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 .
DETAILED ACTION
This action is responsive to the communications filed 06/09/2025 (claimed priority date 03/23/2018):
Claims 1-20 have been examined.
Legend: “Under BRI” = “under broadest reasonable interpretation;”
“[Prior Art/Analogous/Non-Analogous Art Reference] discloses through the invention” means “See/read entire document;” Paragraph [No..] = e.g., Para [0005] = paragraph 5; P = page, e.g., p4 = page 4; C = column, e.g. c3 = column 3;
Ln = line, e.g., ln25 = line 25; ln25-36 = lines 25 through 36.
Claim Objections
1. Claims 8 and 15 objected to because of the following informalities: it is advised to amend the corresponding limitation/feature in claims 8 and 15: “receiving robotic state data of the robot” as “receive robotic state data of the robot” accordingly. Appropriate correction is required.
Claim Rejections - 35 USC § 112
1. The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
1.1 Claims 1-20 rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claims contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
1.1.1 Independent claims 1, 8 and 15 recite the limitation/feature “determining/determine, based on the natural language input, a robotic task,” which is not described or supported and/or does not exist in the specification. The specification, in several paragraphs (e.g., abstract, Para [0003, 0026], at least as published) provides support for the “training model (e.g., deep neural network model) that can be utilized, at each of a plurality of time steps, to determine a corresponding robotic action for completing a robotic task,” BUT, HOWEVER, the specification is silent about the currently claimed “determining/determine, based on the natural language input, a robotic task.” Additionally, the Examiner finds that the currently claimed limitation/feature “determining/determine, based on the natural language input, a robotic task” is also NOT described or supported and/or does not exist in other family parent applications specifications, e.g., US18601159, now US Patent 12327169; US17040299, now US Patent 11972339.
Clarification is required, and Applicant is kindly requested to provide an information on where, in the specification, a support for the currently claimed “determining/determine, based on the natural language input, a robotic task” can be found.
For the purpose of this examination, in view of the specification, and under BRI, the currently claimed “determining/determine, based on the natural language input, a robotic task” is not given a patentable weight, and withdrawn from consideration.
Hence, the Examiner will interpret scope of the instant claims similar to how it was interpreted during previous examinations while examining the other family parent applications.
1.1.2 Independent claims 1, 8 and 15 recite the limitation/feature “robotic state data,” which is not described or supported and/or does not exist in the specification. The specification, in several paragraphs (e.g., abstract, Para [0019, 0028], at least as published) provides support for the “generating at least one robot state embedding based on processing the instance of robot sensor data using a state branch of a neural network model;” “a natural language embedding that can be generated based on the final forward and backward states, and based on an attention function (e.g., represented by a trained attention layer) that is based on the hidden states and that is based on vision embedding(s),” (and/or other embedding(s) based on sensor data that indicates the state of the robot,” BUT, HOWEVER, the specification is silent about the currently claimed “robotic state data.”
Additionally, the Examiner finds that the currently claimed limitation/feature “robotic state data” is also NOT described or supported and/or does not exist in other family parent applications specifications, e.g., US18601159, now US Patent 12327169; US17040299, now US Patent 11972339.
Clarification is required, and Applicant is kindly requested to provide an information on where, in the specification, a support for the currently claimed “robotic state data” can be found.
For the purpose of this examination, in view of the specification, and under BRI, the currently claimed “robotic state data” is not given a patentable weight, and withdrawn from consideration.
Hence, the Examiner will interpret scope of the instant claims similar to how it was interpreted during previous examinations while examining the other family parent applications, wherein the currently claimed “robotic state data” appears to be “sensor data that indicates the state of the robot,” as outlined in Para [0028] of the instant specification, at least as published.
1.1.3 Claims 2-7, 9-14 and 16-20 rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), 1st paragraph, because of their dependencies on rejected independent claims, and for failing to cure the deficiencies listed above.
2. The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
2.1 Claims 1-20 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
2.1.1 Independent claims 1, 8 and 15 recite the limitation/feature “determining/determine, based on the natural language input, a robotic task,” which is unclear what it is, OR how or why it is being executed/performed/achieved, etc., which renders the claims indefinite.
