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 .
DETAILED ACTION
Per Applicant’s Request for Continued Examination 3/13/26
Claims 1 and 19-20 have been amended.
Claims 1-20 are pending.
Response to Arguments
Applicant’s arguments with respect to the pending claims have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Double Patenting
I. 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).
II. 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 USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The 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/process/file/efs/guidance/eTD-info-I.jsp.
III. CLAIMS 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims of U.S. Patent No. 11,830,299. Although the claims at issue are not identical, they are not patentably distinct from each other as indicated below.
Conflicting Patent – 11,830,299
(US App 17/979,980)
Instant Application – 18/388695
1, 18, 19. A method comprising using at least one hardware processor to:
receive sensor data, collected by one or more sensor systems of one or more vehicles, and submitted by a first user via at least one network;
automatically analyze the sensor data to detect one or more characteristics of the sensor data and to enhance the sensor data, prior to publishing a description of the sensor data in an online marketplace, wherein enhancing the sensor data comprises removing data that identifies a location from the sensor data by pruning a beginning portion of the sensor data and an ending portion of the sensor data from the sensor data; and
generate a graphical user interface comprising one or more screens of the online marketplace via which a second user may view the description of the sensor data and purchase the sensor data for download via the at least one network.
1, 19, 20. A method comprising using at least one hardware processor to:
receive sensor data, collected by one or more sensor systems of one or more vehicles driving through a geographical location at a past time, and submitted by a first user via at least one network;
automatically analyze the sensor data to detect one or more characteristics of the sensor data and to enhance the sensor data, prior to publishing a description of the sensor data in an online marketplace, wherein enhancing the sensor data comprises, performing all of the following at a future time that is subsequent to the past time and after the one or more vehicles have finished driving:
identifying the geographic location and the past time associated with the sensor data, retrieving weather conditions, associated with the geographic location at the past time at which the sensor data were collected, from an external third-party weather system, via the at least one network, and associating the weather conditions with the sensor data; and
generate a graphical user interface comprising one or more screens of the online marketplace via which a second user may view the description of the sensor data and purchase the sensor data for download via the at least one network.
2. The method of claim 1, wherein detecting one or more characteristics comprises parsing the sensor data to determine whether or not the sensor data adheres to Robot Operating System (ROS) bag format.
2. The method of Claim 1, wherein detecting one or more characteristics comprises parsing the sensor data to determine whether or not the sensor data adheres to Robot Operating System (ROS) bag format.
3. The method of claim 1, further comprising using the at least one hardware processor to, when at least one characteristic is detected by the analysis of the sensor data and the at least one characteristic comprises a problem: notify the first user about the problem; and receive corrected sensor data from the first user via the at least one network.
3. The method of Claim 1, further comprising using the at least one hardware processor to, when at least one characteristic is detected by the analysis of the sensor data and the at least one characteristic comprises a problem: notify the first user about the problem; and receive corrected sensor data from the first user via the at least one network.
4. The method of claim 1, wherein enhancing the sensor data comprises:
analyzing the one or more characteristics of the sensor data to detect one or more events in the sensor data; and adding an indication of the detected one or more events to the description of the sensor data.
4. The method of Claim 1, wherein enhancing the sensor data comprises:
analyzing the one or more characteristics of the sensor data to detect one or more events in the sensor data; and adding an indication of the detected one or more events to the description of the sensor data.
5. The method of claim 1, wherein enhancing the sensor data comprises:
computing one or more metrics of the sensor data, wherein computing one or more metrics of the sensor data comprises comparing the sensor data to one or more other sensor data to determine a metric of how up-to-date the sensor data is; and
adding an indication of the computed one or more metrics to the description of the sensor data.
5. The method of Claim 1, wherein enhancing the sensor data comprises:
computing one or more metrics of the sensor data; and adding an indication of the computed one or more metrics to the description of the sensor data.
6. The method of Claim 5, wherein computing one or more metrics of the sensor data comprises comparing the sensor data to one or more other sensor data to determine a metric of how up-to-date the sensor data is.
7. The method of claim 1, further comprising using the at least one hardware processor to:
receive one or more criteria from the second user, wherein the one or more criteria comprise one or more of a geographical location within which the sensor data was collected, a characteristic of the sensor data, an event represented in the sensor data, or a metric of the sensor data;
determine that the sensor data satisfies the one or more criteria; and
notify the second user that the sensor data is available for purchase.
