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 .
Status of Claims
This action is in reply to the application field on 27 September 2023
Claims 1-16 are currently pending and have been examined.
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statements (IDSs) submitted on 26 February 2024, 22 December 2023, and 15 December 2023 have been considered by the examiner and initialed copies of the IDS is hereby attached.
Specification
The disclosure is objected to because of the following informalities:
In paragraph [0056] “tailoreed” should be replaced with “tailored”.
In paragraph [0066] “return shop path 208” should be replaced with “return shop path 248”. The examiner notes that 208 has been used to describe the staging area.
Appropriate correction is required.
Claim Objections
Claim 13 objected to because of the following informalities:
“application gateway recieves” in line 9 should be replaced with “application gateway receives”. Appropriate correction is required.
“the machine acutator” in line 15 should be replaced with “the machine actuator”. Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-16 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites “ the server memory drive” in line 8. There is insufficient antecedent basis for this limitation in the claim.
Claim 1 recites “meets requirements”. It is not clear what the scope of “meets requirements” entails. First the examiner notes that the requirements have not been described nor how to determine that the requirements have been met. Does “meet requirements” require that the digital asset is capable of performing the project operation, does it require that the digital asset is capable of completing the project operation at a certain efficiency, or does it have to meet the machine criteria requirements? Further, it is not clear how it is determined that the reusable digital asset meets the requirements. The examiner recommends reciting a determination of the requirements and a further checking step of determining if the requirements are met as supported by the specification.
Claim 3 recites “the working machine’s implementation…” There is insufficient antecedent basis for this limitation in the claim. Claim 4 has a similar recitation and is rejected for the same reason.
Claim 12 recites “the machine learning model” in line 2. There is insufficient antecedent basis for this limitation in the claim.
Claim 13 recites “a working machine for automated work comprising: an application gateway having a first communication card configured to communicate over a communication network with a networked server, which includes a server communication card and a server memory comprising reusable digital asset storage”. The examiner notes that the claim is directed to the working machine. The server, the server communication card and the server memory including reusable digital asset storage are not part of the working machine. Reciting features of a server in the claim covering the working machine makes it unclear if the server and thus the system of the working machine and server are intended to be claimed. For purposes of examination, the examiner will interpret the application gateway to be configured to communicate of a network with a server to meet the claim. Further, claim 13 recites “the application gateway receives a mission plan from the server over the communication network, wherein the mission plan is generated by the server to instruct the working machine to perform a project, and the mission plan includes machine instructions selected from a reusable digital asset from the reusable digital asset storage in the server”. Again the examiner notes that the claim is directed to the working machine and thus, the claim only requires that the application gateway receives a mission plan from the server over the communication network.
Claims 2-12 depend from claim 1 and are similarly rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, based on their dependency on claim 1.
Claims 14-16 depend from claim 13 and are similarly rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, based on their dependency on claim 13.
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 1-12 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
Following the 2019 Revised Patent Subject Matter Eligibility Guidance (84 Fed. Reg. 50-57 and MPEP § 2106, hereinafter 2019 Guidance), the claim(s) appear to recite at least one abstract idea, as explained in the Step 2A, Prong I analysis below. Furthermore, the judicial exception(s) does/do not appear to be integrated into a practical application as explained in the Step 2A, Prong II analysis below. Further still, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception(s) as explained in the Step 2B analysis below.
STEP 1:
Step 1, of the 2019 Guidance, first looks to whether the claimed invention is directed to a statutory category, namely a process, machine, manufactures, and compositions of matter.
Claim 1 is directed toward management system and is therefore eligible for further analysis.
STEP 2A, PRONG I:
Step 2A, prong I, of the 2019 Guidance, first looks to whether the claimed invention recites any judicial exceptions, including certain groupings of abstract ideas (i.e., mathematical concepts, certain methods of organizing human activities such as a fundamental economic practice, or mental processes).
Independent claim 6 includes limitations that recite an abstract idea (emphasized below) and will be used as a representative claim(s) for the remainder of the 101 rejection.
Claim 1 recites:
A management system for automated work, comprising: a networked server system, comprising:
a server communication card configured to communicate over a communication network,
a server memory, which comprises reusable digital asset storage, and
a server controller operatively connected to the server communication card and the server memory, the server controller is configured to manage the server memory drive and communication over the server communication card;
a working machine, comprising:
an application gateway having a first communication card configured to communicate over the communication network with the server communication card,
a machine control unit comprising a machine processor and a machine memory, which stores machine operating instructions, and
a machine actuator system having a machine control actuator; and
wherein the server controller receives a project request via the server communication card and analyzes the project request to determine a project operation, and wherein the server controller selects a reusable digital asset from the reusable digital asset storage that meets requirements for the project operation;
wherein a mission planning system of the networked server generates a mission plan for the working machine, wherein the mission plan includes machine instructions from the selected reusable digital asset and additional operational instructions.
The examiner submits that the foregoing bolded limitation(s) constitute a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. Specifically, the “analyzes the project request to determine a project operation” and “selects a reusable digital asset from the reusable digital asset storage that meets requirements for the project operation” “generates a mission plan for the working machine” steps encompass a human reviewing a project request such as mowing a field and determining a map that could be used to perform the mowing operation and planning the sequence of moving steps.
STEP 2A, PRONG II:
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application”.
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”):
Claim 1 recites:
A management system for automated work, comprising: a networked server system, comprising:
a server communication card configured to communicate over a communication network,
a server memory, which comprises reusable digital asset storage, and
a server controller operatively connected to the server communication card and the server memory, the server controller is configured to manage the server memory drive and communication over the server communication card;
a working machine, comprising:
an application gateway having a first communication card configured to communicate over the communication network with the server communication card,
a machine control unit comprising a machine processor and a machine memory, which stores machine operating instructions, and
a machine actuator system having a machine control actuator; and
wherein the server controller receives a project request via the server communication card and analyzes the project request to determine a project operation, and wherein the server controller selects a reusable digital asset from the reusable digital asset storage that meets requirements for the project operation;
wherein a mission planning system of the networked server generates a mission plan for the working machine, wherein the mission plan includes machine instructions from the selected reusable digital asset and additional operational instructions.
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application:
Regarding the additional limitations “a server communication card configured to communicate over a communication network”, “a server memory, which comprises reusable digital asset storage”, “a server controller operatively connected to the server communication card and the server memory”, “the server controller is configured to manage the server memory drive and communication over the server communication card;”, “a working machine, comprising: an application gateway having a first communication card configured to communicate over the communication network with the server communication card,”, “a machine control unit comprising a machine processor and a machine memory, which stores machine operating instructions,” and “a machine actuator system having a machine control actuator;” “wherein the server controller receives a project request via the server communication card” ,”a mission planning system of the networked server” “wherein the mission plan includes machine instructions from the selected reusable digital asset and additional operational instructions.” the examiner submits that these limitations merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use and do not integrate a judicial exception into a “practical application”.
Specifically, the courts have held that merely reciting the works “apply it” (or an equivalent) with the judicial exception, or merely including or are more than mere instructions to implement an abstract idea on a computer, or merely using the computer as a tool to perform an abstract idea, does not integrate a judicial exception into a practical application. See MPEP 2106.05(f). The additional limitations of “a server communication card configured to communicate over a communication network”, “a server memory, which comprises reusable digital asset storage”, “a server controller operatively connected to the server communication card and the server memory”, “the server controller is configured to manage the server memory drive and communication over the server communication card;”, “ an application gateway having a first communication card configured to communicate over the communication network with the server communication card,”, “a machine control unit comprising a machine processor and a machine memory, which stores machine operating instructions,” and “wherein a mission planning system of the networked server” are recited at a high level of generality and simply describes using the computer as a tool to perform the abstract idea of “detecting” “determining”, and “generating” are recited at a high level of generality that merely automates the analysis and selecting steps, therefore acting as a generic computer or generic components such as processors, memory, memory, communication cards, application gateways, that are simply employed as a tool to perform the abstract idea (see at least [0138]). Thus, the additional limitations are no more than mere instructions to apply the exception using a general purpose computer (see [0138] of the instant application).
Further, the courts have the courts have also identified limitations that generally linking the use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a practical application. The examiner notes that the limitations of “a working machine” and “a machine actuator system having a machine control actuator;” generally link the judicial exception to a particular technological environment or field of use, and thus, does not integrate the judicial exception in a practical application.“ (see MPEP § 2106.05(h)). Further, the examiner notes that there is no indication of applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception (see MPEP § 2106.05(e)).
