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 .
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1-20 are directed to determining a route for navigation, determining whether a terrain map for the route is available, and generating a terrain map. Decision-making processes fall within a subject matter grouping of abstract ideas which the Courts have considered ineligible (mental processes or concepts performed in the human mind: i.e., an observation, evaluation, judgement, or opinion). The claims do not integrate the abstract idea into a practical application, and do not include additional elements that provide an inventive concept (are sufficient to amount to significantly more than the abstract idea).
Under step 1 of the Alice/Mayo framework, it must be considered whether the claims are directed to one of the four statutory classes of invention. In the instant case, claims 1-8 recite an apparatus with one or more computer-readable memories and one or more processors. Claims 9-15 recite a method with at least one step. Claims 16-19 recite an apparatus with one or more computer-readable memories and one or more processors. Claim 20 recites a method with at least one step. Therefore, the claims are each directed to one of the four statutory categories of invention (apparatus, method, apparatus, method).
Under step 2 of the Alice/Mayo framework, it must be considered whether the claims are “directed to” an abstract idea. That is, whether the claims recite an abstract idea and fail to integrate the abstract idea into a practical application.
Regarding independent claim 1, the claim sets forth the abstract idea(s) of determining a route for navigation, determining whether a terrain map for the route is available, and generating a terrain map in the following limitations:
determine a route for navigation;
… determine whether a terrain map for the route is available;
in response to a determination that the terrain map is unavailable at the navigation managing system, generate the terrain map while navigating the route.
The above-recited limitations establish the use of generic computing devices (one or more computer-readable memories storing instructions, one or more processors) to perform a decision-making process. This arrangement amounts to using a computer as a tool to perform an abstract idea. This concept has been considered ineligible as a mental process by the Courts (See MPEP 2106.05(f)). A human being is capable of mentally determining a route for navigation, determining whether a terrain map for the route is available, and generating a terrain map while navigating the route in response to a determination that the terrain map is unavailable at the navigation managing system (e.g., mentally or with the assistance of pen and paper).
Claim 1 does recite additional elements:
An autonomous system
one or more computer-readable memories storing instructions;
and one or more processors coupled to the one or more computer-readable memories and configured to execute the instructions to:
communicate with a navigation managing system to determine whether a terrain map for the route is available…
These additional elements merely amount to reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea. The specification sets forth the general-purpose nature of the computing technology. Paragraph [0052] discloses that “The one or more processors may include one or more hardware devices with processing capabilities, such as general-purpose processors, digital signal processors, central processing units (CPUs), graphical processing units (GPUs), microcontrollers, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a programmable logic device, a discrete gate or transistor logic component, a discrete hardware component, or other programmable logic device.” Paragraph [0055] further discloses that “he storage system 410 may include one or more storage devices. Examples of the storage devices may include, but are not limited to, solid state device, random access memory (RAM), read-only memory (ROM), an erasable programmable read-only memory (EPROM), electrically erasable programmable ROM (EEPROM), a digital versatile disk (DVD), flash memory, compact disk (CD) ROM or other optical disk storage, magnetic disk storage, a portable computer diskette, or a hard disk. In some embodiments, the storage system 410 is one or more local storage devices that are disposed inside the autonomous system.” That is, the technology used to implement the invention is not specific or integral to the claim.
Accordingly, the Examiner concludes that the claim fails to integrate the abstract idea into a practical application, and is therefore “directed to” the abstract idea.
Under step 2B of the Alice/Mayo framework, it must finally be considered whether the claim includes any additional element or combination of elements that provide an inventive concept (i.e., whether the additional element or elements amount to significantly more than the abstract idea). In the instant case, the additional elements, considered both individually and as an ordered combination, merely generally link the use of the judicial exception to a particular technological environment and append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (see MPEP 2106.05(f)). Communicating with a navigation managing system amounts to a manner of receiving or transmitting data over a network, which has been repeatedly considered well-understood, routine, and conventional activity by the Courts (See MPEP 2106.05(d)). Accordingly, the Examiner asserts that the limitations do not provide an inventive concept, and the claim is ineligible for patent.
Independent claims 9, 16, and 20 are parallel in scope to claim 1 and are ineligible for similar reasons.
Regarding claim 2, which sets forth:
the autonomous system further comprises a sensor system including one or more sensors.
Such a recitation merely introduces the additional element of a sensor system including one or more sensors and amounts to embellishing upon the technological environment and the abstract idea of determining a route for navigation, determining whether a terrain map for the route is available, and generating a terrain map applied to generic computer hardware. The written description sets forth the general-purpose nature of the sensor system in at least paragraph [0051]: “The sensor system 402 may include any number, any type of sensor capable of capturing, measuring, and/or sensing data associated with the autonomous system and the environment of the autonomous system.” That is, the technology used to implement the invention is not specific or integral to the claim. As such, it does not integrate the abstract idea into a practical application, and does not provide an inventive concept. Accordingly, the claim does not confer eligibility on the claimed invention and is ineligible for similar reasons to claim 1.
Regarding claim 3, which sets forth:
the terrain map is generated using one or more artificial intelligence or machine learning (AI/ML) models based on sensor data collected by the one or more sensors.
Such a recitation merely embellishes upon the abstract idea of generating the terrain map by further specifying that the terrain map is generated using one or more artificial intelligence or machine learning models. This amounts to reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea. As such, it does not integrate the abstract idea into a practical application, and does not provide an inventive concept. Accordingly, the claim does not confer eligibility on the claimed invention and is ineligible for similar reasons to claim 1.
Claim 10 is parallel in scope to claim 3 and is ineligible for similar reasons.
Regarding claim 4, which sets forth:
the one or more processors are further configured to execute the instructions to: send the generated terrain map to the navigation managing system.
Such a recitation merely introduces the additional element of sending the generated terrain map to the navigation managing system. Sending the generated terrain map to the navigation managing system amounts to a manner of receiving or transmitting data over a network, which has been repeatedly considered well-understood, routine, and conventional activity by the Courts (See MPEP 2106.05(d)). As such, it does not integrate the abstract idea into a practical application, and does not provide an inventive concept. Accordingly, the claim does not confer eligibility on the claimed invention and is ineligible for similar reasons to claim 1.
Claim 11 is parallel in scope to claim 4 and is ineligible for similar reasons.
Regarding claim 5, which sets forth:
the one or more processors are further configured to execute the instructions to: compress the generated terrain map using at least one compression algorithm;
and send a compressed terrain map to the navigation managing system.
Such a recitation merely embellishes upon the abstract idea of generating the terrain map by further requiring compression of the generated terrain map using at least one compression algorithm. A human being is capable of applying a compression algorithm mentally or with the assistance of pen and paper. Sending the compressed terrain map to the navigation managing system amounts to a manner of receiving or transmitting data over a network, which has been repeatedly considered well-understood, routine, and conventional activity by the Courts (See MPEP 2106.05(d)). As such, it does not integrate the abstract idea into a practical application, and does not provide an inventive concept. Accordingly, the claim does not confer eligibility on the claimed invention and is ineligible for similar reasons to claim 1.
Claim 12 is parallel in scope to claim 5 and is ineligible for similar reasons
Regarding claim 6, which sets forth:
the at least one compression algorithm comprises an autoencoder.
