DETAILED CORRESPONDENCE
This final office action is in response to the Amendments filed on 15 July 2026, regarding application number 19/027,833.
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.
Response to Amendment
Claims 1-20 remain pending in the application. Claims 1-2, 5, 8-9, 12, 15-16 and 19 were amended in the Amendments to the Claims. Claims 3-4, 6-7, 10-11, 13-14, 17-18 and 20 are original.
Applicant’s amendments to the Specification and Claims have overcome each and every objection and 35 U.S.C. 112(b) rejections previously set forth in the non-final office action mailed 16 April 2026. Therefore, the objections and rejections have been withdrawn.
Response to Arguments
Applicant’s arguments, see Pages 10-13, filed 15 July 2026, with respect to the rejections of the claims under 35 U.S.C. § 102 and 35 U.S.C. § 103 have been fully considered and are persuasive. Therefore, the rejections have been withdrawn. However, upon further consideration, a new ground(s) of rejection is made further in view of newly cited reference Hayes-Roth et al. (US 6031549 A). See full details below.
Applicant’s arguments, see Page 13, filed with respect to the rejections of claims 1-20 on the ground of nonstatutory obviousness-type double patenting have been fully considered but they are not persuasive. Applicant has stated the following “…Applicant does not necessarily agree with the Examiner's characterizations concerning the claims set forth in this application, as well as those set forth in the '170 patent. Furthermore, since none of the allegedly conflicting claims has issued, no action need be taken by Applicant at this time because it is unknown whether the claims in the current application will even issue in their current form. Therefore, no Terminal Disclaimer is needed at this time with respect to these provisional obviousness-type double patenting rejections.”. Accordingly, the double patenting rejections have been maintained because no specific arguments were presented. See full details below.
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 § 2146 et seq. 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 filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual 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/apply/applying-online/eterminal-disclaimer.
Claims 1-2, 5-9, 12-16 and 19-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 12-13, 16 and 18 of U.S. Patent No. US 11618170 B2 (and '170 hereinafter), in view of Hayes-Roth et al. (US 6031549 A and Hayes-Roth hereinafter).
Regarding Claims 1, 8 and 15
‘170 recites a computer-implemented method for controlling a social robot (see claim 12), the computer-implemented method comprising:
detecting, by one or more processors, a stimulus corresponding to a set of predefined stimuli based on one or more events experienced by the social robot (see claim 12);
selecting, by the one or more processors, a response to the stimulus based at least in part on a personality profile correlated to a specific mood in a computer memory operatively coupled to the social robot, wherein the personality profile comprises a set of quantitative personality trait values (see claim 12); and
causing, by the one or more processors, the social robot to perform the response (see claim 12).
‘170 is silent regarding each quantitative personality trait value corresponding to a position on a bipolar scale between a pair of opposite personality traits.
