Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 7/30/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Claims 1-11 are directed to a system (i.e., machine), Claim 12 is directed to computer program product (i.e., machine), and claim 13 is directed to a method (i.e., a process). Therefore, Claims 1-18 all fall within the one of the four statutory categories of invention.
Step 2A, Prong One
Independent claim 1 substantially recites :receive a task input comprising at least one of a timeline, a location, and a payload; receive a capacity input comprising at least one of a location, a payload and an operational condition for each of the plurality of uncrewed vehicles; receive a traffic input comprising at least one of a location and a flight plan for each of the plurality of uncrewed vehicles in a predetermined area; receive a risk input and determine if the risk input passes a predetermined risk threshold; determine a flight plan based on at least one of the task input, the capacity input, the traffic input, and the risk input; and send the flight plan to at least one of the plurality of uncrewed vehicles to deploy the uncrewed vehicle to execute a task.
Independent claim 12 substantially recites : receiving a task input comprising at least one of a timeline, a location, and a payload; receiving a capacity input comprising at least one of a location, a payload and an operational condition for each of a plurality of uncrewed vehicles; receiving a traffic input comprising at least one of a location and a flight plan for each of the plurality of uncrewed vehicles in a predetermined area; receiving a risk input and determining if the risk input passes a predetermined risk threshold; determining a flight plan based on at least one of the task input, the capacity input, the traffic input, and the risk input; and sending the flight plan to at least one of the plurality of uncrewed vehicles to deploy the uncrewed vehicle to execute a task. Claim 13 recites similar abstract ideas.
The limitations stated above are processes/ functions that under broadest reasonable interpretation covers “certain methods of organizing human activity” (managing personal behavior or relationships or interactions between people and commercial or legal interactions or sales activities and following rules or instructions) because the claims recite steps of collecting, analyzing and outputting the data (i.e. determining flight plan to dispatch a vehicle). The claims recite concepts related to mental processes—concepts performed in the human mind (including an observation, evaluation, judgment, opinion). See specification [0039] A basic analogy is to think of TAN as a 21st century 9-1-1 dispatcher, except not exclusively used for emergencies. Therefore, the claims recite an abstract idea.
Step 2A, Prong Two
The judicial exception is not integrated into a practical application. Claims 1 and 5 as a whole amounts to: (i) merely invoking generic components as a tool to perform the abstract idea or “apply it” (or an equivalent). The independent claims recite the additional elements: (i) a user interface module, a resource capacity management module, a traffic management module, a risk management module, A computer program product comprising a non-transitory processor-readable storage medium having stored therein program code of one or more software programs wherein the program code, when executed by at least one processing device comprising a processor coupled to a memory, one processing device comprising a processor operatively coupled to a memory, transmit, transmitting, automatically, these are recited at a high-level of generality (See specification: [0049] The C2 Orchestration layer 120 interacts with the available aircraft network 105 through communication and software interfaces 115 through either direct access to an onboard agent running on a companion computer on the aircraft, which communicates directly with the autopilot, or via API interactions with the ground control station(s). [0063] The resource capacity management module 124 functions to determine/measure the current and predicted future status of each resource utilized by TAN [0065] First, a task is generated 510 by a user, for example through a user-friendly mobile or web third-party application with a user interface. The generated task is communicated to TAN through the application layer module. The task is then automatically converted to a mission 515 and a mission request 520 is generated. This process is iterative between the C2 Orchestration module and the Traffic Management module. The Automation Orchestration module will pick the asset and payload that it thinks is best suited for the task and then tell the C2 Orchestration module to calculate a flight plan 525. C2 Orchestration module will send this suggested plan to the Traffic Management module to verify flight planning and provide clearance for execution. [0071], [0026].). such that, when viewed as whole/ordered combination (as shown in Fig. 1), it amounts to no more than mere instruction to apply the judicial exception using generic computer components or “apply it” (See MPEP 2106.05(f)).
The independent claims recite (ii) a ground station executing a command and control subsystem in operable communication with the plurality of uncrewed vehicles, which is recited at a high-level of generality (See Paras. [0039-40] TAN integrates with the various craft ground control stations (GCS) or directly with the onboard flight control systems. It translates user intent (i.e., what is the task that needs to be performed) into flight plans, in-flight control messages, and traceable mission historical records. TAN operates as a set of cloud-based services running on cloud computing hardware in a third-party data center. Physical systems such as radar, weather sensors, communications systems, etc. provide data to the TAN cloud- based services when viewed as whole/ordered combination, do no more than generally link the use of the judicial exception to a particular technological environment or field of use.
Accordingly, these additional elements, when viewed as a whole/ordered combination (as shown in Fig. 1), do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Thus, the claim is directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional elements amount to no more than: (i) “apply it” (or an equivalent). The same analysis applies here in Step 2B, i.e., (i) merely invoking the generic components as a tool to perform the abstract idea or “apply it”, (ii) generally link the use of a judicial exception to a particular technological environment or field of use, which do not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B.
Therefore, the additional elements of: (i) a user interface module, a resource capacity management module, a traffic management module, a risk management module, A computer program product comprising a non-transitory processor-readable storage medium having stored therein program code of one or more software programs wherein the program code, when executed by at least one processing device comprising a processor coupled to a memory, one processing device comprising a processor operatively coupled to a memory, transmit, transmitting, automatically and ( ii) a ground station executing a command and control subsystem in operable communication with the plurality of uncrewed vehicles ,do not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination, nothing in the claims adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, the claims are ineligible.
Dependent Claims Step 2A:
The limitations of the dependent claims but for those addressed below merely set forth further refinements of the abstract idea without changing the analysis already presented ( i.e., they merely narrow the abstract idea without adding any new additional elements beyond it). Additionally, for the same reasons as above, the limitations fail to integrate the abstract idea into a practical application because they use the same general technological environment and instructions to implement the abstract idea (e.g., using computers and internet) as the independent claims. Claims 2 and 3 add the elements “secure data management module”, “scheduling module”, these fail to integrate the abstract idea into a practical application because merely invoking the generic components as a tool to perform the abstract idea or “apply it”.