Such a recitation merely embellishes upon the abstract idea of generating the terrain map by further requiring that the at least one compression algorithm used to compress the terrain map comprises an autoencoder. This amounts to reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea. As such, it does not integrate the abstract idea into a practical application, and does not provide an inventive concept. Accordingly, the claim does not confer eligibility on the claimed invention and is ineligible for similar reasons to claim 1.
Claim 13 is parallel in scope to claim 6 and is ineligible for similar reasons.
Regarding claim 7, which sets forth:
the navigation managing system comprises at least one of: a network node configured to communicate with the autonomous system using wireless signal, a vendor configured to communicate with the autonomous system via Internet, or one or more other autonomous systems configured to communicate with the autonomous system.
Such a recitation merely embellishes upon the additional element of the navigation managing system, and the claimed acts of communication amount to a manner of receiving or transmitting data over a network, which has been repeatedly considered well-understood, routine, and conventional activity by the Courts (See MPEP 2106.05(d)). As such, it does not integrate the abstract idea into a practical application, and does not provide an inventive concept. Accordingly, the claim does not confer eligibility on the claimed invention and is ineligible for similar reasons to claim 1.
Regarding claim 8, which sets forth:
the one or more processors are further configured to execute the instructions to: in response to a determination that the terrain map is available at the navigation managing system, obtain the terrain map from the navigation managing system;
and perform the navigation based on the obtained terrain map.
Such a recitation merely embellishes upon the abstract idea of determining whether the terrain map is available and introduces the additional element of obtaining the terrain map from the navigation managing system, which amounts to a manner of receiving or transmitting data over a network, which has been repeatedly considered well-understood, routine, and conventional activity by the Courts (See MPEP 2106.05(d)). A human being is capable of performing navigation based on the obtained terrain map (e.g., by providing verbal navigation instructions). As such, it does not integrate the abstract idea into a practical application, and does not provide an inventive concept. Accordingly, the claim does not confer eligibility on the claimed invention and is ineligible for similar reasons to claim 1.
Regarding claim 14, which sets forth:
the determining whether the terrain map is available further comprises: transmitting a request signal to the navigation managing system, the request signal comprising an indication of the route,
and at least one of: a type of the autonomous system, at least one parameter related to weather condition, at least one size of the autonomous system, at least one functional feature of the autonomous system, or a type of work needs to be done by the autonomous system during navigation;
and receiving a feedback signal from the navigation managing system.
Such a recitation merely embellishes upon the abstract idea of determining whether the terrain map is available and introduces additional elements of transmitting and receiving signals, which amounts to a manner of receiving or transmitting data over a network, which has been repeatedly considered well-understood, routine, and conventional activity by the Courts (See MPEP 2106.05(d)). As such, it does not integrate the abstract idea into a practical application, and does not provide an inventive concept. Accordingly, the claim does not confer eligibility on the claimed invention and is ineligible for similar reasons to claim 1.
Claim 15 is parallel in scope to claim 14 and is ineligible for similar reasons. Claim 16 differs slightly in that claim 16 requires “inputting an inquiry on a user interface provided by the navigation managing system”. The act of inputting information into an interface amounts to a mental process of parsing and evaluating data using a computer processing system (see MPEP 2016.04(a)(2)) and therefore does not confer eligibility on the claimed invention.
Regarding claim 17, which sets forth:
the one or more processors are further configured to execute the instructions to: receive, from the autonomous system, the terrain map generated by the autonomous system while navigating the navigation route.
Such a recitation merely embellishes upon the abstract idea of generating the terrain map by applying additional elements of receiving the terrain map from the autonomous system while the autonomous system is navigating the navigation route, applied to generic computing hardware. Receiving the terrain map amounts to a manner of receiving or transmitting data over a network, which has been repeatedly considered well-understood, routine, and conventional activity by the Courts (See MPEP 2106.05(d)). As such, it does not integrate the abstract idea into a practical application, and does not provide an inventive concept. Accordingly, the claim does not confer eligibility on the claimed invention and is ineligible for similar reasons to claim 1.
Regarding claim 18, which sets forth:
the terrain map received from the autonomous system is a compressed terrain map,
and the one or more processors are further configured to execute the instructions to: reconstruct the terrain map based on the compressed terrain map using at least one algorithm,
the at least one algorithm comprising an autoencoder.
Such a recitation is similar in scope to that discussed above with respect to claims 5-6 and 12-13, and is ineligible for similar reasons. Claim 18 differs slightly in that the claim requires reconstructing the terrain map based on the compressed terrain map using the at least one algorithm; however, a human being is likewise capable of applying an algorithm (e.g., with the assistance of pen and paper) to reconstruct the terrain map. This arrangement amounts to reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea. As such, it does not integrate the abstract idea into a practical application, and does not provide an inventive concept. Accordingly, the claim does not confer eligibility on the claimed invention and is ineligible for similar reasons to claim 1.
Regarding claim 19, which sets forth:
the one or more processors are further configured to execute the instructions to: in response to a determination that the navigation managing system has the requested terrain map, optimize the terrain map based on the one or more parameters associated with the autonomous system;
and provide an optimized terrain map.
Such a recitation merely embellishes upon the abstract idea of generating the terrain map by further requiring the one or more processors to optimize the terrain map and provide an optimized terrain map. The optimization of a terrain map based on one or more parameters is an abstract decision-making process capable of being performed mentally or with the assistance of pen and paper. As such, the above recitation amounts to reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea. As such, it does not integrate the abstract idea into a practical application, and does not provide an inventive concept. Accordingly, the claim does not confer eligibility on the claimed invention and is ineligible for similar reasons to claim 1.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-2, 4, 7-9, 11, 14, 16-17, and 19-20 is/are rejected under 35 U.S.C. 102(a)(1)/(a)(2) as being anticipated by Kulkarni et al. (US 2023/0324543 A1), hereinafter Kulkarni.
Regarding claim 1, Kulkarni discloses an autonomous system, comprising:
one or more computer-readable memories storing instructions;
Kulkarni discloses ([0031]): "FIG. 2 is a block diagram of a position estimation system 200, according to an embodiment. The position estimation system 200 collects data from various different sources and outputs a position estimate of the vehicle. This position estimate can be used by an automated driving system, ADAS system, and/or other systems on the vehicle, as well as systems (e.g., traffic monitoring systems) remote to the vehicle. Additionally, as noted, the position estimate of the vehicle can be used by a mapping system of the vehicle when performing the techniques for mapping described hereafter... One or more components of the position estimation system 200 may be implemented in hardware and/or software, such as one or more hardware and/or software components of the mobile computing system 1200 illustrated in FIG. 12 and described in more detail below. For example, the positioning unit 260 may be implemented by one or more processing units." Kulkarni further discloses ([0119]): "The memory 1260 of the mobile computing system 1200 also can comprise software elements (not shown in FIG. 12), including an operating system, device drivers, executable libraries, and/or other code, such as one or more application programs, which may comprise computer programs provided by various embodiments, and/or may be designed to implement methods, and/or configure systems, provided by other embodiments, as described herein."
