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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 04/08/2026 has been considered by the examiner.
Response to Amendment
The amendment filed on 06/09/2026 is being entered. Claims 1-3, 5-18, 20, and 24-25 are pending. Claims 24-25 are new. Claims 4 and 19 are cancelled. Claims 21-23 are withdrawn. The amendment overcomes the 35 U.S.C. 112(a) rejection, the previous 35 U.S.C. 112(b) rejection, and the previous 35 U.S.C. 102(a)(1) rejection. However, after further consideration and search, the claims are rejected under a new 35 U.S.C. 112(b) rejection and a new 35 U.S.C. 102(a)(1) rejection. Therefore, responsive to this amendment, this rejection has been made final as necessitated by the amendment.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 5, 7, and 16 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 5 recites the limitation " target regions " in line 2. There is insufficient antecedent basis for this limitation in the claim.
Claim 7 recites the limitation " one or more points " in line 3 and lines 6-7. There is insufficient antecedent basis for this limitation in the claim.
Claim 16 recites the limitation " target regions " in lines 3-4. There is insufficient antecedent basis for this limitation in the claim.
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.
Claims 1, 3, 5-6, 18, 20, and 24-25 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Niewiadomski (U.S. Publication No. 2021/0146915 A1) hereinafter Niewiadomski.
Regarding claim 1, Niewiadomski discloses a method comprising:
determining, based at least on sensor data obtained using one or more sensors of a machine, a presence of a target region within an environment, the target region including one or more target areas corresponding to one or more expected locations, within a coordinate system associated with the target region, for one or more target-object types [see Paragraph 0078 - discusses that a parking area (target region) is determined from at least one sensor, the parking area is a potential location for a curb (target-object type), and see Figure 2 below, and see Paragraph 0046 - discusses accessing a map stored in a memory that is accessed by the navigation system, the map includes the length and width of the parking areas (target regions), and the parking direction of the parking area (target region), and see Paragraph 0051 - discusses using a map to identify parking areas when the sensors are not in range to detect and once the parking area is in range using the sensor to re-identify the edges of the parking area - the sensors generate spatial data in a coordinate frame in a local vehicle-centered coordinate system - that allows the system to represent the position of objects, lines, and spaces (target region) relative to the vehicle];
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Figure 2 of Niewiadomski
determining, based at least on a correlation of points of the sensor data within at least one target area of the target region, a presence of at least one target object of the one or more target-object types within the at least one target are [see Paragraph 0079 - discusses identifying a curb (target-object type) within the parking area based on a camera and/or LIDAR using image recognition/object identification techniques, cameras use pixels (see Paragraph 0054) and LIDARs use point clouds (see Paragraph 0052)];
based at least on the presence of at least one target object, tracking, within the coordinate system associated within the target region, one or more predicted locations of the at least one target object responsive to one or more movements associated with the machine [see Paragraph 0065 - discusses after a vehicle has started to enter a parking area, identifying a height of a curb (target-object type) in order to determine a parking position, and see Paragraph 0079 - discusses continuously updating the location and height of the curb - therefore, after the vehicle has started to enter a parking area, that a vehicle identifies and continuously updates (tracks) the location and height of the curb in the local vehicle-centered coordinate system]; and
performing one or more operations associated with the machine based at least on the tracking of the one or more predicted locations of the at least one target object [see Paragraphs 0086-0087 - discusses that the vehicle parks at the parking position based on the height and location of the curb, the vehicle commands the propulsion and steering system (operations) to park the vehicle].
Regarding claim 3, Niewiadomski discloses the invention with respect to claim 1. Niewiadomski further discloses updating the one or more predicted locations of the at least one target object based at least on second sensor data obtained subsequent to the one or more movements [see Paragraph 0089 - discusses detecting an object (see Paragraph 0079 - discusses continuously updating the location and height of the curb via sensors) that prevents the vehicle from entering the parking position, therefore an updated height/location of the curb is detected when the vehicle attempts to park at the parking position]; and performing one or more second operations associated with the machine based at least on the updating of the one or more predicted locations [see Paragraph 0089 - discusses that after the autonomous vehicle stops in the parking area, the vehicle determines that the vehicle is not sufficiently within the parking area due to the detected object and the vehicle exits the parking area (second operation)].
