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 action is in response to applicant’s amendment of 10 July 2025. Claims 1, 8 and 14 have been amended. Claim 15 is cancelled. Claims 1-14 and 16-20 are pending and examined herein.
Allowable Subject Matter
The indicated allowability of the subject matter of claims 1-20 indicated in the Non-Final Rejection of 24 February 2025 is withdrawn in view of newly discovered reference(s). Rejections based on the newly cited reference(s) follow.
Response to Arguments
Applicant's arguments with respect to the rejection of claims 1-20 under 35 USC 101 have been fully considered but they are not persuasive. Specifically, applicant argues that the claims have been amended to recite performance of “one or more localization, control or navigation operations for maneuvering a machine”, and as such, the claims recite a practical application. Applicant’s arguments have been carefully considered but not persuasive. The examiner respectfully disagrees that the amended limitations integrate the abstract idea into practical application. The amended limitation is recited at a high level of generality and amounts to mere post solution actions, which is a form of insignificant extra solution activity. Specifically, under a broadest reasonable interpretation, the amended limitation of claim 1 can include navigating a machine based on correspondence between the sensor data and the HD map data. This could include a human driver navigating/driving a vehicle based on the resulting comparison. This is the equivalent of adding the words “apply it” to the claim. As such, the rejection of claims 1-14 and 16-20 under 35 USC 101 has not been overcome.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-14 and 16-20 are rejected under 35 U.S.C. 101 because they recite an abstract idea without significantly more.
101 Analysis – Step 1
Claims 1-7 recite a series of steps, therefore claims 1-7 are a method/process which is within at least one of the four statutory categories.
Claims 8-20 recite a system/ machine, therefore claims 8-20 are system/ machine which is within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong 1
Regarding Prong 1 of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
Independent claims 1, 8, and 14 include limitations that recite an abstract idea (emphasized below). Claim 1, 8, and 14 recite, respectively:
1. A method comprising:
determining a correspondence between a first point cloud and a second point cloud based at least on comparing one or more first points of the first point cloud to one or more second points of the second point cloud, the comparing being constrained according to whether the one or more first points and the one or more second points correspond to ground points or non-ground points; and
performing one or more localization, control, or navigation operations for maneuvering a machine based at least on the correspondence.
8. A processor comprising:
processing circuitry to cause performance of operations comprising:
determining a first correspondence between one or more first ground points of a first point cloud and one or more second ground points of a second point cloud;
determining a second correspondence between one or more first non-ground points and one or more second non-ground points; and
determining a pose of a machine based at least on the first correspondence and the second correspondence; and
causing the machine to perform one or more localization, control, or navigation operations for maneuvering the machine based at least on the pose.
14. A system comprising:
one or more processing units to cause performance of operations comprising:
determining one or more first ground points and one or more first non-ground points of a first point cloud;
determining a correspondence between the first point cloud and a second point cloud based at least on at least one of:
comparing the one or more first ground points to one or more second ground points of the second point cloud; or
comparing the one or more first non-ground points to one or more second non-ground points of the second point cloud;
aligning the first point cloud with the second point cloud based at least on the correspondence; and
causing the machine to perform one or more localization, control, or navigation operations for maneuvering the machine based at least on the aligning of the first point cloud with the second point cloud.
The limitations highlighted in claims 1, 8 and 14 above is a mental process that can be practicably performed in the human mind and, therefore, an abstract idea. These limitations, as drafted, is a system that, under its broadest reasonable interpretation, covers performance of the limitation as certain mental process. That is, nothing in the claim elements preclude the steps from practically being performed as certain mental process. For example, “determining…” and “comparing …” encompass a human aligning data point, determining machine location or pose based on data or parameter in mind, with or without using a physical aid, like a pen and paper or a calculator, to make such calculations or comparison, the use of a physical aid would not negate the mental nature of this limitation. See MPEP 2106.04(a)(2), subsection III.B.. Thus, the claims recite at least one abstract idea. If given the sensor (first point cloud data) a person can mentally determine if the sensor data aligns with second sensor data (map data). As such, the claims recite an abstract idea.
