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 .
Response to Amendment
A supplemental amendment was received on 20 August 2026, and has been entered accordingly. The previous drawing objections, claim objections, and rejections of claims 1-7 under 35 U.S.C. 112(a) and 112(b) have been withdrawn as a result of amendment. The examiner notes, however, that the drawings still appear to have been produced using Generative AI, and while this does not violate any USPTO guidelines, the examiner believes it is important to note for the record.
Response to Arguments
Applicant's arguments filed 16 July 2026 have been fully considered but they are not persuasive.
Regarding claim 1, Applicant argues that the previously applied prior art fails to teach "a trained AI, or a guidance and control system that generates control signals." Specifically, Applicant asserts that the Stevens reference "describes an event-classification model: it maps sensor input data to 'events' or 'event types,' exemplified by recognizing a particular user's voice. Classifying inputs into events is fundamentally different from what claim 1 requires — a guidance and control system, comprising a trained AI model, that generates control signals to which the actuators respond to perform autonomous walking and task execution. Nothing in the cited portion of Stevens describes its event models producing walking or motion guidance, generating control signals for actuators, or participating in locomotion control at all. Stevens' companion device personalizes its responses to a recognized user; it does not disclose AI driven autonomous navigation or gait control." Further, Applicant argues that "the Office does not — and cannot — identify any guidance and control system (with a trained AI model) in Sato that provides walking or motion guidance. Li is a mechanically assembled toy with servomotors and no perception-driven control whatsoever. Accordingly, even if the references were combined exactly as the Office proposes — inserting Stevens' user-recognition event model into Sato's robot with Li's mouth — the resulting robot would, at most, classify sensor outputs into events for personalization. It would still lack guidance and control system [sic] (with a trained AI model) generating control signals as claim 1 requires."
Further, Applicant asserts that the articulated reasoning behind the previous rejection of claim 1 cannot sustain the rejection, asserting that "[t]he stated rationale for adding Stevens is 'to provide better means of processing environmental data' so that 'the robot's responses to environmental data [can] be more personalized for the user.' That rationale is tethered to Stevens' actual teaching — user recognition and personalization — and, at most, would motivate a skilled artisan to add a voice recognition event classifier to Sato's robot. It provides no articulated reasoning with a rational underpinning … for the very different modification the amended claims require: replacing or augmenting Sato's pre-programmed event-monitoring and movement logic with a trained AI model that itself provides walking and motion guidance and rives real-time generation of guidance and control signals for the locomotion actuators. Indeed, Sato's stated principle of operation depends on deterministic, prioritized processing that can interrupt all analysis to react to dangerous substances; wholesale substitution of that safety-critical, rule-based control scheme with a trained model for locomotion guidance would change Sato's principle of operation, and the Office offers no reason — other than the roadmap provided by Applicant's own disclosure — why a skilled artisan would have done so. The rejection therefor rests on impermissible hindsight." The examiner respectfully disagrees for at least the following reasons.
Regarding Applicant's assertion that the previously applied prior art fails to teach "a trained AI, or a guidance and control system that generates control signals," the examiner notes that Applicant repeatedly asserts that the AI model must produce signals "to perform autonomous walking and task execution." The examiner notes, however, that there is no portion of claim 1 that requires this to be the case. Rather, claim 1 recites, inter alia, "wherein the guidance and control system is configured to process the environmental data captured by the plurality of sensors and generate control signals; and a plurality of actuators responsive to the control signals generated by the guidance and control system, wherein the actuators are configured to manipulate at least the head and legs to perform autonomous walking and task execution." That is, there is no requirement that the control signals be, in any way, control signals for autonomous walking or task execution, merely that the actuators are responsive to the control signals, and separately, that the actuators manipulate portions of the robotic dog to perform walking and task execution. Additionally, Applicant asserts that "the Office does not — and cannot — identify any guidance and control system (with a trained AI model) in Sato that provides walking or motion guidance." The examiner notes that Applicant does not argue that Sato fails to teach "a guidance and control system that provides walking or motion guidance," merely that Sato fails to teach "a guidance and control system (with a trained AI model)…." Particularly, the examiner points to both the parenthetical provided by Applicant, as well as the language of claim 1, which recites "a guidance and control system comprising a trained artificial intelligence (AI) model…," as evidence that the guidance and control system must merely include "a trained AI model," rather than the guidance and control system be a "trained AI model" wholesale.