Dependent Claims Step 2B:
The dependent claims merely use the same general technological environment and instructions to implement a narrowed abstract idea. They do not add any additional elements not already analyzed and the abstract idea has the same ineligible relationship when viewed in combination as the independent claims do. Claim 2 and 3 add the elements “secure data management module”, “scheduling module”, that are recited at a high-level of generality (see [00041] The C2 layer 120 performs its control functions using a suite of service subsystems responsible for critical tasks shown in FIG. 1. All internal TAN services and subsystem communicate via a secure data exchange through APIs or standardized data streaming protocols. [0064] The priority-based scheduling module 132 enables TAN to be shareable with entities that span federal, state, and commercial interests), these do not amount to significantly more for the same reasons they fail to integrate the abstract idea into a practical application.
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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
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, 3-10, 13, and15-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Raptopoulos (US 20240038081) in view of Gentry (US9858822B1)
As per claim 1, Raptopoulos teaches:
A taskable aerial network system comprising: a plurality of uncrewed vehicles; and a ground station executing a command and control subsystem in operable communication with the plurality of uncrewed vehicles, (see at least: Fig.1 Abstract, [0007] the systems include the following components: autonomous electric flying vehicles, automated ground stations, and logistics software that operates the system [0008])
the command and control subsystem comprising a processor coupled to a memory (see at least: Fig. 4 [0014] a computer system manages a delivery system of unmanned aerial vehicles comprising one or more hardware processors in communication with a computer readable medium storing software modules [0137])
the processor configured to: receive via a user interface module a task input comprising at least one of a timeline, a location, and a payload; ( see at least: [0069] mobile application provides for the interaction of a user with the ground station or logistics system to obtain tracking information about a package. Such a mobile application can also allow the user to schedule a package drop off or locate a suitable ground station, for example, through identification of a current location or a desired location.)
receive via a resource capacity management module a capacity input comprising at least one of a location, a payload and an operational condition for each of the plurality of uncrewed vehicles; ( see at least: [0067] The ground station and the logistics system can communicate to exchange data such as remaining capacity, package information, battery status, time, weather, route information, or the like.[0110] [0096-97] The vehicle tracking 424 communicates with one or more UAVs or ground stations to determine information about the UAVs. For example, the UAVs can report their current location and status. The vehicle tracking module 424 can keep track of the UAVs and allow the delivery system 400 to perform higher level functions, such as, for example, load distribution, coordinated deliveries, and other higher-level functions)
receive via a traffic management module a traffic input (see at least: [0095] the logistics system and network coordinates traffic by providing new waypoints to a UAV during a mission that are known to be collision free)
Raptopoulos does not explicitly teach input comprising at least one of a location and a flight plan for each of the plurality of uncrewed vehicles in a predetermined area. However, this is taught by Gentry (see at least: Col.8 Lines 26-62, The data analysis module 208 may compare the preregistered flight plans, the current operating characteristics of nearby UAVs, and the UAV's 102 own flight plan to determine a likelihood of interaction. the dynamic flight plan optimization module 210 may consider additional factors, such as fuel capacity, an urgency factor associated with the UAV 102 or flight plans associated with individual ones of the nearby UAVs, relative location of one or more nearby UAVs, external factors (e.g., weather, air traffic congestion, etc.), and/or availability of one or more inactive UAVs within a predetermined distance threshold. The dynamic flight plan optimization module 210 may evaluate one or more flight plans that are alternatives to the current flight plan and iterate the evaluation to determine an optimized flight plan with respect to total flight time, total fuel consumption, impact to the flight plans of one or more other UAVs within the airspace 100, and/or a likelihood of interaction with one or more nearby UAVs. Col.4 Lines 51-61, A UAV may be required to participate in automated flight plan management with one or more UAVs operating within a common airspace. For instance, a UAV may detect one or more nearby UAVs operating within the common airspace. The UAV may determine the proximity of individual nearby UAVs and receive flight plan data from the one or more nearby UAVs. The UAV may compare its own flight plan with the flight plan of individual nearby UAVs and confidence values associated with the flight plans to iteratively negotiate updated flight plans for the individual UAVs)
It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to combine the flight plans of vehicles in a predetermined area feature for the same reasons its useful in Gentry -namely, to minimize interaction with one or more nearby UAVs in the common airspace. Moreover, this is merely a combination of old elements in the art. In the combination, no element would serve purpose other than it already did independently, and one skilled in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
Raptopoulos further teaches receive via a risk management module a risk input (see at least: [0091] the logistics system and network decides whether to ground a segment or area of the delivery system based on risk factors. The risk factors can include, for example, weather, information from authorities, the presence of emergency vehicles or personnel, time of day, or other suitable risk factors [0100-102] The ability to monitor and predict weather 428 allows the delivery system to optimally fly the UAVs to avoid adverse weather conditions, for example)
Raptopoulos does not explicitly teach determine if the risk input passes a predetermined risk threshold; However, this is taught by Gentry (see at least: Col.8 Lines 26-62, The data analysis module 208 may compare the preregistered flight plans, the current operating characteristics of nearby UAVs, and the UAV's 102 own flight plan to determine a likelihood of interaction. Where the likelihood of interaction exceeds a maximum threshold, the dynamic flight plan optimization module 210 may determine an optimized flight plan that minimizes or eliminates the likelihood of interaction [risk] The UAV 102 may then execute the updated flight plan. the dynamic flight plan optimization module 210 may consider additional factors, such as fuel capacity, an urgency factor associated with the UAV 102 or flight plans associated with individual ones of the nearby UAVs, relative location of one or more nearby UAVs, external factors (e.g., weather, air traffic congestion, etc.), and/or availability of one or more inactive UAVs within a predetermined distance threshold. The dynamic flight plan optimization module 210 may evaluate one or more flight plans that are alternatives to the current flight plan and iterate the evaluation to determine an optimized flight plan with respect to total flight time, total fuel consumption, impact to the flight plans of one or more other UAVs within the airspace 100, and/or a likelihood of interaction with one or more nearby UAVs.)