7. The method of Claim 1, further comprising using the at least one hardware processor to:
receive one or more criteria from the second user;
determine that the sensor data satisfies the one or more criteria; and
notify the second user that the sensor data is available for purchase.
8. The method of Claim 7, wherein the one or more criteria comprise one or more of the geographical location within which the sensor data was collected, a characteristic of the sensor data, an event represented in the sensor data, or a metric of the sensor data.
8. The method of claim 1, further comprising using the at least one hardware processor to:
receive one or more criteria from the first user;
receive a search or request for sensor data from the second user, wherein the search or request for sensor data satisfies the one or more criteria; and
notify the first user about the searched or requested sensor data.
9. The method of Claim 1, further comprising using the at least one hardware processor to:
receive one or more criteria from the first user; receive a search or request for sensor data from the second user, wherein the search or request for sensor data satisfies the one or more criteria; and notify the first user about the searched or requested sensor data.
9. The method of claim 1, further comprising using the at least one hardware processor to:
receive a software module, submitted by a third user, via the at least one network, wherein the software module comprises instructions for controlling an autonomous system of a vehicle;
automatically analyze the software module to derive information about the software module, wherein analyzing the software module comprises computing a metric for the software module, and wherein the computed metric comprises one or both of a functional safety compliance metric or a computational performance metric; and
generate a graphical user interface comprising one or more screens of the online marketplace via which another user may view a description of the software module and purchase the software module for download via the at least one network, wherein the description of the software module comprises the computed metric.
10. The method of Claim 1, further comprising using the at least one hardware processor to: receive a software module, submitted by a third user, via the at least one network, wherein the software module comprises instructions for controlling an autonomous system of a vehicle; automatically analyze the software module to derive information about the software module, wherein analyzing the software module comprises computing a metric for the software module, and wherein the computed metric comprises one or both of a functional safety compliance metric or a computational performance metric; and
generate a graphical user interface comprising one or more screens of the online marketplace via which another user may view a description of the software module and purchase the software module for download via the at least one network, wherein the description of the software module comprises the computed metric.
10. The method of claim 9, wherein analyzing the software module comprises determining whether or not the software module is compatible with an application programming interface (API) of a robot operating system for interacting with the autonomous system of the vehicle.
11. The method of Claim 10, wherein analyzing the software module comprises determining whether or not the software module is compatible with an application programming interface (API) of a robot operating system for interacting with the autonomous system of the vehicle.
11. The method of claim 9, wherein analyzing the software module further comprises testing the software module using a plurality of types of sensors, and wherein the description of the software module further comprises each one of the plurality of types of sensors for which the software module was successfully tested.
12. The method of Claim 10, wherein analyzing the software module further comprises testing the software module using a plurality of types of sensors, and wherein the description of the software module further comprises each one of the plurality of types of sensors for which the software module was successfully tested.
12. The method of claim 1, further comprising using the at least one hardware processor to:
receive a description of a service, submitted by a fourth user, via the at least one network, wherein the service is related to autonomous vehicles; and
generate a graphical user interface comprising one or more screens of the online marketplace via which another user may view a description of the service and purchase the service.
13. The method of Claim 1, further comprising using the at least one hardware processor to: receive a description of a service, submitted by a fourth user, via the at least one network, wherein the service is related to autonomous vehicles; and generate a graphical user interface comprising one or more screens of the online marketplace via which another user may view a description of the service and purchase the service.
13. The method of claim 1, further comprising using the at least one hardware processor to:
receive a virtual map, submitted by a fifth user, via the at least one network; and
generate a graphical user interface comprising one or more screens of the online marketplace via which another user may view a description of the virtual map and purchase the virtual map for download via the at least one network.
14. The method of Claim 1, further comprising using the at least one hardware processor to: receive a virtual map, submitted by a fifth user, via the at least one network; and
generate a graphical user interface comprising one or more screens of the online marketplace via which another user may view a description of the virtual map and purchase the virtual map for download via the at least one network.
14. The method of claim 13, further comprising using the at least one hardware processor to:
analyze the virtual map to determine whether or not the virtual map comprises a three-dimensional point cloud; and, when the virtual map is determined to comprise a three-dimensional point cloud, add an indication that the virtual map comprises a three-dimensional point cloud to the description of the virtual map.