Further, the limitations of “wherein the server controller receives a project request via the server communication card” “wherein the mission plan includes machine instructions from the selected reusable digital asset and additional operational instructions.” is recited at a high level of generality (i.e. as a general means of data gathering or data output) and amounts to mere data gathering, which is a form of insignificant extra-solution activity. See at least MPEP 2106.05(g). Thus, these additional elements merely reflect insignificant extra-solution activity.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
STEP 2B:
Regarding Step 2B of the Revised Guidance, the representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application.
As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of ““a server communication card configured to communicate over a communication network”, “a server memory, which comprises reusable digital asset storage”, “a server controller operatively connected to the server communication card and the server memory”, “the server controller is configured to manage the server memory drive and communication over the server communication card;”, “ an application gateway having a first communication card configured to communicate over the communication network with the server communication card,”, “a machine control unit comprising a machine processor and a machine memory, which stores machine operating instructions,” and “wherein a mission planning system of the networked server” amounts to nothing more than mere instructions to apply the exception using a generic computer or generic components (see [0138] of the instant application). Mere instructions to apply an exception using a generic computer or generic components that are simply employed as a tool cannot provide an inventive concept. Further, the limitations of “a working machine” and “a machine actuator system having a machine control actuator;” generally link the judicial exception to a particular technological environment or field of use, and thus, does not integrate the judicial exception in a practical application.“ (see MPEP § 2106.05(h)). Finally, as discussed above, the additional limitations of “wherein the server controller receives a project request via the server communication card” “wherein the mission plan includes machine instructions from the selected reusable digital asset and additional operational instructions.” the examiner submits are insignificant extra-solution activity. Hence, the claim is not patent eligible.
Dependent claim(s) 2-12 do not recite any further limitations that cause the claim(s) to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception, and/or well-understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application. Specifically, the claims only recite limitations further defining the mental process, “apply it”, generally link the judicial exception to a particular technological environment or field of use, and insignificant extra-solution activity. These additional elements fail to integrate the abstract idea into a practical application because they do not impose meaningful limits on the claimed invention. As such, the additional elements individually and in combination do not amount to significantly more than the abstract idea. Therefore, when considering the combination of elements and the claimed invention as a whole, claims 2-12 are not patent eligible.
The examiner notes that claim 1 simply generates a mission plan, but does not execute or cause the plan to execute. Claim 13 is patent eligible as it requires that the machine control unite to execute the machine instructions form the mission plan.
Accordingly, claims 1-12 are not patent eligible.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Drew (US Pub. No. US-20140371979-A1, hereinafter “Drew”), in view of Jespersen et al. (US Pub. No. US-20060104497-A1, hereinafter “Jespersen") and Sheehan et al. (US Pub. No. US-20060067209-A1) .
Regarding claim 1, Drew discloses a management system for automated work, comprising:
a networked server system comprising (see at least Drew Figure 5 and [0055] “In this regard, FIG. 5 illustrates a system in which an embodiment of the present invention may be employed by processing of data at a central facility (e.g., application server 540). Thus, for example, although the apparatus of FIG. 2 may be embodied at a yard maintenance vehicle itself, in other embodiments such an apparatus may alternatively or additionally be located at a central facility or server.” See also [0032-0033] and Fig. 2 which discloses that the positioning module may be disposed in the riding yard maintenance vehicle and/or a remote computer, including at the central facility [0055]):
a server communication [[card]] configured to communicate over a communication network (see at least Drew Figure 5 and [0041-0042] “For example, in some cases, Bluetooth, WiFi or other wireless communication modules may be provided by the device interface 220 in order to allow wireless downloading of software, support information or other data, or allow wireless uploading of data to network devices for support, management or other purposes. In some embodiments, Bluetooth, WiFi or other short range wireless communication modules may be used to communicate data to an intermediate device (e.g., a cell phone), which may then communicate the data to a computer or other device at which certain analysis and/or display may be performed. In still other cases, a removable memory device may be used to transfer information from the memory 214 to the removable memory device and thereafter to the remote computer” See also [0057-0059] “In an example embodiment, one of the devices to which the clients 520 may be coupled via the network 530 may include one or more application servers (e.g., application server 540), and/or a database server 542, which together may form respective elements of a server network 532.” See also [0032-0033].[0033] The processing circuitry 210 may be configured to perform data processing, control function execution and/or other processing and management services according to an example embodiment of the present invention. In some embodiments, the processing circuitry 210 may be embodied as a chip or chip set. In other words, the processing circuitry 210 may comprise one or more physical packages (e.g., chips) including materials, components and/or wires on a structural assembly (e.g., a baseboard). The structural assembly may provide physical strength, conservation of size, and/or limitation of electrical interaction for component circuitry included thereon. The processing circuitry 210 may therefore, in some cases, be configured to implement an embodiment of the present invention on a single chip or as a single "system on a chip." As such, in some cases, a chip or chipset may constitute means for performing one or more operations for providing the functionalities described herein.”)
a server controller operatively connected to the server communication [[card]] and the server memory, the server controller is configured to manage the server memory drive and communication over the server communication [[card]] (see at least Drew Figure 5 and Figure 2 wherein the processing circuitry 210 including a processor and memory corresponds to the server controller and wherein of the positioning model 150 is part of the server as described in [0032]);
a working machine (See at least Drew Figures 1A and 1B and 0022] FIG. 1, which includes FIGS. 1A and 1B, illustrates an example of a riding yard maintenance vehicle 10 having a bagging attachment 12.), comprising:
[[an application gateway having a first communication card]] configured to communicate over the communication network with the server communication [[card]] (see at least Drew Figure 5, client 520 including client application 522, connected to network 530 which is connected to the server 532, 540 see also Figure 2. See also Drew [0055] “ As shown in FIG. 5, a system 500 according to an example embodiment may include one or more clients 520 that may, in some cases, be associated with different corresponding riding yard maintenance vehicles or other remote nodes… As such, each one of the clients 520 may be, for example, a computer (e.g., a personal computer, laptop computer, network access terminal, or the like) or may be another form of computing device (e.g., a personal digital assistant (PDA), cellular phone, smart phone, or the like) capable of communication with a network 530 via any short range (e.g., WiFi, Bluetooth, etc.) or long range communication protocols (e.g., 3G, 4G, LTE, etc.). As such, the clients 520 may be fixed at or integrated into riding yard maintenance vehicles, may be removable or transferable accessories or components associated with riding yard maintenance vehicles, or may be separate devices (e.g., a smart phone) capable of running applications useable in connection with operation of riding yard maintenance vehicles.”),
a machine control unit comprising a machine processor and a machine memory, which stores machine operating instructions (see at least Drew Figure 2, and processing circuitry 210 and [0034] “In an example embodiment, the processing circuitry 210 may include one or more instances of a processor 212 and memory 214 that may be in communication with or otherwise control a device interface 220 and, in some cases, a user interface 230.” and [0036] “ The device interface 220 may include one or more interface mechanisms for enabling communication with other devices (e.g., sensors of a sensor network and/or other accessories or functional units 270 such as motors, servos, switches or other operational control devices for automatic responses” See also [0040] “As such, in some embodiments, the processor 212 (or the processing circuitry 210) may be said to cause each of the operations described in connection with the positioning module 150 by directing the positioning module 150 to undertake the corresponding functionalities responsive to execution of instructions or algorithms configuring the processor 212 (or processing circuitry 210) accordingly. As an example, the positioning module 150 may be configured to record position and/or orientation information, or other operational parameters regarding the tasks performed by riding yard maintenance vehicle 10 as described herein. The positioning module 150 may then, in some cases, process the information to generate alerts, warnings, route optimization, route guidance, maintenance recommendations, position histories, work histories, and/or the like.”), and
a machine actuator system having a machine control actuator (see at least Drew [0023] FIG. 1A illustrates a side view of the riding yard maintenance vehicle 10 and FIG. 1B illustrates a perspective view of the riding yard maintenance vehicle 10. The riding yard maintenance vehicle may include a steering assembly 20 (e.g., including a steering wheel, handle bars, or other steering apparatus) functionally connected to wheels of the riding yard maintenance vehicle 10 to which steering inputs are provided (e.g., the front and/or rear wheels in various different embodiments) to allow the operator to steer the riding yard maintenance vehicle 10. In some embodiments, the riding yard maintenance vehicle 10 may include seat 30 that may be disposed at a center, rear or front portion of the riding yard maintenance vehicle 10. The operator may sit on the seat 30, which may be disposed to the rear of the steering assembly 20 to provide input for steering of the riding yard maintenance vehicle 10 via the steering assembly 20.” [0036] “ The device interface 220 may include one or more interface mechanisms for enabling communication with other devices (e.g., sensors of a sensor network and/or other accessories or functional units 270 such as motors, servos, switches or other operational control devices for automatic responses”); and