Additionally this limitation/feature NEITHER is described or supported and/or exists in instant the specification, NOR it is described or supported and/or exists in other family parent applications specifications, e.g., US18601159, now US Patent 12327169; US17040299, now US Patent 11972339, which renders the claims indefinite. Clarification is required.
For the purpose of this examination, in view of the specification, and under BRI, the currently claimed “determining/determine, based on the natural language input, a robotic task” is not given a patentable weight, and withdrawn from consideration.
Hence, the Examiner will interpret scope of the instant claims similar to how it was interpreted during previous examinations while examining the other family parent applications.
2.1.2 Independent claims 1, 8 and 15 recite the limitation/feature “robotic state data,” which is unclear what it is, what it represents, etc., which renders the claims indefinite.
Additionally this limitation/feature NEITHER is described or supported and/or exists in instant the specification, NOR it is described or supported and/or exists in other family parent applications specifications, e.g., US18601159, now US Patent 12327169; US17040299, now US Patent 11972339, which renders the claims indefinite. Clarification is required.
For the purpose of this examination, in view of the specification, and under BRI, the currently claimed “robotic state data” is not given a patentable weight, and withdrawn from consideration.
Hence, the Examiner will interpret scope of the instant claims similar to how it was interpreted during previous examinations while examining the other family parent applications, wherein the currently claimed “robotic state data” appears to be “sensor data that indicates the state of the robot,” as outlined in Para [0028] of the instant specification, at least as published.
2.1.3 Claims 2-7, 9-14 and 16-20 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, because of their dependencies on rejected independent claims, and for failing to cure the deficiencies listed above.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
1. Claims 1-20 rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 and 10 of U.S. Patent No.: 12327169 and over claims 1 and 19-20 of U.S. Patent No.: 11972339. Although the claims at issue are not identical, they are not patentably distinct from each other because of the following:
it is obvious that the narrower claim combination of narrower claims 1 of U.S. Patent No.: 12327169 and narrower claims 1 and 19-20 of U.S. Patent No.: 11972339 covers broader claim combination of broader claims 1 and 15 of the instant application;
it is obvious that the narrower claim combination of narrower claims 1 and 10 of U.S. Patent No.: 12327169 and narrower claims 1 and 19-20 of U.S. Patent No.: 11972339 covers broader claim combination of broader claims 8 and 15 of the instant application.
2. Claims 2-7, 9-14 and 16-20 rejected under the nonstatutory double patenting rejections, because of their dependencies on rejected independent claims.
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.
1. Claims 1-20 rejected under 35 U.S.C. 103 as being unpatentable over Sawada (US20060184273) in view of Anderson (NPL: "Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments," 11/20/2017, last accessed on 08/02/2023).
As per claims 1, 8 and 15, Sawada discloses through the invention (see entire document), a method implemented by one or more processors/robot comprising: one or more sensors; one or more actuators;
memory storing instructions; and one or more processors operable to execute the instructions/non-transitory computer readable storage medium configured to store instructions (fig. 1-28, Para [0010, 0021, 0067, 0078, 0219, 0231, 0235, 0281]), the method/robot/non-transitory computer readable storage medium configured to store instructions comprising:
receiving language input, the language input generated based on input provided by a user via one or more user interface input devices (fig. 1-28, Para [0195, 0211,0219]);
determining, based on the language input, a robotic task (fig. 2, 19, Para [0061, 0072, 0219] – teaching implementing a body motion of the robot device 1 according to a command for a predetermined pattern of movement; interface 25 that supplies and receives data to and from the camera 15, microphone 16 or speaker 17; the drivers 53.sub.1 to 53.sub.n in the drive unit 50; a sound performer 172, motion controller 173 and LED controller 174, as all being objects to implement a robot motion; the sound performance 172 as an object to output a speech or voice; that it synthesizes a sound correspondingly to a text or command supplied from the SBL 102 via the RM 116 and delivers the sound at the speaker in the robot body; motion controller 173 as an object to operate each joint actuator of the robot body; in response to a command supplied from the RML 102 via the RM 116 to move the hand, leg or the like, the motion controller 173 that calculates an angle of a joint in consideration; LED controller 174 as an object to have the LED flicker; in response to a command received from the SBL 102 via the RM 116, the LED controller 174 that controls the LED 19 to flicker);
receiving, from one or more sensors of a robot, robotic vision data (fig. 1-28, Para [0059, 0070, 0072, 0082, 0190, 0194, 0200, 0213]);
generating action prediction output that indicates a robotic action to be performed (fig. 1-28, abstract, Para [0016-0020, 0025]); and
controlling one or more actuators of the robot based on the action prediction output, wherein controlling the one or more actuators of the robot causes the robot to perform the robotic action indicated by the action prediction output (fig. 1-28, abstract, Para [0061, 0070, 0207, 0219]).