Hayes-Roth teaches a computer-implemented method for controlling a social robot (see all Figs., especially Fig. 15; Col. 3, lines 42-67), the computer-implemented method comprising:
selecting, by the one or more processors, a response based at least in part on a personality profile correlated to a specific mood in a computer memory operatively coupled to the social robot (see Fig. 15, all; Abstract, "A system and method for directing the improvisational behavior of a computer-controlled character which enables the character to reflect personality, mood, and other life-like qualities ... The current state includes the character's current mood, directional state, activity state, and location in a virtual world. The method also includes the step of identifying from the set of possible behaviors a subset of feasible behaviors for the character in the current state. Each of the feasible behaviors is evaluated to determine a respective desirability rating of the feasible behavior in the current state. The method further includes the step of selecting a behavior to be executed by the character from the subset of feasible behaviors."; Col. 3, lines 42-67; Col. 11, line 13 - Col. 12, line 5, all, especially "In the preferred embodiment, each mood value is an integer value between -10 and +10. Of course, alternative representations of the character's current mood are possible in alternative embodiments. Mood dimensions 152A, 152B, and 152C also include weights 156A, 156B, and 156C, respectively. The weights are for weighting the relative importance of each mood dimension in determining feasibility and desirability ratings of the possible behaviors, as will be described in detail below."), wherein the personality profile comprises a set of quantitative personality trait values, each quantitative personality trait value corresponding to a position on a bipolar scale between a pair of opposite personality traits (see Fig. 15, all; Fig. 28. elements 222A-C; Col. 11, line 13 - Col. 12, line 5, all, especially "Referring to FIG. 15, the first character's current mood is represented by three mood values on three corresponding mood dimensions. The mood dimensions include an emotional dimension 152A, e.g. sad to happy, an energy dimension 152B, e.g. tired to peppy, and a friendliness dimension 152C, e.g. shy to friendly. Mood values 154A, 154B, and 154C represent the character's current mood on mood dimensions 152A, 152B, and 152C, respectively. In alternative embodiments, other mood dimensions may be used in place of or in addition to mood dimensions 152A, 152B, and 152C. In the preferred embodiment, each mood value is an integer value between -10 and +10. Of course, alternative representations of the character's current mood are possible in alternative embodiments. Mood dimensions 152A, 152B, and 152C also include weights 156A, 156B, and 156C, respectively. The weights are for weighting the relative importance of each mood dimension in determining feasibility and desirability ratings of the possible behaviors, as will be described in detail below."; Col. 15, line 66 - Col. 16, line 11, "Referring again to FIG. 28, screen 216 also includes three adjustable mood sliders 222A, 222B and 222C for displaying the character's current mood values on the three mood dimensions."); and
causing, by the one or more processors, the social robot to perform the response (see Fig. 13, all; Col. 10, lines 19-22, "FIG. 13 shows first and second characters 138A and 138B in a virtual world 136. Characters 138A and 138B are driven by agent applications 50A and 50B, respectively, to execute behaviors in virtual world 136."; Col. 11, lines 56-66Fig. 13, all; Col. 10, lines 19-22, "FIG. 13 shows first and second characters 138A and 138B in a virtual world 136. Characters 138A and 138B are driven by agent applications 50A and 50B, respectively, to execute behaviors in virtual world 136."; Col. 11, lines 56-66).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the process/non-transitory computer-readable medium/computer system of ‘170 to further include a personality profile with quantitative personality trait values corresponding to a position on a bipolar scale between a pair of opposite personality traits, as taught by Hayes-Roth, in order to provide a user interface to easily adjust the social robots personality trait values.
Regarding Claims 2, 9 and 16
Modified ‘170 recites the computer-implemented method of claim 1, the non-transitory computer-readable medium of claim 8 and the computer system of claim 15 (as discussed above in claims 1, 8 and 15),
‘170 further recites wherein the detecting the stimulus corresponding to the set of predefined stimuli based on the set of events experienced by the social robot includes:
receiving, by the one or more processors, sensor data or modeled environment data via a data stream or file (see claim 16);
detecting, by the one or more processors, one or more events corresponding to the sensor data (see claims 12 and 18); and
comparing, by the one or more processors, the one or more events to a stimuli library to determine the stimulus, wherein the stimuli library includes one or more stimuli associated with a defined social response for the social robot (see claim 18).
Regarding Claims 5, 12 and 19
Modified ‘170 recites the computer-implemented method of claim 1, the non-transitory computer-readable medium of claim 8 and the computer system of claim 15 (as discussed above in claims 1, 8 and 15),
‘170 further recites wherein the personality profile comprises a set of quantitative personality trait values, and wherein the response includes a social response (see claim 12).
Regarding Claims 6, 13 and 20
Modified ‘170 recites the computer-implemented method of claim 1, the non-transitory computer-readable medium of claim 8 and the computer system of claim 15 (as discussed above in claims 1, 8 and 15),
‘170 further recites wherein the causing the social robot to perform the response includes sending a set of commands to one or more lower level device drivers or one or more modules (see claim 13).