It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to combine the predetermined risk threshold feature for the same reasons its useful in Gentry -namely, to determine an optimized flight plan that minimizes or eliminates the likelihood of interaction. Moreover, this is merely a combination of old elements in the art. In the combination, no element would serve a purpose other than it already did independently, and one skilled in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
Raptopoulos further teaches determine a flight plan based on at least one of the task input, the capacity input, the traffic input, and the risk input; (see at least: [0096] The vehicle routing module 420 can include a routing algorithm. The routing algorithm can calculate the best route for moving a UAV from point to point. The routing algorithm can take into consideration factors such as, the distance, UAV capacity, ground station capacity, power levels, and battery availability to determine an appropriate vehicle route. [0103-104] The package routing 430 module can decide on an appropriate route or path for a package. It can also ensure that the delivery system operates within its capacity. the package routing module 430 can take into account a number of factors, such as, for example, the number of UAVs, their position, the capacity of particular UAVs, ground station status, ground station capacity, maximum ground station package size, energy, cost, battery availability, battery charge state, whether a route is in use, whether the system has grounded a route, distance, route capacity, package size, as well as avoiding areas of the delivery network that may be damages or unusable for weather or other reasons. [risk] the package routing logic can take into account factors such as weather, time of day, or other factors that may not be as relevant to Internet packet routing logic.)
Raptopoulos further teaches transmit the flight plan to at least one of the plurality of uncrewed vehicles to deploy the uncrewed vehicle to execute a task. (see at least: [0015] the software modules further comprise a weather monitoring module configured to determine appropriate flying conditions between the first and second ground station and communicate with the route authorization module to authorize the flight when the conditions are appropriate [0124] The logistics system and network can then determine a UAV suitable for the mission and plan a flight path. The selected UAV can execute the flight plan, either delivering a package to the location without a ground station or flying to the location to pick up a package. [0114])
As per claim 3, Raptopoulos in view of Gentry teaches claim 1 as above. Raptopoulos further teach:
wherein the processor is further configured via a scheduling module, task input and flight plan (see at least: [0069] Such a mobile application can also allow the user to schedule a package drop off or locate a suitable ground station, for example, through identification of a current location or a desired location. [0015] determine appropriate flying conditions between the first and second ground station and communicate with the route authorization module to authorize the flight when the conditions are appropriate.)
Raptopoulos does not explicitly teach assigning a priority factor to each task input, wherein the priority factor comprises at least one of a deadline for task completion and a task type, and wherein the flight plan is determined based on the priority factor. However, this is taught by Gentry (see at least: Fig.7, Col lines A UAV 102 may further negotiate the priority of individual UAV missions at 610. For example, a UAV may assign a priority score to individual missions associated with a UAV 102 as well as individual missions associated with UAVs throughout the mesh network. Priority scores may be included in mesh data distributed throughout the network. The priority score may factor in the mission urgency based on mission variables such as a “track-and-report” assignment (as discussed in detail with respect to FIG. 7) [ task type]. Furthermore, a UAV may be assigned a higher mission urgency where the UAV's operational capabilities (trajectory change, speed range, altitude range, etc.) do not facilitate rapid trajectory changes necessary to effectuate a required flight plan change. Mission urgency may also factor in fuel loads of individual UAVs, distance to a recharging station, the availability of replacement UAVs within the mesh network to carry on a failed mission, etc. Conflicts that cannot be resolved between individual UAVs may resort to a default hierarchy rating based on date of manufacture, flight certificate issue date, or some similar comparable parameter that is external to the current mission variables.)
It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to combine the priority factor feature for the same reasons its useful in Gentry -namely, to determine an optimized flight plan that minimizes or eliminates the likelihood of interaction. Moreover, this is merely a combination of old elements in the art. In the combination, no element would serve a purpose other than it already did independently, and one skilled in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
As per claim 4, Raptopoulos in view of Gentry teaches claim 1 as above. Raptopoulos further teach:
wherein the processor is further configured to transmit data to a user via the user interface module, the data comprising at least one of the flight plan, a vehicle location, a task progress, a vehicle telemetry feed, a video feed, an audio feed, and a multispectral sensor measurement. (See at least: [0069] The ground station and/or logistics system can also provide a remote interface for user interaction with the system. For example, a user can interact with a website or application on a mobile device that communicates with the ground station and/or logistics system. The website or application can provide information about the system to the user or accept input from the user. For example, the website or application can provide status information. The system can also provide for the control and/or monitoring of the entire system or components thereof through a website or application. In an embodiment, a mobile application provides for the interaction of a user with the ground station or logistics system to obtain tracking information about a package. Such a mobile application can also allow the user to schedule a package drop off or locate a suitable ground station, for example, through identification of a current location or a desired location)
As per claim 5, Raptopoulos in view of Gentry teaches claim 1 as above. Raptopoulos further teach:
wherein the traffic input comprises a location of other vehicles and objects in the predetermined area. (See at least: [0064] the UAVs can be capable of detecting and avoiding stationary obstacles, such as, for example, trees, buildings, radio towers, and the like and also detecting and avoiding moving objects, such as, for example, birds, aircraft, and the like. A UAV can therefore adjust its flight path. a UAV detects a stationary object and reports the stationary object back to the delivery system. In an embodiment, a UAV flight path avoids a stationary object based on information received from the delivery system. [0094] The UAVs can periodically, for example, every n seconds, send position and other state information to the ground station and/or logistics system and network [0095] the logistics system and network coordinates traffic by providing new waypoints to a UAV during a mission that are known to be collision free.)
Raptopoulos does not explicitly teach a location of other vehicles, However, this is taught by Gentry (see at least: Col. 3 Lines 30-38 triangulate the location of an unverified object. For example, three UAVs operating within a common airspace or two UAVs and an air traffic control tower Col.4 Lines 1-20, A UAV may interrogate its physical surroundings to detect other objects operating within a common airspace. Additionally, a UAV may send local mesh data to a central mesh data source and receive central mesh data from the central source. Upon detection of one or more UAVs within the common airspace, a UAV may request identification from the one or more other unverified UAVs. Upon receipt of an identifying certificate, a UAV may verify the authenticity of the certificate using digital decryption methods and comparison of physical characteristics and operating characteristics of the individual UAV with data provided by in the identifying certificate. A UAV may then update its own local mesh with collected data associated with the individual UAV such as physical features, flight characteristics, current location, flight plan(s), digital certificates, and/or an associated timestamp with each piece of data within the mesh. If necessary, a UAV may update its flight plan or flight mode as a result of the detected and/or received data.)