Regarding claim 5, Niewiadomski discloses the invention with respect to claim 1. Niewiadomski further discloses wherein the target regions correspond to a parking space in the environment [see Paragraph 0035 - discusses a parking area, and see Figure 2 below – depicts a parking area (space)] and the one or more expected locations correspond to one or more average locations of the one or more target-object types in the parking space [see Paragraph 0053 - discusses that the location of the curb is tracked based on length, distance of the curb to other features, curbs are potential objects in a parking area (space)].
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Figure 2 of Niewiadomski
Regarding claim 6, Niewiadomski discloses the invention with respect to claim 5. Niewiadomski further discloses wherein the one or more target-object types correspond to one or more parking barriers, the one or more parking barriers including see Paragraph 0035 - discusses a curb]
Regarding claim 18, Niewiadomski discloses at least one processor comprising:
processing circuitry to perform one or more operations associated with a machine [see Paragraphs 0086-0087 - discusses that the vehicle parks at the parking position based on the height and location of the curb, the vehicle commands the propulsion and steering system (operations) to park the vehicle] based at least on tracking, within a coordinate system associated with a target region [see Paragraph 0046 - discusses accessing a map stored in a memory that is accessed by the navigation system, the map includes the length and width of the parking areas (target regions), and the parking direction of the parking area (target region), and see Paragraph 0051 - discusses using a map to identify parking areas when the sensors are not in range to detect and once the parking area is in range using the sensor to re-identify the edges of the parking area - the sensors generate spatial data in a coordinate frame in a local vehicle-centered coordinate system - that allows the system to represent the position of objects, lines, and spaces (target region) relative to the vehicle], a predicted location of a target object in an environment responsive to one or more previous operations of the machine [see Paragraph 0065 - discusses after a vehicle has started to enter a parking area, identifying a height of a curb in order to determine a parking position, and see Paragraph 0079 - discusses continuously updating the location and height of the curb - therefore, after the vehicle has started to enter a parking area, a vehicle identifies and continuously, or at intervals, updates (tracks) the location and height of the curb],
the predicted location of the target object at least one of determined or updated while the machine was positioned at one or more previous locations based at least on sensor data indicating a presence of one or more objects within one or more target spaces of the target region, the one or more target spaces corresponding to one or more expected locations, within the coordinate system, for one or more target-object types [see Paragraph 0079 – discusses identifying the curb at a first instance and then continuously, or at intervals, updating the location and height of the curb based on the local vehicle-centered coordinate system determined from the map and sensor data (see Paragraphs 0046 and 0051)].
Regarding claim 20, Niewiadomski discloses the invention with respect to claim 18. Niewiadomski further discloses wherein the processor is comprised in at least one of: a control system for an autonomous or semi-autonomous machine [see Paragraph 0038 - discusses that the vehicle operates in an autonomous or semi-autonomous mode, and the mode is controlled by a computer (control system)].
Regarding claim 24, Niewiadomski discloses the invention with respect to claim 1. Niewiadomski further discloses wherein the tracking comprises continuing to track the one or more predicted locations of the at least one target object after movement of the machine and while subsequent sensor data corresponding to the at least one target object is insufficient to update the one or more predicted locations [see Paragraphs 0051 and 0078 - discusses continuously updating the edges of the parking area over time as more data is collected - the further way the vehicle is (sensors) the less accurate the data is, as the vehicle moves closer more data is captured and improves the location of detected edges - therefore when the vehicle is farther away the data is insufficient to update until the sensors are within the sensors detection range and the vehicle continuously updates the data to improve the location of the detected edges].