wherein the server controller receives a project request via the server communication [[card]] and analyzes the project request to determine a project operation, and wherein the server controller selects a reusable digital asset from the reusable digital asset storage that meets requirements for the project operation (The examiner notes that the instant application at [0039] indicates that reusable digital assets include maps, routes, settings, etc. and thus, the examiner uses the map and/or route information of Drew to teach the reusable digital assets. However, the examiner notes that any data that is stored can be considered a reusable digital asset. See at least Drew [0052] “…After working of the parcel is complete, the route information may be saved in connection with the corresponding parcel or customer as one instance of a route run on the corresponding parcel. Thereafter, the operator may be enabled to enter the identifier and retrieve route information for the corresponding parcel or customer. Alerts, warnings, route optimization and other services, such as those described herein by way of example, may further be provided relative to self mapped route information.” See also [0056] In some cases, each one of the clients 520 may include (or otherwise have access to) memory for storing instructions or applications for the performance of various functions and a corresponding processor for executing stored instructions or applications. Each one of the clients 520 may also include software and/or corresponding hardware for enabling the performance of the respective functions of the clients as described herein in relation to recording (or providing information for remote recording) of information indicative of vehicle position and/or orientation. In an example embodiment, one or more of the clients 520 may include a client application 522 configured to operate in accordance with an example embodiment of the present invention. In this regard, for example, the client application 522 may include software for enabling a respective one of the clients 520 to communicate with the network 530 for requesting and/or receiving information indicative of vehicle position and/or orientation in the context of a route or parcel in the form of a deliverable component (e.g., as downloadable software to configure the client, or as a transferable memory device including instructions to configure the client). As such, for example, the client application 522 may include corresponding executable instructions for configuring the client 520 to provide corresponding functionalities as described in greater detail herein.” See also [0047-0049] “In some embodiments, the positioning module 150 may be configured to generate an optimal route for display to guide the operator or to inform the operator of a proposed path for working a parcel of land. The optimal route may be generated using algorithms designed to consider desirable criteria relative to performance over past routes, or relative to expected performance for a route for which detailed geographic information regarding a parcel is known a priori. As an example, the optimal route may be generated based on analyzing past routes for the time taken to complete each route and determining, based on the past routes, an optimal route for fastest completion of working a particular parcel. Alternatively, fuel economy, cut quality, blade torque minimization, risk of damage to operator or machine, tilt exposure minimization, or any number of other criteria may be used as criteria for generation of optimal routes. In some cases, the criteria used may be considered relative to a number or previous routes, or relative to models created based on vehicle performance testing, in order to generate recommendations regarding routes and/or specific driving strategies to be employed while running routes in order to optimally run the route relative to the selected criteria….[0049] FIG. 4 illustrates an example of an optimal route 330 that may be proposed relative to any criteria based on a previously run route (e.g., the route 300 of FIG. 3 or modeled performance). In FIG. 4 also, the parcel may be graphically displayed based on locally or remotely generated data, or based on third party data received in connection with the parcel. Moreover, in some cases, locally or remotely generated data may be merged with third party data to generate a view of the parcel with route information displayed thereon.” See also [0061] “ As such, the environment of FIG. 5 illustrates an example in which provision of recorded obstacle locations to an onsite device (e.g., the riding yard maintenance vehicle 10 or a mobile phone or device of the operator of the riding yard maintenance vehicle 10) may be accomplished by a remote entity (e.g., the application server 540). As such, the onsite device may be enabled to generate or utilize map or other geographic data even if the onsite device did not necessarily record some of the data itself. Moreover, in some embodiments, provision of location information may be provided from the onsite device to the remote entity for recording and later provision of such data, or of functions driven off of such data, either to the onsite device or another device that ends up at the same site in the future. “)
wherein a mission planning system of the networked server generates a mission plan for the working machine, wherein the mission plan includes machine instructions from the selected reusable digital asset and additional operational instructions (see at least Drew, Figure 5, module of application server See at least [0047-0049] “In some embodiments, the positioning module 150 may be configured to generate an optimal route for display to guide the operator or to inform the operator of a proposed path for working a parcel of land. The optimal route may be generated using algorithms designed to consider desirable criteria relative to performance over past routes, or relative to expected performance for a route for which detailed geographic information regarding a parcel is known a priori. As an example, the optimal route may be generated based on analyzing past routes for the time taken to complete each route and determining, based on the past routes, an optimal route for fastest completion of working a particular parcel. Alternatively, fuel economy, cut quality, blade torque minimization, risk of damage to operator or machine, tilt exposure minimization, or any number of other criteria may be used as criteria for generation of optimal routes. In some cases, the criteria used may be considered relative to a number or previous routes, or relative to models created based on vehicle performance testing, in order to generate recommendations regarding routes and/or specific driving strategies to be employed while running routes in order to optimally run the route relative to the selected criteria….[0049] FIG. 4 illustrates an example of an optimal route 330 that may be proposed relative to any criteria based on a previously run route (e.g., the route 300 of FIG. 3 or modeled performance). In FIG. 4 also, the parcel may be graphically displayed based on locally or remotely generated data, or based on third party data received in connection with the parcel. Moreover, in some cases, locally or remotely generated data may be merged with third party data to generate a view of the parcel with route information displayed thereon.” [0061] “ As such, the environment of FIG. 5 illustrates an example in which provision of recorded obstacle locations to an onsite device (e.g., the riding yard maintenance vehicle 10 or a mobile phone or device of the operator of the riding yard maintenance vehicle 10) may be accomplished by a remote entity (e.g., the application server 540). As such, the onsite device may be enabled to generate or utilize map or other geographic data even if the onsite device did not necessarily record some of the data itself. Moreover, in some embodiments, provision of location information may be provided from the onsite device to the remote entity for recording and later provision of such data, or of functions driven off of such data, either to the onsite device or another device that ends up at the same site in the future. “ See also [0064] In an example embodiment, a method for processing position information of a riding yard maintenance vehicle, as shown in FIG. 6, may include receiving information indicative of vehicle position and/or orientation at operation 600 and generating route information based on the position information to define a current route at operation 610. The method may further include comparing the current route to a previous route or a derivative route at operation 620 and providing feedback to the operator based on information associated with the current route at operation 630. The feedback may be guidance related, may be a visual representation of the current route and/or the derivative route, may include alerts or warnings, may include a map view, may include waypoints and data associated with the waypoints, or any of a number of other visual or audible feedback queues. In some cases, the method may include (in addition to or as an alternative to operation 620) generating a derivative route based on one or more routes associated with a same location as the current route at operation 640.” See also [0060] for additional instructions).
The examiner notes that while Drew teaches a server capable of communicating over a communication network and a working machine capable of communicating over the communication network with the server, Drew does not explicitly teach a server communication card, an application gateway, and a first communication card.
Jespersen teaches a server communication card (see at least [0076] “The server 220 includes a wireless communication card 234 for communicating with wireless portable devices 240. These devices 240 are similar to portable digital assistants (PDAs).”.).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Drew with the teaching of Jespersen to include a server communication card, with a reasonable expectation of success, because as Jespersen teaches a communication card allows for communication with wireless portable devices. (see at least Jespersen[0076]). Further Jespersen is analogous art, as servers are used in a variety of technologies, and further Jespersen indicates that the teachings are applicable to vehicles.
The combination of Drew and Jespersen does not an application gateway, and a first communication card
Sheehan teaches application gateway, and a first communication card (see at least Sheehan [0028-0029] “The application gateway architecture provides support for multi-vendor facilities architectures and is able to control supported apparatus by hosting, storing and communicating operating rules and protocols necessary to communicate with and manage any particular piece of facilities equipment. …[0029] The application gateway may expose data from one or more devices 112A-C to a variety of enterprise applications 108, simultaneously, in standard formats recognizable to those applications. The application gateway, deployed on discreet serial processors 114 (e.g., about the size of a deck of cards) or embedded communication cards 116, can connect the intelligent device(s) 112A-C to the enterprise application 108, or other upstream applications. The application gateway may expose data from one or more devices 112A-C to a variety of enterprise applications 108, simultaneously, in standard formats recognizable to those applications. The application gateway, deployed on discreet serial processors 114 (or embedded communication cards 116, can connect the intelligent device(s) 112A-C to the enterprise application 108, or other upstream applications.”.)