Regarding Claims 7 and 14
Modified ‘170 recites the computer-implemented method of claim 6 and the non-transitory computer-readable medium of claim 13 (as discussed above in claims 6 and 13),
‘170 further recites wherein the one or more lower level device drivers or the one or more modules respond by performing the response (see claim 13).
Claims 3, 10 and 17 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 12, 16 and 18 of U.S. Patent No. ‘170 (as modified by Hayes-Roth), in view of Le Borgne et al. (US 20170100842 A1).
Regarding Claims 3, 10 and 17
Modified ‘170 recites the computer-implemented method of claim 2, the non-transitory computer-readable medium of claim 9 and the computer system of claim 16 (as discussed above in claims 2, 9 and 16),
‘170 is silent regarding the computer-implemented method further comprising:
recording, by the one or more processors, the sensor data in a memory.
Le Borgne teaches a computer-implemented method for controlling a social robot (see all Figs.; [0007]-[0014]), the computer-implemented method comprising:
detecting, by one or more processors, a stimulus corresponding to a set of predefined stimuli based on a set of events experienced by a social robot (see Figs. 2-3, event detection 202; [0010 "...storing as temporary stimuli in a stimuli store, events detected within a humanoid robot environment, the events being stored with at least an indication of the position of the event and being grouped according to the type of the event detected in at least one of movement stimuli group, sound stimuli group, touch stimuli group, people stimuli group, the stimuli store further storing permanent stimuli to force an action of the humanoid robot;..."]-[0013] and [0045]);
selecting, by the one or more processors, a response to the stimulus based at least in part on a personality profile in a computer memory operatively coupled to the social robot (see [0010]-[0014 "...in response to the processing step, generating one or more actions of the humanoid robot."] and [0043]); and
causing, by the one or more processors, the social robot to perform the response (see [0014 "...in response to the processing step, generating one or more actions of the humanoid robot."], [0043] and [0056]-[0062]);
wherein the detecting the stimulus corresponding to the set of predefined stimuli based on the set of events experienced by the social robot includes:
receiving, by the one or more processors, sensor data or modeled environment data via a data stream or file (see Fig. 3, all; [0038], [0045] and [0070 "The plurality of detectors may be equipped with sensors such as camera, microphone, tactile and olfactory sensors to name a few in order to receive and sense images, sound, odor, taste, etc. The sensor readings are preprocessed so as to extract relevant data in relation to the position of the robot, identification of objects/human beings in its environment, distance of said objects/human beings, words pronounced by human beings or emotions thereof."]-[0076]);
detecting, by the one or more processors, one or more events corresponding to the sensor data (see [0010 "...storing as temporary stimuli in a stimuli store, events detected within a humanoid robot environment, the events being stored with at least an indication of the position of the event and being grouped according to the type of the event detected in at least one of movement stimuli group, sound stimuli group, touch stimuli group, people stimuli group, the stimuli store further storing permanent stimuli to force an action of the humanoid robot;..."], [0045] and [0070]); and
comparing, by the one or more processors, the one or more events to a stimuli library to determine the stimulus, wherein the stimuli library includes one or more stimuli associated with a defined social response for the social robot (see [0010], [0011 "...determining when an event detected fits a people stimulus, i.e. a stimulus originating from a human;…"]-[0014], [0042 "The interaction handling system 200 comprises a stimuli store 204 to store stimuli outputted by the event detection component 202. The interaction handling system 200 further comprises a stimulus selection component 206 coupled to a pertinence rules database 207 defining a set of rules for selecting a stimulus to be processed by a stimulus processing component 210."] and [0051]);
the computer-implemented method further comprising:
recording, by the one or more processors, the sensor data in a memory (see Figs. 2-3, stimuli store/database 204; [0010], [0045]-[0046] and [0071 "The people perception detector generates people perception stimuli to be stored in the group of people perception stimuli in the stimuli database 204."], [0072 "The sound detector generates sound stimuli to be stored in the group of sound stimuli in the stimuli database 204."], [0073 "the tactile detector generates tactile stimuli to be stored in the group of tactile stimuli in the stimuli database 204."] and [0074 "The movement detector generates movement stimuli to be stored in the group of movement stimuli in the stimuli database 204."]-[0076]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to further modify the process/non-transitory computer-readable medium/computer system of modified ‘170 to include a step of recording the sensor data in a memory, as taught by Le Borgne, in order to classify a type of stimulus sensed to facilitate the social robot response.