Regarding claim 25, Niewiadomski discloses the invention with respect to claim 1. Niewiadomski further discloses wherein the tracking the predicted location of the target object within the coordinate system associated with the target region comprises tracking the predicted location of the target object based at least on movement of the machine relative to the coordinate system while subsequent sensor data corresponding to the target object is insufficient to update or confirm the predicted location of the target object [see Paragraphs 0051 and 0078 - discusses continuously updating the edges of the parking area over time as more data is collected - the further way the vehicle is (sensors) the less accurate the data is, as the vehicle moves closer more data is captured and improves the location of detected edges - therefore when the vehicle is farther away the data is insufficient to update until the sensors are within the sensors detection range and the vehicle continuously updates the data to improve the location of the detected edges].
Claims 11-13, 15, and 17 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Pfeiffer (U.S. Publication No. 2023/0004744 A1) hereinafter Pfeiffer.
Regarding claim 11, Pfeiffer discloses a system comprising: one or more processors to:
determine, based at least on sensor data corresponding to a target region in an environment, a probability associated with one or more target objects being disposed in one or more target areas corresponding to one or more expected locations, within a coordinate system associated with the target region [see Paragraph 0053 - discusses using SLAM (simultaneous localization and mapping) to determine a location and orientation of the vehicle - this method maps the vehicle into a local coordinate map], for one or more target-object types [see Paragraphs 0030-0031 and 0074 - discusses generating sensor data of a target region (see Figure 1 below – the target region including objects of a sidewalk, object (fire hydrant), and driving surface), and see Paragraph 0032 – discusses analyzing the sensor data to determine probabilities associated with the points of objects and potential objects (curb) being disposed in a target area (sidewalk, driving surface, and curb) of the target region];
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Figure 1 of Pfeiffer
track, within the coordinate system associated with the target region [see Paragraph 0053 – discusses continuously determining the location and orientation of a vehicle in a map using the SLAM technique], one or more predicted locations corresponding to the one or more target objects based at least on the probability meeting or exceeding a threshold [see Paragraphs 0032 and 0074-0078- discusses that the vehicle selects the points for object(s) that are equal to or greater than a probability threshold]; and
perform one or more operations associated with a machine within the target region based at least on the tracking of the one or more predicted locations [see Paragraph 0079 - discusses the vehicle performs one or more actions based on the objects (curb)].
Regarding claim 12, Pfeiffer discloses the invention with respect to claim 11. Pfeiffer further discloses wherein the determination of the probability associated with the one or more target objects being disposed in the one or more target areas comprises determining whether a number of points of the sensor data that correspond to the one or more target areas meets or exceeds a threshold [see Paragraphs 0032 and 0074 - discusses that the points are equal to or greater than a threshold probability, see Paragraph 0031 – discusses generating sensor data over a period of time to generate a greater number of points – therefore, the threshold probability is determined for the generated number of points].
Regarding claim 13, Pfeiffer discloses the invention with respect to claim 11. Pfeiffer further discloses determine one or more orientations of the one or more target objects based at least on an alignment associated with one or more points of the sensor data [see Paragraph 0037 - discusses generating a curve that represents a curb based on the points in the sensor data, the curve indicates the orientation of the curb].
Regarding claim 15, Pfeiffer discloses the invention with respect to claim 11. Pfeiffer further disclose wherein the target region corresponds to a parking space in the environment [see Paragraph 0031 – discusses the driving surface being a parking lot, which comprises multiple parking spaces] and wherein the one or more target objects correspond to one or more parking barriers associated with the parking space, the one or more parking barriers including see Paragraph 0015 – discusses the potential object is a curb].
Regarding claim 17, Pfeiffer discloses the invention with respect to claim 11. Pfeiffer further disclose wherein the system is comprised in at least one of: a control system for an autonomous or semi-autonomous machine [see Paragraph 0052 - discusses a computing device of an autonomous vehicle or semi-autonomous].
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.
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 2 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Niewiadomski in view of Pfeiffer.
Regarding claim 2, Niewiadomski discloses the invention with respect to claim 1.