It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to combine the location of other vehicles feature for the same reasons its useful in Gentry -namely, UAV may update its flight plan or flight mode as a result of the detected and/or received data. Moreover, this is merely a combination of old elements in the art. In the combination, no element would serve purpose other than it already did independently, and one skilled in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
As per claim 6, Raptopoulos in view of Gentry teaches claim 1 as above. Raptopoulos further teach:
wherein the risk input comprises at least one of air risk issues, ground risk issues, and health, integrity and performance data associated with each of the plurality of uncrewed vehicles. (See at least: [0091] the logistics system and network decides whether to ground a segment or area of the delivery system based on risk factors. The risk factors can include, for example, weather, information from authorities, the presence of emergency vehicles or personnel, time of day, or other suitable risk factors.[0090] if telemetry data suggests that a UAV has a defective motor that is likely to cause a crash, a “land” command is sent to the ground station closest to that vehicle and from the ground station to the vehicle.[0015] the software modules further comprise a weather monitoring module configured to determine appropriate flying conditions between the first and second ground station and communicate with the route authorization module to authorize the flight when the conditions are appropriate[0103])
As per claim 7, Raptopoulos in view of Gentry teaches claim 6 as above. Raptopoulos further teach:
wherein the air risk issues comprise at least one of suitable communications, global navigation satellite system performance, weather, surveillance availability, traffic density, and airspace restrictions. (See at least: [0091] the logistics system and network decides whether to ground a segment or area of the delivery system based on risk factors. The risk factors can include, for example, weather, information from authorities, the presence of emergency vehicles or personnel, time of day, or other suitable risk factors.[0103] To ensure that the system is operating with capacity, the package routing module 430 can take into account a number of factors, such as, for example, the number of UAVs, their position, the capacity of particular UAVs, ground station status, ground station capacity, maximum ground station package size, energy, cost, battery availability, battery charge state, whether a route is in use, whether the system has grounded a route, distance, route capacity, package size, as well as avoiding areas of the delivery network that may be damages or unusable for weather or other reasons.)
As per claim 8, Raptopoulos in view of Gentry teaches claim 6 as above. Raptopoulos further teach:
The ground risk issues comprise at least one of population density, restricted areas, battery reserves, a vehicle size and a vehicle weight. (See at least: [0091] the logistics system and network decides whether to ground a segment or area of the delivery system based on risk factors. The risk factors can include, for example, weather, information from authorities, the presence of emergency vehicles or personnel, time of day, or other suitable risk factors [0106] authorities can provide instructions to the delivery system that a particular route or group of routes should not be authorized [restricted areas]).
As per claim 9, Raptopoulos in view of Gentry teaches claim 1 as above. Raptopoulos further teach:
wherein the processor is further configured to: continuously receive at least one of the task input, the capacity input, the traffic input, and the risk input; ( see at least: [0094] The UAVs can periodically, for example, every n seconds, send position and other state information to the ground station and/or logistics system and network. The state information can include, for example, battery level, weather conditions, vehicle condition, information repeated from a ground station, or other suitable state information.)
automatically assess if the flight plan needs to be reconfigured based on the received input; automatically determine a new flight plan based on the received input; ( see at least: [0064] the UAVs can be capable of detecting and avoiding stationary obstacles, such as, for example, trees, buildings, radio towers, and the like and also detecting and avoiding moving objects, such as, for example, birds, aircraft, and the like. A UAV can therefore adjust its flight path [0088] the ground stations and delivery system can adjust the UAV mission based on real-time detected weather conditions.)
and transmit the new flight plan to the uncrewed vehicle. (see at least: [066] If such a change occurs, the ground station can communicate the change to the UAV to adjust the flight plan. In an embodiment, the ground station provides route information to a UAV.)
As per claim 10, Raptopoulos in view of Gentry teaches claim 1 as above. Raptopoulos further teach:
wherein the plurality of uncrewed vehicles are selected from a small uncrewed aircraft system, an electric vertical take-off and landing aircraft system, an urban air mobility vehicle, a drone, and an air ambulance vehicle. (see at least [0032] autonomous electric flying vehicles [0040] VTOL)
As per claim 12, Raptopoulos teaches:
A computer program product comprising a non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code, when executed by at least one processing device comprising a processor coupled to a memory, causes the at least one processing device to: (see at least: Fig. 4 [0014] a computer system manages a delivery system of unmanned aerial vehicles comprising one or more hardware processors in communication with a computer readable medium storing software modules [0137])
receive via a user interface module a task input comprising at least one of a timeline, a location, and a payload; (see at least: [0069] mobile application provides for the interaction of a user with the ground station or logistics system to obtain tracking information about a package. Such a mobile application can also allow the user to schedule a package drop off or locate a suitable ground station, for example, through identification of a current location or a desired location.[0036])
Raptopoulos teaches determine a flight plan based on at least the task input ( See at least: [0096] [0103])
Raptopoulos does not explicitly teach receiving a task prioritization input based on at least one of a task timeline, a resource availability and a user-defined parameter. determine a flight plan based on at least the task prioritization input However, this is taught by Gentry (see at least: Col. 13 Lines 47-63, A UAV 102 may further negotiate the priority of individual UAV missions at 610. For example, a UAV may assign a priority score to individual missions associated with a UAV 102 as well as individual missions associated with UAVs throughout the mesh network. Priority scores may be included in mesh data distributed throughout the network. The priority score may factor in the mission urgency based on mission variables such as a “track-and-report” assignment (as discussed in detail with respect to FIG. 7) Furthermore, a UAV may be assigned a higher mission urgency where the UAV's operational capabilities (trajectory change, speed range, altitude range, etc.) do not facilitate rapid trajectory changes necessary to effectuate a required flight plan change. Mission urgency may also factor in fuel loads of individual UAVs, distance to a recharging station, the availability of replacement UAVs within the mesh network to carry on a failed mission, etc. [resource availability])
It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to combine the task prioritization feature for the same reasons its useful in Gentry -namely, to determine an optimized flight plan. Moreover, this is merely a combination of old elements in the art. In the combination, no element would serve a purpose other than it already did independently, and one skilled in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
Raptopoulos further teaches receive via a resource capacity management module a capacity input comprising at least one of a location, a payload and an operational condition for each of a plurality of uncrewed vehicles; see at least: [0067] The ground station and the logistics system can communicate to exchange data such as remaining capacity, package information, battery status, time, weather, route information, or the like.[0110] [0096-97] The vehicle tracking 424 communicates with one or more UAVs or ground stations to determine information about the UAVs. For example, the UAVs can report their current location and status. The vehicle tracking module 424 can keep track of the UAVs and allow the delivery system 400 to perform higher level functions, such as, for example, load distribution, coordinated deliveries, and other higher level functions)
Raptopoulos further teaches receive via a traffic management module a traffic input n (see at least: [0095] the logistics system and network coordinates traffic by providing new waypoints to a UAV during a mission that are known to be collision free.)