Claims 4, 11 and 18 rejected on the ground of nonstatutory double patenting as being unpatentable over claims 12, 16 and 18 of U.S. Patent No. ‘170 (as modified by Hayes-Roth), in view of Saito (US 20020016128 A1).
Regarding Claims 4, 11 and 18
Modified ‘170 recites the computer-implemented method of claim 2, the non-transitory computer-readable medium of claim 9 and the computer system of claim 16 (as discussed above in claims 2, 9 and 16),
‘170 is silent regarding the computer-implemented method further comprising:
placing, by the one or more processors, an identifier corresponding to the detected one or more events in a memory.
Saito teaches a computer-implemented method for controlling a social robot (see all Figs.; [0002] and [0008]), the computer-implemented method comprising:
detecting, by one or more processors, a stimulus corresponding to a set of predefined stimuli based on a set of events experienced by a social robot (see Fig. 8, all; [0008], [0040], [0043 "The stimulus recognition unit 11 detects the existence of a stimulus from the outside based on the stimulus signal from the stimulus sensors 5, and distinguishes the contents of the stimulus (kinds or stimulus places)."]-[0050], [0058] and [0061 "Further, in the field “INPUT No.” as shown in FIGS. 5 to 7, stimulus numbers (i-01 to i-07 . . . ), which show the classifications (the stimulus given parts or contents) of the stimulus (input) from the outside, are written. The correspondence relation between the stimulus numbers and their meanings are referred to FIG. 8."]-[0063]);
selecting, by the one or more processors, a response to the stimulus based at least in part on a personality profile in a computer memory operatively coupled to the social robot (see "Voice No." and "Action No." in Figs. 5-7 and 9-10; [0011 "...it is preferable to further provide a character state map, in which a plurality of character parameters that affect the reaction behavior of the interactive toy is set."], [0041]-[0043 "The stimulus recognition unit 11 detects the existence of a stimulus from the outside based on the stimulus signal from the stimulus sensors 5, and distinguishes the contents of the stimulus (kinds or stimulus places). In the embodiment of the present invention, as described later, the reaction behavior (output) of the dog type robot 1 changes with contents of a stimulus."], [0051 "A fundamental behavior tendency, the reaction behavior to stimulus, and degree of the growth, or the like, depend on the character parameter XY."]-[0052] and [0061]-[0063]); and
causing, by the one or more processors, the social robot to perform the response (see Figs. 5-7, all; [0008 "...a control member for controlling the action member to make the interactive toy take reaction behavior to the stimulus detected from the stimulus detecting member, is provided."], [0041] and [0062 "After taking this appearance probability into consideration, supposing the reaction behavior pattern 31 is selected based on a random number, the voice “vce(01)” and the action “act(01)” will be selected. As a result, according to FIGS. 9 and 10, the dog type robot 1 “draws back” yelping “yap!”, that is, the dog type robot 1 takes the same action as an actual dog."]-[0063]);
wherein the detecting the stimulus corresponding to the set of predefined stimuli based on the set of events experienced by the social robot includes:
receiving, by the one or more processors, sensor data or modeled environment data via a data stream or file (see Fig. 2, stimulus sensors 5; [0008], [0040 "Here, the stimulus sensors 5 are sensors that detect the stimulus received from the outside. A touch sensor, an optical sensor, and a microphone or the like are used therein. The touch sensor is a sensor that detects whether a user touched a predetermined portion of the dog type robot 1 or not, that is, a sensor for detecting a touch stimulus. The optical sensor is a sensor that detects the change of the external brightness, that is, a sensor for detecting a light stimulus. The microphone is a sensor that detects addressing form a user, that is, a sensor for detecting a sound stimulus."]-[0043] and [0062]-[0063]);
