DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 USC 102 and 103 (or as subject to pre-AIA 35 USC 102 and 103) is incorrect, any correction of the statutory basis 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.
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.
Claim(s) 1-3 and 11-13 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Xu (US 2022/0011448 A1).
In regard to claim 1, Xu discloses a vehicle (¶31-32) comprising:
a controller (21, Fig. 9) having a global navigation system satellite (GNSS) positioning module (GPS Positioning Result, Fig. 1; ¶31; ¶34) and a sensor fusion module (Fusion Positioning Result, Fig. 1; ¶34; ¶39);
a plurality of vehicle sensors connected to the controller (Inertial Navigation Positioning Result, Vision Positioning Result; Laster Positioning Result, Fig. 1; ¶34);
the sensor fusion module including software configured to fuse sensor data from the plurality of vehicle sensors and a GNSS position by applying an error weight to each element of data from the plurality of vehicle sensors and the GNSS position (Weight 1 through Weight 4; ¶40) [where accuracy is a measure of error, where are higher accuracy means a smaller error, and a lower accuracy means a bigger error], and
wherein the error weight of the GNSS position is variable dependent upon a GNSS error model map (¶71; ¶78-79; ¶94) [where the GNSS error weight is based on the satellite signal quality/satellite accuracy, where the GNSS error map is a GNSS error map model in that it is modeling the GNSS error as a simple binary model, either high satellite signal quality/satellite accuracy or low satellite signal quality/satellite accuracy, whereas a real satellite signal quality/satellite accuracy would have a particular value that doesn't have to be one of two values].
In regard to claim 11, Xu discloses a method for fusing sensor data (Fusion Positioning Result, Fig. 1; ¶34; ¶39) on a vehicle (¶31-32) comprising:
applying an error weight to each element of data from a plurality of vehicle sensors and a GNSS position (Weight 1 through Weight 4; ¶40) [where accuracy is a measure of error, where are higher accuracy means a smaller error, and a lower accuracy means a bigger error], and
wherein the error weight of the GNSS position is variable dependent upon a GNSS error model map and a location of a vehicle (¶71; ¶78-79; ¶94) [where the GNSS error weight is based on the satellite signal quality/satellite accuracy, where the GNSS error map is a GNSS error map model in that it is modeling the GNSS error as a simple binary model, either high satellite signal quality/satellite accuracy or low satellite signal quality/satellite accuracy, whereas a real satellite signal quality/satellite accuracy would have a particular value that doesn't have to be one of two values.
In regard to claims 2 and 12, Xu further discloses the GNSS error model map is divided into a plurality of spatial regions and wherein each spatial region has a corresponding expected GNSS error (¶5; ¶71) [where there are a plurality of areas/spatial regions].
In regard to claims 3 and 13, Xu further discloses the corresponding expected GNSS error accounts for at least one of GNSS signal blockage and GNSS multi-path errors (Fig. 4; ¶104; ¶114).
Claim Rejections - 35 USC § 103
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.
Claim(s) 4, 7, 14, and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Xu, as applied to claims 2 and 12, above, and further in view of Ishigami (US 2021/0215485 A1).
In regard to claims 4 and 14, Xu fails discloses the corresponding expected GNSS error is based on a variation between a relative position of the vehicle determined via the plurality of vehicle sensors and a GNSS position of the vehicle determined by the GNSS positioning module.
Ishigami teaches an expected GNSS error is based on a variation between a relative position of the vehicle determined via a plurality of vehicle sensors and a GNSS position of the vehicle determined by a GNSS positioning module (110, 113, Fig. 1; ¶122; ¶234).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include this feature into the combination with a reasonable expectation of success in order to implement determining which areas/regions have high GNSS signal quality/high GNSS accuracy/low GNSS error and which areas have low GNSS signal quality/low GNSS accuracy/high GNSS error.
Additionally, this is a combining of prior art elements according to known methods to yield predictable results, the predictable result being that the high GNSS signal quality/high GNSS accuracy/low GNSS error areas and the low GNSS signal quality/low GNSS accuracy/high GNSS error areas are determined.
In regard to claims 7 and 17, Xu fails discloses the expected GNSS error of each spatial region is based on a discrepancy variance of observation points within the spatial region.
Ishigami teaches an expected GNSS error of each spatial region is based on a discrepancy variance of observation points within the spatial region (110, 113, Fig. 1; Fig. 10; ¶122; ¶234).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include this feature into the combination with a reasonable expectation of success in order to implement determining which areas/regions have high GNSS signal quality/high GNSS accuracy/low GNSS error and which areas have low GNSS signal quality/low GNSS accuracy/high GNSS error.