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Drew and Jespersen to include an application gateway having a first communication card as taught by Sheehan, with a reasonable expectation of success, because as Sheehan teaches the application gateway with a communication card allows for connection, communication and management of equipment and devices (see at least Sheehan [0029-0029]).
Regarding claim 2, the combination of Drew, Jespersen and Sheehan teaches the management system according to claim 1, wherein the additional operational instructions are selected from a second reusable digital asset from the reusable digital asset storage (see at least Drew [0049] “In FIG. 4 also, the parcel may be graphically displayed based on remotely generated data, or based on third party data received in connection with the parcel. Moreover, in some cases, locally or remotely generated data may be merged with third party data to generate a view of the parcel with route information displayed thereon.”).
Regarding claim 3, the combination of Drew, Jespersen and Sheehan teaches the management system according to claim 1, wherein the mission plan includes operational rules to guide the working machine's implementation of the mission plan (See at least Drew Figure 3 and [0051-0053] “As an example, if a hill or ditch has a steep slope that would present a rollover risk if approached the wrong way (e.g., sideways instead of straight on), such areas may be identified as tilt exposure risk areas on a map view or other display showing route information. In some embodiments, the tilt exposure risk may also be used to trigger process interventions. For example, if tilt as indicated by the accelerometer 250 reaches a predefined level, the positioning module 150 may be configured to stop providing driving power to a blade motor that drives the cutting blade or blades within the cutting deck 40 or to a drive motor that provides power to the wheels. In some embodiments, warnings may be issued instead of or prior to initiation of any process interventions. Tilt may also or alternatively present risks relative to machine integrity or maintenance. For example, riding at the same angle for a long period of time may concentrate oil to one side of the crankcase and impact engine wear. Thus, the positioning module 150 may configured to track the amount of time that the riding yard maintenance vehicle 10 spends at a particular angle (or angles above a threshold) and issue a warning when the amount of time exceeds a predetermined amount. In some cases, speed restricted areas (e.g., based on slope or obstacle frequency) may also be identified to the operator as area with increased risk exposure. Areas that present risks above a certain threshold may be identified with overlaid graphics, color shading or any other suitable distinguishing characteristics on a map view or as a highlighted portion of a route. FIG. 3 illustrates an example of a risk-related regional alert 340 that is indicative of a risk being associated with the highlighted region…After working of the parcel is complete, the route information may be saved in connection with the corresponding parcel or customer as one instance of a route run on the corresponding parcel. Thereafter, the operator may be enabled to enter the identifier and retrieve route information for the corresponding parcel or customer. Alerts, warnings, route optimization and other services, such as those described herein by way of example, may further be provided relative to self mapped route information….[0053] The recordation of position and/or orientation data for the riding yard maintenance vehicle 10 may provide a number of uses to operators. As indicated above, route optimization services, route guidance services, and the provision of alerts and warnings may all be provided based on the storage of route information including position and/or orientation data. However, the knowledge of past routes may also provide a number of other uses. For example, variation of the orientation of lawn striping may be easily accomplished (e.g., in a guided or unguided format) by informing the operator of the orientation of previous striping. Accordingly, the operator does not need to try to remember the way a parcel was worked on a previous occasion.” See also [0047] “Alternatively or additionally, alerts, alarms or warnings may be provided as audible or visual indicators that the operator is straying from a previous route or derivative route by more than a threshold amount. The alerts may be indicated on the display or via separate lights (e.g., flashing or solid, red or yellow lights).” The examiner interprets the tilt level, the tilt for a predetermined time, speed restrictions, and threshold distance of the route to be operational rules to guide the working machine's implementation of the mission plan.)
Regarding claim 4, the combination of Drew, Jespersen and Sheehan teaches the management system according to claim 3, wherein the operational rules are selected from another reusable digital asset from the reusable digital asset storage (See at least Drew Figure 3 and [0051-0053] and [0047] as cited above with respect to claim 3. The examiner interprets the tilt level, the tilt for a predetermined time, speed restrictions, and threshold distance of the route to be operational rules that are stored as another reusable digital asset).
Regarding claim 5, Drew, Jespersen and Sheehan teaches the management system according to claim 1, wherein the mission plan includes trigger-based operational rules to modify the working machine's implementation of the mission plan (See at least Drew Figure 3 and [0051-0053] “As an example, if a hill or ditch has a steep slope that would present a rollover risk if approached the wrong way (e.g., sideways instead of straight on), such areas may be identified as tilt exposure risk areas on a map view or other display showing route information. In some embodiments, the tilt exposure risk may also be used to trigger process interventions. For example, if tilt as indicated by the accelerometer 250 reaches a predefined level, the positioning module 150 may be configured to stop providing driving power to a blade motor that drives the cutting blade or blades within the cutting deck 40 or to a drive motor that provides power to the wheels. In some embodiments, warnings may be issued instead of or prior to initiation of any process interventions. Tilt may also or alternatively present risks relative to machine integrity or maintenance. For example, riding at the same angle for a long period of time may concentrate oil to one side of the crankcase and impact engine wear. Thus, the positioning module 150 may configured to track the amount of time that the riding yard maintenance vehicle 10 spends at a particular angle (or angles above a threshold) and issue a warning when the amount of time exceeds a predetermined amount. In some cases, speed restricted areas (e.g., based on slope or obstacle frequency) may also be identified to the operator as area with increased risk exposure. Areas that present risks above a certain threshold may be identified with overlaid graphics, color shading or any other suitable distinguishing characteristics on a map view or as a highlighted portion of a route. FIG. 3 illustrates an example of a risk-related regional alert 340 that is indicative of a risk being associated with the highlighted region…After working of the parcel is complete, the route information may be saved in connection with the corresponding parcel or customer as one instance of a route run on the corresponding parcel. Thereafter, the operator may be enabled to enter the identifier and retrieve route information for the corresponding parcel or customer. Alerts, warnings, route optimization and other services, such as those described herein by way of example, may further be provided relative to self mapped route information….[0053] The recordation of position and/or orientation data for the riding yard maintenance vehicle 10 may provide a number of uses to operators. As indicated above, route optimization services, route guidance services, and the provision of alerts and warnings may all be provided based on the storage of route information including position and/or orientation data. However, the knowledge of past routes may also provide a number of other uses. For example, variation of the orientation of lawn striping may be easily accomplished (e.g., in a guided or unguided format) by informing the operator of the orientation of previous striping. Accordingly, the operator does not need to try to remember the way a parcel was worked on a previous occasion.” See also [0047] “Alternatively or additionally, alerts, alarms or warnings may be provided as audible or visual indicators that the operator is straying from a previous route or derivative route by more than a threshold amount. The alerts may be indicated on the display or via separate lights (e.g., flashing or solid, red or yellow lights).” The examiner interprets the alert or notification of the vehicle based on the tilt level, the tilt for a predetermined time, speed restrictions, and threshold distance of the route to correspond to be a trigger based operation rules to modify the working machine’s implementation of the mission plan).
Regarding claim 6, Drew, Jespersen and Sheehan teaches the management system according to claim 5, wherein the trigger-based operational rules are selected from another reusable digital asset from the reusable digital asset storage (See at least Drew Figure 3 and [0051-0053] and [0047] as cited above with respect to claim 5. The examiner interprets the tilt level, the tilt for a predetermined time, speed restrictions, and threshold distance of the route to be the trigger-based operational rules that are stored as another reusable digital asset).