Sawada does not explicitly disclose through the invention, or is missing, natural language input; generating, based on the robotic vision data, semantic vision data; receiving robotic state data of the robot; generating, based on processing of the semantic vision data, the robotic state data, and the robotic task, action prediction output that indicates a robotic action to be performed
However, Anderson teaches these limitations/features through the invention (see entire document), particularly in 5th paragraph from the top, in Section 5.1, on page 9/16; in 3rd paragraph from the top, in Section 4.1, on page 7/16; in 6th paragraph from the top, in Section 5.1, on page 9/16 through 1st paragraph on the top, in Section 5.1, on page 10/16, similar to how it was discussed and presented in the previous office action while examining the family parent application US17040299, now US Patent 11972339, filed 08/10/2023.
It would have been obvious to one of ordinary skill in the art, who is also a person of ordinary creativity, not an automation, before the effective filing date of the claimed invention, to modify the teaching of Sawada by incorporating, applying and utilizing the above steps, technique and features as taught by Anderson, who is in the same field of endeavor. A person of ordinary skill, ordinary creativity would have been motivated to do so, with a reasonable expectation of success, for the purpose of and/or in order to use the Matterport3D Simulator - a large-scale reinforcement learning environment based on real imagery, to enable and encourage the application of vision and language methods to the problem of interpreting visually-grounded navigation instructions, the simulator, which can in future support a range of embodied vision and language tasks, to provide the first benchmark dataset for visually-grounded natural language navigation in real buildings - the Room-to-Room (R2R) dataset (see entire Anderson document, particularly in abstract on pages 1/16-2/16).
As per claims 2, 9 and 16, Sawada does not explicitly disclose through the invention, or is missing, generating, based on the robotic vision data, the semantic vision data that comprises: generating natural language labels of objects captured in at least some of the robot vision data.
However, Anderson teaches these limitations/features through the invention (see entire document), particularly in left column, 2nd paragraph from the top, in Section 1 - Introduction, on page 5/16; in right column, 3rd paragraph from the top, in Section 2 - Related Work, on page 5/16.
It would have been obvious to one of ordinary skill in the art, who is also a person of ordinary creativity, not an automation, before the effective filing date of the claimed invention, to modify the teaching of Sawada by incorporating, applying and utilizing the above steps, technique and features as taught by Anderson, who is in the same field of endeavor. A person of ordinary skill, ordinary creativity would have been motivated to do so, with a reasonable expectation of success, for the purpose of and/or in order to use the Matterport3D Simulator - a large-scale reinforcement learning environment based on real imagery, to enable and encourage the application of vision and language methods to the problem of interpreting visually-grounded navigation instructions, the simulator, which can in future support a range of embodied vision and language tasks, to provide the first benchmark dataset for visually-grounded natural language navigation in real buildings - the Room-to-Room (R2R) dataset (see entire Anderson document, particularly in abstract on pages 1/16-2/16).
As per claims 3, 10 and 17, Sawada does not explicitly disclose through the invention, or is missing, natural language labels of the objects as directly human interpretable.
However, Anderson teaches these limitations/features through the invention (see entire document), particularly in left column, 2nd paragraph from the top, in Section 1 - Introduction, on page 5/16; in right column, 3rd paragraph from the top, in Section 2 - Related Work, on page 5/16.
