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
Claims 1, 10 and 16 are amended.
Claims 3-7, 9, 12-15 and 18-20 were previously cancelled.
Claims 1-2, 8, 10-11, 16-17, 21 and 22 are pending.
Response to Arguments/Remarks
Claim Rejections under 35 USC 103
Applicant argues: “Applicant respectfully asserts that the cited references fail to render obvious the present claims.”
Examiner respectfully disagrees and would like to point out that; 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.
Examiner believes that obviousness rejection has been achieved in the 103 rejection below.
Applicant further argues:
Arksey as understood fails to disclose "determining a target workpiece and a storage location thereof in response to an assistance message obtained by a first terminal located at a construction location, wherein the assistance message is used to indicate the target workpiece absent in a maintenance operation, and the construction location is located within a factory" and "in a case where the task type is a complex type, obtaining a historical path of the first terminal carried by a maintenance personnel into the construction location, wherein the case where the task type is the complex type comprises that the environmental information indicates that the construction location is in an area with densely distributed devices, the first terminal comprises a companion drone following the maintenance personnel, and the historical path of the first terminal comprises a historical flight path of the companion drone," let alone the other limitations in the above distinguishing technical features, and thus Arksey fails to disclose the above distinguishing technical features.
Examiner respectfully disagrees, the claims in the instant application are interpreted in the Broadest Reasonable Interpretation. Examiner has added new ART to overcome the remarks and the amendments (see 35 USC 103 below for clarification).
Note that under a broadest reasonable interpretation (BRI), words of the claim must be given their plain meaning, unless such meaning is inconsistent with the specification. The plain meaning of a term means the ordinary and customary meaning given to the term by those of ordinary skill in the art at the relevant time. The ordinary and customary meaning of a term may be evidenced by a variety of sources, including the words of the claims themselves, the specification, drawings, and prior art. However, the best source for determining the meaning of a claim term is the specification - the greatest clarity is obtained when the specification serves as a glossary for the claim terms. The words of the claim must be given their plain meaning unless the plain meaning is inconsistent with the specification. 2111.01 (I). See also In re Marosi, 710 F.2d 799, 802, 218 USPQ 289, 292 (Fed. Cir. 1983) ("'[C]laims are not to be read in a vacuum, and limitations therein are to be interpreted in light of the specification in giving them their ‘broadest reasonable interpretation.'"2111.01 (II)
With respect to the interpretation of claim terms, MPEP 2111 states:
The Patent and Trademark Office ("PTO") determines the scope of claims in patent applications not solely on the basis of the claim language, but upon giving claims their broadest reasonable construction "in light of the specification as it would be interpreted by one of ordinary skill in the art." In re Am. Acad. of Sci. Tech. Ctr., 367 F.3d 1359, 1364[, 70 USPQ2d 1827, 1830] (Fed. Cir. 2004). Indeed, the rules of the PTO require that application claims must "conform to the invention as set forth in the remainder of the specification and the terms and phrases used in the claims must find clear support or antecedent basis in the description so that the meaning of the terms in the claims may be ascertainable by reference to the description." 37 CFR 1.75(d)(1).
The words of the claim must be given their plain meaning unless the plain meaning is inconsistent with the specification In re Zletz, 893 F.2d 319, 13 USPQ2d 1320 (Fed. Cir. 1989).
"Though understanding the claim language may be aided by explanations contained in the written description, it is important not to import into a claim limitations that are not part of the claim. For example, a particular embodiment appearing in the written description may not be read into a claim when the claim language is broader than the embodiment." Superguide Corp. v. DirecTV Enterprises, Inc., 358 F.3d 870, 875, 69 USPQ2d 1865, 1868 (Fed. Cir. 2004).(see MPEP 2111.01).
During patent examination, the pending claims must be "given their broadest reasonable interpretation consistent with the specification." The broadest reasonable interpretation does not mean the broadest possible interpretation. Rather, the meaning given to a claim term must be consistent with the ordinary and customary meaning of the term (unless the term has been given a special definition in the specification), and must be consistent with the use of the claim term in the specification and drawings. Further, the broadest reasonable interpretation of the claims must be consistent with the interpretation that those skilled in the art would reach. In re Cortright, 165 F.3d 1353, 1359, 49 USPQ2d 1464, 1468 (Fed. Cir. 1999) (see PMEP 2111).
Accordingly, the claims herein will be interpreted in accordance with the MPEP 2111.
Arksey in the abstract does a similar action as noted in the Abstract which indicates finding and mapping locations for a drone. A companion computer which can vary with the use as stated in ¶ 0125. With the new art the companion computer idea is shown in more detail.