Regarding claim 7, Drew, Jespersen and Sheehan teaches the management system according to claim 1, wherein the reusable digital asset from the reusable digital asset storage has been created from an analysis of a project plan by an analysis system, wherein the analysis identifies subsections of the project plan that are reusable for other project operations (The examiner notes that the instant application at [0039] indicates that reusable digital assets include maps, routes, settings, etc. and thus, the examiner interprets using portions of maps and routes of many past routes after analysis of the past routes and maps of Drew to teach the reusable digital assets. See at least Drew Figure 3 and 4 wherein portions or subsections of the route are reused 330 and obstacle locations from the map are reused to determine the optimal route after analysis. Further, the examiner notes that any data that is stored can be considered a reusable digital asset. See at least Drew [0052] “…After working of the parcel is complete, the route information may be saved in connection with the corresponding parcel or customer as one instance of a route run on the corresponding parcel. Thereafter, the operator may be enabled to enter the identifier and retrieve route information for the corresponding parcel or customer. Alerts, warnings, route optimization and other services, such as those described herein by way of example, may further be provided relative to self mapped route information.” See also [0056] In some cases, each one of the clients 520 may include (or otherwise have access to) memory for storing instructions or applications for the performance of various functions and a corresponding processor for executing stored instructions or applications. Each one of the clients 520 may also include software and/or corresponding hardware for enabling the performance of the respective functions of the clients as described herein in relation to recording (or providing information for remote recording) of information indicative of vehicle position and/or orientation. In an example embodiment, one or more of the clients 520 may include a client application 522 configured to operate in accordance with an example embodiment of the present invention. In this regard, for example, the client application 522 may include software for enabling a respective one of the clients 520 to communicate with the network 530 for requesting and/or receiving information indicative of vehicle position and/or orientation in the context of a route or parcel in the form of a deliverable component (e.g., as downloadable software to configure the client, or as a transferable memory device including instructions to configure the client). As such, for example, the client application 522 may include corresponding executable instructions for configuring the client 520 to provide corresponding functionalities as described in greater detail herein.” See also [0047-0049] “In some embodiments, the positioning module 150 may be configured to generate an optimal route for display to guide the operator or to inform the operator of a proposed path for working a parcel of land. The optimal route may be generated using algorithms designed to consider desirable criteria relative to performance over past routes, or relative to expected performance for a route for which detailed geographic information regarding a parcel is known a priori. As an example, the optimal route may be generated based on analyzing past routes for the time taken to complete each route and determining, based on the past routes, an optimal route for fastest completion of working a particular parcel. Alternatively, fuel economy, cut quality, blade torque minimization, risk of damage to operator or machine, tilt exposure minimization, or any number of other criteria may be used as criteria for generation of optimal routes. In some cases, the criteria used may be considered relative to a number or previous routes, or relative to models created based on vehicle performance testing, in order to generate recommendations regarding routes and/or specific driving strategies to be employed while running routes in order to optimally run the route relative to the selected criteria….[0049] FIG. 4 illustrates an example of an optimal route 330 that may be proposed relative to any criteria based on a previously run route (e.g., the route 300 of FIG. 3 or modeled performance). In FIG. 4 also, the parcel may be graphically displayed based on locally or remotely generated data, or based on third party data received in connection with the parcel. Moreover, in some cases, locally or remotely generated data may be merged with third party data to generate a view of the parcel with route information displayed thereon.” See also [0061] “ As such, the environment of FIG. 5 illustrates an example in which provision of recorded obstacle locations to an onsite device (e.g., the riding yard maintenance vehicle 10 or a mobile phone or device of the operator of the riding yard maintenance vehicle 10) may be accomplished by a remote entity (e.g., the application server 540). As such, the onsite device may be enabled to generate or utilize map or other geographic data even if the onsite device did not necessarily record some of the data itself. Moreover, in some embodiments, provision of location information may be provided from the onsite device to the remote entity for recording and later provision of such data, or of functions driven off of such data, either to the onsite device or another device that ends up at the same site in the future. “)
Claim(s) 3-7 and 8-12 is/are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Drew, Jespersen, and Sheehan in view of Hurd et al. (US Pub. No. 2020/0159220, hereinafter “Hurd”) .
Regarding claims 3 and 4, while the examiner interprets that the combination of Drew, Jespersen and Sheehan to teach the management system according to claim 1, wherein the mission plan includes operational rules to guide the working machine's implementation of the mission plan wherein the operational rules are selected from another reusable digital asset from the reusable digital asset storage (See at least Drew Figure 3 and [0051-0053] and [0047] as rejected above), to further prosecution, the examiner also notes that Hurd teaches the mission plan includes operational rules to guide the working machine's implementation of the mission plan wherein the operational rules are selected from another reusable digital asset from the reusable digital asset storage (see at least Hurd [0049] and [0052] “At steps 460 and 470, the perception and safety system 160 analyzes sensor data collected from the plurality of sensors to detect and classify objects in field of view of the one or more machines 102, and determines a response to a presence of an object in that field of view. This may include initiating a change in navigational or other characteristics of navigational control of the one or more machines 102, such as for example changing speed, changing gears, stopping, braking, or adjusting some other aspect of the vehicular state of the one or more machines 102.” See also [0055-0056] which teaches that the vehicle controls are manipulated based on sensor data of multiple vehicles and thus the sensor data and the machine learning model is reused).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Drew, Jespersen and Sheehan with the teaching of Hurd, with a reasonable expectation of success, because as Hurd teaches the common software structural architecture allows for collection of data that can be used to “learn” and improve on vehicle-to-vehicle functionality for future operation and further the system can fuse data from multiple sensors and vehicle to provide the autonomously-operated machinery with situational awareness to avoid obstacles and other terrain characteristics (see at least Hurd [0039-0040]).
Regarding claims 5 and 6, while the examiner interprets that the combination of Drew, Jespersen and Sheehan to teach the management system according to claim 1, wherein the mission plan includes trigger-based operational rules to modify the working machine's implementation of the mission plan and wherein the trigger-based operational rules are selected from another reusable digital asset from the reusable digital asset storage (see at least Drew Figure 3 and [0051-0053] and [0047] as rejected above), to further prosecution, the examiner also notes that Hurd teaches wherein the mission plan includes trigger-based operational rules to modify the working machine's implementation of the mission plan and wherein the trigger-based operational rules are selected from another reusable digital asset from the reusable digital asset (see at least Hurd [0049] and [0052] “At steps 460 and 470, the perception and safety system 160 analyzes sensor data collected from the plurality of sensors to detect and classify objects in field of view of the one or more machines 102, and determines a response to a presence of an object in that field of view. This may include initiating a change in navigational or other characteristics of navigational control of the one or more machines 102, such as for example changing speed, changing gears, stopping, braking, or adjusting some other aspect of the vehicular state of the one or more machines 102.” See also [0055-0056] which teaches that the vehicle controls are manipulated based on sensor data stored of multiple vehicles and thus the sensor data and the machine learning model is reused).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Drew, Jespersen and Sheehan with the teaching of Hurd, with a reasonable expectation of success, because as Hurd teaches the common software structural architecture allows for collection of data that can be used to “learn” and improve on vehicle-to-vehicle functionality for future operation and further the system can fuse data from multiple sensors and vehicle to provide the autonomously-operated machinery with situational awareness to avoid obstacles and other terrain characteristics (see at least Hurd [0039-0040]).
Regarding claim 7, while the examiner interprets that the combination of Drew, Jespersen and Sheehan to teach the management system according to claim 1, wherein the reusable digital asset from the reusable digital asset storage has been created from an analysis of a project plan by an analysis system, wherein the analysis identifies subsections of the project plan that are reusable for other project operations. (see at least Drew [0052], [0056], [0047-0049] and [0061] as rejected above), to further prosecution, the examiner also notes that Hurd teaches herein the reusable digital asset from the reusable digital asset storage has been created from an analysis of a project plan by an analysis system, wherein the analysis identifies subsections of the project plan that are reusable for other project operations. (see at least Hurd [0049] “In this step, the common software structural architecture 100 is configured to perform several high-level system functions, such as one account management, arrange for centralized data storage for information such as field data and sensor data collected by the plurality of sensors coupled to the one or more machines 102, a pairing of the one or more machines 102 to be used in the autonomous performance of the agricultural activity 104, and machine configuration management.” [0052] “At steps 460 and 470, the perception and safety system 160 analyzes sensor data collected from the plurality of sensors to detect and classify objects in field of view of the one or more machines 102, and determines a response to a presence of an object in that field of view. This may include initiating a change in navigational or other characteristics of navigational control of the one or more machines 102, such as for example changing speed, changing gears, stopping, braking, or adjusting some other aspect of the vehicular state of the one or more machines 102.” See also [0055-0056] which teaches that the vehicle controls are manipulated based on sensor data stored of multiple vehicles and thus the sensor data and the machine learning model is reused).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Drew, Jespersen and Sheehan with the teaching of Hurd, with a reasonable expectation of success, because as Hurd teaches the common software structural architecture allows for collection of data that can be used to “learn” and improve on vehicle-to-vehicle functionality for future operation and further the system can fuse data from multiple sensors and vehicle to provide the autonomously-operated machinery with situational awareness to avoid obstacles and other terrain characteristics (see at least Hurd [0039-0040]).
Regarding claim 8, the combination of Drew, Jespersen, and Sheehan do not teach the management system according to claim 1, wherein the reusable digital asset comprises a machine learning model.