101 Analysis – Step 2A, Prong 2
Regarding Prong 2 of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”):
emphasized below). Claim 1, 8, and 14 recite, respectively:
1. A method comprising:
determining a correspondence between a first point cloud and a second point cloud based at least on comparing one or more first points of the first point cloud to one or more second points of the second point cloud, the comparing being constrained according to whether the one or more first points and the one or more second points correspond to ground points or non-ground points; and
performing one or more localization, control, or navigation operations for maneuvering a machine based at least on the correspondence.
8. A processor comprising:
processing circuitry to cause performance of operations comprising:
determining a first correspondence between one or more first ground points of a first point cloud and one or more second ground points of a second point cloud;
determining a second correspondence between one or more first non-ground points and one or more second non-ground points; and
determining a pose of a machine based at least on the first correspondence and the second correspondence; and
causing the machine to perform one or more localization, control, or navigation operations for maneuvering the machine based at least on the pose.
14. A system comprising:
one or more processing units to cause performance of operations comprising:
determining one or more first ground points and one or more first non-ground points of a first point cloud;
determining a correspondence between the first point cloud and a second point cloud based at least on at least one of:
comparing the one or more first ground points to one or more second ground points of the second point cloud; or
comparing the one or more first non-ground points to one or more second non-ground points of the second point cloud;
aligning the first point cloud with the second point cloud based at least on the correspondence; and
causing the machine to perform one or more localization, control, or navigation operations for maneuvering the machine based at least on the aligning of the first point cloud with the second point cloud.
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional limitations of using a processor, processing circuitry, and one or more processing units to perform aligning data point, determining machine location or pose based on data or parameter, the examiner submits that these limitations are mere instructions to apply the above-noted abstract idea by merely using a general processor to perform the process (MPEP § 2106.05). In particular, the devices recited at a high-level of generality (i.e., as a generic processor processing aligning data point, determining machine location or pose based on data or parameter) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Further, the performing limitations are recited at a high level of generality and amount to mere post solution actions, which is a form of insignificant extra solution activity. Specifically, under a broadest reasonable interpretation, the performing limitations can include navigating a machine based on correspondence between the sensor data and the HD map data. This could include a human driver navigating/driving a vehicle based on the resulting comparison (see paragraph [0123] that discusses the claimed system/techniques can be applied to vehicles with human drivers). This is the equivalent of adding the words “apply it” to the claim.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular process for aligning data point, determining machine location or pose based on data or parameter, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B
Regarding Step 2B in the 2019 PEG, representative independent claim 11 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of a processor, processing circuitry, and one or more processing units to perform aligning data point, determining machine location or pose based on data or parameter amounts to nothing more than applying the exception using a generic computer component. Generally applying an exception using a generic computer component cannot provide an inventive concept.
Therefore, claims 1, 8, and 14 is ineligible under 35 USC §101.
Dependent claims 2-7, 9-13, and 16-20 specify limitations that elaborate on the abstract idea of claims 1, 8, and 14 and thus is directed to an abstract idea nor does it recite additional limitations that integrate the claim into a practical application or amount to “significantly more” for similar reasons.
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 1-14 and 16-20 are rejected under 35 U.S.C. 103 as being unpatentable over Jensen (US 2019/0101649) in view of Allais et al. (US 11022693).
With respect to claim 1, Jensen teaches a method (see at least Abstract) comprising: determining a correspondence between a first point cloud and a second point cloud based at least on comparing one or more first points of the first point cloud to one or more second points of the second point cloud (see at least ¶ [0018]-[0019] wherein maps may include 3-D point cloud; ¶[0021] “overlap score provides an indication of how well position information derived from three-dimensional LIDAR point cloud captured by autonomous vehicle matches position information (e.g. point cloud data) included in a particular map at a particular location and, in some embodiments, orientation. The autonomous vehicle generates multiple overlap scores from a single set of captured position information by calculating the overlap score at different candidate positions within the particular map”; ¶[0026] “The controller or vehicle computing system 106 compares data collected by the sensor 104 to map data included in the map database 118.” ; and ¶[0045] “The vehicle controller 106 may be configured to capture multiple point cloud data sets from the sensor 104 and compare the point cloud data sets to map data in the map database 118. “) ; and
performing one or more localization, control, or navigation operations for maneuvering a machine based at least on the correspondence (see at least ¶[0045] “based on the comparison, the controller 106 may determine a position of the vehicle 102. The vehicle controller 106 may control the position and/or speed of the vehicle 102 by issuing commands to one or more of the motor controller 210, steering controller 212, and/or braking controller 214”).