Raptopoulos does not explicitly teach input comprising at least one of a location and a flight plan for each of the plurality of uncrewed vehicles in a predetermined area. However, this is taught by Gentry (see at least: Col.8 Lines 26-62, The data analysis module 208 may compare the preregistered flight plans, the current operating characteristics of nearby UAVs, and the UAV's 102 own flight plan to determine a likelihood of interaction. the dynamic flight plan optimization module 210 may consider additional factors, such as fuel capacity, an urgency factor associated with the UAV 102 or flight plans associated with individual ones of the nearby UAVs, relative location of one or more nearby UAVs, external factors (e.g., weather, air traffic congestion, etc.), and/or availability of one or more inactive UAVs within a predetermined distance threshold. The dynamic flight plan optimization module 210 may evaluate one or more flight plans that are alternatives to the current flight plan and iterate the evaluation to determine an optimized flight plan with respect to total flight time, total fuel consumption, impact to the flight plans of one or more other UAVs within the airspace 100, and/or a likelihood of interaction with one or more nearby UAVs. Col.4 Lines 51-61, A UAV may be required to participate in automated flight plan management with one or more UAVs operating within a common airspace. For instance, a UAV may detect one or more nearby UAVs operating within the common airspace. The UAV may determine the proximity of individual nearby UAVs and receive flight plan data from the one or more nearby UAVs. The UAV may compare its own flight plan with the flight plan of individual nearby UAVs and confidence values associated with the flight plans to iteratively negotiate updated flight plans for the individual UAVs)
It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to combine the flight plans of vehicles in a predetermined area feature for the same reasons its useful in Gentry -namely, to minimize interaction with one or more nearby UAVs in the common airspace. Moreover, this is merely a combination of old elements in the art. In the combination, no element would serve a purpose other than it already did independently, and one skilled in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
Raptopoulos further teaches receive via a risk management module a risk input; (see at least: [0091] the logistics system and network decides whether to ground a segment or area of the delivery system based on risk factors. The risk factors can include, for example, weather, information from authorities, the presence of emergency vehicles or personnel, time of day, or other suitable risk factors [0100-102] The ability to monitor and predict weather 428 allows the delivery system to optimally fly the UAVs to avoid adverse weather conditions, for example)
Raptopoulos does not explicitly teach determine if the risk input passes a predetermined risk threshold. However, this is taught by Gentry (see at least: Col.8 Lines 26-62, The data analysis module 208 may compare the preregistered flight plans, the current operating characteristics of nearby UAVs, and the UAV's 102 own flight plan to determine a likelihood of interaction. Where the likelihood of interaction exceeds a maximum threshold, the dynamic flight plan optimization module 210 may determine an optimized flight plan that minimizes or eliminates the likelihood of interaction [risk] The UAV 102 may then execute the updated flight plan. the dynamic flight plan optimization module 210 may consider additional factors, such as fuel capacity, an urgency factor associated with the UAV 102 or flight plans associated with individual ones of the nearby UAVs, relative location of one or more nearby UAVs, external factors (e.g., weather, air traffic congestion, etc.), and/or availability of one or more inactive UAVs within a predetermined distance threshold. The dynamic flight plan optimization module 210 may evaluate one or more flight plans that are alternatives to the current flight plan and iterate the evaluation to determine an optimized flight plan with respect to total flight time, total fuel consumption, impact to the flight plans of one or more other UAVs within the airspace 100, and/or a likelihood of interaction with one or more nearby UAVs.)
It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to combine the predetermined risk threshold feature for the same reasons its useful in Gentry -namely, to determine an optimized flight plan that minimizes or eliminates the likelihood of interaction. Moreover, this is merely a combination of old elements in the art. In the combination, no element would serve a purpose other than it already did independently, and one skilled in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
Raptopoulos further teaches automatically determine a flight plan based on at least one of the task input, the capacity input, the traffic input, and the risk input; (see at least: [0096] The vehicle routing module 420 can include a routing algorithm. The routing algorithm can calculate the best route for moving a UAV from point to point. The routing algorithm can take into consideration factors such as, the distance, UAV capacity, ground station capacity, power levels, and battery availability to determine an appropriate vehicle route. [0103-104] The package routing 430 module can decide on an appropriate route or path for a package. It can also ensure that the delivery system operates within its capacity. the package routing module 430 can take into account a number of factors, such as, for example, the number of UAVs, their position, the capacity of particular UAVs, ground station status, ground station capacity, maximum ground station package size, energy, cost, battery availability, battery charge state, whether a route is in use, whether the system has grounded a route, distance, route capacity, package size, as well as avoiding areas of the delivery network that may be damages or unusable for weather or other reasons. [risk] the package routing logic can take into account factors such as weather, time of day, or other factors that may not be as relevant to Internet packet routing logic.)