Regarding Applicant's assertion that "the articulated reasoning behind the previous rejection of claim 1 cannot sustain the rejection," the examiner points to both MPEP § 2144(IV) and MPEP 2145(X)(A), which state, respectively, that "[t]he reason or motivation to modify the reference may often suggest what the inventor has done, but for a different purpose or to solve a different problem. It is not necessary that the prior art suggest the combination to achieve the same advantage or result discovered by applicant…" and "[a]ny judgment on obviousness is in a sense necessarily a reconstruction based on hindsight reasoning, but so long as it takes into account only knowledge which was within the level of ordinary skill in the art at the time the claimed invention was made and does not include knowledge gleaned only from applicant’s disclosure, such a reconstruction is proper." Hence, Applicant's arguments are not persuasive.
Specification
The attempt to incorporate subject matter into this application by reference to “Large Language Models in Action: Design, Build, and Deploy Intelligent LLM Applications” by Liam Sturgis is ineffective because no copy of the publication has been furnished, and the examiner is unable to find the publication.
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 1-7 are rejected under 35 U.S.C. 103 as being unpatentable over Sato (US 20120316677 A1), hereafter Sato, in view of Li (US 20230072465 A1), hereafter Li, and in view of Stevens (US 20210001077 A1), hereafter Stevens, and further in view of Nagy et al. ("Deep Learning-Based Recognition and Analysis of Limb-Independent Dog Behavior for Ethorobotical Application"), hereafter Nagy.
Regarding claim 1, Sato discloses a robotic dog comprising:
a) A body (0031, robot dog 1, see also Figs. 1-3) comprising:
(i) a head (0031, the robot dog 1 includes a head portion 2, see also Figs. 1-3);
(ii) a plurality of eyes (0054, The robot dog 1 includes image acquisition units 61L and 61R that acquire left and right images at the positions of the left and right eyes on the head portion 2. See also Figs. 1-3);
(iii) a plurality of ears (0054, The robot dog 1 also includes microphones 62L and 62R that acquire left and right sound (i.e., stereo sound) at the positions of the left and right ears 13 on the head portion 2. See also Figs. 1-3);
(iv) a nose (0033, the left and right nostrils 12L and 12R of the nose 11 on the front surface 10 of the head portion 2 of the robot dog 1 are sampling holes and the detection unit 100 is housed behind the nose 11. See also Figs. 1-3);
(vi) a body structure to house or connect robot components (0031, the robot dog 1 includes … a neck portion 3, a trunk portion 4, … a rump portion 6… the robot dog includes an internal bus 9 that passes through the head portion 2, the neck portion 3, the trunk portion 4, and the rump portion 6 to reach the tail portion 7 and distributes data and power, so that the various functions incorporated in the robot dog 1 are capable of communicating with one another, see also Figs. 1-3);
(vii) a plurality of legs with paws (0031, the robot dog 1 includes … a leg portion 5, See also Figs. 1-3); and
(viii) a tail (0031, the robot dog 1 includes … a tail portion 7, See also Figs. 1-3);
b) A plurality of sensors configured to capture environmental data, including at least one video camera and at least one audio microphone (0054, The robot dog 1 includes image acquisition units 61L and 61R that acquire left and right images at the positions of the left and right eyes on the head portion 2… The robot dog 1 also includes microphones 62L and 62R that acquire left and right sound (i.e., stereo sound) at the positions of the left and right ears 13 on the head portion 2.);
c) A power supply (0031, A battery 8 is housed in the trunk portion 4 so that the robot dog 1 is capable of moving freely on its own.);
d) A guidance and control system comprising a processing system, wherein the guidance and control system is configured to process the environmental data captured by the plurality of sensors and generate control signals (0033, The robot dog 1 also includes an event monitoring unit 30 that determines an occurrence of an event and the occurrence direction of the event relative to the robot dog 1 based on at least one of changes in the chemical substances detected at the respective sampling points and changes in the concentration of the detected chemical substances. 0054, The robot dog 1 is capable of moving the head portion 2 up, down, to the left, and to the right relative to the trunk portion 4 by way of an actuator 15 provided in the neck portion 3. Accordingly, by orienting the head portion 2 in the event occurrence direction, it is possible to obtain images and sound in the event occurrence direction.); and
e) A plurality of actuators responsive to the control signals generated by the guidance and control system, wherein the actuators are configured to manipulate at least the head and legs to perform autonomous walking and task execution (0054, The robot dog 1 is capable of moving the head portion 2 up, down, to the left, and to the right relative to the trunk portion 4 by way of an actuator 15 provided in the neck portion 3. Accordingly, by orienting the head portion 2 in the event occurrence direction, it is possible to obtain images and sound in the event occurrence direction. 0064, If the central control unit 55 determines in step 704 that it is necessary to move or transport the robot dog 1 in response to the event, in step 705 the robot dog 1 moves or travels in the event occurrence direction using the moving unit 500.).