While Jensen teaches the comparing of first point cloud data from a sensor to second point cloud data from a map, Jensen does not explicitly teach that the comparing being constrained according to whether the one or more first points and the one or more second points correspond to ground points or non-ground points. However, in the same field of endeavor, such matter is taught by Allais et al. (see at least col. 10, line 52-col. 11, line 9 wherein Alias teaches the aligning of the point cloud data coming from a sensor to data in a map to determine ground points (and non-ground points).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to use the teachings of Allais et al. going to the teachings to comparing sensor point cloud data with map data to determine ground and non-ground points with the teachings of Jensen going to the comparing of sensor point cloud data to stored map point cloud data, as both systems used stored data to verify (or interpret) data coming from a Lidar sensor with that of a stored map and the determining of ground points versus non-ground points would aid in the navigation and maneuvering of an autonomous vehicle through and environment.
With respect to claim 8, Jensen teaches a processor comprising: processing circuitry to cause performance of operations (see at least ¶[0030] comprising: determining a first correspondence between one or more first points of a first point cloud and one or more second points of a second point cloud (see at least ¶ [0018]-[0019] wherein maps may include 3-D point cloud; ¶[0021] “overlap score provides an indication of how well position information derived from three-dimensional LIDAR point cloud captured by autonomous vehicle matches position information (e.g. point cloud data) included in a particular map at a particular location and, in some embodiments, orientation. The autonomous vehicle generates multiple overlap scores from a single set of captured position information by calculating the overlap score at different candidate positions within the particular map”; ¶[0026] “The controller or vehicle computing system 106 compares data collected by the sensor 104 to map data included in the map database 118.” ; and ¶[0045] “The vehicle controller 106 may be configured to capture multiple point cloud data sets from the sensor 104 and compare the point cloud data sets to map data in the map database 118. “);
determining a second correspondence between one or more first and one or more second points (see at least ¶ [0018]-[0019] wherein maps may include 3-D point cloud; ¶[0021] “overlap score provides an indication of how well position information derived from three-dimensional LIDAR point cloud captured by autonomous vehicle matches position information (e.g. point cloud data) included in a particular map at a particular location and, in some embodiments, orientation. The autonomous vehicle generates multiple overlap scores from a single set of captured position information by calculating the overlap score at different candidate positions within the particular map”; ¶[0026] “The controller or vehicle computing system 106 compares data collected by the sensor 104 to map data included in the map database 118.” ; and ¶[0045] “The vehicle controller 106 may be configured to capture multiple point cloud data sets from the sensor 104 and compare the point cloud data sets to map data in the map database 118. “); and
determining a pose of a machine based at least on the first correspondence and the second correspondence (see at least ¶[0045] “based on the comparison, the controller 106 may determine a position of the vehicle 102. The vehicle controller 106 may control the position and/or speed of the vehicle 102 by issuing commands to one or more of the motor controller 210, steering controller 212, and/or braking controller 214”); and
causing the machine to perform one or more localization, control, or navigation operations for maneuvering the machine based at least on the pose (see at least ¶[0045] “based on the comparison, the controller 106 may determine a position of the vehicle 102. The vehicle controller 106 may control the position and/or speed of the vehicle 102 by issuing commands to one or more of the motor controller 210, steering controller 212, and/or braking controller 214”).