Applicant further argues:
Mingtao as understood does not disclose receiving an assistance message from a companion drone that follows a maintenance personnel and is located at a construction location, nor does it disclose applying a drone in a construction location located in an area with densely distributed devices, or obtaining a flight route or path during the drone flight. Therefore, Mingtao fails to disclose "determining a target workpiece and a storage location thereof in response to an assistance message obtained by a first terminal located at a construction location, wherein the assistance message is used to indicate the target workpiece absent in a maintenance operation, and the construction location is located within a factory" and "in a case where the task type is a complex type, obtaining a historical path of the first terminal carried by a maintenance personnel into the construction location, wherein the case where the task type is the complex type comprises that the environmental information indicates that the construction location is in an area with densely distributed devices, the first terminal comprises a companion drone following the maintenance personnel, and the historical path of the first terminal comprises a historical flight path of the companion drone," let alone the other limitations in the above distinguishing technical features, and thus Mingtao fails to disclose the above distinguishing technical features.
Examiner respectfully disagrees. No where in the non-final action of 12/04/2025, does it claim that Mingtao teaches the features underlined above. Mingtao is supportive ART. See additional ART in the new 35 USC 103 below.
Examiner would appreciate an interview to further prosecution, after Applicant has had a chance to review this final. Thank you for your time and consideration on this matter.
Claim Objections
Claims 1, 10 and 16 are objected to because of the following informalities: Type is not clearly articulated in the claims, Suggest you take out type, such as “determining a task type according to the environmental information; in a case where the task type is a complex type, obtaining a historical path of the first terminal carried by a maintenance personnel into the construction location, wherein the case where the task type is the complex type comprises” would be stronger if it said something like “determining a specific task a complex situation comprises…”. Or “task is complex.” Appropriate correction is appreciated.
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) 1-2, 8, 10-11, 16-17, 21 and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Arksey et al. [US20220397917, now Arksey], with Mingtao et al. [CN108960695, now Mingtao], further with Zuckerman [US11565807, now Zuckerman].
Claim 1
Arksey discloses a control method for drone-assisted maintenance, comprising: determining a target workpiece and a storage location thereof in response to an assistance message obtained by a first terminal located at a construction location, wherein the assistance message is used to indicate the target workpiece absent in a maintenance operation, and the construction location is located within a factory [see at least Arksey, ¶ 0006, discloses updating drone technology to perform any task needed; 0024 (“Yet another application of a drone is delivery of items. Short and long range delivery may be performed via fixed wing drones.”); 0126 (“include the basic unit of work not being a single complex drone…Thus allowing “any of number of drones to fail and still have the dRAID capable of continuing its mission.” Further the drones have “a reconfigurable drone array considerably can further reduce the burden on planning, piloting, and processing systems.” And further, “each component may be an independent drone”); 0150 discloses (“employ an overall system that can significantly increase manageability, interoperability, programmability, and scalability, as well as improving privacy and security.”)];
determining environmental information for flight of a drone according to the construction location, wherein the environmental information indicates complexity of an environment or difficulty of the flight of the drone [see at least Arksey, ¶ 0027 (“conventional systems often work by having planning software predetermine a set of waypoints in 3D space, then when this mission is uploaded to the vehicle, it is the responsibility of the vehicle to safely navigate the received waypoint set without knowledge of the operational environment”); 0044 (“Conventional SLAM algorithms assume a single vehicle mapping the environment, but the systems and methods described herein can take advantage of a plurality of drones working together to build better models, significantly faster...”); 0042 discloses (“prior knowledge of the physical environment is needed, and a bespoke mission is planned accordingly.”)];
determining a task type according to the environmental information in a case where the task type is a complex type, obtaining a historical path of the first terminal carried by a maintenance personnel into the construction location, wherein the case where the task type is the complex type comprises that the environmental information indicates that the construction location is in an area with densely distributed devices, the first terminal comprises a companion drone, and the historical path of the first terminal comprises a historical flight path of the companion drone [see at least Arksey, ¶ 0044-0045 (“[0045] Particular embodiments disclosed herein may be implemented using one or more example processes...The methods may be performed, for example, by the system of FIG. 6 and FIG. 10...The intent may be received, for example, from a customer and/or system operator… and may use the inventory and parameters of the space, such as trees, and other obstacles, to determine a collection of drones for surveying the location.”); 0072 (“In the event that the desired end position cannot be achieved, the system may enter a “fault handling” condition and the drone returns to the base station, following a previously determined “safe” trajectory.”); 0153 (“Additionally, with every mission run there is an opportunity to improve the system by automatic learning from previous missions. Everything from RF models to path planning can have a continuous feedback loop between the actual execution in the physical world and the simulated world.”); ];