and one or more processors coupled to the one or more computer-readable memories and configured to execute the instructions to:
Kulkarni discloses ([0031]): "FIG. 2 is a block diagram of a position estimation system 200, according to an embodiment. The position estimation system 200 collects data from various different sources and outputs a position estimate of the vehicle. This position estimate can be used by an automated driving system, ADAS system, and/or other systems on the vehicle, as well as systems (e.g., traffic monitoring systems) remote to the vehicle. Additionally, as noted, the position estimate of the vehicle can be used by a mapping system of the vehicle when performing the techniques for mapping described hereafter... One or more components of the position estimation system 200 may be implemented in hardware and/or software, such as one or more hardware and/or software components of the mobile computing system 1200 illustrated in FIG. 12 and described in more detail below. For example, the positioning unit 260 may be implemented by one or more processing units. "
determine a route for navigation;
Kulkarni discloses ([0043]): "The method may begin with the functionality shown at arrow 320, in which the vehicle 315 sends a notification to the server regarding its current location along with an indication of which HD map layers the vehicle 315 can consume… The vehicle 315 may send the notification based on different triggering events, such as entering or coming within a threshold distance of a geographical region of an HD map, determining a navigation route that enters the geographical region, exiting or coming within a threshold distance of a boundary of a previously-downloaded HD map, communicating with a cellular base station (or other wireless network access point) within the geographical region, or the like."
communicate with a navigation managing system to determine whether a terrain map for the route is available;
Kulkarni discloses ([0043]): "The method may begin with the functionality shown at arrow 320, in which the vehicle 315 sends a notification to the server regarding its current location along with an indication of which HD map layers the vehicle 315 can consume… The vehicle 315 may send the notification based on different triggering events, such as entering or coming within a threshold distance of a geographical region of an HD map, determining a navigation route that enters the geographical region, exiting or coming within a threshold distance of a boundary of a previously-downloaded HD map, communicating with a cellular base station (or other wireless network access point) within the geographical region, or the like." Kulkarni further discloses ([0045]): "The server may then respond as indicated at arrow 325, in which the relevant HD map layers and meta information is provided by the server to the vehicle 315. If the requested HD map is incomplete or unavailable, the server may send a notification to the vehicle 315 that requested map layers are unavailable."
and in response to a determination that the terrain map is unavailable at the navigation managing system, generate the terrain map while navigating the route.
Kulkarni discloses ([0045]): "The server may then respond as indicated at arrow 325, in which the relevant HD map layers and meta information is provided by the server to the vehicle 315. If the requested HD map is incomplete or unavailable, the server may send a notification to the vehicle 315 that requested map layers are unavailable. The meta information, provided by the server along with the HD map layers, may comprise information about the HD map and map layers, including region descriptions (e.g., tile indicators) of regions/layers to be updated and/or region descriptions of regions/layers that do not need updating... In an example implementation, for regions in which the server notifies the vehicle 315 that map updates are not needed, the vehicle 315 does not publish any radar-camara data to the server. In other regions, the vehicle 315 may publish the data as illustrated at arrow 335 if other criteria are satisfied. (The publication of data is described hereafter.)" Kulkarni further discloses ([0046]): " The switch 365 may comprise a logical block that publishes the metadata, processed camera data, and processed radar data to the server (as shown at arrow 335) if the publish flag 330 is ON (i.e., activated)." Kulkarni even further discloses ([0074]): "At block 810, published data uploaded by vehicles is unified. As previously noted (e.g., with regard to block 370 of FIG. 3), data may be unified to a common format and scale, which may vary across vehicles based on sensor type, capabilities, etc." Kulkarni still further discloses ([0075]): "At block 815, the unified data may be stored into memory/cache by the server and aggregated over time. As previously noted with regard to FIG. 6, when the map update trigger 820 is ON (or equivalent), the aggregated data may then be used for optimizing the different map layers, and the trajectory of the vehicles that reported the data."
Regarding claim 2, Kulkarni discloses the aforementioned limitations of claim 1. Kulkarni further discloses:
the autonomous system further comprises a sensor system including one or more sensors.
Kulkarni discloses ([0029]): "FIG. 1 is a drawing of a perspective view of a vehicle 110, illustrating how crowdsourced mapping by the vehicle 110 generally may be performed, according to embodiments. Here, the vehicle 110 (also referred to as the “ego vehicle”) may first determine its position, then use its determined position along with sensors such as cameras and radar to gather information for one or more layers of the HD map." Kulkarni further discloses ([0036]): "The radar 235 may comprise one or more radar sensors disposed in or on the vehicle... Radar can complement other sensors to help provide robust autonomous features. For example, enabling autonomous driving in true sense may require robust solutions for localization in all types of weather and environmental conditions, such that a vehicle knows its pose within few centimeters."
Regarding claim 4, Kulkarni discloses the aforementioned limitations of claim 1. Kulkarni further discloses:
the one or more processors are further configured to execute the instructions to: send the generated terrain map to the navigation managing system.
Kulkarni discloses ([0046]): " The switch 365 may comprise a logical block that publishes the metadata, processed camera data, and processed radar data to the server (as shown at arrow 335) if the publish flag 330 is ON (i.e., activated)." Kulkarni further discloses ([0074]): "At block 810, published data uploaded by vehicles is unified. As previously noted (e.g., with regard to block 370 of FIG. 3), data may be unified to a common format and scale, which may vary across vehicles based on sensor type, capabilities, etc." Kulkarni even further discloses ([0075]): "At block 815, the unified data may be stored into memory/cache by the server and aggregated over time. As previously noted with regard to FIG. 6, when the map update trigger 820 is ON (or equivalent), the aggregated data may then be used for optimizing the different map layers, and the trajectory of the vehicles that reported the data."
Regarding claim 7, Kulkarni discloses the aforementioned limitations of claim 1. Kulkarni further discloses:
the navigation managing system comprises at least one of: a network node configured to communicate with the autonomous system using wireless signal, a vendor configured to communicate with the autonomous system via Internet, or one or more other autonomous systems configured to communicate with the autonomous system.
Kulkarni discloses ([0120]): " FIG. 13 is a block diagram of an embodiment of a computer system 1300, which may be used, in whole or in part, to provide the functions of a server or other computing device as described in the embodiments herein (e.g., the cloud/edge server described with respect to FIGS. 3-10)." Kulkarni further discloses ([0123]): "The computer system 1300 may also include a communications subsystem 1330, which may comprise wireless communication technologies managed and controlled by a wireless communication interface 1333, as well as wired technologies (such as Ethernet, coaxial communications, universal serial bus (USB), and the like). The wireless communication interface 1333 may comprise one or more wireless transceivers that may send and receive wireless signals 1355 (e.g., signals according to 5G NR or LTE) via wireless antenna(s) 1350. Thus the communications subsystem 1330 may comprise a modem, a network card (wireless or wired), an infrared communication device, a wireless communication device, and/or a chip set, and/or the like, which may enable the computer system 1300 to communicate on any or all of the communication networks described herein to any device on the respective network, including a User Equipment (UE), base stations and/or other TRPs, and/or any other electronic devices described herein."