Hurd teaches wherein the reusable digital asset comprises a machine learning model (see at least Hurd, [0052-0056] which teaches information from sensors of more than one vehicle is analyzed by a neural network (i.e. a model) specifically [0052] “At steps 460 and 470, the perception and safety system 160 analyzes sensor data collected from the plurality of sensors to detect and classify objects in field of view of the one or more machines 102, and determines a response to a presence of an object in that field of view. This may include initiating a change in navigational or other characteristics of navigational control of the one or more machines 102, such as for example changing speed, changing gears, stopping, braking, or adjusting some other aspect of the vehicular state of the one or more machines 102….[0055] “As noted above, the common software structural architecture 100 may allow for one or more layers or techniques of artificial intelligence to be applied to assist various aspects of the present invention to operate, such as for example analyzing images and reflected signals from the plurality of sensors to detect and classify the objects in the field of view of the one or more machines 102. Additionally, these artificial intelligence techniques may be used to evaluate a vehicular state for controlling the movement and the speed of the one or more machines 102 in response to the presence of objects, such as evaluating one or more of latitude, longitude, speed, heading, yaw-rate, a turning radius, and global position system zones representing a geographical location…[0056] Artificial intelligence and other types of machine learning may be used to associate and compare information in various types of sensor data, and to identify attributes in such sensor data, to produce detections of objects and to predict movement of those detected objects. The applications of artificial intelligence in the present invention may include one or more neural networks configured to develop relationships among and between the information within the various types of sensor data to recognize objects across images and reflected signals from different types of sensors having different fields of view, which are used to determine whether action needs to be taken to manipulate and control the autonomously-operated machines and vehicles 102. Artificial intelligence may therefore be used in the present invention at least within the perception and safety module 160 for safe operation of the one or more machines 102 in the performance of an agricultural activity 104.” See also [0049] which teaches sensor information from more than one machine is used for the analysis.).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Drew, Jespersen, and Sheehan with the teaching of Hurd, with a reasonable expectation of success, because as Hurd teaches the common software structural architecture allows for collection of data that can be used to “learn” and improve on vehicle-to-vehicle functionality for future operation and further the system can fuse data from multiple sensors and vehicle to provide the autonomously-operated machinery with situational awareness to avoid obstacles and other terrain characteristics (see at least Hurd [0039-0040]).
Regarding claim 9, the combination of Drew, Jespersen, Sheehan, and Hurd teach the management system according to claim 8, wherein the machine learning model is configured for execution by the machine control unit to manage a sensor array system of the working machine (see at least Hurd, [0052-0056] “[0052] At steps 460 and 470, the perception and safety system 160 analyzes sensor data collected from the plurality of sensors to detect and classify objects in field of view of the one or more machines 102, and determines a response to a presence of an object in that field of view. This may include initiating a change in navigational or other characteristics of navigational control of the one or more machines 102, such as for example changing speed, changing gears, stopping, braking, or adjusting some other aspect of the vehicular state of the one or more machines 102….[0055] “As noted above, the common software structural architecture 100 may allow for one or more layers or techniques of artificial intelligence to be applied to assist various aspects of the present invention to operate, such as for example analyzing images and reflected signals from the plurality of sensors to detect and classify the objects in the field of view of the one or more machines 102. Additionally, these artificial intelligence techniques may be used to evaluate a vehicular state for controlling the movement and the speed of the one or more machines 102 in response to the presence of objects, such as evaluating one or more of latitude, longitude, speed, heading, yaw-rate, a turning radius, and global position system zones representing a geographical location…[0056] Artificial intelligence and other types of machine learning may be used to associate and compare information in various types of sensor data, and to identify attributes in such sensor data, to produce detections of objects and to predict movement of those detected objects. The applications of artificial intelligence in the present invention may include one or more neural networks configured to develop relationships among and between the information within the various types of sensor data to recognize objects across images and reflected signals from different types of sensors having different fields of view, which are used to determine whether action needs to be taken to manipulate and control the autonomously-operated machines and vehicles 102. Artificial intelligence may therefore be used in the present invention at least within the perception and safety module 160 for safe operation of the one or more machines 102 in the performance of an agricultural activity 104.” See also [0049] which teaches sensor information from more than one machine is used for the analysis.)
Regarding claim 10, the combination of Drew, Jespersen, and Sheehan teach the management system according to claim 1, wherein the working machine includes a sensor array system connected to the machine control unit (see at least Drew Figure 2 and [0036-0037]), but does not teach wherein the machine control unit applies the machine instructions based on the reusable digital asset to manage the sensor array system.
Hurd teaches wherein the working machine includes a sensor array system connected to the machine control unit, and wherein the machine control unit applies the machine instructions based on the reusable digital asset to manage the sensor array system (see at least Hurd, [0052-0056] which teaches information from sensors of more than one vehicle is analyzed by a neural network (i.e. a model) specifically [0052] “At steps 460 and 470, the perception and safety system 160 analyzes sensor data collected from the plurality of sensors to detect and classify objects in field of view of the one or more machines 102, and determines a response to a presence of an object in that field of view. This may include initiating a change in navigational or other characteristics of navigational control of the one or more machines 102, such as for example changing speed, changing gears, stopping, braking, or adjusting some other aspect of the vehicular state of the one or more machines 102….[0055] “As noted above, the common software structural architecture 100 may allow for one or more layers or techniques of artificial intelligence to be applied to assist various aspects of the present invention to operate, such as for example analyzing images and reflected signals from the plurality of sensors to detect and classify the objects in the field of view of the one or more machines 102. Additionally, these artificial intelligence techniques may be used to evaluate a vehicular state for controlling the movement and the speed of the one or more machines 102 in response to the presence of objects, such as evaluating one or more of latitude, longitude, speed, heading, yaw-rate, a turning radius, and global position system zones representing a geographical location…[0056] Artificial intelligence and other types of machine learning may be used to associate and compare information in various types of sensor data, and to identify attributes in such sensor data, to produce detections of objects and to predict movement of those detected objects. The applications of artificial intelligence in the present invention may include one or more neural networks configured to develop relationships among and between the information within the various types of sensor data to recognize objects across images and reflected signals from different types of sensors having different fields of view, which are used to determine whether action needs to be taken to manipulate and control the autonomously-operated machines and vehicles 102. Artificial intelligence may therefore be used in the present invention at least within the perception and safety module 160 for safe operation of the one or more machines 102 in the performance of an agricultural activity 104.” See also [0049] which teaches sensor information from more than one machine is used for the analysis.).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Drew, Jespersen, and Sheehan with the teaching of Hurd, with a reasonable expectation of success, because as Hurd teaches the common software structural architecture allows for collection of data that can be used to “learn” and improve on vehicle-to-vehicle functionality for future operation and further the system can fuse data from multiple sensors and vehicle to provide the autonomously-operated machinery with situational awareness to avoid obstacles and other terrain characteristics (see at least Hurd [0039-0040]).
Regarding claim 11, the combination of Drew, Jespersen, Sheehan and Hurd teach the management system according to claim 9, wherein the reusable digital asset comprises a machine learning model that is incorporated into the mission plan, and the machine control unit executes the machine learning model to configure the sensor array system (see at least Hurd, [0052-0056] “[0052] At steps 460 and 470, the perception and safety system 160 analyzes sensor data collected from the plurality of sensors to detect and classify objects in field of view of the one or more machines 102, and determines a response to a presence of an object in that field of view. This may include initiating a change in navigational or other characteristics of navigational control of the one or more machines 102, such as for example changing speed, changing gears, stopping, braking, or adjusting some other aspect of the vehicular state of the one or more machines 102….[0055] “As noted above, the common software structural architecture 100 may allow for one or more layers or techniques of artificial intelligence to be applied to assist various aspects of the present invention to operate, such as for example analyzing images and reflected signals from the plurality of sensors to detect and classify the objects in the field of view of the one or more machines 102. Additionally, these artificial intelligence techniques may be used to evaluate a vehicular state for controlling the movement and the speed of the one or more machines 102 in response to the presence of objects, such as evaluating one or more of latitude, longitude, speed, heading, yaw-rate, a turning radius, and global position system zones representing a geographical location…[0056] Artificial intelligence and other types of machine learning may be used to associate and compare information in various types of sensor data, and to identify attributes in such sensor data, to produce detections of objects and to predict movement of those detected objects. The applications of artificial intelligence in the present invention may include one or more neural networks configured to develop relationships among and between the information within the various types of sensor data to recognize objects across images and reflected signals from different types of sensors having different fields of view, which are used to determine whether action needs to be taken to manipulate and control the autonomously-operated machines and vehicles 102. Artificial intelligence may therefore be used in the present invention at least within the perception and safety module 160 for safe operation of the one or more machines 102 in the performance of an agricultural activity 104.” See also [0049] which teaches sensor information from more than one machine is used for the analysis.).