and transmit the flight plan to at least one of the plurality of uncrewed vehicles to deploy the uncrewed vehicle to execute a task. (see at least: [0015] the software modules further comprise a weather monitoring module configured to determine appropriate flying conditions between the first and second ground station and communicate with the route authorization module to authorize the flight when the conditions are appropriate [0124] The logistics system and network can then determine a UAV suitable for the mission and plan a flight path. The selected UAV can execute the flight plan, either delivering a package to the location without a ground station or flying to the location to pick up a package. [0114])
As per claim 13, Raptopoulos teaches:
A method for automating and optimizing aerial operations using a taskable aerial network (see at least: Fig.1 Abstract, [0007] the systems include the following components: autonomous electric flying vehicles, automated ground stations, and logistics software that operates the system [0008])
comprising the steps of receiving a task input comprising at least one of a timeline, a location, and a payload; (see at least: [0069] mobile application provides for the interaction of a user with the ground station or logistics system to obtain tracking information about a package. Such a mobile application can also allow the user to schedule a package drop off or locate a suitable ground station, for example, through identification of a current location or a desired location.)
receiving a capacity input comprising at least one of a location, a payload and an operational condition for each of a plurality of uncrewed vehicles; ( see at least: [0067] The ground station and the logistics system can communicate to exchange data such as remaining capacity, package information, battery status, time, weather, route information, or the like.[0110] [0096-97] The vehicle tracking 424 communicates with one or more UAVs or ground stations to determine information about the UAVs. For example, the UAVs can report their current location and status. The vehicle tracking module 424 can keep track of the UAVs and allow the delivery system 400 to perform higher level functions, such as, for example, load distribution, coordinated deliveries, and other higher level functions)
receiving a traffic input (see at least: [0095] the logistics system and network coordinates traffic by providing new waypoints to a UAV during a mission that are known to be collision free.)
Raptopoulos does not explicitly teach input comprising at least one of a location and a flight plan for each of the plurality of uncrewed vehicles in a predetermined area. However, this is taught by Gentry (see at least: Col.8 Lines 26-62, The data analysis module 208 may compare the preregistered flight plans, the current operating characteristics of nearby UAVs, and the UAV's 102 own flight plan to determine a likelihood of interaction. the dynamic flight plan optimization module 210 may consider additional factors, such as fuel capacity, an urgency factor associated with the UAV 102 or flight plans associated with individual ones of the nearby UAVs, relative location of one or more nearby UAVs, external factors (e.g., weather, air traffic congestion, etc.), and/or availability of one or more inactive UAVs within a predetermined distance threshold. The dynamic flight plan optimization module 210 may evaluate one or more flight plans that are alternatives to the current flight plan and iterate the evaluation to determine an optimized flight plan with respect to total flight time, total fuel consumption, impact to the flight plans of one or more other UAVs within the airspace 100, and/or a likelihood of interaction with one or more nearby UAVs. Col.4 Lines 51-61, A UAV may be required to participate in automated flight plan management with one or more UAVs operating within a common airspace. For instance, a UAV may detect one or more nearby UAVs operating within the common airspace. The UAV may determine the proximity of individual nearby UAVs and receive flight plan data from the one or more nearby UAVs. The UAV may compare its own flight plan with the flight plan of individual nearby UAVs and confidence values associated with the flight plans to iteratively negotiate updated flight plans for the individual UAVs)
It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to combine the flight plans of vehicles in a predetermined area feature for the same reasons its useful in Gentry -namely, to minimize interaction with one or more nearby UAVs in the common airspace. Moreover, this is merely a combination of old elements in the art. In the combination, no element would serve a purpose other than it already did independently, and one skilled in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
While Raptopoulos teaches receiving a risk input (see at least: [0091] the logistics system and network decides whether to ground a segment or area of the delivery system based on risk factors. The risk factors can include, for example, weather, information from authorities, the presence of emergency vehicles or personnel, time of day, or other suitable risk factors [0100-102] The ability to monitor and predict weather 428 allows the delivery system to optimally fly the UAVs to avoid adverse weather conditions, for example) Raptopoulos does not explicitly teach determining if the risk input passes a predetermined risk threshold. However, this is taught by Gentry (see at least: Col.8 Lines 26-62, The data analysis module 208 may compare the preregistered flight plans, the current operating characteristics of nearby UAVs, and the UAV's 102 own flight plan to determine a likelihood of interaction. Where the likelihood of interaction exceeds a maximum threshold, the dynamic flight plan optimization module 210 may determine an optimized flight plan that minimizes or eliminates the likelihood of interaction [risk] . The UAV 102 may then execute the updated flight plan. the dynamic flight plan optimization module 210 may consider additional factors, such as fuel capacity, an urgency factor associated with the UAV 102 or flight plans associated with individual ones of the nearby UAVs, relative location of one or more nearby UAVs, external factors (e.g., weather, air traffic congestion, etc.), and/or availability of one or more inactive UAVs within a predetermined distance threshold. The dynamic flight plan optimization module 210 may evaluate one or more flight plans that are alternatives to the current flight plan and iterate the evaluation to determine an optimized flight plan with respect to total flight time, total fuel consumption, impact to the flight plans of one or more other UAVs within the airspace 100, and/or a likelihood of interaction with one or more nearby UAVs.)
It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to combine the predetermined risk threshold feature for the same reasons its useful in Gentry -namely, to determine an optimized flight plan that minimizes or eliminates the likelihood of interaction. Moreover, this is merely a combination of old elements in the art. In the combination, no element would serve a purpose other than it already did independently, and one skilled in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
Raptopoulos further teaches determining a flight plan based on at least one of the task input, the capacity input, the traffic input, and the risk input (see at least: [0096] The vehicle routing module 420 can include a routing algorithm. The routing algorithm can calculate the best route for moving a UAV from point to point. The routing algorithm can take into consideration factors such as, the distance, UAV capacity, ground station capacity, power levels, and battery availability to determine an appropriate vehicle route. [0103-104] The package routing 430 module can decide on an appropriate route or path for a package. It can also ensure that the delivery system operates within its capacity. the package routing module 430 can take into account a number of factors, such as, for example, the number of UAVs, their position, the capacity of particular UAVs, ground station status, ground station capacity, maximum ground station package size, energy, cost, battery availability, battery charge state, whether a route is in use, whether the system has grounded a route, distance, route capacity, package size, as well as avoiding areas of the delivery network that may be damages or unusable for weather or other reasons. [risk] the package routing logic can take into account factors such as weather, time of day, or other factors that may not be as relevant to Internet packet routing logic.)