Regarding claim 8, Kulkarni discloses the aforementioned limitations of claim 1. Kulkarni further discloses:
the one or more processors are further configured to execute the instructions to: in response to a determination that the terrain map is available at the navigation managing system, obtain the terrain map from the navigation managing system;
Kulkarni discloses ([0045]): "The server may then respond as indicated at arrow 325, in which the relevant HD map layers and meta information is provided by the server to the vehicle 315. If the requested HD map is incomplete or unavailable, the server may send a notification to the vehicle 315 that requested map layers are unavailable." Kulkarni further discloses ([0046]): "After receiving the HD map layers, the vehicle 315 may perform the functions illustrated in block 305. In particular, the vehicle 315 can use the HD map layers for generating pose estimates of the vehicle 315 and enabling autonomous driving (e.g., as described with regard to FIG. 2)."
and perform the navigation based on the obtained terrain map.
Kulkarni discloses ([0043]): "The method may begin with the functionality shown at arrow 320, in which the vehicle 315 sends a notification to the server regarding its current location along with an indication of which HD map layers the vehicle 315 can consume… The vehicle 315 may send the notification based on different triggering events, such as entering or coming within a threshold distance of a geographical region of an HD map, determining a navigation route that enters the geographical region, exiting or coming within a threshold distance of a boundary of a previously-downloaded HD map, communicating with a cellular base station (or other wireless network access point) within the geographical region, or the like." Kulkarni further discloses ([0046]): "After receiving the HD map layers, the vehicle 315 may perform the functions illustrated in block 305. In particular, the vehicle 315 can use the HD map layers for generating pose estimates of the vehicle 315 and enabling autonomous driving (e.g., as described with regard to FIG. 2)."
Regarding claim 9, Kulkarni discloses a computer-implemented method for an autonomous system, comprising:
determining a route for navigation;
Kulkarni discloses ([0043]): "The method may begin with the functionality shown at arrow 320, in which the vehicle 315 sends a notification to the server regarding its current location along with an indication of which HD map layers the vehicle 315 can consume… The vehicle 315 may send the notification based on different triggering events, such as entering or coming within a threshold distance of a geographical region of an HD map, determining a navigation route that enters the geographical region, exiting or coming within a threshold distance of a boundary of a previously-downloaded HD map, communicating with a cellular base station (or other wireless network access point) within the geographical region, or the like."
communicating with a navigation managing system to determine whether a terrain map for the route is available;
Kulkarni discloses ([0043]): "The method may begin with the functionality shown at arrow 320, in which the vehicle 315 sends a notification to the server regarding its current location along with an indication of which HD map layers the vehicle 315 can consume… The vehicle 315 may send the notification based on different triggering events, such as entering or coming within a threshold distance of a geographical region of an HD map, determining a navigation route that enters the geographical region, exiting or coming within a threshold distance of a boundary of a previously-downloaded HD map, communicating with a cellular base station (or other wireless network access point) within the geographical region, or the like." Kulkarni further discloses ([0045]): "The server may then respond as indicated at arrow 325, in which the relevant HD map layers and meta information is provided by the server to the vehicle 315. If the requested HD map is incomplete or unavailable, the server may send a notification to the vehicle 315 that requested map layers are unavailable."
and in response to a determination that the terrain map is unavailable at the navigation managing system, generating the terrain map while navigating the route.
Kulkarni discloses ([0045]): "The server may then respond as indicated at arrow 325, in which the relevant HD map layers and meta information is provided by the server to the vehicle 315. If the requested HD map is incomplete or unavailable, the server may send a notification to the vehicle 315 that requested map layers are unavailable. The meta information, provided by the server along with the HD map layers, may comprise information about the HD map and map layers, including region descriptions (e.g., tile indicators) of regions/layers to be updated and/or region descriptions of regions/layers that do not need updating... In an example implementation, for regions in which the server notifies the vehicle 315 that map updates are not needed, the vehicle 315 does not publish any radar-camara data to the server. In other regions, the vehicle 315 may publish the data as illustrated at arrow 335 if other criteria are satisfied. (The publication of data is described hereafter.)" Kulkarni further discloses ([0046]): " The switch 365 may comprise a logical block that publishes the metadata, processed camera data, and processed radar data to the server (as shown at arrow 335) if the publish flag 330 is ON (i.e., activated)." Kulkarni even further discloses ([0074]): "At block 810, published data uploaded by vehicles is unified. As previously noted (e.g., with regard to block 370 of FIG. 3), data may be unified to a common format and scale, which may vary across vehicles based on sensor type, capabilities, etc." Kulkarni still further discloses ([0075]): "At block 815, the unified data may be stored into memory/cache by the server and aggregated over time. As previously noted with regard to FIG. 6, when the map update trigger 820 is ON (or equivalent), the aggregated data may then be used for optimizing the different map layers, and the trajectory of the vehicles that reported the data."
Regarding claim 11, Kulkarni discloses the aforementioned limitations of claim 9. Kulkarni further discloses:
sending the generated terrain map to the navigation managing system.
Kulkarni discloses ([0046]): " The switch 365 may comprise a logical block that publishes the metadata, processed camera data, and processed radar data to the server (as shown at arrow 335) if the publish flag 330 is ON (i.e., activated)." Kulkarni further discloses ([0074]): "At block 810, published data uploaded by vehicles is unified. As previously noted (e.g., with regard to block 370 of FIG. 3), data may be unified to a common format and scale, which may vary across vehicles based on sensor type, capabilities, etc." Kulkarni even further discloses ([0075]): "At block 815, the unified data may be stored into memory/cache by the server and aggregated over time. As previously noted with regard to FIG. 6, when the map update trigger 820 is ON (or equivalent), the aggregated data may then be used for optimizing the different map layers, and the trajectory of the vehicles that reported the data."
Regarding claim 14, Kulkarni discloses the aforementioned limitations of claim 9. Kulkarni further discloses:
the determining whether the terrain map is available further comprises: transmitting a request signal to the navigation managing system, the request signal comprising an indication of the route,
Kulkarni discloses ([0043]): "The method may begin with the functionality shown at arrow 320, in which the vehicle 315 sends a notification to the server regarding its current location along with an indication of which HD map layers the vehicle 315 can consume… The vehicle 315 may send the notification based on different triggering events, such as entering or coming within a threshold distance of a geographical region of an HD map, determining a navigation route that enters the geographical region, exiting or coming within a threshold distance of a boundary of a previously-downloaded HD map, communicating with a cellular base station (or other wireless network access point) within the geographical region, or the like." Kulkarni further discloses ([0045]): "The server may then respond as indicated at arrow 325, in which the relevant HD map layers and meta information is provided by the server to the vehicle 315. If the requested HD map is incomplete or unavailable, the server may send a notification to the vehicle 315 that requested map layers are unavailable."
and at least one of: a type of the autonomous system, at least one parameter related to weather condition, at least one size of the autonomous system, at least one functional feature of the autonomous system, or a type of work needs to be done by the autonomous system during navigation;
Kulkarni discloses ([0043]): "The method may begin with the functionality shown at arrow 320, in which the vehicle 315 sends a notification to the server regarding its current location along with an indication of which HD map layers the vehicle 315 can consume…" The Examiner has interpreted the indication of which HD map layers the vehicle 315 can consume as a functional feature of the autonomous system.
and receiving a feedback signal from the navigation managing system.