The examiner notes that while Sato appears to disclose a mouth in at least Fig. 2, in order to promote compact prosecution, the examiner is relying on Li in teaching "a mouth".
Li, in an analogous field of endeavor, does teach a dog-like robot having a mouth (0015, the head includes an upper pieces and a lower piece. The upper piece is hinged with the lower piece through a head rotary shaft, the front end of the upper piece is provided with canine teeth, and the front end of the lower piece is provided with a dog tongue.).
Sato and Li are analogous because they are in a similar field of endeavor, e.g., robotic dog systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the mouth of Li in order to provide a more realistic dog-like robot. The motivation to combine is to allow the robot to better emulate a dog.
The combination of Sato and Li fails to teach, however, wherein the processing system includes a trained artificial intelligence (AI) model.
Stevens, however, in an analogous field of endeavor, does teach a dog-like robot, wherein the processing system includes a trained artificial intelligence (AI) model (0045, In examples, one or more artificial intelligence event models can be used for mapping (e.g., via a classification model; via a neural network model; etc.) input data (e.g., sensor input data; input data of different types; etc.) to one or more events (and/or event types; etc.). In a specific example, one or more event models and/or any other suitable models can be trained upon a user's inputs (e.g., to be able to recognize a user's voice, etc.) for user recognition, such as where scene determination based on events associated with the corresponding user's inputs can be personalized for that user (e.g., tailored to the corresponding user's preferences, needs, etc.).).
Sato, Li, and Stevens are analogous because they are in a similar field of endeavor, e.g., robotic dog systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the artificial intelligence model of Stevens in order to provide better means of processing environmental data. The motivation to combine is to allow the robot’s responses to environmental data to be more personalized for the user.
The combination of Sato, Li, and Stevens fails to explicitly teach, however, wherein the trained AI model is configured to learn behaviors, movements, and responses of a real dog.
Nagy, however, in an analogous field of endeavor, does teach a trained AI model configured to learn behaviors, movements, and responses of a real dog (Page 3827, Col. 1, Paragraph 4, The system is prepared to observe dogs and humans simultaneously in a specified room, focusing on individual behavior patterns and their interactions. Collect and store data, and based on the observations, the behavior analysis can be automatized. Using deep learning algorithms the system can learn how to predict a behavior which can be used to generate more precise ethograms to describe the behavior of the dog or the prediction capability can be used to implement a dog-inspired behavior model into an autonomous mobile robot in the future.).
Sato, Li, Stevens, and Nagy are analogous because they are in a similar field of endeavor, e.g., dog-like robotics systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the AI model trained on a real dog of Nagy in order to provide a means of emulating a unique animal. The motivation to combine is to allow the processing system to better emulate a real animal (see at least the Abstract of Nagy).
Regarding claim 2, the combination of Sato, Li, Stevens, and Nagy teaches the robotic dog of claim 1, and Sato further teaches wherein the plurality of eyes comprises at least one visual camera and at least one infrared camera (0054, The robot dog 1 includes image acquisition units 61L and 61R that acquire left and right images at the positions of the left and right eyes on the head portion 2. The image acquisition units 61L and 61R are capable of obtaining not only three-dimensional images in the range of visible light but are also capable of obtaining three-dimensional images in the range of infrared light and are therefore able to see in the dark. See also Figs. 1-3).