Raptopoulos further teaches transmitting the flight plan to at least one of the plurality of uncrewed vehicles to deploy the uncrewed vehicle to execute a task; see at least: [0015] the software modules further comprise a weather monitoring module configured to determine appropriate flying conditions between the first and second ground station and communicate with the route authorization module to authorize the flight when the conditions are appropriate [0124] The logistics system and network can then determine a UAV suitable for the mission and plan a flight path. The selected UAV can execute the flight plan, either delivering a package to the location without a ground station or flying to the location to pick up a package. [0114])
Raptopoulos further teaches the steps are performed by at least one processing device comprising a processor operatively coupled to a memory. (see at least: [0134] [0137])
As per claim 15, Raptopoulos in view of Gentry teaches claim 13 as above. Raptopoulos further teach:
receiving, by the processor, at least one of a task timeline, a resource availability and a user-defined parameter; determining the flight plan based on the task input (see at least: [0096] The vehicle routing module 420 can include a routing algorithm. The routing algorithm can calculate the best route for moving a UAV from point to point. The routing algorithm can take into consideration factors such as, the distance, UAV capacity, ground station capacity, power levels, and battery availability to determine an appropriate vehicle route. [0103-104] The package routing 430 module can decide on an appropriate route or path for a package. It can also ensure that the delivery system operates within its capacity. the package routing module 430 can take into account a number of factors, such as, for example, the number of UAVs, their position, the capacity of particular UAVs, ground station status, ground station capacity, maximum ground station package size, energy, cost, battery availability, battery charge state, whether a route is in use, whether the system has grounded a route, distance, route capacity, package size, as well as avoiding areas of the delivery network that may be damages or unusable for weather or other reasons. [risk] the package routing logic can take into account factors such as weather, time of day, or other factors that may not be as relevant to Internet packet routing logic.)
Raptopoulos does not explicitly teach determining a task prioritization input based on the at least one of the task timeline, the resource availability and the user-defined parameter; and determining the flight plan based on the task prioritization input. However, this is taught by Gentry (see at least: Col. Lines, A UAV 102 may further negotiate the priority of individual UAV missions at 610. For example, a UAV may assign a priority score to individual missions associated with a UAV 102 as well as individual missions associated with UAVs throughout the mesh network. Priority scores may be included in mesh data distributed throughout the network. The priority score may factor in the mission urgency based on mission variables such as a “track-and-report” assignment (as discussed in detail with respect to FIG. 7) Furthermore, a UAV may be assigned a higher mission urgency where the UAV's operational capabilities (trajectory change, speed range, altitude range, etc.) do not facilitate rapid trajectory changes necessary to effectuate a required flight plan change. Mission urgency may also factor in fuel loads of individual UAVs, distance to a recharging station, the availability of replacement UAVs within the mesh network to carry on a failed mission, etc. [resource availability])
It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to combine the task prioritization feature for the same reasons its useful in Gentry -namely, to determine an optimized flight plan. Moreover, this is merely a combination of old elements in the art. In the combination, no element would serve a purpose other than it already did independently, and one skilled in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
As per claim 16, Raptopoulos in view of Gentry teaches claim 15 as above. Raptopoulos further teach:
allocating an uncrewed vehicle based on the task input, the capacity input (see at least: [0069] mobile application provides for the interaction of a user with the ground station or logistics system to obtain tracking information about a package. Such a mobile application can also allow the user to schedule a package drop off or locate a suitable ground station, for example, through identification of a current location or a desired location. [0067] The ground station and the logistics system can communicate to exchange data such as remaining capacity, package information, battery status, time, weather, route information, or the like. [0036])
Raptopoulos does not explicitly teach allocating an uncrewed vehicle based the task prioritization input. However, this is taught by Gentry (see at least: Col. 13 Lines 47-63, A UAV 102 may further negotiate the priority of individual UAV missions at 610. For example, a UAV may assign a priority score to individual missions associated with a UAV 102 as well as individual missions associated with UAVs throughout the mesh network. Priority scores may be included in mesh data distributed throughout the network. The priority score may factor in the mission urgency based on mission variables such as a “track-and-report” assignment (as discussed in detail with respect to FIG. 7) Furthermore, a UAV may be assigned a higher mission urgency where the UAV's operational capabilities (trajectory change, speed range, altitude range, etc.) do not facilitate rapid trajectory changes necessary to effectuate a required flight plan change. Mission urgency may also factor in fuel loads of individual UAVs, distance to a recharging station, the availability of replacement UAVs within the mesh network to carry on a failed mission, etc. [resource availability])
It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to combine the task prioritization feature for the same reasons its useful in Gentry -namely, to determine an optimized flight plan. Moreover, this is merely a combination of old elements in the art. In the combination, no element would serve a purpose other than it already did independently, and one skilled in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
As per claim 17, Raptopoulos in view of Gentry teaches claim 13 as above. Raptopoulos further teach:
continuously receiving, by the processor, at least one of the task input, the capacity input, the traffic input, and the risk input; (see at least; [0094] The UAVs can periodically, for example, every n seconds, send position and other state information to the ground station and/or logistics system and network. The state information can include, for example, battery level, weather conditions, vehicle condition, information repeated from a ground station, or other suitable state information. [0043] The UAVs can receive and transmit signals providing real-time state characterization, such as, for example, location, velocity, destination, time, package status, weather conditions, UAV system status, energy system state, energy system needs status, system load, or other real-time or near real time state characterizations.)