However, Niewiadomski fails to disclose determining, based at least on a second correlation of second points of sensor data within at least one target area, one or more second predicted locations of at least one target object; and determining to track one or more predicted locations instead of the one or more second predicted locations based at least on a first score associated with the correlation being greater than a second score associated with the second correlation.
Pfeiffer discloses:
determining, based at least on a second correlation of second points of sensor data within at least one target area, one or more second predicted locations of at least one target object [see Paragraphs 0014-0015 - discusses analyzing points of sensor data that are generated over a period of time, the points include first points and second points that are then selected/discarded during the probability analysis]; and
determining to track one or more predicted locations instead of the one or more second predicted locations based at least on a first score associated with the correlation being greater than a second score associated with the second correlation [see Paragraph 0015 - discusses discarding first (second) points and selecting second (first) points when identifying a location of a curb, the determination of the discard/select is based on whether the probabilities of the points are greater than a threshold probability (score)].
Pfeiffer suggests that the points are used to identify a curb proximate to the vehicle [see Paragraph 0015], and that an autonomous vehicle needs to determine the location of a curb so that the autonomous vehicle avoids the curb or to pick up and drop off a user at a location proximate to the curb [see Paragraph 0001]. Pfeiffer further suggests that identifying point with a higher score (meet or exceed probability threshold), has a higher confidence for accuracy in order to identify a curb [see Paragraph 0015].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the tracking of the target object as taught by Niewiadomski to determine, based at least on a second correlation of second points of sensor data within at least one target area, one or more second predicted locations of at least one target object and determine to track one or more predicted locations instead of the one or more second predicted locations based at least on a first score associated with the correlation being greater than a second score associated with the second correlation as taught by Pfeiffer in order to have a higher confidence for accuracy when identifying a curb [Pfeiffer, see Paragraph 0015] which helps an autonomous vehicle determine the location of a curb so that the autonomous vehicle avoids the curb or to pick up and drop off a user at a location proximate to the curb [Pfeiffer, see Paragraph 0001].
Regarding claim 7, Niewiadomski discloses the invention with respect to claim 1.
However, Niewiadomski fails to disclose wherein the determining that the points correspond to the at least one target object comprises:
generating, based at least on the one or more target areas and the one or more points, data indicating at least one of a proposed location or a proposed orientation associated with the at least one target object;
calculating one or more metrics indicative of at least an alignment of the one or more points and the data; and
determining whether the points correspond to the at least one target object based at least on evaluating one or more values of the one or more metrics with respect to one or more thresholds.
Pfeiffer discloses wherein determining that one or more points correspond to at least one target object comprises:
generating, based at least on the one or more target areas and the points, data indicating at least one of a proposed location or a proposed orientation associated with the at least one target object [see Paragraph 0035 - discusses determining separation points, from the sensor data) that indicates a location and orientation of a potential curb];
calculating one or more metrics indicative of at least an alignment of the one or more points and the data [see Paragraph 0043 - discusses determining an energy (metric) associated with a potential separation point that is based on differences of the location of points, see Paragraph 0046 - discusses determining a final separation that corresponds to a potential separation point]; and
determining whether the points correspond to the at least one target object based at least on evaluating one or more values of the one or more metrics with respect to one or more thresholds [see Paragraphs 0046-0048 - discusses using the final separation points to generate a curve that represents the curb, discusses determining whether the final separation points are associated with a maximum energy (threshold)].
Pfeiffer suggests that determining separation points (data) from the sensor data and the separation points energies (metrics) more accurately generates a curve that represents the curb [see Paragraph 0021].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the invention as taught by Niewiadomski to generate, based at least on the one or more target areas and the points, data indicating at least one of a proposed location or a proposed orientation associated with the at least one target object, calculate one or more metrics indicative of at least an alignment of the points and the data, and determine whether the one or more points correspond to the at least one target object based at least on evaluating one or more values of the one or more metrics with respect to one or more thresholds as taught by Pfeiffer in order to more accurately generate a curve that represents the curb [Pfeiffer, see Paragraph 0021].