Regarding claim 12, the combination of Drew, Jespersen, Sheehan and Hurd teach the management system according to claim 10, wherein the machine control unit executes the machine learning model to analyze sensor data from the sensor array system (see at least Hurd, [0052-0056] “[0052] At steps 460 and 470, the perception and safety system 160 analyzes sensor data collected from the plurality of sensors to detect and classify objects in field of view of the one or more machines 102, and determines a response to a presence of an object in that field of view. This may include initiating a change in navigational or other characteristics of navigational control of the one or more machines 102, such as for example changing speed, changing gears, stopping, braking, or adjusting some other aspect of the vehicular state of the one or more machines 102….[0055] “As noted above, the common software structural architecture 100 may allow for one or more layers or techniques of artificial intelligence to be applied to assist various aspects of the present invention to operate, such as for example analyzing images and reflected signals from the plurality of sensors to detect and classify the objects in the field of view of the one or more machines 102. Additionally, these artificial intelligence techniques may be used to evaluate a vehicular state for controlling the movement and the speed of the one or more machines 102 in response to the presence of objects, such as evaluating one or more of latitude, longitude, speed, heading, yaw-rate, a turning radius, and global position system zones representing a geographical location…[0056] Artificial intelligence and other types of machine learning may be used to associate and compare information in various types of sensor data, and to identify attributes in such sensor data, to produce detections of objects and to predict movement of those detected objects. The applications of artificial intelligence in the present invention may include one or more neural networks configured to develop relationships among and between the information within the various types of sensor data to recognize objects across images and reflected signals from different types of sensors having different fields of view, which are used to determine whether action needs to be taken to manipulate and control the autonomously-operated machines and vehicles 102. Artificial intelligence may therefore be used in the present invention at least within the perception and safety module 160 for safe operation of the one or more machines 102 in the performance of an agricultural activity 104.” .).
Claim(s) 13-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Drew in view of and Sheehan and Hurd.
Regarding claim 13, Drew discloses a working machine for automated work (See at least Drew Figures 1A and 1B and 0022] FIG. 1, which includes FIGS. 1A and 1B, illustrates an example of a riding yard maintenance vehicle 10 having a bagging attachment 12.), comprising:
[[an application gateway having a first communication card]] configured to communicate over a communication network with a networked server, which includes a server communication card and a server memory comprising reusable digital asset storage (see at least Drew Figure 5, client 520 including client application 522, connected to network 530 which is connected to the server 532, 540 see also Figure 2. See also Drew [0055] “ As shown in FIG. 5, a system 500 according to an example embodiment may include one or more clients 520 that may, in some cases, be associated with different corresponding riding yard maintenance vehicles or other remote nodes… As such, each one of the clients 520 may be, for example, a computer (e.g., a personal computer, laptop computer, network access terminal, or the like) or may be another form of computing device (e.g., a personal digital assistant (PDA), cellular phone, smart phone, or the like) capable of communication with a network 530 via any short range (e.g., WiFi, Bluetooth, etc.) or long range communication protocols (e.g., 3G, 4G, LTE, etc.). As such, the clients 520 may be fixed at or integrated into riding yard maintenance vehicles, may be removable or transferable accessories or components associated with riding yard maintenance vehicles, or may be separate devices (e.g., a smart phone) capable of running applications useable in connection with operation of riding yard maintenance vehicles.” The examiner notes that the claim is directed to the working machine. The server, the server communication card and the server memory including reusable digital asset storage are not part of the working machine. For purposes of examination, the examiner will interpret the application gateway to be configured to communicate over a network with a server to meet the claim limitations).
a machine control unit comprising a machine processor and a machine memory which stores machine operating instructions; (see at least Drew Figure 2, and processing circuitry 210 including processor 212 and memory 214 See at least [0034] “In an example embodiment, the processing circuitry 210 may include one or more instances of a processor 212 and memory 214 that may be in communication with or otherwise control a device interface 220 and, in some cases, a user interface 230.” and [0036] “ The device interface 220 may include one or more interface mechanisms for enabling communication with other devices (e.g., sensors of a sensor network and/or other accessories or functional units 270 such as motors, servos, switches or other operational control devices for automatic responses” See also [0040] “As such, in some embodiments, the processor 212 (or the processing circuitry 210) may be said to cause each of the operations described in connection with the positioning module 150 by directing the positioning module 150 to undertake the corresponding functionalities responsive to execution of instructions or algorithms configuring the processor 212 (or processing circuitry 210) accordingly. As an example, the positioning module 150 may be configured to record position and/or orientation information, or other operational parameters regarding the tasks performed by riding yard maintenance vehicle 10 as described herein. The positioning module 150 may then, in some cases, process the information to generate alerts, warnings, route optimization, route guidance, maintenance recommendations, position histories, work histories, and/or the like.”),and
a machine actuator system having a drive control actuator (see at least Drew [0023] FIG. 1A illustrates a side view of the riding yard maintenance vehicle 10 and FIG. 1B illustrates a perspective view of the riding yard maintenance vehicle 10. The riding yard maintenance vehicle may include a steering assembly 20 (e.g., including a steering wheel, handle bars, or other steering apparatus) functionally connected to wheels of the riding yard maintenance vehicle 10 to which steering inputs are provided (e.g., the front and/or rear wheels in various different embodiments) to allow the operator to steer the riding yard maintenance vehicle 10. In some embodiments, the riding yard maintenance vehicle 10 may include seat 30 that may be disposed at a center, rear or front portion of the riding yard maintenance vehicle 10. The operator may sit on the seat 30, which may be disposed to the rear of the steering assembly 20 to provide input for steering of the riding yard maintenance vehicle 10 via the steering assembly 20.” [0036] “ The device interface 220 may include one or more interface mechanisms for enabling communication with other devices (e.g., sensors of a sensor network and/or other accessories or functional units 270 such as motors, servos, switches or other operational control devices for automatic responses” See also “[0051] “For example, if tilt as indicated by the accelerometer 250 reaches a predefined level, the positioning module 150 may be configured to stop providing driving power to a blade motor that drives the cutting blade or blades within the cutting deck 40 or to a drive motor that provides power to the wheels.”); and
wherein [[the application gateway]] receives a mission plan from the server over the communication network, wherein the mission plan is generated by the server to instruct the working machine to perform a project, and the mission plan includes machine instructions selected from a reusable digital asset from the reusable digital asset storage in the server (The examiner notes that the instant application at [0039] indicates that reusable digital assets include maps, routes, settings, etc. and thus, the examiner uses the map and/or route information of Drew to teach the reusable digital assets. However, the examiner notes that any data that is stored can be considered a reusable digital asset. See at least Drew [0052] “…After working of the parcel is complete, the route information may be saved in connection with the corresponding parcel or customer as one instance of a route run on the corresponding parcel. Thereafter, the operator may be enabled to enter the identifier and retrieve route information for the corresponding parcel or customer. Alerts, warnings, route optimization and other services, such as those described herein by way of example, may further be provided relative to self mapped route information.” See also [0056] “In this regard, for example, the client application 522 may include software for enabling a respective one of the clients 520 to communicate with the network 530 for requesting and/or receiving information indicative of vehicle position and/or orientation in the context of a route or parcel in the form of a deliverable component (e.g., as downloadable software to configure the client, or as a transferable memory device including instructions to configure the client). As such, for example, the client application 522 may include corresponding executable instructions for configuring the client 520 to provide corresponding functionalities as described in greater detail herein.” See also [0047-0049] “In some embodiments, the positioning module 150 may be configured to generate an optimal route for display to guide the operator or to inform the operator of a proposed path for working a parcel of land. The optimal route may be generated using algorithms designed to consider desirable criteria relative to performance over past routes, or relative to expected performance for a route for which detailed geographic information regarding a parcel is known a priori. As an example, the optimal route may be generated based on analyzing past routes for the time taken to complete each route and determining, based on the past routes, an optimal route for fastest completion of working a particular parcel. Alternatively, fuel economy, cut quality, blade torque minimization, risk of damage to operator or machine, tilt exposure minimization, or any number of other criteria may be used as criteria for generation of optimal routes. In some cases, the criteria used may be considered relative to a number or previous routes, or relative to models created based on vehicle performance testing, in order to generate recommendations regarding routes and/or specific driving strategies to be employed while running routes in order to optimally run the route relative to the selected criteria….[0049] FIG. 4 illustrates an example of an optimal route 330 that may be proposed relative to any criteria based on a previously run route (e.g., the route 300 of FIG. 3 or modeled performance). In FIG. 4 also, the parcel may be graphically displayed based on locally or remotely generated data, or based on third party data received in connection with the parcel. Moreover, in some cases, locally or remotely generated data may be merged with third party data to generate a view of the parcel with route information displayed thereon.” See also [0061] “ As such, the environment of FIG. 5 illustrates an example in which provision of recorded obstacle locations to an onsite device (e.g., the riding yard maintenance vehicle 10 or a mobile phone or device of the operator of the riding yard maintenance vehicle 10) may be accomplished by a remote entity (e.g., the application server 540). As such, the onsite device may be enabled to generate or utilize map or other geographic data even if the onsite device did not necessarily record some of the data itself. Moreover, in some embodiments, provision of location information may be provided from the onsite device to the remote entity for recording and later provision of such data, or of functions driven off of such data, either to the onsite device or another device that ends up at the same site in the future.” )
While Drew teaches receiving the mission plan (optimal route, route information and map including elevation and obstacles) and controls the working machine in response to the machine instructions (see at least Drew [0031] which teaches displaying based on the optimized route), Drew does not explicitly teach wherein the machine control unit executes the machine instructions from the mission plan, and the machine actuator system controls the working machine in response to the machine instructions.
