DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . 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 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.
Joint Inventors
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.
Response to Amendment
The amendments filed on 12/04/2025 have been entered. Claims 1-20 remain pending in the application.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
“a navigation implementation module configured to: …” in claim 14
“a path calculation module configured to …” in claim 14
“a node interaction module configured to: …” in claim 14
“a monitoring module configured to …” in claim 14
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-12, 14-17, and 19-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Nie et al., US 20240319750 A1, herein referred to as Nie.
Regarding claim 1,
Nie discloses the following:
deploying a plurality of nodes over a predetermined space, wherein each of the plurality of nodes is associated with a corresponding one or more regions of the predetermined space, and wherein each of the plurality of nodes is trained based on a predetermined set of traffic rules (Figs. 3A-3B, Paragraphs 0051, 0089-0091)
multiple vertices (nodes) may be established in a predetermined space
of the multiple vertices (nodes) in the predetermined space, a portion are established for each corresponding floor, where each floor may be considered as one or more regions of the predetermined space
a global critic may be established for all floors and vertices (nodes) within the predetermined space
the global critic may be trained which includes a training of the vertices (nodes) based on rewards for plan or task execution
the planning may be considered a predetermined set of traffic rules as it includes searching of vertices (nodes) based on breadth-first or depth-first for optimized path planning of the autonomous robots
examiner notes that “traffic rules” under BRI can include any set of rules or parameters related to movement of traffic (the autonomous robots of Nie) and the search planning disclosed above satisfies this set of rules as it is related to movement of the autonomous robots (which vertices are most optimal for movement to achieve the task)
examiner also notes that the task parameters may also be considered as traffic rules as they indicate target times for pickup and drop-off, as well as energy efficiency, all of which are related to movement of the autonomous robots
deploying a plurality of agents in the predetermined space, wherein each of the plurality of agents is associated with a starting location (Figs. 1A-1C, Paragraph 0028)
the predetermined space may have multiple autonomous robots present, each with its own starting position
determining a destination for each of the plurality of agents (Fig. 3A, Paragraph 0051)
each autonomous robot may have a corresponding target location (delivery vertex for transportation task) based on the current task
determining, by each of the plurality of agents, a path to the destination corresponding to that agent (Fig. 3A, Paragraphs 0068-0069)
a path may be established for traveling from a current location to the target location
querying, by each agent, at least one of the plurality of nodes associated with the corresponding region encompassing a current position of the agent, to determine a direction of travel (Fig. 3A, Paragraphs 0068-0069, 0086)
a robot may plan a path for transportation
the robot may utilize a local critic and a global critic for evaluation of the path
this evaluation of the path determines which vertices (nodes) the robot must pass through in order to reach the target location (delivery vertex)
this can be considered as querying at least one of the nodes associated with a corresponding region to determine directions for travel as the selection of vertices (nodes) for planning will dictate the direction the robot will go
this process may be performed for multiple robots that are performing a given transportation task
the queried nodes may be within a given floor which may encompass the autonomous robot’s current position/vertex
determining, by at least one of the queried nodes, a preferred direction of travel for the querying agent based on the predetermined set of traffic rules (Paragraphs 0086-0087)
preferred directions of travel for a robot are dictated by which vertices (nodes) are selected for the optimized task plan (best rewards)
the vertices (nodes) that are best for the task are based on a global critic and an associated reward
as stated above, the global critic includes a vertex (node) search method for optimization (breadth and depth searches) which can be considered the predetermined set of rules
sending the preferred direction of travel from the queried node to the querying agent (Paragraph 0042)
control signals may be transmitted to each of the autonomous robots
control signals may be based on the optimized path determined by the global critic evaluation of the nodes within the predetermined space
travelling, by the querying agent, in the preferred direction from the current position of the agent (Figs. 2 step 206, 3A, Paragraph 0048)
a transportation task may be executed by one of the autonomous robots in accordance with the determined optimal path which indicates a preferred direction (at least the first trajectory between the current vertex and the next optimized vertex)
Regarding claim 2,
Nie discloses all the limitations of claim 1. Nie further discloses the following:
the predetermined set of traffic rules are generated based on a machine learning model (Paragraphs 0051, 0092)
task parameters and/or task planning (vertex search based on breadth/depth) may be used for task optimization and are generated based on the global critic
these parameters and search rules are based off the global critic which is trained utilizing a machine learning model
Regarding claim 3,
Nie discloses all the limitations of claim 1. Nie further discloses the following:
one or more of the regions are non-overlapping in the predetermined space (Fig. 1E, Paragraph 0046)
as stated above, each floor is considered its own region within the predetermined space
a multi-floor model may be used for multi-floor factories, warehouses, etc.