planning and generating a second path according to the construction location and the storage location [see at least Arksey, ¶ 0067 (“ machine learning techniques are used across a non-zero subset of possible trajectories by first defining an objective function, which can be the weighting of the time, signal strength and the battery used for a trip. While an initial set of trajectories may be less than optimal (but feasible), after survey data is received from the drones, the 3D model is updated which then drives updates to the trajectories as well. A primary constraint can be that each drone has limited battery life, so some paths can have high (e.g., essentially infinite) weights. A random collection for N drones to reach M positions can be chosen and the cost function can be calculated. The cost function can be a function of time and battery consumption (with paths that are infeasible marked out). Gradient descent can be used to find new optimal trajectories. This method can be thought of as an augmentation of simulated annealing but with different turns for 3D geometry. The weight of the different paths may be determined by the distance and altitude traveled, since vertical travel is more “expensive” for a drone to achieve.”)];
determining a complex area according to the construction location [see at least Arksey, ¶ 0088 (“With modern systems, an operator has to manage many complex tasks, from de-conflicting flights and monitoring battery status to stepping through a series of image processing steps and working with very different hardware in the drone, base station and cloud.”); 0116; 0150 (“Furthermore, from a large-scale fleet-wide view, for achieving Internet-scale, some embodiments described herein employ an overall system that can significantly increase manageability, interoperability, programmability, and scalability, as well as improving privacy and security... With respect to the interoperability, the system may allow any drone to be integrated into operations. For example, the technical solutions can be software for an existing fleet and the drone management software... As an example, a drone mission can be run against a 3D world model, instructions can be generated to simulate hives traversing that world, and then drones can be deployed in the simulation. Individual modules can be easily tested just by simulating the systems above and below. In addition, by using a declarative language, complex path planning can be handled at the lowest level, thereby considerably simplifying a programmer's workload. Some cases include the system being trained using real-world missions.”)];
determining a first trajectory point from which the complex area is entered, from the second path [see at least Arksey, ¶ 0043 (“Missions are defined as time optimal trajectories instead of static waypoints, allowing for trajectory optimization techniques to be used, optimizing flight time,”); 0051 (“Any type of line segment or set of points can define a flight path/trajectory.”); 0069 (“Particular embodiments disclosed herein may be implemented in relation to different example use cases. ..herein can be used to plan a mission for tunnel inspection—an initial 3D tunnel model can be used, and an initial trajectory set planned around, through and across the 3D tunnel model. The systems and methods may be used for planning indoor missions in GPS-denied areas.”)];
determining a second trajectory point closest to the first trajectory point from the historical path [see at least Arksey, ¶ 0072 (“…if a potential collision is detected (estimated), a new trajectory is calculated…”); 0153 (“with every mission run there is an opportunity to improve the system by automatic learning from previous missions.”); 0190 (“The cloud planning system may takes the current 3D models over time as a 4D model 10310. This may include previous data that is at a similar time and date as well as weather, wind, sun locations and other data.”)]:
Note: if determining a new trajectory that would be a second trajectory or third, etc.
merging a portion of the second path after the first trajectory point with a portion of the historical path after the second trajectory point, to obtain a merged path [see at least Arksey, ¶ 0072 (“ Rerouting may be done by assessing the current trajectory, determining where the current trajectory intersects with any potential obstacle, and if a potential collision is detected (estimated), a new trajectory is calculated.“); 0153 (“Additionally, with every mission run there is an opportunity to improve the system by automatic learning from previous missions.”); 0193 (“The scheduler may merge existing missions that are to be run in the mission database 10450 and may calculate new virtual missions that may include multiple missions so that a single physical mission run may include multiple desired scans.”)];
splicing a portion of the second path before the first trajectory point with the merged path, to obtain a flight path for a transport task [see at least Arksey, ¶ 0190]; and
controlling, according to the flight path, [[a]]the drone to transport the target workpiece to the construction location [see at least Arksey, Abstract; ¶ 0011; 0047 (“FIG. 1 illustrates a method for controlling a plurality of drones to survey a location..”)].