15. The method of Claim 14, further comprising using the at least one hardware processor to: analyze the virtual map to determine whether or not the virtual map comprises a three- dimensional point cloud; and, when the virtual map is determined to comprise a three-dimensional point cloud, add an indication that the virtual map comprises a three-dimensional point cloud to the description of the virtual map.
15. The method of claim 13, further comprising using the at least one hardware processor to:
receive a request for a virtual map of a geographical region that satisfies one or more criteria, via the at least one network;
extract a portion, comprising the geographical region and satisfying the one or more criteria, from an existing virtual map that comprises the geographical region and at least one other geographical region; and
provide the extracted portion, in response to the request, via the at least one network.
16. The method of Claim 14, further comprising using the at least one hardware processor to: receive a request for a virtual map of a geographical region that satisfies one or more criteria, via the at least one network;
extract a portion, comprising the geographical region and satisfying the one or more criteria, from an existing virtual map that comprises the geographical region and at least one other geographical region; and
provide the extracted portion, in response to the request, via the at least one network.
16. The method of claim 13, further comprising using the at least one hardware processor to:
receive a request for a virtual map of a geographical region that satisfies one or more criteria, via the at least one network;
generate a composite map, comprising the geographical region and satisfying the one or more criteria, from two or more existing virtual maps that each comprise a portion of the geographical region; and
provide the composite map, in response to the request, via the at least one network.
17. The method of Claim 14, further comprising using the at least one hardware processor to: receive a request for a virtual map of a geographical region that satisfies one or more criteria, via the at least one network;
generate a composite map, comprising the geographical region and satisfying the one or more criteria, from two or more existing virtual maps that each comprise a portion of the geographical region; and
provide the composite map, in response to the request, via the at least one network.
17. The method of claim 1, further comprising using the at least one hardware processor to:
compute one or more aggregate metrics for a plurality of the sensor data; and
provide the one or more aggregate metrics for purchase or analysis via one or more screens of the online marketplace.
18. The method of Claim 1, further comprising using the at least one hardware processor to: compute one or more aggregate metrics for a plurality of the sensor data; and
provide the one or more aggregate metrics for purchase or analysis via one or more screens of the online marketplace.
Allowable Subject Matter
IV. CLAIMS 1-20 have been deemed allowable over the 35 U.S.C. 102 and 35 U.S.C. 103 prior art statutes. Other than the above Double Patenting rejection, no prior art has been found to anticipate, teach or suggest the detailed features of the claimed inventive scope.
Independent Claims 1 and 19-20 claim to: “receive sensor data, collected by one or more sensor systems of one or more vehicles driving through a geographical location at a past time, and submitted by a first user via at least one network; automatically analyze the sensor data to detect one or more characteristics of the sensor data and to enhance the sensor data, prior to publishing a description of the sensor data in an online marketplace, wherein enhancing the sensor data comprises, performing all of the following at a future time that is subsequent to the past time and after the one or more vehicles have finished driving: identifying the geographic location and the past time associated with the sensor data, retrieving weather conditions, associated with the geographic location at the past time at which the sensor data were collected, from an external third-party weather system, via the at least one network, and associating the weather conditions with the sensor data; and generate a graphical user interface comprising one or more screens of the online marketplace via which a second user may view the description of the sensor data and purchase the sensor data for download via the at least one network”. Cited prior art teaches monitoring and tracking weather conditions using sensor, yet fails to explicitly teach that prior to publishing a description of the sensor data in an online marketplace, enhancing the sensor data by performing all of the following at a future time that is subsequent to the past time and after the one or more vehicles have finished driving: identifying the geographic location and the past time associated with the sensor data, retrieving weather conditions, associated with the geographic location at the past time at which the sensor data were collected, from an external third-party weather system, via the at least one network, and associating the weather conditions with the sensor data; and generating a graphical user interface of online marketplace via which a second user may view the description of the sensor data and purchase the sensor data for download via the at least one network. The dependent 2-18 inherit the allowable subject matter from independent claim 1 and are therefore deemed allowable over the prior art under the same basis.
Conclusion
V. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: US 2017/0067747.
VI. Any inquiry concerning this communication or earlier communications from the examiner should be directed to KRISTIE D SHINGLES whose telephone number is (571)272-3888. The examiner can normally be reached on Monday-Thursday 10am-7pm.
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/KRISTIE D SHINGLES/
Primary Examiner, Art Unit 2448