Regarding claim 3, the combination of Sato, Li, Stevens, and Nagy teaches the robotic dog of claim 1, and Sato further teaches wherein the nose comprises at least one olfactory sensor configured to detect drugs or explosives (0033, This robot dog 1 includes a detection unit 100 that detects chemical substances included in a fluid at a plurality of sampling points. In the present embodiment, the detection unit 100 includes an IMS sensor and is sometimes referred to hereinafter as the "IMS unit". The robot dog 1 also includes an event monitoring unit 30 that determines an occurrence of an event and the occurrence direction of the event relative to the robot dog 1 based on at least one of changes in the chemical substances detected at the respective sampling points and changes in the concentration of the detected chemical substances. More specifically, the left and right nostrils 12L and 12R of the nose 11 on the front surface 10 of the head portion 2 of the robot dog 1 are sampling holes and the detection unit 100 is housed behind the nose 11. The detection unit 100 may output information on the chemical substances themselves or may output information that changes (varies) according to the presence of chemical substances, that is, "chemical substance-related information". 0076, The specifying of chemical substances is realized by the function for adjusting the angles of the two independent nasal cavities 12R and 12L, the function for adjusting the suction speed, the internally provided detection unit 100 with humidity controller, and the data processing unit 55, and the like. One characteristic of the olfactory robot dog 1 is that the dog is configured to give priority to process relating to explosive substances that are extremely dangerous and/or poisons, poisonous gas, and harmful substances, so that it is possible, if necessary, to react to an emergency by stopping all analysis and carrying out the prioritized processing.).
Regarding claim 4, the combination of Sato, Li, Stevens, and Nagy teaches the robotic dog of claim 1, and Li further teaches wherein the mouth further comprises teeth and a tongue configured to allow the robotic dog to grip and interact with objects (0055, As shown in FIGS. 23 to 24, in the present disclosure, the head 21 includes an upper piece 211 and a lower piece 212. The upper piece 211 is hinged with the lower piece 212 through a head rotary shaft 213. The front end of the upper piece 211 is provided with canine teeth 214, and the front end of the lower piece 212 is provided with a dog tongue 215… The canine teeth 214 and tongue 215 at the front of the mouth can hold and stabilize additional accessories, such as decorative props, extended sensor modules, and the like).
Sato, Li, Stevens, and Nagy are analogous because they are in a similar field of endeavor, e.g., dog-like robotics systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the teeth and tongue of Li in order to provide a more realistic dog-like robot. The motivation to combine is to allow the robot to better emulate a dog.
Regarding claim 5, the combination of Sato, Li, Stevens, and Nagy teaches the robotic dog of claim 1, and Sato further teaches wherein the guidance and control system further comprises a navigation module configured to use Global Positioning System (GPS) signals for determining a location and path of the robotic dog (0055, In addition, the robot dog 1 includes a GPS unit 63 and is capable of including a global position of the robot dog 1 in the event appended information.).
Regarding claim 6, the combination of Sato, Li, Stevens, and Nagy teaches the robotic dog of claim 1, and Stevens further teaches wherein the power supply comprises a battery and a wireless charging system allowing the robotic dog to charge the battery autonomously (0106, Embodiments of the system 200 can include one or more dog device attachments 206 (e.g., a base, emulating the appearance of a blanket and/or dog bed; attachments physically and/or wirelessly connectable to any suitable regions of the dog device 205; etc.). Dog device attachments 206 can charge the dog device 205 (e.g., wired charging; wireless charging such as inductive wireless charging with a battery coil positioned at the stomach region and/or other suitable region of a dog device 205; etc.), communicate with the dog device 205 (e.g., for performing system updates; for receiving and/or transmitting data; etc.), and/or performing any suitable functionality associated with embodiments of the method 100.).
Sato, Li, Stevens, and Nagy are analogous because they are in a similar field of endeavor, e.g., dog-like robotics systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the wireless charging system of Stevens in order to provide a means of charging the power system of the robot. The motivation to combine is to reduce the need for wired charging, in order to better emulate a dog.
Regarding claim 7, the combination of Sato, Li, Stevens, and Nagy teaches the robotic dog of claim 1, and Li further teaches wherein the mouth further comprises one or more movable parts configured to simulate barking (0015, the head includes an upper pieces and a lower piece. The upper piece is hinged with the lower piece through a head rotary shaft, the front end of the upper piece is provided with canine teeth, and the front end of the lower piece is provided with a dog tongue. Examiner's note: the limitation of "configured to simulate barking" is extremely broad, and "simulating barking" could be reasonably interpreted as merely "opening the mouth.").
Sato, Li, Stevens, and Nagy are analogous because they are in a similar field of endeavor, e.g., dog-like robotics systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the mouth of Li in order to provide a more realistic dog-like robot. The motivation to combine is to allow the robot to better emulate a dog.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BLAKE A WOOD whose telephone number is (571)272-6830. The examiner can normally be reached M-F, 8:00 AM to 4:30 PM Eastern.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Thomas Worden can be reached at (571) 272-4876. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/BLAKE A WOOD/ Primary Examiner, Art Unit 3658