each floor is separate from each other and do not overlap one another
Regarding claim 4,
Nie discloses all the limitations of claim 1. Nie further discloses the following:
each of the plurality of agents lacks computational resources to determine the preferred direction of travel within a predetermined time interval (Fig. 1E)
as explained above in the rationale for claim 1, the preferred direction for each of the autonomous robots is performed through a global critic which searches the vertices (nodes) for an optimal plan for task execution
this preferred direction as determined through the global critic is performed on an edge server
this can be considered as each of the autonomous robots lacking computational resources to determine the preferred direction
Regarding claim 5,
Nie discloses all the limitations of claim 1. Nie further discloses the following:
the starting location associated with each of the plurality of agents is different from other starting locations of all other agents (Figs. 1A-1C, 3A, Paragraph 0036 at least)
path planning may be optimized towards resolving competitive collisions during task execution
this allows for collisions to be optimized around such that no two autonomous robots encounter a collision
this means that no two autonomous vehicles will have the same starting location as this would cause a collision
examiner also notes that from a physical standpoint, no two autonomous robots can occupy a single location (x, y coordinate as seen in Fig. 3A) as this would either be a collision (system is optimized to avoid) or an impossibility (physical constraint)
Regarding claim 6,
Nie discloses all the limitations of claim 1. Nie further discloses the following:
the at least one of the nodes is queried by more than one of the plurality of agents (Paragraphs 0052, 0073)
a delivery vertex (destination/delivery node) may be determined for each transportation task that is assigned to a given autonomous robot
in a multi-floor model, robots performing a transportation task may have different delivery vertices (destination/delivery node)
some vertices may be queried by multiple robots (same delivery vertex)
Regarding claim 7,
Nie discloses all the limitations of claim 1. Nie further discloses the following:
the same predetermined set of traffic rules is used for training each of the plurality of nodes (Figs. 3A-3B, 9A-9H, Paragraphs 0051, 0089-0091)
the global critic may be trained which includes a training of the vertices (nodes) based on rewards for plan or task execution
the planning may be considered a predetermined set of traffic rules as it includes searching of vertices (nodes) based on breadth-first or depth-first for optimized path planning of the autonomous robots
examiner notes that “traffic rules” under BRI can include any set of rules or parameters related to movement of traffic (the autonomous robots of Nie) and the search planning disclosed above satisfies this set of rules as it is related to movement of the autonomous robots (which vertices are most optimal for movement to achieve the task)
examiner also notes that the task parameters may also be considered as traffic rules as they indicate target times for pickup and drop-off, as well as energy efficiency, all of which are related to movement of the autonomous robots
Figs. 9A-9H show training of both the global and local critics over time, indicating that the traffic rules as explained above are continuously used for training the global critic
Regarding claim 8,
Nie discloses all the limitations of claim 1. Nie further discloses the following:
each of the plurality of agents comprise a physical vehicle (Fig. 2, Paragraph 0042)
each of the autonomous robots may be a physical entity
Regarding claim 9,
Nie discloses all the limitations of claim 1. Nie further discloses the following:
each of the plurality of agents comprise a virtual agent in a simulated environment (Paragraph 0115)
experiments may be run to simulate tasks for a multitude of robots
the robots in these simulated tasks may be considered as simulated agents
Regarding claim 10,
Nie discloses all the limitations of claim 1. Nie further discloses the following:
the direction of travel comprises a speed component (Paragraph 0047)
the optimized path for a task includes an optimized speed
Regarding claim 11,
Nie discloses all the limitations of claim 1. Nie further discloses the following:
the path determined by each of the plurality of agents is a shortest path from the current position of the corresponding one of the plurality of agents to the determined destination, wherein determining, by the at least one of the nodes, the preferred direction of travel for the corresponding one of the plurality of agents is based on the shortest path (Paragraph 0104, 0124)
optimization of the path for a robot task may be one in which a shortest path is selected