While Jensen teaches the comparing of first point cloud data from a sensor to second point cloud data from a map, Jensen does not explicitly teach that the comparing going to points and non-ground points. However, in the same field of endeavor, such matter is taught by Allais et al. (see at least col. 10, line 52-col. 11, line 9 wherein Alias teaches the aligning of the point cloud data coming from a sensor to data in a map to determine ground points (and non-ground points).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to use the teachings of Allais et al. going to the teachings to comparing sensor point cloud data with map data to determine ground and non-ground points with the teachings of Jensen going to the comparing of sensor point cloud data to stored map point cloud data, as both systems used stored data to verify (or interpret) data coming from a Lidar sensor with that of a stored map and the determining of ground points versus non-ground points would aid in the navigation and maneuvering of an autonomous vehicle through and environment.
With respect to claim 14, Jensen teaches a system comprising: one or more processing units to cause performance of operations (see at least ¶[0030] comprising:
determining one or more first points and one or more first points of a first point cloud (see at least ¶ [0018]-[0019] wherein maps may include 3-D point cloud; ¶[0021] “overlap score provides an indication of how well position information derived from three-dimensional LIDAR point cloud captured by autonomous vehicle matches position information (e.g. point cloud data) included in a particular map at a particular location and, in some embodiments, orientation. The autonomous vehicle generates multiple overlap scores from a single set of captured position information by calculating the overlap score at different candidate positions within the particular map”; ¶[0026] “The controller or vehicle computing system 106 compares data collected by the sensor 104 to map data included in the map database 118.” ; and ¶[0045] “The vehicle controller 106 may be configured to capture multiple point cloud data sets from the sensor 104 and compare the point cloud data sets to map data in the map database 118. “); determining a correspondence between the first point cloud and a second point cloud based at least on at least one of: comparing the one or more first points to one or more second points of the second point cloud; or comparing the one or more first points to one or more second points of the second point cloud (see at least ¶ [0018]-[0019] wherein maps may include 3-D point cloud; ¶[0021] “overlap score provides an indication of how well position information derived from three-dimensional LIDAR point cloud captured by autonomous vehicle matches position information (e.g. point cloud data) included in a particular map at a particular location and, in some embodiments, orientation. The autonomous vehicle generates multiple overlap scores from a single set of captured position information by calculating the overlap score at different candidate positions within the particular map”; ¶[0026] “The controller or vehicle computing system 106 compares data collected by the sensor 104 to map data included in the map database 118.” ; and ¶[0045] “The vehicle controller 106 may be configured to capture multiple point cloud data sets from the sensor 104 and compare the point cloud data sets to map data in the map database 118.“);
aligning the first point cloud with the second point cloud based at least on the correspondence (see at least ¶[0045] “based on the comparison, the controller 106 may determine a position of the vehicle 102. The vehicle controller 106 may control the position and/or speed of the vehicle 102 by issuing commands to one or more of the motor controller 210, steering controller 212, and/or braking controller 214”); and causing the machine to perform one or more localization, control, or navigation operations for maneuvering the machine based at least on the aligning of the first point cloud with the second point cloud (see at least ¶[0045] “based on the comparison, the controller 106 may determine a position of the vehicle 102. The vehicle controller 106 may control the position and/or speed of the vehicle 102 by issuing commands to one or more of the motor controller 210, steering controller 212, and/or braking controller 214”).
While Jensen teaches the comparing of first point cloud data from a sensor to second point cloud data from a map, Jensen does not explicitly teach that the comparing going to points and non-ground points. However, in the same field of endeavor, such matter is taught by Allais et al. (see at least col. 10, line 52-col. 11, line 9 wherein Alias teaches the aligning of the point cloud data coming from a sensor to data in a map to determine ground points (and non-ground points).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to use the teachings of Allais et al. going to the teachings to comparing sensor point cloud data with map data to determine ground and non-ground points with the teachings of Jensen going to the comparing of sensor point cloud data to stored map point cloud data, as both systems used stored data to verify (or interpret) data coming from a Lidar sensor with that of a stored map and the determining of ground points versus non-ground points would aid in the navigation and maneuvering of an autonomous vehicle through and environment.
With respect to claims 2, and commensurate claims 9 and 16, Jensen teaches wherein: the first point cloud is obtained using a sensor associated with the machine; and the second point cloud corresponds to map data corresponding to a region in which the machine is located (see at least ¶ [0018]-[0019] wherein maps may include 3-D point cloud; ¶[0021] “overlap score provides an indication of how well position information derived from three-dimensional LIDAR point cloud captured by autonomous vehicle matches position information (e.g. point cloud data) included in a particular map at a particular location and, in some embodiments, orientation. The autonomous vehicle generates multiple overlap scores from a single set of captured position information by calculating the overlap score at different candidate positions within the particular map”).