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Niewiadomski in view of Panthri et al. (U.S. Publication No. 2025/0091569 A1) hereinafter Panthri.
Regarding claim 8, Niewiadomski discloses the invention with respect to claim 1.
However, Niewiadomski fails to disclose obtaining map data indicating one or more locations of one or more target regions in the environment; and evaluating the sensor data with respect to the map data, wherein the determining the presence of the target region within the environment is based at least on the evaluating.
Panthri discloses obtaining map data indicating one or more locations of one or more target regions in the environment; and evaluating the sensor data with respect to the map data, wherein the determining the presence of the target region within the environment is based at least on the evaluating [see Paragraph 0042 - discusses comparing sensor data with map data to indicate the location of a parking lot].
Panthri suggests that evaluating the sensor with the map data, determines that a vehicle is within a threshold distance of a parking space (target region) [see Paragraph 0042]. Further, it is known to one having ordinary skill in the art that using different data such as sensor data and map data increases the accuracy of location determination.
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the invention as taught by Niewiadomski to obtain map data indicating one or more locations of one or more target regions in the environment; and evaluate the sensor data with respect to the map data, wherein the determining the presence of the target region within the environment is based at least on the evaluation as taught by Panthri in order to increase location determination accuracy and to determine that a vehicle is within a threshold distance of a parking space [Panthri, see Paragraph 0042].
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Niewiadomski in view of Widjaja et al. (U.S. Publication No. 2023/0260298 A1) hereinafter Widjaja.
Regarding claim 9, Niewiadomski discloses the invention with respect to claim 1.
However, Niewiadomski fails to disclose generating, using the sensor data, a map representing one or more locations corresponding to one or more detected objects in the environment, wherein the tracking of the one or more predicted locations of the at least one target object comprises tracking a location of an identifier on the map, the identifier corresponding to the at least one target object.
Widjaja discloses generating, using the sensor data, a map representing one or more locations corresponding to one or more detected objects in the environment, wherein the tracking of the one or more predicted locations of the at least one target object comprises tracking a location of an identifier on the map, the identifier corresponding to the at least one target object [see Paragraph 0077 - discusses a mapping engine that updates a map with location/orientation and semantic information about objects (classifications such as a curb), and see Paragraphs 0110-0118 - discusses that an enhanced semantic mapping engine that uses sensor data to generate an annotated map].
Widjaja suggests that cleaner and more efficient maps are generated using raw point features (from sensors) [see Paragraph 0022 and 0076] and that the autonomous vehicle relies on maps to navigate [see Paragraph 0002].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the invention as taught by Niewiadomski to generate, using sensor data, a map representing one or more locations corresponding to one or more detected objects in the environment, wherein the tracking of the one or more predicted locations of the at least one target object comprises tracking a location of an identifier on the map, the identifier corresponding to the at least one target object as taught by Widjaja in order to generate cleaner and more efficient maps for autonomous vehicle navigation [Widjaja, see Paragraphs 0002, 0022 and 0076].
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Niewiadomski in view of Park et al. (U.S. Publication No. 2022/0390608 A1) hereinafter Park.
Regarding claim 10, Niewiadomski discloses the invention with respect to claim 1.
However, Niewiadomski fails to disclose wherein the one or more target-object types are associated with one or more vertical dimensions that are less than a threshold vertical dimension, and the determining that the points correspond to the at least one target object is further based at least on one or more vertical measurements associated with one or more of the points being less than the threshold vertical dimension.
Park discloses wherein: one or more target-object types are associated with one or more vertical dimensions that are less than a threshold vertical dimension [see Paragraphs 0075-0086 - discusses determining whether sample points are equal to or less than a height threshold], and determining that the points correspond to the one or more target-object types is further based at least on one or more vertical measurements associated one or more of the points being less than the threshold vertical dimension [see Paragraph 0109 - discusses that the multiple sample points are determined to be curb candidate points based on the sample points being equal to or less than the height threshold].