Kulkarni discloses ([0045]): "The server may then respond as indicated at arrow 325, in which the relevant HD map layers and meta information is provided by the server to the vehicle 315. If the requested HD map is incomplete or unavailable, the server may send a notification to the vehicle 315 that requested map layers are unavailable."
Regarding claim 16, Kulkarni discloses a navigation managing system, comprising:
one or more computer-readable memories storing instructions;
Kulkarni discloses ([0031]): "FIG. 2 is a block diagram of a position estimation system 200, according to an embodiment. The position estimation system 200 collects data from various different sources and outputs a position estimate of the vehicle. This position estimate can be used by an automated driving system, ADAS system, and/or other systems on the vehicle, as well as systems (e.g., traffic monitoring systems) remote to the vehicle. Additionally, as noted, the position estimate of the vehicle can be used by a mapping system of the vehicle when performing the techniques for mapping described hereafter... One or more components of the position estimation system 200 may be implemented in hardware and/or software, such as one or more hardware and/or software components of the mobile computing system 1200 illustrated in FIG. 12 and described in more detail below. For example, the positioning unit 260 may be implemented by one or more processing units." Kulkarni further discloses ([0119]): "The memory 1260 of the mobile computing system 1200 also can comprise software elements (not shown in FIG. 12), including an operating system, device drivers, executable libraries, and/or other code, such as one or more application programs, which may comprise computer programs provided by various embodiments, and/or may be designed to implement methods, and/or configure systems, provided by other embodiments, as described herein." Kulkarni even further discloses ([0124]): "In many embodiments, the computer system 1300 will further comprise a working memory 1335, which may comprise a RAM or ROM device, as described above. Software elements, shown as being located within the working memory 1345, may comprise... one or more applications 1345, which may comprise computer programs provided by various embodiments, and/or may be designed to implement methods, and/or configure systems, provided by other embodiments, as described herein."
and one or more processors coupled to the one or more computer-readable memories and configured to execute the instructions to:
Kulkarni discloses ([0031]): "FIG. 2 is a block diagram of a position estimation system 200, according to an embodiment. The position estimation system 200 collects data from various different sources and outputs a position estimate of the vehicle. This position estimate can be used by an automated driving system, ADAS system, and/or other systems on the vehicle, as well as systems (e.g., traffic monitoring systems) remote to the vehicle. Additionally, as noted, the position estimate of the vehicle can be used by a mapping system of the vehicle when performing the techniques for mapping described hereafter... One or more components of the position estimation system 200 may be implemented in hardware and/or software, such as one or more hardware and/or software components of the mobile computing system 1200 illustrated in FIG. 12 and described in more detail below. For example, the positioning unit 260 may be implemented by one or more processing units." Kulkarni further discloses ([0121]): "The computer system 1300 is shown comprising hardware elements... The hardware elements may include processor(s) 1310..." Kulkarni even further discloses ([0124]): "In many embodiments, the computer system 1300 will further comprise a working memory 1335, which may comprise a RAM or ROM device, as described above. Software elements, shown as being located within the working memory 1345, may comprise... one or more applications 1345, which may comprise computer programs provided by various embodiments, and/or may be designed to implement methods, and/or configure systems, provided by other embodiments, as described herein. Merely by way of example, one or more procedures described with respect to the method(s) discussed above might be implemented as code and/or instructions executable by a computer (and/or a processor within a computer)...
receive, from an autonomous system, a request for a terrain map of a navigation route,
Kulkarni discloses ([0043]): "The method may begin with the functionality shown at arrow 320, in which the vehicle 315 sends a notification to the server regarding its current location along with an indication of which HD map layers the vehicle 315 can consume… The vehicle 315 may send the notification based on different triggering events, such as entering or coming within a threshold distance of a geographical region of an HD map, determining a navigation route that enters the geographical region, exiting or coming within a threshold distance of a boundary of a previously-downloaded HD map, communicating with a cellular base station (or other wireless network access point) within the geographical region, or the like." Kulkarni further discloses ([0045]): "The server may then respond as indicated at arrow 325, in which the relevant HD map layers and meta information is provided by the server to the vehicle 315. If the requested HD map is incomplete or unavailable, the server may send a notification to the vehicle 315 that requested map layers are unavailable."
the request comprising one or more parameters associated with the autonomous system;
Kulkarni discloses ([0043]): "The method may begin with the functionality shown at arrow 320, in which the vehicle 315 sends a notification to the server regarding its current location along with an indication of which HD map layers the vehicle 315 can consume… The vehicle 315 may send the notification based on different triggering events, such as entering or coming within a threshold distance of a geographical region of an HD map, determining a navigation route that enters the geographical region, exiting or coming within a threshold distance of a boundary of a previously-downloaded HD map, communicating with a cellular base station (or other wireless network access point) within the geographical region, or the like." Kulkarni further discloses ([0045]): "The server may then respond as indicated at arrow 325, in which the relevant HD map layers and meta information is provided by the server to the vehicle 315. If the requested HD map is incomplete or unavailable, the server may send a notification to the vehicle 315 that requested map layers are unavailable."
in response to a determination that the terrain map is available at the navigation managing system, provide the terrain map to the autonomous system; or in response to a determination that the terrain map is unavailable at the navigation managing system, provide an indication of unavailability of the terrain map to the autonomous system.
Kulkarni discloses ([0043]): "The method may begin with the functionality shown at arrow 320, in which the vehicle 315 sends a notification to the server regarding its current location along with an indication of which HD map layers the vehicle 315 can consume… The vehicle 315 may send the notification based on different triggering events, such as entering or coming within a threshold distance of a geographical region of an HD map, determining a navigation route that enters the geographical region, exiting or coming within a threshold distance of a boundary of a previously-downloaded HD map, communicating with a cellular base station (or other wireless network access point) within the geographical region, or the like." Kulkarni further discloses ([0045]): "The server may then respond as indicated at arrow 325, in which the relevant HD map layers and meta information is provided by the server to the vehicle 315. If the requested HD map is incomplete or unavailable, the server may send a notification to the vehicle 315 that requested map layers are unavailable."
Regarding claim 17, Kulkarni discloses the aforementioned limitations of claim 16. Kulkarni further discloses:
the one or more processors are further configured to execute the instructions to: receive, from the autonomous system, the terrain map generated by the autonomous system while navigating the navigation route.
Kulkarni discloses ([0045]): "The server may then respond as indicated at arrow 325, in which the relevant HD map layers and meta information is provided by the server to the vehicle 315. If the requested HD map is incomplete or unavailable, the server may send a notification to the vehicle 315 that requested map layers are unavailable. The meta information, provided by the server along with the HD map layers, may comprise information about the HD map and map layers, including region descriptions (e.g., tile indicators) of regions/layers to be updated and/or region descriptions of regions/layers that do not need updating... In an example implementation, for regions in which the server notifies the vehicle 315 that map updates are not needed, the vehicle 315 does not publish any radar-camara data to the server. In other regions, the vehicle 315 may publish the data as illustrated at arrow 335 if other criteria are satisfied. (The publication of data is described hereafter.)" Kulkarni further discloses ([0046]): " The switch 365 may comprise a logical block that publishes the metadata, processed camera data, and processed radar data to the server (as shown at arrow 335) if the publish flag 330 is ON (i.e., activated)." Kulkarni even further discloses ([0074]): "At block 810, published data uploaded by vehicles is unified. As previously noted (e.g., with regard to block 370 of FIG. 3), data may be unified to a common format and scale, which may vary across vehicles based on sensor type, capabilities, etc." Kulkarni still further discloses ([0075]): "At block 815, the unified data may be stored into memory/cache by the server and aggregated over time. As previously noted with regard to FIG. 6, when the map update trigger 820 is ON (or equivalent), the aggregated data may then be used for optimizing the different map layers, and the trajectory of the vehicles that reported the data."