It would have been obvious to one of ordinary skill in the art, who is also a person of ordinary creativity, not an automation, before the effective filing date of the claimed invention, to modify the teaching of Sawada by incorporating, applying and utilizing the above steps, technique and features as taught by Anderson, who is in the same field of endeavor. A person of ordinary skill, ordinary creativity would have been motivated to do so, with a reasonable expectation of success, for the purpose of and/or in order to use the Matterport3D Simulator - a large-scale reinforcement learning environment based on real imagery, to enable and encourage the application of vision and language methods to the problem of interpreting visually-grounded navigation instructions, the simulator, which can in future support a range of embodied vision and language tasks, to provide the first benchmark dataset for visually-grounded natural language navigation in real buildings - the Room-to-Room (R2R) dataset (see entire Anderson document, particularly in abstract on pages 1/16-2/16).
As per claims 4, 11 and 18, Sawada does not explicitly disclose through the invention, or is missing, generating, based on the robotic vision data, the semantic vision data that comprises: generating embeddings of objects captured in at least some of the robot vision data.
However, Anderson teaches these limitations/features through the invention (see entire document), particularly in 5th paragraph from the top, in Section 5.1, on page 9/16; in 3rd paragraph from the top, in Section 4.1, on page 7/16; in 6th paragraph from the top, in Section 5.1, on page 9/16 through 1st paragraph on the top, in Section 5.1, on page 10/16, similar to how it was discussed and presented in the previous office action while examining the family parent application US17040299, now US Patent 11972339, filed 08/10/2023.
It would have been obvious to one of ordinary skill in the art, who is also a person of ordinary creativity, not an automation, before the effective filing date of the claimed invention, to modify the teaching of Sawada by incorporating, applying and utilizing the above steps, technique and features as taught by Anderson, who is in the same field of endeavor. A person of ordinary skill, ordinary creativity would have been motivated to do so, with a reasonable expectation of success, for the purpose of and/or in order to use the Matterport3D Simulator - a large-scale reinforcement learning environment based on real imagery, to enable and encourage the application of vision and language methods to the problem of interpreting visually-grounded navigation instructions, the simulator, which can in future support a range of embodied vision and language tasks, to provide the first benchmark dataset for visually-grounded natural language navigation in real buildings - the Room-to-Room (R2R) dataset (see entire Anderson document, particularly in abstract on pages 1/16-2/16).
As per claims 5, 12 and 19, Sawada does not explicitly disclose through the invention, or is missing, generating, based on the robotic vision data, the semantic vision data that comprises: generating one or more bounding boxes for objects captured in at least some of the robot vision data.
However, Anderson teaches these limitations/features through the invention (see entire document), particularly in 2nd paragraph from the top, in Section 3.2.1, on page 6/16 - teaching "[t]o construct the simulator, ... allowing an embodied agent to virtually 'move' throughout a scene by adopting poses coinciding with panoramic viewpoints; agent poses defined in terms of 3D position, heading, and camera elevation, where Vis the set of 3D points associated with panoramic viewpoints in the scene; the simulator that outputs an RGB image observation corresponding to the agent's first person camera view. Images are generated from perspective projections of precomputed cube-mapped images at each viewpoint; future extensions to the simulator that will also support depth image observations (RGB-D), and additional instrumentation in the form of rendered object class and object instance segmentations (based on the underlying Matterport 3D mesh annotations)."
It would have been obvious to one of ordinary skill in the art, who is also a person of ordinary creativity, not an automation, before the effective filing date of the claimed invention, to modify the teaching of Sawada by incorporating, applying and utilizing the above steps, technique and features as taught by Anderson, who is in the same field of endeavor. A person of ordinary skill, ordinary creativity would have been motivated to do so, with a reasonable expectation of success, for the purpose of and/or in order to use the Matterport3D Simulator - a large-scale reinforcement learning environment based on real imagery, to enable and encourage the application of vision and language methods to the problem of interpreting visually-grounded navigation instructions, the simulator, which can in future support a range of embodied vision and language tasks, to provide the first benchmark dataset for visually-grounded natural language navigation in real buildings - the Room-to-Room (R2R) dataset (see entire Anderson document, particularly in abstract on pages 1/16-2/16).