Park suggests that precise positioning of a vehicle using detected curbs is important for autonomous driving [see Paragraph 0225]
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the invention as taught by Niewiadomski to determine that points corresponding to on or more target-object type is further based at least on one or more vertical measurements associated with one or more points being less than the threshold vertical dimension as taught by Park in order to precisely position a vehicle with respect to a curb [Park, see Paragraph 0025].
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Pfeiffer in view of Niewiadomski.
Regarding claim 14, Pfeiffer discloses the invention with respect to claim 11.
However, Pfeiffer fails to disclose one or more processors further to:
update the one or more predicted locations of the one or more target objects based at least on second sensor data obtained subsequent to the performance of the one or more operations; and perform one or more second operations associated with the machine based at least on the update of the one or more predicted locations.
Niewiadomski discloses one or more processors further to: update one or more predicted locations of one or more target objects based at least on second sensor data obtained subsequent to the performance of the one or more operations [see Paragraph 0089 - discusses detecting an object (see Paragraph 0079 - discusses continuously updating the location and height of the curb via sensors) that prevents the vehicle from entering the parking position, therefore an updated height/location of the curb is detected when the vehicle attempts to park at the parking position]; and perform one or more second operations associated with the machine based at least on the update of the one or more predicted locations [see Paragraph 0089 - discusses that after the autonomous vehicle stops in the parking area, the vehicle determines that the vehicle is not sufficiently within the parking area due to the detected object and the vehicle exits the parking area (second operation)].
Niewiadomski suggests that an object prevents the vehicle from parking in a parking position and the vehicle then determining identifying a new parking area [see Paragraph 0089].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the invention as taught by Pfeiffer to update one or more predicted locations of one or more target objects based at least on second sensor data obtained subsequent to the performance of the one or more operations and perform one or more second operations associated with the machine based at least on the update of the one or more predicted locations as taught by Niewiadomski in order to identify a new parking position when the object prevents the vehicle from parking [Niewiadomski, see Paragraph 0089].
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Pfeiffer in view of Panthri.
Regarding claim 16, Pfeiffer discloses the invention with respect to claim 11.
However, Pfeiffer fails to disclose one or more processors further to: obtain map data indicating one or more locations of one or more target regions in the environment; and analyze the sensor data with respect to the map data, wherein the determination of the probability associated with the one or more target objects being disposed in the one or more target areas of the target region is based at least on the analysis.
Panthri discloses one or more processors further to: obtain map data indicating one or more locations of one or more target regions in the environment; and analyze the sensor data with respect to the map data, wherein the determination of the probability associated with the one or more target objects being disposed in the one or more target areas of the target region is based at least on the analysis [see Paragraph 0042 - discusses comparing sensor data with map data to indicate the location of a parking lot to determine whether a location of a vehicle is within a threshold distance from the parking space].
Panthri suggests that evaluating the sensor with the map data, determines that a vehicle is within a threshold distance of a parking space (target region) [see Paragraph 0042]. Further, it is known to one having ordinary skill in the art that using different data such as sensor data and map data increases the accuracy of location determination.
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the one or more processors as taught by Pfeiffer to obtain map data indicating one or more locations of one or more target regions in the environment; and analyze the sensor data with respect to the map data, wherein the determination of the probability associated with the one or more target objects being disposed in the one or more target areas of the target region is based at least on the analysis as taught by Panthri before the determination of the probability associated with the one or more target objects being disposed in the one or more target areas of the one or more target regions in order to increase location determination accuracy and to determine that a vehicle is within a threshold distance of a parking space [Panthri, see Paragraph 0042] before performing the one or more actions based on the target object.
Response to Arguments
Applicants’ arguments appear to be directed solely to the amended subject matter, and are not persuasive, as noted supra in the rejections of that claimed subject matter.
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 Shayne M Gilbertson whose telephone number is (571)272-4862. The examiner can normally be reached Tuesday - Friday: 10:30 AM - 9:30 PM EST.
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/SHAYNE M. GILBERTSON/Examiner, Art Unit 3665
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