Regarding claim 19, Kulkarni discloses the aforementioned limitations of claim 16. Kulkarni further discloses:
the one or more processors are further configured to execute the instructions to: in response to a determination that the navigation managing system has the requested terrain map, optimize the terrain map based on the one or more parameters associated with the autonomous system;
Kulkarni discloses ([0043]): "The method may begin with the functionality shown at arrow 320, in which the vehicle 315 sends a notification to the server regarding its current location along with an indication of which HD map layers the vehicle 315 can consume. The current location may be a rough location estimate (e.g., within tens of meters) or precise location estimate, and may be based on GNSS information and/or a position estimate as described with regard to FIG. 2. The vehicle 315 may be capable of consuming HD map layers corresponding with vehicle sensors. For example, if the vehicle 315 comprises radar, cameras, and lidar, it may be capable of consuming radar, camera, and lidar HD map layers. The vehicle 315 may further indicate this capability of consuming radar, camera, and lidar HD map layers into the notification sent at arrow 320. The vehicle 315 may send the notification based on different triggering events, such as entering or coming within a threshold distance of a geographical region of an HD map, determining a navigation route that enters the geographical region, exiting or coming within a threshold distance of a boundary of a previously-downloaded HD map, communicating with a cellular base station (or other wireless network access point) within the geographical region, or the like." Kulkarni further discloses ([0045]): "The server may then respond as indicated at arrow 325, in which the relevant HD map layers and meta information is provided by the server to the vehicle 315." The Examiner has interpreted the providing of relevant HD map layers as amounting to optimizing the terrain map based on the HD map layers the vehicle is capable of utilizing.
and provide an optimized terrain map.
Kulkarni discloses ([0045]): "The server may then respond as indicated at arrow 325, in which the relevant HD map layers and meta information is provided by the server to the vehicle 315."
Regarding claim 20, Kulkarni discloses a computer-implemented method for a navigation managing system, comprising:
receiving, from an autonomous system, a request for a terrain map of a navigation route,
Kulkarni discloses ([0043]): "The method may begin with the functionality shown at arrow 320, in which the vehicle 315 sends a notification to the server regarding its current location along with an indication of which HD map layers the vehicle 315 can consume… The vehicle 315 may send the notification based on different triggering events, such as entering or coming within a threshold distance of a geographical region of an HD map, determining a navigation route that enters the geographical region, exiting or coming within a threshold distance of a boundary of a previously-downloaded HD map, communicating with a cellular base station (or other wireless network access point) within the geographical region, or the like." Kulkarni further discloses ([0045]): "The server may then respond as indicated at arrow 325, in which the relevant HD map layers and meta information is provided by the server to the vehicle 315. If the requested HD map is incomplete or unavailable, the server may send a notification to the vehicle 315 that requested map layers are unavailable."
the request comprising one or more parameters associated with the autonomous system;
Kulkarni discloses ([0043]): "The method may begin with the functionality shown at arrow 320, in which the vehicle 315 sends a notification to the server regarding its current location along with an indication of which HD map layers the vehicle 315 can consume… The vehicle 315 may send the notification based on different triggering events, such as entering or coming within a threshold distance of a geographical region of an HD map, determining a navigation route that enters the geographical region, exiting or coming within a threshold distance of a boundary of a previously-downloaded HD map, communicating with a cellular base station (or other wireless network access point) within the geographical region, or the like." Kulkarni further discloses ([0045]): "The server may then respond as indicated at arrow 325, in which the relevant HD map layers and meta information is provided by the server to the vehicle 315. If the requested HD map is incomplete or unavailable, the server may send a notification to the vehicle 315 that requested map layers are unavailable."
in response to a determination that the terrain map is available at the navigation managing system, providing the terrain map to the autonomous system; or in response to a determination that the terrain map is unavailable at the navigation managing system, providing an indication of unavailability of the terrain map to the autonomous system.
Kulkarni discloses ([0043]): "The method may begin with the functionality shown at arrow 320, in which the vehicle 315 sends a notification to the server regarding its current location along with an indication of which HD map layers the vehicle 315 can consume… The vehicle 315 may send the notification based on different triggering events, such as entering or coming within a threshold distance of a geographical region of an HD map, determining a navigation route that enters the geographical region, exiting or coming within a threshold distance of a boundary of a previously-downloaded HD map, communicating with a cellular base station (or other wireless network access point) within the geographical region, or the like." Kulkarni further discloses ([0045]): "The server may then respond as indicated at arrow 325, in which the relevant HD map layers and meta information is provided by the server to the vehicle 315. If the requested HD map is incomplete or unavailable, the server may send a notification to the vehicle 315 that requested map layers are unavailable."
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.
Claim(s) 3 and 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kulkarni in view of Arditi (US 2019/0147331 A1).
Regarding claim 3, Kulkarni teaches the aforementioned limitations of claim 2. However, Kulkarni does not outright teach that the terrain map is generated using one or more artificial intelligence or machine learning (AI/ML) models based on sensor data collected by the one or more sensors. Arditi teaches generation and updating of HD maps using data from heterogeneous sources, comprising:
the terrain map is generated using one or more artificial intelligence or machine learning (AI/ML) models based on sensor data collected by the one or more sensors.
Arditi teaches ([0029]): "Once CNN 450 and DCNN 470 have been trained, the machine-learning model may be used to generate HD map data using newly gathered sensor data and any associated metadata and environmental data. "
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kulkarni to incorporate the teachings of Arditi to provide that the terrain map is generated using one or more artificial intelligence or machine learning (AI/ML) models based on sensor data collected by the one or more sensors. Kulkarni and Arditi are each directed towards similar pursuits in the field of vehicle terrain map systems. Accordingly, one of ordinary skill in the art would find it advantageous to incorporate the machine-learning model(s) of Arditi, as doing so beneficially allows for the generation of HD map data using newly gathered sensor data and any associated metadata and environmental data, as recognized by Arditi (see at least [0029]). The machine learning models of Arditi are advantageously trained iteratively to improve feature pattern recognition, as recognized by Arditi (see at least [0020]).
Regarding claim 10, Kulkarni teaches the aforementioned limitations of claim 9. However, Kulkarni does not outright teach that generating the terrain map while navigating the route comprises: training one or more artificial intelligence or machine learning (AI/ML) models using sensor data collected by one or more sensors of the autonomous system. Arditi teaches generation and updating of HD maps using data from heterogeneous sources, comprising:
generating the terrain map while navigating the route comprises: training one or more artificial intelligence or machine learning (AI/ML) models using sensor data collected by one or more sensors of the autonomous system.