detecting, by the one or more processors, one or more events corresponding to the sensor data (see Fig. 8, Stimulus Part (Content); [0043 "The stimulus recognition unit 11 detects the existence of a stimulus from the outside based on the stimulus signal from the stimulus sensors 5, and distinguishes the contents of the stimulus (kinds or stimulus places)."], [0058 "The stimulus that the dog type robot 1 received, is classified into categories, concretely, in a contact stimulus (the touch stimulus) and a non-contact stimulus (the light stimulus or the sound stimulus) corresponding to the contents of the stimulus."]-[0050], [0058] and [0061]-[0063]); and
comparing, by the one or more processors, the one or more events to a stimuli library to determine the stimulus, wherein the stimuli library includes one or more stimuli associated with a defined social response for the social robot (see Fig. 8, Stimulus No.; [0043], [0050], [0058] and [0061 "Further, in the field “INPUT No.” as shown in FIGS. 5 to 7, stimulus numbers (i-01 to i-07 . . . ), which show the classifications (the stimulus given parts or contents) of the stimulus (input) from the outside, are written. The correspondence relation between the stimulus numbers and their meanings are referred to FIG. 8. Further, in the field “OUTPUT No.”, an output ID, which shows the contents of the reaction behavior (output) of the dog type robot 1, is written. "]-[0063]).
the computer-implemented method further comprising:
placing, by the one or more processors, an identifier corresponding to the detected one or more events in a memory (see Fig. 3, external stimulus data 22; Fig. 8, Stimulus No.; [0043], [0050 "In the reaction behavior data storage unit 12, various kinds of data related to the reaction behavior that the dog type robot 1 takes, are stored. Concretely, as shown in FIG. 3, a reaction behavior pattern table 21, an external stimulus data table 22, a voice data table 23, and an action data table 24 or the like, are housed therein."], and [0061 "Further, in the field “INPUT No.” as shown in FIGS. 5 to 7, stimulus numbers (i-01 to i-07 . . . ), which show the classifications (the stimulus given parts or contents) of the stimulus (input) from the outside, are written. The correspondence relation between the stimulus numbers and their meanings are referred to FIG. 8."]-[0063]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to further modify the process/non-transitory computer-readable medium/computer system of modified ‘170 to include a step of placing an identifier corresponding to the detected one or more events in a memory, as taught by Saito, in order to classify various stimuli and to determine an appropriate response to each of the stimuli.
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.
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.
Claims 1-2, 4, 6-9, 11, 13-16, 18 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Saito (US 20020016128 A1 and Saito hereinafter), in view of Hayes-Roth et al. (US 6031549 A and Hayes-Roth hereinafter).
Regarding Claims 1, 8 and 15
Regarding claim 1, Saito teaches a computer-implemented method for controlling a social robot (see all Figs.; [0002] and [0008]), the computer-implemented method comprising:
detecting, by one or more processors, a stimulus corresponding to a set of predefined stimuli based on one or more events experienced by the social robot (see Fig. 8, all; [0008], [0040], [0043 "The stimulus recognition unit 11 detects the existence of a stimulus from the outside based on the stimulus signal from the stimulus sensors 5, and distinguishes the contents of the stimulus (kinds or stimulus places)."]-[0050], [0058] and [0061 "Further, in the field “INPUT No.” as shown in FIGS. 5 to 7, stimulus numbers (i-01 to i-07 . . . ), which show the classifications (the stimulus given parts or contents) of the stimulus (input) from the outside, are written. The correspondence relation between the stimulus numbers and their meanings are referred to FIG. 8."]-[0063]);
selecting, by the one or more processors, a response to the stimulus based at least in part on a personality profile correlated to a specific mood in a computer memory operatively coupled to the social robot (see "Voice No." and "Action No." in Figs. 5-7 and 9-10; [0011 "...it is preferable to further provide a character state map, in which a plurality of character parameters that affect the reaction behavior of the interactive toy is set."], [0041]-[0043 "The stimulus recognition unit 11 detects the existence of a stimulus from the outside based on the stimulus signal from the stimulus sensors 5, and distinguishes the contents of the stimulus (kinds or stimulus places). In the embodiment of the present invention, as described later, the reaction behavior (output) of the dog type robot 1 changes with contents of a stimulus."], [0051 "A fundamental behavior tendency, the reaction behavior to stimulus, and degree of the growth, or the like, depend on the character parameter XY. In other words, changes in the reaction behavior of the dog type robot 1 occurs by changes of the value of the character parameter XY housed in the character state storage unit 13."]