automatically assessing, by the processor, if the flight plan needs to be reconfigured based on the received input; automatically determining, by the processor, a new flight plan based on the received input; (see at least: [0088]
The ground stations can detect weather conditions and permit the delivery system to adjust for weather conditions in real-time. The ground stations and delivery system can adjust the UAV mission based on real-time detected weather conditions. The ground stations can also collect data regarding conditions from external sources, such as, for example, other ground stations, UAVs, the internet, weather stations, or other suitable data sources Based on the weather monitoring, the delivery system can make decisions such as whether to ground portions or segments of the delivery system. [0066] For example, in flight, the environmental status of a flight path can change. If such a change occurs, the ground station can communicate the change to the UAV to adjust the flight plan [0095])
and transmitting, by the processor, the new flight plan to the uncrewed vehicle. ( see at least: [0066] For example, in flight, the environmental status of a flight path can change. If such a change occurs, the ground station can communicate the change to the UAV to adjust the flight plan. In an embodiment, the ground station provides route information to a UAV. [0095] the logistics system and network coordinates traffic by providing new waypoints to a UAV during a mission that are known to be collision free. )
As per claim 18, Raptopoulos in view of Gentry teaches claim 14 as above. Raptopoulos further teach:
transmitting, by the processor, data to a user, the data comprising at least one of the flight plan, an uncrewed vehicle location, a task progress, a vehicle telemetry feed, a video feed, an audio feed, and a multispectral sensor measurement. (see at least: [0069] a mobile application provides for the interaction of a user with the ground station or logistics system to obtain tracking information about a package.[0105] the package tracking module 434 can provide delivery exceptions, delivery completion notifications, package acceptance notification, or other suitable information for an end user [0121] User 690 can alternatively receive updates from the system throughout the process, so that user 690 is kept up to date regarding the status of the delivery.)
Claim(s) 2 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Raptopoulos (US 20240038081) in view of Gentry (US9858822B1) in further view of Evans (US20190158597)
As per claim 2, Raptopoulos in view of Gentry teaches claim 1 as above. Raptopoulos further teach:
payload data collected by at least one of the plurality of uncrewed vehicles ( see at least: [0066] the UAV and ground station can communicate to exchange data such as location, telemetry data, health monitoring, status, package information, energy output, remaining capacity, time, weather, route status, obstructions, or the like [0088] ground stations can also collect data regarding conditions from external sources, such as, for example, other ground stations, UAVs, the internet, weather stations, or other suitable data sources.)
Raptopoulos does not explicitly teach the processor is further configured via a secure data management module to segregate payload data and to transmit the payload data only to an end user of the system. However, this is taught by Evans (see at least: [0018] using a requestor identifier that identifies the requesting entity, the flight data management device can determine which pieces of the flight data are accessible to the requesting device. [0011] UAV flight data can be stored by the flight data management device in a manner designed to control access to the flight data by different entities. For example, a UAV user, or UAV pilot, might have access to all of the flight data, a law enforcement officer might have access to a first subset of the flight data, and a civilian might have access to a second subset of the flight data [0064] flight data management device 230 can determine a subset of flight data the organization has permission to access (e.g., using an access control list and an identifier of the organization) and obtain the subset of flight data (e.g., from a database) using permissions and the window of time to limit flight data determined to be response data.[0066] providing a notification to the requesting device 250 that provided the flight data request [0059]).
It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to combine the secure data feature for the same reasons its useful in Evans -namely, to determine which portions of flight data the entity can access (par.59). In the combination, no element would serve a purpose other than it already did independently, and one skilled in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
As per claim 14, Raptopoulos in view of Gentry teaches claim 13 as above. Raptopoulos further teach:
receiving, by the processor, data collected by one of the plurality of uncrewed vehicles in response to the task input; (see at least: [0066] the UAV and ground station can communicate to exchange data such as location, telemetry data, health monitoring, status, package information, energy output, remaining capacity, time, weather, route status, obstructions, or the like [0088] ground stations can also collect data regarding conditions from external sources, such as, for example, other ground stations, UAVs, the internet, weather stations, or other suitable data sources.)
Raptopoulos does not explicitly teach segregating the data from data collected data collected by other uncrewed vehicles and transmitting the data to a user that transmitted the task input. However, this is taught by Evans (see at least: [0018] using a requestor identifier that identifies the requesting entity, the flight data management device can determine which pieces of the flight data are accessible to the requesting device. [0011] UAV flight data can be stored by the flight data management device in a manner designed to control access to the flight data by different entities. [0063] flight data can be stored in a database using a table for a UAV, rows for UAV flights of the UAV, and a column for each piece of flight data. In this example, flight data management device 230 can store data indicating which tables, rows, and/or columns an entity or role can access. Based on an entity identifier or role associated with a flight data request, flight data management device 230 can determine access based on the entity and obtain the corresponding flight data from the database, identifying or storing the corresponding flight data as response data. [0064] flight data management device 230 can determine a subset of flight data the organization has permission to access (e.g., using an access control list and an identifier of the organization) and obtain the subset of flight data (e.g., from a database) using permissions and the window of time to limit flight data determined to be response data[0066] providing a notification to the requesting device 250 that provided the flight data request.[0077-78]).
It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to combine the segregating data feature for the same reasons its useful in Evans -namely, to determine which portions of flight data the entity can access (par.59). In the combination, no element would serve a purpose other than it already did independently, and one skilled in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Raptopoulos (US 20240038081) in view of Gentry (US9858822B1) in further view of Burks (US 20180327091)
As per claim 11, Raptopoulos in view of Gentry teaches claim 1 as above. Raptopoulos further teach:
drone control subsystem (see at least: [0041] The UAVs can have electronic control systems and sensors. The control systems and sensors can help stabilize the UAV in certain embodiments).
Raptopoulos does not explicitly teach a beyond visual line of sight drone control subsystem. However, this is taught by Burks (See at least: [0040] a drone's flight can be a Beyond Visual Line of Sight (BVLOS) flight path. In a BVLOS flight path, a drone can be flown without the land-based drone operator/pilot having to keep the drone in visual line of sight at all times. This can provide better and earlier situational awareness relating to an incident so that a first responder can take informed decisions in addressing the emergency. For example, using BVLOS, first responders are provided with a live video of the scene of an incident scene prior to first responders arriving at the scene of the incident. In some embodiments, a BVLOS flight path is based on data gathered from various sources to identify and avoid obstructions on the flight path, such as airplanes or other drones)
It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to combine the Beyond Visual Line of Sigh feature for the same reasons its useful in Burks -namely, to provide better and earlier situational awareness relating to an incident so that a first responder can take informed decisions in addressing the emergency (par.40). In the combination, no element would serve a purpose other than it already did independently, and one skilled in the art would have recognized that the combination could have been implemented through routine engineering producing predictable results.
Conclusion
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/MANAL A. ALSAMIRI/Examiner, Art Unit 3628
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