With respect to claim 3, Jensen teaches wherein the sensor includes a light detection and ranging (LIDAR) sensor (see at least ¶[0033]).
With respect to claim 4, and commensurate claims 10 and 17, Jensen does not explicitly teach wherein at least one of a roll, a pitch, or an altitude of the machine is determined based at least on an orientation of a ground plane determined based at least on the one or more first ground points. However, such matter is taught by Allais et al. (see at least col. 10, lines 7-32). It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to use the teachings of Allais et al. going to the teachings to comparing sensor point cloud data with map data to determine ground and non-ground points with the teachings of Jensen going to the comparing of sensor point cloud data to stored map point cloud data, as both systems used stored data to verify (or interpret) data coming from a Lidar sensor with that of a stored map and the determining of ground points versus non-ground points would aid in the navigation and maneuvering of an autonomous vehicle through and environment.
With respect to claim 5, and commensurate claims 11 and 18, Jensen does not explicitly teach wherein, during execution of the determining of the correspondence, comparing of one or more first ground points of the one or more first points to one or more second ground points of the one or more second points is weighted differently than comparing of one or more first non-ground points of the one or more points to one or more second non-ground points of the one or more second points. While Jensen teaches the comparing of first point cloud data from a sensor to second point cloud data from a map, Jensen does not explicitly teach that the comparing going to points and non-ground points. However, in the same field of endeavor, such matter is taught by Allais et al. (see at least col. 10, line 52-col. 11, line 9).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to use the teachings of Allais et al. going to the teachings to comparing sensor point cloud data with map data to determine ground and non-ground points with the teachings of Jensen going to the comparing of sensor point cloud data to stored map point cloud data, as both systems used stored data to verify (or interpret) data coming from a Lidar sensor with that of a stored map and the determining of ground points versus non-ground points would aid in the navigation and maneuvering of an autonomous vehicle through and environment.
With respect to claim 6, and commensurate claims 12 and 19, Jensen does not explicitly teach further comprising segmenting the first point cloud to identify one or more first ground points and one or more first non-ground points of the one or more first points. However, in the same field of endeavor, such matter is taught by Allais et al. (see at least col. 10, line 52-col. 11, line 9).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to use the teachings of Allais et al. going to the teachings to comparing sensor point cloud data with map data to determine ground and non-ground points with the teachings of Jensen going to the comparing of sensor point cloud data to stored map point cloud data, as both systems used stored data to verify (or interpret) data coming from a Lidar sensor with that of a stored map and the determining of ground points versus non-ground points would aid in the navigation and maneuvering of an autonomous vehicle through and environment.
With respect to claim 7, and commensurate claims 8 and 20, Jensen does not explicitly teach wherein one or more first ground points of the one or more first points are compared to one or more second ground points of the one or more second points separately from one or more first non-ground points of the one or more first points being compared to one or more second non-ground points of the one or more second points. However, in the same field of endeavor, such matter is taught by Allais et al. (see at least col. 10, line 52-col. 11, line 9).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to use the teachings of Allais et al. going to the teachings to comparing sensor point cloud data with map data to determine ground and non-ground points with the teachings of Jensen going to the comparing of sensor point cloud data to stored map point cloud data, as both systems used stored data to verify (or interpret) data coming from a Lidar sensor with that of a stored map and the determining of ground points versus non-ground points would aid in the navigation and maneuvering of an autonomous vehicle through and environment.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-14 and 16-20 rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-18 of U.S. Patent No. 11598876. Although the claims at issue are not identical, they are not patentably distinct from each other because the limitations of the claims of the present application are broader versions of claims 1-18 of the ‘876 patent and as such, each limitation of claims 1-14 and 16-20 of the present application can be directly mapped to a limitation of claims 1-18 of the ‘876 patent.
Conclusion
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Prosecution Insights