Mingtao more specifically teaches a control method for drone-assisted maintenance [see at least Mingtao, abstract (“The invention belongs to the technical field of logistics, courier and commercial service and claims a unmanned aerial vehicle operation method, operating platform and operating method comprises: the client generating and sending requirement order information, supply product storage point receives a demand order information. and reading the requirement order information, unmanned aerial vehicle loading supplement to the requirement order indication or preset landing point.”)];
message [see at least Mingtao, ¶ 71(“said background receiving and notifying the drone pick/put to the receiving person to related information, the related information comprises descending to the landing point, stopping after cargo release, hovering at the appointed position and drop after confirming information”);
determining environmental information for flight of a drone according to the construction location; determining a task type [see at least Mingtao, ¶ 47-48 (“invention claims the mobile phone APP or PC order management system is further provided with: information of mobile phone APP or PC management system is configured on the unmanned aerial vehicle.”); 54 (“In the emergency, after deployment, emergency [can be handheld] unit transporting emergency materials to the regular landing point, the route is preset in the unmanned aerial vehicle control system.“); 57 (“for before takeoff to be queried whether the parameter meets the preset value, so as to determine whether can take-off and flight of the unmanned aerial vehicle way, if weather monitoring device finding abnormal weather burst of unmanned aerial vehicle to continue flying timely informing ground control unmanned aerial vehicle is returning, landing, changing the route, or hovering the waiting takeoff control system.“); 67 (“all communication devices before takeoff unmanned aerial vehicle route are needed along with the ground or the unmanned aerial vehicle to a communication attempt, for verifying work normally.“);];
planning [see at least Mingtao, abstract];
controlling [see at least Mingtao, ¶ 116 (“unmanned aerial vehicle before returning, loading the garbage, …, effectively reduces the labour intensity of the worker, liberates the labour force”)].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the “method for controlling a plurality of drones to survey a location [abstract] of Arksey with the more specific “logistics, courier and commercial service, especially claims a unmanned aerial vehicle operation method and operation platform [Technical Field] of Mingtao. Providing a more efficient (Arksey, ¶ 0028; Mingtao, ¶ 30), effective and safer (Arksey, ¶ 027)platform for drones to operate in a specific areas.
Both Arksey and Mingtao disclose drones and even the concept of companion drones but Zuckerman more specifically teaches the construction location, wherein the environmental information indicates complexity of an environment or difficulty of the flight of the drone [see at least Zuckerman, Col. 7, line 41- Col. 8, line 23 (“FIG. 1A illustrates one embodiment of a drone 10 employing various resources and multiple sensors including cameras with image sensors… various communication interfaces 5-comm that may include cellular communication devices and drone peer-to-peer communication devices, data processing components 5-cpu that may include various computational resources … in which all or part of the resources and sensors may be used by the drone in conjunction with flying itself autonomously or semi autonomously, for example along roads and slightly above car traffic, and in which all of the various resources and multiple sensors may be integrated in-drone… which means that drone 10 may be fully autonomous, or it may be semi-autonomous, with various possible degrees of flying automation, starting with simple car traffic and obstacle avoidance and going all the way up to full autonomous flight and interaction with various static and non-static ground-related objects using minimal or zero pilot intervention.”);
obtaining a historical path of the first terminal carried by a maintenance personnel into the construction location, wherein the case where the task type is the complex type comprises that the environmental information indicates that the construction location is in an area with densely distributed devices [see at least Zuckerman, Col. 7, line 41- Col. 8, line 23; Col. 39, lines 3-33 (“ and using data gathered by a plurality of drones… that have previously flown over the road 1-road; and updating over time,”); Col. 47, line 51- Col. 48, line 2 (“analysis of the environment”)].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the “method for controlling a plurality of drones to survey a location [abstract] of Arksey with the more specific “logistics, courier and commercial service, especially claims a unmanned aerial vehicle operation method and operation platform [Technical Field] of Mingtao, and further with the ability to move/transport cargo between different locations Of Zuckerman. Providing a more efficient (Arksey, ¶ 0028; Mingtao, ¶ 30), effective and safer (Arksey, ¶ 027)platform for drones to operate in a specific areas.
Claim 2
Arksey, Mingtao and Zuckerman disclose/teach the method of Claim 1.