Additionally, this is a combining of prior art elements according to known methods to yield predictable results, the predictable result being that the high GNSS signal quality/high GNSS accuracy/low GNSS error areas and the low GNSS signal quality/low GNSS accuracy/high GNSS error areas are determined.
Claim(s) 5-6 and 15-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Xu and Ishigami, as applied to claims 4 and 14, above, and further in view of Ma (CN 115200569 A).
In regard to claims 5 and 15, Xu and Ishigami fail to teach the relative position of the vehicle is determined via comparing an output of the plurality of vehicle sensors to a point cloud map of a region in which a vehicle is operating.
Ma teaches a type of map used in the fusion of outputs of a plurality of vehicle sensors (p. 2, Contents of Invention, ¶1) is a point cloud map of a region in which a vehicle is operating (p. 3, ¶3).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include this feature into the combination with a reasonable expectation of success in order to implement the map of Xu with a known type of map in the art.
Additionally, this is a combining of prior art elements according to known methods to yield predictable results, the predictable result being that a known type of map in the art is used in implementing the invention of Xu.
In regard to claims 6 and 16, Xu and Ishigami fail to teach the relative position of the vehicle is determined via comparing an output of the plurality of vehicle sensors to a semantic map of a region in which a vehicle is operating.
Ma teaches a type of map used in the fusion of outputs of a plurality of vehicle sensors (p. 2, Contents of Invention, ¶1) is a semantic map of a region in which a vehicle is operating (p. 3, ¶3).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include this feature into the combination with a reasonable expectation of success in order to implement the map of Xu with a known type of map in the art.
Additionally, this is a combining of prior art elements according to known methods to yield predictable results, the predictable result being that a known type of map in the art is used in implementing the invention of Xu.
Claim(s) 8-9 and 18-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Xu and Ishigami, as applied to claims 7 and 17, above, and further in view of He (US 2018/0283882 A1).
In regard to claims 8 and 18, Xu and Ishigami fail to teach the expected GNSS error of each spatial region is interpolated across multiple observation points within the spatial region.
He teaches interpolating observation values from individual observation points in a region to get a value for the region (¶251).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include this feature into the combination with a reasonable expectation of success in order to implement taking individual expected GNSS error measurements at individual points in Ishigami and from that determine an expected GNSS error for a corresponding region in Xu.
Additionally, this is a combining of prior art elements according to known methods to yield predictable results, the predictable result being that the expected GNSS error for each region is determined by taking expected GNSS error measurements at individual points.
In regard to claims 9 and 19, He further teaches the interpolation is at least one of a splines based interpolation, a kriging based interpolation, a nearest neighbor based interpolation, and a natural neighbor based interpolation (¶251) [where Gaussian process interpolation is the same thing as kriging based interpolation, as admitted by applicant in ¶76 of the specification].
Claim(s) 10 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Xu as applied to claims 1 and 11 above, and further in view of Gustafsson (US 2020/0072620 A1)
Xu fails to disclose the GNSS error model map is derived from a plurality of vehicles.
Gustafsson teaches a map is derived from a plurality of vehicles (¶15).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include this feature into the combination with a reasonable expectation of success in order to implement the generation of the map to use in the invention of Xu.
Additionally, this is a combining of prior art elements according to known methods to yield predictable results, the predictable result being that a known map-generation method is used to generate the map of Xu.
In the combination, the map is a GNSS error model map.
The following reference(s) is/are also found relevant:
Collins English Dictionary (model), which defines "model" as "a simplified representation or description of a system or complex entity, especially one designed to facilitate calculations and predictions" (definition 9).
An Illustrated Dictionary of Aviation (inertial navigation), which defines "inertial navigation" as dead reckoning performed automatically by a computer.
Moeglein (US 2010/0178934 A1), which teaches an error model map where the error is based on geographical areas (¶21; ¶68-69), the errors based on elevation (¶68), the elevation based on a geographical model (¶21).
Applicant is encouraged to consider these documents in formulating their response (if one is required) to this Office Action, in order to expedite prosecution of this application.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Fred H. Mull whose telephone number is 571-272-6975. The examiner can normally be reached on Monday through Friday from approximately 9-5:30 Eastern Time.
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Fred H. Mull
Examiner
Art Unit 3648
/F. H. M./
Examiner, Art Unit 3648
/BERNARR E GREGORY/Primary Examiner, Art Unit 3648
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