Hurd teaches wherein the machine control unit executes the machine instructions from the mission plan, and the machine actuator system controls the working machine in response to the machine instructions (see at least Hurd [0052] At steps 460 and 470, the perception and safety system 160 analyzes sensor data collected from the plurality of sensors to detect and classify objects in field of view of the one or more machines 102, and determines a response to a presence of an object in that field of view. This may include initiating a change in navigational or other characteristics of navigational control of the one or more machines 102, such as for example changing speed, changing gears, stopping, braking, or adjusting some other aspect of the vehicular state of the one or more machines 102.” And [0056] “The applications of artificial intelligence in the present invention may include one or more neural networks configured to develop relationships among and between the information within the various types of sensor data to recognize objects across images and reflected signals from different types of sensors having different fields of view, which are used to determine whether action needs to be taken to manipulate and control the autonomously-operated machines and vehicles 102. Artificial intelligence may therefore be used in the present invention at least within the perception and safety module 160 for safe operation of the one or more machines 102 in the performance of an agricultural activity 104.”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Drew with the teaching of Hurd, with a reasonable expectation of success, because as Hurd teaches, this allows the working vehicle to avoid obstacles and increase safety (see at least Hurd [0056]).
The combination of Drew and Hurd do not explicitly teach an application gateway.
Sheehan teaches application gateway (see at least Sheehan [0028-0029] “The application gateway architecture provides support for multi-vendor facilities architectures and is able to control supported apparatus by hosting, storing and communicating operating rules and protocols necessary to communicate with and manage any particular piece of facilities equipment. …[0029] The application gateway may expose data from one or more devices 112A-C to a variety of enterprise applications 108, simultaneously, in standard formats recognizable to those applications. The application gateway, deployed on discreet serial processors 114 (e.g., about the size of a deck of cards) or embedded communication cards 116, can connect the intelligent device(s) 112A-C to the enterprise application 108, or other upstream applications. The application gateway may expose data from one or more devices 112A-C to a variety of enterprise applications 108, simultaneously, in standard formats recognizable to those applications. The application gateway, deployed on discreet serial processors 114 (or embedded communication cards 116, can connect the intelligent device(s) 112A-C to the enterprise application 108, or other upstream applications.”.)
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the combination of Drew and Hurd to include an application gateway as taught by Sheehan, with a reasonable expectation of success, because as Sheehan teaches the application gateway with a communication card allows for connection, communication and management of equipment and devices (see at least Sheehan [0029-0029]).
Regarding claim 14, the combination of Drew, Hurd and Sheehan teach the working machine according to claim 13, further comprising a sensor array system connected to the machine control unit (see at least Figure 1 and [0040] “This module, referred to in FIG. 1 as a “perception” system 160, recognizes and distinguishes terrain to be covered by autonomously-operated equipment, and performs tasks such as identification of obstacles and other characteristics that enable safe, efficient, and confident performance of machines and vehicles 102 in such an operating environment.”)
Regarding claim 15, the combination of Drew, Hurd and Sheehan teach the working machine according to claim 14, wherein the reusable digital asset comprises a machine learning model that is included in the mission plan, and the machine control unit executes the machine learning model to configure the sensor array system (see at least Hurd, [0052-0056] “[0052] At steps 460 and 470, the perception and safety system 160 analyzes sensor data collected from the plurality of sensors to detect and classify objects in field of view of the one or more machines 102, and determines a response to a presence of an object in that field of view. This may include initiating a change in navigational or other characteristics of navigational control of the one or more machines 102, such as for example changing speed, changing gears, stopping, braking, or adjusting some other aspect of the vehicular state of the one or more machines 102….[0055] “As noted above, the common software structural architecture 100 may allow for one or more layers or techniques of artificial intelligence to be applied to assist various aspects of the present invention to operate, such as for example analyzing images and reflected signals from the plurality of sensors to detect and classify the objects in the field of view of the one or more machines 102. Additionally, these artificial intelligence techniques may be used to evaluate a vehicular state for controlling the movement and the speed of the one or more machines 102 in response to the presence of objects, such as evaluating one or more of latitude, longitude, speed, heading, yaw-rate, a turning radius, and global position system zones representing a geographical location…[0056] Artificial intelligence and other types of machine learning may be used to associate and compare information in various types of sensor data, and to identify attributes in such sensor data, to produce detections of objects and to predict movement of those detected objects. The applications of artificial intelligence in the present invention may include one or more neural networks configured to develop relationships among and between the information within the various types of sensor data to recognize objects across images and reflected signals from different types of sensors having different fields of view, which are used to determine whether action needs to be taken to manipulate and control the autonomously-operated machines and vehicles 102. Artificial intelligence may therefore be used in the present invention at least within the perception and safety module 160 for safe operation of the one or more machines 102 in the performance of an agricultural activity 104.” See also [0049] which teaches sensor information from more than one machine is used for the analysis.).
Regarding claim 16, the combination of Drew, Hurd and Sheehan teach the working machine according to claim 15, wherein the machine control unit executes the machine learning model to analyze sensor data from the sensor array system (see at least Hurd, [0052-0056] “[0052] At steps 460 and 470, the perception and safety system 160 analyzes sensor data collected from the plurality of sensors to detect and classify objects in field of view of the one or more machines 102, and determines a response to a presence of an object in that field of view. This may include initiating a change in navigational or other characteristics of navigational control of the one or more machines 102, such as for example changing speed, changing gears, stopping, braking, or adjusting some other aspect of the vehicular state of the one or more machines 102….[0055] “As noted above, the common software structural architecture 100 may allow for one or more layers or techniques of artificial intelligence to be applied to assist various aspects of the present invention to operate, such as for example analyzing images and reflected signals from the plurality of sensors to detect and classify the objects in the field of view of the one or more machines 102. Additionally, these artificial intelligence techniques may be used to evaluate a vehicular state for controlling the movement and the speed of the one or more machines 102 in response to the presence of objects, such as evaluating one or more of latitude, longitude, speed, heading, yaw-rate, a turning radius, and global position system zones representing a geographical location…[0056] Artificial intelligence and other types of machine learning may be used to associate and compare information in various types of sensor data, and to identify attributes in such sensor data, to produce detections of objects and to predict movement of those detected objects. The applications of artificial intelligence in the present invention may include one or more neural networks configured to develop relationships among and between the information within the various types of sensor data to recognize objects across images and reflected signals from different types of sensors having different fields of view, which are used to determine whether action needs to be taken to manipulate and control the autonomously-operated machines and vehicles 102. Artificial intelligence may therefore be used in the present invention at least within the perception and safety module 160 for safe operation of the one or more machines 102 in the performance of an agricultural activity 104.” .).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Roy (US-11993279-B1) and Diekhans (US-20070282523-A1) are cited for showing storing reusable assets (see Figure 20 and col. 12 of Roy and Figure 4 and associated description of Diekhans).
Miura (US-20210203573-A1) is cited as teaching storing reusable assets (setting information) and reusing the setting information very pertinent to the independent claims.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JENNIFER M. ANDA whose telephone number is (571)272-5042. The examiner can normally be reached Monday-Friday 8:30 am-5pm MST.
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/JENNIFER M ANDA/Examiner, Art Unit 3662