an optimized shortest path indicates directions from vertex to vertex that results in a shortest path based on the task
Regarding claim 12,
Nie discloses all the limitations of claim 1. Nie further discloses the following:
further repeating steps of querying the at least one of the nodes associated with at least one of the corresponding regions encompass a current position of the querying agent, determining, by the at least one of the nodes, the preferred direction of travel for the querying agent based on the predetermined set of traffic rules, sending the preferred direction of travel from the at least one of the nodes to the querying agent, and enabling the querying agent to travel in the preferred direction from a current location to the destination until the current position of the querying agent is equal to the determined destination (Figs. 3A-3B, Paragraphs 0042, 0051, 0086-0091 0068-0069, 0114-0118, at least)
examiner notes that the claim is a repeat of steps as disclosed in claim 1, and as such, the rational for each of the respective parts can be found in the rationale of claim 1 above
additionally, Nie discloses that an experiment may be run utilizing 31 robots over a multi-floor scenario to simulate non-stationary tasks (delivery/transportation) at specific timesteps, wherein the system is reconfigured at each timestep
the reconfiguration at given timesteps may be considered a repeat of the prior steps of querying nodes, determining the preferred direction, etc.
Regarding claim 14, a portion of the claim limitations are similar to those of claim 1 and are rejected using the same rationale as seen above in claim 1. Nie additionally discloses a monitoring module configured to determine the current position of the corresponding one or more agents is equal to the assigned destination or not (Paragraph 0054; system may determine if a robot has executed delivery within a given time frame; this would require the system to determine the robot’s current position as being that of the delivery vertex).
Regarding claims 15-17 and 19, the claim limitations are similar to those in claims 2, 4, 11, and 10, respectively, and are rejected using the same rationale as seen above in claims 2, 4, 11, and 10.
Regarding claim 20, the claim limitations are similar to those in claim 14 and are rejected using the same rationale as seen above in claim 14.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 13 and 18 are rejected under 35 U.S.C. 103 as being obvious over Nie, and in view of Anand et al., US 20230266766 A1, herein referred to as Anand.
Regarding claim 13, Nie discloses all the limitations of claim 1. Nie further discloses the one or more nodes are Graph Convolutional Neural Network (GCNN) nodes (Paragraphs 0037, 0060; neural networks may include GCNNs which comprise neurons (nodes) for use in a graph format data structures), but fails to disclose the one or more nodes are Graph Recurrent Neural Network (GRNN) nodes. However, Anand, in an analogous field of endeavor, teaches the one or more nodes are Graph Recurrent Neural Network (GRNN) nodes (Paragraph 0035; spatial representation of nodes may be represented through a Recurrent Graph Neural Network). Therefore, from the teaching of Anand, it would have been obvious to one of ordinary skill in the art before the effective filing date to have modified, with a reasonable expectation for success, the multi-robot system of Nie to include the one or more nodes are Graph Recurrent Neural Network (GRNN) nodes, as taught/suggested by Anand. The motivation to do so would be to utilize a well-known alternative neural network for robot tasking. This can lead to potentially higher efficiency when allocating tasks for each robot or generating the most optimized path, etc. when utilizing a node representation.
Regarding claim 18, the claim limitations are similar to those in claim 13 and are rejected using the same rationale as seen above in claim 13.
Response to Arguments
Applicant's arguments filed 12/04/2025 have been fully considered but they are not persuasive.
Applicant is arguing that the prior art of Nie fails to disclose the claim limitations. Specifically, Applicant is arguing that the agents of Nie do not query at least one of the nodes. Applicant specifically points out that the robots of Nie only determine a collision avoidance path. However, at least Fig. 3A, Paragraphs 0068-0069, 0086 of Nie clearly discloses that traversal of a given space requires the robots to pass through given vertices in order to perform traversal (and obstacle avoidance). This passing through of nodes is clearly a form of querying as the robot evaluates the nodes in a given environment in order to successfully traverse it.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
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/C.A.B./Examiner, Art Unit 3658
/JASON HOLLOWAY/Primary Examiner, Art Unit 3658