Arditi teaches ([0020]): "The machine-learning model may be trained using any suitable training techniques, including using supervised machine learning to learn from labeled training data, unsupervised machine learning to learn from unlabeled training data, and semi-supervised machine learning to learn from both labeled and unlabeled training data. In particular embodiments where supervised machine-learning is used to train the machine-learning model, the training data set may include a large number of training samples (e.g., thousands or millions) gathered from various sources (e.g., data-gathering vehicles with different sensor configurations, equipment, etc.). In particular embodiments, each training sample may be associated with an instance of data captured by a data-gathering vehicle at a particular location. For example, at the particular location (e.g., at coordinates (x, y), latitude/longitude positions, etc.), a data-gathering vehicle may have gathered data in the training sample using its camera, LiDAR, radar, sonar, and/or any other suitable sensors as described herein." Arditi further teaches ([0029]): "Once CNN 450 and DCNN 470 have been trained, the machine-learning model may be used to generate HD map data using newly gathered sensor data and any associated metadata and environmental data. "
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kulkarni to incorporate the teachings of Arditi to provide that generating the terrain map while navigating the route comprises: training one or more artificial intelligence or machine learning (AI/ML) models using sensor data collected by one or more sensors of the autonomous system. Kulkarni and Arditi are each directed towards similar pursuits in the field of vehicle terrain map systems. Accordingly, one of ordinary skill in the art would find it advantageous to incorporate the machine-learning model(s) of Arditi, as doing so beneficially allows for the generation of HD map data using newly gathered sensor data and any associated metadata and environmental data, as recognized by Arditi (see at least [0029]). The machine learning models of Arditi are advantageously trained iteratively to improve feature pattern recognition, as recognized by Arditi (see at least [0020]).
Claim(s) 5 and 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kulkarni in view of Yang et al. (US 2018/0192059 A1), hereinafter Yang.
Regarding claim 5, Kulkarni teaches the aforementioned limitations of claim 1. However, Kulkarni does not outright teach that the one or more processors are further configured to execute the instructions to: compress the generated terrain map using at least one compression algorithm; and send a compressed terrain map to the navigation managing system. Yang teaches generating high definition maps for autonomous vehicles, comprising:
the one or more processors are further configured to execute the instructions to: compress the generated terrain map using at least one compression algorithm;
Yang teaches ([0059]): "The representation compression module 220 may package the codes 285 to generate the packaged compressed codes 225. In various embodiments, the packaged compressed codes 225 further includes compressed codes for the bitmap that indicates the presence or absence of pixel values in an image channel 255... In various embodiments, the representation compression module 220 can include additional metadata of the point cloud. Examples of additional metadata include color information, a semantic label (e.g., ground, tree, and the like), and other information that is useful for map building and localization." Yang further teaches ([0060]): "The vehicle computing system 120 transmits the packaged compressed codes 225 to the online HD map system 110 such that the online HD map system 110 can decode the packaged compressed codes 225 and generate the HD map with high precision."
and send a compressed terrain map to the navigation managing system.
Yang teaches ([0060]): "The vehicle computing system 120 transmits the packaged compressed codes 225 to the online HD map system 110 such that the online HD map system 110 can decode the packaged compressed codes 225 and generate the HD map with high precision."
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kulkarni to incorporate the teachings of Yang to provide that the one or more processors are further configured to execute the instructions to: compress the generated terrain map using at least one compression algorithm; and send a compressed terrain map to the navigation managing system. Kulkarni and Yang are each directed towards similar pursuits in the field of vehicle terrain map systems. Accordingly, one of ordinary skill in the art would find it advantageous to incorporate the encoding and compression algorithm(s) of Yang, as doing so significantly improves compression ratios while minimizing the rate of error when generating HD map data, as recognized by Yang (see at least [0008]).
Regarding claim 12, Kulkarni teaches the aforementioned limitations of claim 11. However, Kulkarni does not outright teach compressing the generated terrain map using at least one compression algorithm and sending a compressed terrain map to the navigation managing system. Yang teaches generating high definition maps for autonomous vehicles, comprising:
compressing the generated terrain map using at least one compression algorithm;
Yang teaches ([0059]): "The representation compression module 220 may package the codes 285 to generate the packaged compressed codes 225. In various embodiments, the packaged compressed codes 225 further includes compressed codes for the bitmap that indicates the presence or absence of pixel values in an image channel 255... In various embodiments, the representation compression module 220 can include additional metadata of the point cloud. Examples of additional metadata include color information, a semantic label (e.g., ground, tree, and the like), and other information that is useful for map building and localization." Yang further teaches ([0060]): "The vehicle computing system 120 transmits the packaged compressed codes 225 to the online HD map system 110 such that the online HD map system 110 can decode the packaged compressed codes 225 and generate the HD map with high precision."
and sending a compressed terrain map to the navigation managing system.
Yang teaches ([0060]): "The vehicle computing system 120 transmits the packaged compressed codes 225 to the online HD map system 110 such that the online HD map system 110 can decode the packaged compressed codes 225 and generate the HD map with high precision."
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kulkarni to incorporate the teachings of Yang to provide compressing the generated terrain map using at least one compression algorithm and sending a compressed terrain map to the navigation managing system. Kulkarni and Yang are each directed towards similar pursuits in the field of vehicle terrain map systems. Accordingly, one of ordinary skill in the art would find it advantageous to incorporate the encoding and compression algorithm(s) of Yang, as doing so significantly improves compression ratios while minimizing the rate of error when generating HD map data, as recognized by Yang (see at least [0008]).
Claim(s) 6, 13, and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kulkarni in view of Yang, and in further view of Mason et al. (US 2021/0192839 A1), hereinafter Mason.
Regarding claim 6, Kulkarni and Yang teach the aforementioned limitations of claim 5. However, neither Kulkarni nor Yang outright teach that the at least one compression algorithm comprises an autoencoder. Mason teaches an environment autoencoder, comprising:
the at least one compression algorithm comprises an autoencoder.
Mason teaches ([0048]): "The flow diagram begins when an environmental autoencoder 404 is trained to compress and recreate images of an environment. As such, environmental autoencoder 404 takes in input environment map 402 and recreates output environment map 406. One of the byproducts of the trained autoencoder is that the compressed version of the environment map 402 includes lighting latents 408 which include a set of values which represent the lighting of the input environment map 402. For example, the lighting latents 408 may represent brightness, color, and/or other characteristics related to lighting in a scene."
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kulkarni and Yang to incorporate the teachings of Mason to provide that the at least one compression algorithm comprises an autoencoder. Kulkarni, Yang, and Mason are each directed towards similar pursuits in the field of terrain mapping systems. Accordingly, one of ordinary skill in the art would find it advantageous to incorporate the environmental autoencoder of Mason, as the autoencoder is described as being able to compress and recreate images of an environment, and is further capable of including values representing the lighting of the environment map, as recognized by Mason (see at least [0048]).
Regarding claim 13, Kulkarni and Yang teach the aforementioned limitations of claim 12. However, neither Kulkarni nor Yang outright teach that the at least one compression algorithm comprises an autoencoder. Mason teaches an environment autoencoder, comprising:
the at least one compression algorithm comprises an autoencoder.
