermined error…”] and
the second confidence level value [see at least Sakai [see at least Sakai [0122] “The scan matching navigation position calculation unit 33B performs various diagnoses on the calculated position and orientation of the dump truck 2 (step ST644). Specifically, the scan matching navigation position calculation unit 33B discards the calculated position and orientation of the dump truck 2 and performs similar calculation again when … calculated from the detection results of the laser sensor 24B fewer than the predetermined number, when the reliability is lower than predetermined reliability…”]
on a basis of processing position estimate information from the second positioning source and comparing the first confidence level value and the second confidence level value for the selecting of the applied positioning information source [see at least Sakai [0099] "…the diagnosis unit 33E obtains the detection data of the GPS receiver 31 and calculation data of the scan matching navigation position calculation unit 33B. The diagnosis unit 33E compares the GPS position (absolute position) of the dump truck 2 derived from the detection data of the GPS detector 31 with the absolute position of the dump truck 2 calculated by the scan matching navigation position calculation unit 33B, thereby diagnosing the accuracy of the detection data of the GPS detector 31."].
As per claim 3, the combination of Sakai, McFarland, and Agrawal, as shown in the rejection above, discloses all of the limitations of claim 2.
Sakai discloses the apparatus, wherein the processing includes weighting at least some of the position estimate information or the confidence values before selecting the positioning correction source [see at least Sakai [0122] "... the scan matching navigation position calculation unit 33B discards the calculated position and orientation of the dump truck 2 and performs similar calculation again when the calculated position and orientation of the dump truck 2 … when the reliability is lower than predetermined reliability..."].
As per claim 4 (representative of claim 11), the combination of Sakai, McFarland, and Agrawal, as shown in the rejection above, discloses all of the limitations of claim 1.
Sakai discloses the apparatus, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus to define the first confidence level on a basis of quality information from a global navigation satellite system unit [see at least Sakai [0094] "The determination unit 33A determines whether the error of the GPS position detected by the GPS receiver 31 is equal to or smaller than a predetermined error. The determination unit 33A determines whether the solution of the GPS position is the Fix solution"; [0037] "The mining machine 4 is a collective term of machinery used in various operations in a mine."].
As per claim 5 (representative of claim 12), the combination of Sakai, McFarland, and Agrawal, as shown in the rejection above, discloses all of the limitations of claim 4.
Sakai discloses the apparatus, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus to receive an error estimate from a global positioning system device and define the first confidence level by processing the error estimate on a basis of a target positioning accuracy parameter [see at least Sakai [0074] ...The GPS receiver 31 detects a position (GPS position) of the antenna 31A using the data from the positioning satellite 5 and the correction observation data from the GPS base station 19."; [0099] "… The diagnosis unit 33E compares the GPS position (absolute position) of the dump truck 2 derived from the detection data of the GPS detector 31 with the absolute position of the dump truck 2 calculated by the scan matching navigation position calculation unit 33B, thereby diagnosing the accuracy of the detection data of the GPS detector 31."].
As per claim 6 (representative of claim 13), the combination of Sakai, McFarland, and Agrawal, as shown in the rejection above, discloses all of the limitations of claim 5.
Sakai discloses the apparatus, wherein the first confidence level information is defined based on computed probability of correct position residing within a target radius from a reported position [see at least Sakai [0044] “…The positioning status includes a Fix solution (accuracy of approximately ±1 to 2 centimeters), a Float solution (accuracy of approximately ±10 centimeters to several meters), a Single solution (accuracy of approximately ±several meters), and non-positioning (positioning calculation cannot be performed)“].
As per claim 7 (representative of claim 14), the combination of Sakai, McFarland, and Agrawal, as shown in the rejection above, discloses all of the limitations of claim 1.
Sakai discloses the apparatus, wherein the second positioning source is configured to compare scanned tunnel profile data to reference profile data stored in an environment model, and wherein the at least one memory and computer program code are configured to with the at least one processor, cause the apparatus to define the second confidence level information on a basis of level of correlation between the scanned tunnel profile data and the reference profile data [see at least Sakai [0157] "Although the position of the mining machine is detected using the GNSS detector in the above-described embodiment, there is no limitation, and the position of the mining machine may also be detected on the basis of a well-known "position detection device"…it is possible to use self-position estimation and the like of the work machine using…an existing position detection device such as … simultaneous localization and mapping (SLAM), and a landmark (mark provided beside the travel route)."].
As per claim 8, the combination of Sakai, McFarland, and Agrawal, as shown in the rejection above, discloses all of the limitations of claim 1.
Sakai discloses the apparatus, wherein the apparatus is a loading and/or hauling vehicle or a drilling rig configured to operate autonomously [see at least Sakai [0041] "…the dump truck 2 is a so-called unmanned dump truck which autonomously travels the travel route on the basis of a command signal from a management device 10."]
Conclusion
THIS ACTION IS MADE FINAL. 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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/P.L.S/Examiner, Art Unit 3668
/Fadey S. Jabr/Supervisory Patent Examiner, Art Unit 3668
