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 .
2. This Office Action is sent in response to Applicant's Communication received on September 11, 2025 for application number 19/164,249. This Office hereby acknowledges receipt of the following and placed of record in file: Specification, Drawings, Abstract, Oath/Declaration, and Claims.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on September 11, 2025 was submitted in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the Examiner.
Disposition of Claims
Claims 1-10 are pending in this application.
Claims 5-10 are objected as allowable subject matter.
Claims 1-4 are rejected.
Allowable Subject Matter
Claims 5-10 are 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.
Claim Rejections - 35 USC § 102
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-4 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by (BANDO – JP 2019179421 A).
Regarding claim 1, BANDO discloses:
A control device comprising:
a processor (autonomous traveling control device 300: Figs. 2-3),
wherein the processor (autonomous traveling control device 300: Figs. 2-3) is configured to execute:
calculating a state variable at a second timing from a state variable of a vehicle (dump truck 1: Fig. 1) at a first timing, a control input of the vehicle (dump truck 1: Fig. 1) at a second timing after the first timing, and an observation value at the second timing which is detected by a sensor of the vehicle (dump truck 1: Fig. 1);
approximating, with a neural network model, a state space model including a state equation related to the state variable and an observation equation related to the observation value ([0042]: The function fi (*) is assumed to be determined in advance, and may be composed of a plurality of expressions instead of a single expression. Moreover, you may learn a vehicle state using machine learning from an input value and a detected value. Further, although M is its own weight, it may be a status value that only distinguishes between a loaded state and an empty state. The vehicle state determination unit 132 determines the state having the highest calculated probability as the current vehicle state. The vehicle state determination unit 132 outputs the determined vehicle state to both the assumed DR error calculation unit 112 and the adaptive DR error parameter calculation unit 141); and
determining a reliability of the state variable at the second timing from an index based on the control input at the second timing and the observation value at the second timing ([0043]: Next, the assumed DR error calculation unit 112 calculates an error variance value at the assumed DR position calculated in step 103 (S105). The error variance value Σ (t + 1) at the assumed DR position is set to the error variance value Σ (t) at the assumed DR position one sample time before, the error variance value W of the update amount at one sample time set in advance, and This is a value obtained by adding the variance value E [ε .sup.2 (t)] of the adaptive DR error per sampling time corresponding to the vehicle state determined by the vehicle state determination unit 132. The assumed DR error calculation unit 112 calculates an error variance value of the assumed DR position using the following equation (6). The assumed DR error calculation unit 112 outputs the calculated error variance value Σ (t + 1) of the assumed DR position to the existence possibility range calculation unit 113, and proceeds to step S107).
Regarding claim 2, BANDO disclose the control device according to claim 1, and further on BANDO also discloses:
wherein the index is a Mahalanobis distance based on the control input at the second timing and the observation value at the second timing ([0060, 0063]: Specifically, assuming that the assumed DR position calculated by the assumed DR position calculation unit 111 is (xe, ye) t, the error variance at the assumed DR position is Σ, and the previously determined Mahalanobis distance is d. The existence range of the assumed DR position is within the elliptic equation range shown in the following equation (10). FIG. 5 shows a conceptual diagram of the existence possibility range. A point 1001 is an assumed DR position, and an error ellipse 1002 is an error ellipse of an assumed DR error obtained by Expression (10). The error ellipse 1002 is centered on the assumed DR position 1001. This error ellipse 1002 indicates that a position exists within the ellipse with a probability defined by the Mahalanobis distance d. Further, the error ellipse of the adaptive DR error represented by the equation (11) can be expressed by calculating the average value [ε (t)] of the adaptive DR error with the vector 1003 and the average value of the adaptive DR error starting from the assumed DR position [ [epsilon] (t)] = (xd, yd) is a vector that is an end point of the vector represented by t, and this end point indicates the center 1004 of the error ellipse 1005 indicating the adaptive DR error range. That is, the center 1004 of the error ellipse 1005 of the adaptive DR error means a point shifted from the assumed DR position by the average value of the adaptive DR error. Also, an ellipse having an adaptive DR error spread from the center 1004 of the error ellipse of the adaptive DR error is obtained by the equation (11) based on the error variance E [ε .sup.2 (t)] of the adaptive DR error and the Mahalanobis distance d. It is represented by an error ellipse 1005 of the adaptive DR error. The existence range of the position of the dump truck 1 may be considered to be inside either or both of the error ellipse 1002 of the assumed DR error and the error ellipse 1005 of the adaptive DR error).
Regarding claim 3, BANDO disclose the control device according to claim 2, and further on BANDO also discloses:
wherein the processor determines that a reliability of the state variable at the second timing is low when the Mahalanobis distance is larger than a threshold ([0060, 0063, 0067, 0070]: The determination as to whether it is within the range of the ellipse is made by substituting the detection position (X, Y) output from the GNSS sensor 10 into the right side (x, y) of Equation (6), and the result of calculation is 2 of the Mahalanobis distance d. If it is less than or equal to the power, it is determined that it is within the error ellipse range of the assumed DR error (S203 / Yes), and the stability flag is set to "1" (S206). If it is larger than the square of Mahalanobis distance d, it is determined that it is outside the range of the error ellipse of the assumed DR error (S203 / No), and the process proceeds to step S204. The determination as to whether it is within the range of the ellipse is obtained by substituting the GNSS output position (X, Y) output from the GNSS sensor 10 for (x, y) on the right side of the equation (7), and calculating the Mahalanobis distance d. If it is less than or equal to the square of, it is determined that it is within the error ellipse range of the adaptive DR error (S205 / Yes), and the stability flag is set to "1" (S206). If it is greater than the square of Mahalanobis distance d, it is determined that it is outside the range of the error ellipse of the adaptive DR error (S205 / No), and the stability flag is set to “0” (S207). And the process of the position measurement stability judgment part 114 is complete | finished).
Regarding claim 4, BANDO disclose the control device according to claim 1, and further on BANDO also discloses:
wherein the state equation and the observation equation are non-linear (Equations 1-6 and 8-12 are non-linear equations), and the processor (autonomous traveling control device 300: Figs. 2-3) is configured to execute: calculating the state variable using an extended Kalman filter ([0048, 0077]: As a representative method of the stochastic filter, a Kalman filter, a particle filter, or the like can be given. In the present embodiment, the maximum likelihood position and the error variance value are obtained by the {{{Kalman filter}}} from the error variances calculated by the GNSS sensor 10 and the DR device 210, respectively. Next, the maximum likelihood position calculation unit 115 calculates an innovation vector ν in the Kalman filter (S304). The innovation vector ν is obtained from the detection position X of the GNSS sensor 10 and the assumed DR position xtilde as shown in the following expression (12). The maximum likelihood position calculation unit 115 calculates the Kalman gain K (S305). The Kalman gain K is obtained by the following equation (13) because the error variance value of the assumed DR position includes the error variance value of the adaptive DR error so that the modeling error can be taken into consideration).
Pertinent Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
JP S6345438 A – Hideaki
DE 112020001776 T5 – AOKI
US 2025/0093495 A1 – Steinberg
US 2023/0251951 A1 - BOSSE
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Ruben Picon-Feliciano whose telephone number is (571)-272-4938. The examiner can normally be reached on Monday-Thursday within 11:30 am-7:30 pm ET.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Lindsay M. Low can be reached on (571)272-1196. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RUBEN PICON-FELICIANO/Examiner, Art Unit 3747
/GRANT MOUBRY/Primary Examiner, Art Unit 3747
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