Arksey further teaches wherein determining [[a]]the target workpiece and [[a]]the storage location thereof in response to the assistance message obtained by [[a]]the first terminal located at [[a]] the construction location [see at least Arksey, ¶ 0221 - 0222 (“] An onsite operator may use one or more Operator Terminal 10265 to view the Hive 3D Model 10250 and assess the mission and flight. Operator Input 10275 may provide input into multi-drone planner 10280 that may modify the mission such as taking manual control of drones, ordering an early stop, adding new mission parameters. [0222] Remote operators may access the live drone data from the Cloud 3D Model 10350 and may initial a virtual reality (VR) conference 10430 to allow multiple remote operators the ability to see and communicate through the remote terminals 10440. They may communicate with onsite Operator Terminals 10265 and may order changes or additions to the mission plan as needed to meet their requirements.”)];
determining workpiece information of a tool or part absent in the maintenance operation according to semantic information contained in the assistance message in response to the assistance message obtained by the first terminal located at the construction location [see at least “Arksey, ¶ 0045 (“Particular embodiments disclosed herein may be implemented using one or more example processes. Described below are methods for controlling a swarm of drones for surveying a location. The methods may be performed, for example, by the system of FIG. 6 and FIG. 10. The system may receive an “intent” such as “image the object around a specific latitude and longitude”. This intent can be semantic intent, but it is not required to be semantically driven. The intent may be received, for example, from a customer and/or system operator. The system may then take a current status of drones and match that against the received intent. The system may perform an inventory of the number and/or type of drones currently available and may use the inventory and parameters of the space, such as trees, and other obstacles, to determine a collection of drones for surveying the location.”); 00552 (“The intelligent semantic segmentation can be done in cloud 10300 and/or on base station”)].
Arksey does not specifically disclose but Mingtao teaches determining the target workpiece and the storage location thereof from inventory according to the workpiece information [see at least Mingtao, Claim 3].
Therefore, it would be obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify/combine, with a reasonable expectation of success, the “method for controlling a plurality of drones to survey a location [abstract] of Arksey with the more specific “logistics, courier and commercial service, especially claims a unmanned aerial vehicle operation method and operation platform [Technical Field] of Mingtao. Providing a more efficient (Arksey, ¶ 0028; Mingtao, ¶ 30), effective and safer (Arksey, ¶ 027)platform for drones to operate in a specific areas.
3-7. (Cancelled)
Claim 8
Arksey, Mingtao and Zuckerman disclose/teach the method of Claim 1.
Arksey further discloses estimating completion situation of a plurality of loading drones in performing the transport task according to current states of the plurality of loading drones; and determining a loading drone that takes shortest time to complete the transport task according to the completion situation [see at least Arksey, ¶ 0060 (“When images are detected, the system can construct a 3D object description from the camera images taken. The system in the background can do classification and segmentation of data.”); 0079; 0192 (“Optimizer 10330 may then analyzes and segments the mission into a number of segments…The optimizer may run a series of simulations and models with different mission document 10460 parameters and may optimize the mission based on loss function…The optimizer may add multiple hives, as an example, if it determines wind or path are too long so the optimizer may launch drones upwind and they may land downwind to a waiting hive… The optimizer may also determine fixed locations where drones may land and image systems to optimize battery life or other parameters. As an example, if a flight is repetitive, the optimizer may land a drone and put it into a sleep mode away from hives to minimize travel time and power usage and then “pop up” as necessary to take images and land again.”); 0225 (“Optimizer 10330 can then simulate 10320 the entire multi-mission, multi-site model and determine the best as may be measured in lower cost, meeting required accuracy and faster as may be weighted by different missions requirements.”)].
9. (Cancelled)
Claim 10
Claim 10 has similar limitations to claim 1, therefore claim 10 is rejected with the same rationale as claim 1.
Claim 11
Claim 11 has similar limitations to claim 2, therefore claim 11 is rejected with the same rationale as claim 2.
12-15. (Cancelled)
Claim 16
Claim 16 has similar limitations to claim 1, therefore claim 16 is rejected with the same rationale as claim 1.
Claim 17
Claim 17 has similar limitations to claim 2, therefore claim 17 is rejected with the same rationale as claim 2.
18-20. (Cancelled)
Claim 21
Claim 21 has similar limitations to claim 8, therefore claim 21 is rejected with the same rationale as claim 8.
Claim 22
Claim 22 has similar limitations to claim 8, therefore claim 22 is rejected with the same rationale as claim 8.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Freimuth H, König M. A Framework for Automated Acquisition and Processing of As-Built Data with Autonomous Unmanned Aerial Vehicles. Sensors (Basel). 2019 Oct 17;19(20):4513.
Fartook, O., MacLean, K., Oron-Gilad, T. et al. Expanding the Interaction Repertoire of a Social Drone: Physically Expressive Possibilities of a Perched BiRDe. Int J of Soc Robotics 16, 257–280 (2024).
Kim, Bomyeong ; Kim, Hyun Young ; Kim, Jinwoo, “Getting home safely with drone,” Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct, 2016, p.117-120.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOAN T GOODBODY whose telephone number is (571) 270-7952. The examiner can normally be reached on M-TH 7-3 (US Eastern time).
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/JOAN T GOODBODY/
Primary Examiner, Art Unit 3664
(571) 270-7952
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