Mason teaches ([0048]): "The flow diagram begins when an environmental autoencoder 404 is trained to compress and recreate images of an environment. As such, environmental autoencoder 404 takes in input environment map 402 and recreates output environment map 406. One of the byproducts of the trained autoencoder is that the compressed version of the environment map 402 includes lighting latents 408 which include a set of values which represent the lighting of the input environment map 402. For example, the lighting latents 408 may represent brightness, color, and/or other characteristics related to lighting in a scene."
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kulkarni and Yang to incorporate the teachings of Mason to provide that the at least one compression algorithm comprises an autoencoder. Kulkarni, Yang, and Mason are each directed towards similar pursuits in the field of terrain mapping systems. Accordingly, one of ordinary skill in the art would find it advantageous to incorporate the environmental autoencoder of Mason, as the autoencoder is described as being able to compress and recreate images of an environment, and is further capable of including values representing the lighting of the environment map, as recognized by Mason (see at least [0048]).
Regarding claim 18, Kulkarni teaches the aforementioned limitations of claim 17. However, Kulkarni does not outright teach that the terrain map received from the autonomous system is a compressed terrain map, and the one or more processors are further configured to execute the instructions to: reconstruct the terrain map based on the compressed terrain map using at least one algorithm. Yang teaches generating high definition maps for autonomous vehicles, comprising:
the terrain map received from the autonomous system is a compressed terrain map,
Yang teaches ([0059]): "The representation compression module 220 may package the codes 285 to generate the packaged compressed codes 225. In various embodiments, the packaged compressed codes 225 further includes compressed codes for the bitmap that indicates the presence or absence of pixel values in an image channel 255... In various embodiments, the representation compression module 220 can include additional metadata of the point cloud. Examples of additional metadata include color information, a semantic label (e.g., ground, tree, and the like), and other information that is useful for map building and localization." Yang further teaches ([0060]): "The vehicle computing system 120 transmits the packaged compressed codes 225 to the online HD map system 110 such that the online HD map system 110 can decode the packaged compressed codes 225 and generate the HD map with high precision."
and the one or more processors are further configured to execute the instructions to: reconstruct the terrain map based on the compressed terrain map using at least one algorithm,
Yang teaches ([0060]): "The vehicle computing system 120 transmits the packaged compressed codes 225 to the online HD map system 110 such that the online HD map system 110 can decode the packaged compressed codes 225 and generate the HD map with high precision."
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kulkarni to incorporate the teachings of Yang to provide that the terrain map received from the autonomous system is a compressed terrain map, and the one or more processors are further configured to execute the instructions to: reconstruct the terrain map based on the compressed terrain map using at least one algorithm. Kulkarni and Yang are each directed towards similar pursuits in the field of vehicle terrain map systems. Accordingly, one of ordinary skill in the art would find it advantageous to incorporate the encoding and compression algorithm(s) of Yang, as doing so significantly improves compression ratios while minimizing the rate of error when generating HD map data, as recognized by Yang (see at least [0008]).
However, neither Kulkarni nor Yang outright teach that the at least one algorithm comprises an autoencoder. Mason teaches an environment autoencoder, comprising:
the at least one algorithm comprising an autoencoder.
Mason teaches ([0048]): "The flow diagram begins when an environmental autoencoder 404 is trained to compress and recreate images of an environment. As such, environmental autoencoder 404 takes in input environment map 402 and recreates output environment map 406. One of the byproducts of the trained autoencoder is that the compressed version of the environment map 402 includes lighting latents 408 which include a set of values which represent the lighting of the input environment map 402. For example, the lighting latents 408 may represent brightness, color, and/or other characteristics related to lighting in a scene."
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kulkarni and Yang to incorporate the teachings of Mason to provide at least one algorithm comprising an autoencoder. Kulkarni, Yang, and Mason are each directed towards similar pursuits in the field of terrain mapping systems. Accordingly, one of ordinary skill in the art would find it advantageous to incorporate the environmental autoencoder of Mason, as the autoencoder is described as being able to compress and recreate images of an environment, and is further capable of including values representing the lighting of the environment map, as recognized by Mason (see at least [0048]).
Claim(s) 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kulkarni in view of Stephens et al. (US 2017/0322040 A1), hereinafter Stephens.
Regarding claim 15, Kulkarni teaches the aforementioned limitations of claim 9. Kulkarni further teaches:
[an inquiry comprising] at least one of: a type of the autonomous system, at least one parameter related to weather condition, at least one size of the autonomous system, at least one functional feature of the autonomous system, or a type of work needs to be done by the autonomous system during navigation;
Kulkarni teaches ([0043]): "The method may begin with the functionality shown at arrow 320, in which the vehicle 315 sends a notification to the server regarding its current location along with an indication of which HD map layers the vehicle 315 can consume…" The Examiner has interpreted the indication of which HD map layers the vehicle 315 can consume as a functional feature of the autonomous system.
and receiving a response from the navigation managing system.
Kulkarni teaches ([0045]): "The server may then respond as indicated at arrow 325, in which the relevant HD map layers and meta information is provided by the server to the vehicle 315. If the requested HD map is incomplete or unavailable, the server may send a notification to the vehicle 315 that requested map layers are unavailable."
However, Kulkarni does not outright teach that the determining whether the terrain map is available further comprises: inputting an inquiry on a user interface provided by the navigation managing system, the inquiry comprising an indication of the route. Stephens teaches route generation, comprising:
the determining whether the terrain map is available further comprises: inputting an inquiry on a user interface provided by the navigation managing system, the inquiry comprising an indication of the route,
Stephens teaches ([0027]): "Using a user interface 302, a user may provide a request for navigating to a destination. The user request may be provided to a routing algorithm 304. The routing algorithm 304 generates a database query to obtain data about one or more routes between a current location and the destination. The database query is sent to a map database 306. The map database 306 provides requested data to the routing algorithm 304, which generates and sends an optimized route to the user interface 302. For example, the optimized route may include an optimized route that minimizes a cost that includes one or more of a distance cost, a time cost, a cost for reliability of a driver assistance feature or automated driving feature, or the like. For example, the optimized route may provide a short travel time while also routing the vehicle/user along roadways were a driver assistance feature or automated driving feature will be reliable."
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kulkarni to incorporate the teachings of Stephens to provide that the determining whether the terrain map is available further comprises: inputting an inquiry on a user interface provided by the navigation managing system, the inquiry comprising an indication of the route. Kulkarni and Stephens are each directed towards similar pursuits in the field of vehicle terrain map systems. Accordingly, one of ordinary skill in the art would find it advantageous to incorporate the user interface of Stephens, as doing so beneficially allows for presentation of an optimized route based on the user request provided through the user interface, as recognized by Stephens (see at least [0027]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Jafari Tafti et al. (US 2019/0049990 A1) teaches a system and method for providing a map to autonomous vehicles via a cloud-based system, including requesting, by a controller of an autonomous vehicle, map data from a cloud-based server (see at least [0003]), and enabling autonomous navigation features once the map data is received (e.g., planning maneuvers and driving behaviors; see at least [0058] and FIG. 5). Scott et al. (US 2007/0229539 A1) teaches a method of graphically indicating on a wireless communications device that map data is unavailable or still being downloaded (see at least [0004] and Claim 11).
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/F.T.G./ Examiner, Art Unit 3662
/DALE W HILGENDORF/ Primary Examiner, Art Unit 3662