As per claims 6, 13 and 20, Sawada does not explicitly disclose through the invention, or is missing,
action prediction output that indicates one or more motion primitives for the robot.
However, Anderson teaches these limitations/features through the invention (see entire document), particularly in from 1st paragraph from the top, in Section 3.2.2, on page 6/16 through 4th paragraph from the top, in Section 3.2.2, on page 7/16 - teaching " ... main challenge in implementing the simulator as determining the state dependent action space; wishing to prevent agents from teleporting through walls and floors, or traversing other non-navigable regions of space; at each step the simulator that outputs a set of next step reachable viewpoints; agents that interact with the simulator by selecting a new viewpoint, and nominating camera heading and elevation adjustments; actions that are deterministic; to determine viewpoint for each scene the simulator that includes a weighted, undirected graph over panoramic viewpoints, such that the presence of an edge signifies a robot-navigable transition between two viewpoints, and the weight of that edge reflects the straight-line distance between them; to construct the graphs, ray-traced between viewpoints in the Matterport3D scene meshes to detect intervening obstacles; to ensure that motion remains localized, removed edges longer than 5m; verifying each navigation graph to correct for missing obstacles not captured in the meshes (such as windows and mirrors); agent permitted to follow any edges in the navigation graph, provided that the destination is within the current field of view, or visible by glancing up or down; agent that always has the choice to remain at the same viewpoint and simply move the camera; on average each graph that contains 117 viewpoints, with an average vertex degree of 4.1; comparing favorably with grid-world navigation graphs which, due to walls and obstacles, must have an average degree of less than 4; although agent motion discretized, this does not constitute a significant limitation in the context of most high-level tasks; even with a real robot it may not be practical or necessary to continuously re-plan higher-level objectives with every new RGB-D camera view; even agents operating in 3D simulators that notionally support continuous motion typically use discretized action spaces in practice; the simulator that does not define or place restrictions on the agent's goal, reward function, or any additional context (such as natural language navigation instructions).
It would have been obvious to one of ordinary skill in the art, who is also a person of ordinary creativity, not an automation, before the effective filing date of the claimed invention, to modify the teaching of Sawada by incorporating, applying and utilizing the above steps, technique and features as taught by Anderson, who is in the same field of endeavor. A person of ordinary skill, ordinary creativity would have been motivated to do so, with a reasonable expectation of success, for the purpose of and/or in order to use the Matterport3D Simulator - a large-scale reinforcement learning environment based on real imagery, to enable and encourage the application of vision and language methods to the problem of interpreting visually-grounded navigation instructions, the simulator, which can in future support a range of embodied vision and language tasks, to provide the first benchmark dataset for visually-grounded natural language navigation in real buildings - the Room-to-Room (R2R) dataset (see entire Anderson document, particularly in abstract on pages 1/16-2/16).
As per claims 7 and 14, Sawada further discloses through the invention (see entire document), natural language input generated based on a spoken utterance provided by the user and wherein the one or more user interface input devices include a microphone of the robot (fig. 1-28, Para [0195, 0211]).
RELEVANT PRIOR ART THAT WAS CITED BUT NOT APPLIED
The following relevant prior art references that were found, by the Examiner while performing initial and/or additional search, cited but not applied:
CHA (WO2018012645A1) – (see entire CHA document, particularly abstract - teaching a mobile robot capable of communicating with a user and a control method therefor, the mobile robot comprising: a voice input unit for receiving voice information including a specific keyword uttered by a user; and a control unit for generating a keyword map by mapping the specific keyword to an utterance location in which the user uttered the specific keyword, wherein the control unit detects the specific keyword corresponding to a current position of the user from the keyword map so as to predict a behavior of the user and outputs information related to the detected specific keyword before inputting the voice information from the user).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Primary Examiner YURI KAN, P.E., whose phone number is 571- 270-3978. The examiner can normally be reached on Monday – Friday.
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/YURI KAN, P.E./ Primary Examiner, Art Unit 3662
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