-[0053] and [0061]-[0065]), wherein the personality profile comprises a set of quantitative personality trait values (see Figs. 5-7 and 11, all; [0011], [0051]-[0053 "The point counting unit 15 counts a generated action point caused by the reaction behavior of the dog type robot 1. The action point is counted (added/subtracted) to the total value of the action points, and the latest total value is stored in the RAM. Here, an “action point” means a generated score caused by the reaction behavior (output) of the dog type robot 1. The total value of the action points corresponds to the level of communication between the dog type robot 1 and a user. It also becomes a base parameter related to the update of the character parameter XY, which determines the character state of the dog type robot 1."], [0057], [0060 "As for an X value of the character parameter XY, one of the “S”, and “A” to “D” is set, and as for a Y value thereof, one of the “1” to “4” is set. Since the character parameters XY in FIG. 5 are uniformly set to “S1”, the character of the dog type robot 1 in the first stage (a dog level) does not change. Similarly, since the character parameters XY in FIG. 6 are uniformly set to “S2”, the character of the dog type robot 1 in the second stage (a dog+human level) does not change. On the other hand, in the third stage (a human level), since the character parameters XY are classified into sixteen kinds from “A1” to “D4”, by the update of the character parameter XY, the character of the dog type robot 1 changes to sixteen kinds (cf. FIGS. 7 and 11)."] and [0065]); and
causing, by the one or more processors, the social robot to perform the response (see Figs. 5-7, all; [0008 "...a control member for controlling the action member to make the interactive toy take reaction behavior to the stimulus detected from the stimulus detecting member, is provided."], [0041] and [0062 "After taking this appearance probability into consideration, supposing the reaction behavior pattern 31 is selected based on a random number, the voice “vce(01)” and the action “act(01)” will be selected. As a result, according to FIGS. 9 and 10, the dog type robot 1 “draws back” yelping “yap!”, that is, the dog type robot 1 takes the same action as an actual dog."]-[0063]).
Regarding claim 8, Saito additionally teaches a non-transitory computer-readable medium comprising one or more sequences of instructions (see all Figs.; [0008] and [0041]-[0042]), which, when executed by one or more processors, causes a computing system to perform operations comprising the above steps (as discussed above).
Regarding claim 15, Saito additionally teaches a computer system for controlling a social robot (see all Figs.; [0002] and [0008]), comprising:
one or more processors (see [0041]); and
a memory having programming instructions stored thereon (see [0041]-[0042]), which, when executed by the one or more processors, causes the system to perform operations comprising the above steps (as discussed above).
Saito is silent regarding each quantitative personality trait value corresponding to a position on a bipolar scale between a pair of opposite personality traits.
Hayes-Roth teaches a computer-implemented method for controlling a social robot (see all Figs., especially Fig. 15; Col. 3, lines 42-67), the computer-implemented method comprising:
selecting, by the one or more processors, a response based at least in part on a personality profile correlated to a specific mood in a computer memory operatively coupled to the social robot (see Fig. 15, all; Abstract, "A system and method for directing the improvisational behavior of a computer-controlled character which enables the character to reflect personality, mood, and other life-like qualities ... The current state includes the character's current mood, directional state, activity state, and location in a virtual world. The method also includes the step of identifying from the set of possible behaviors a subset of feasible behaviors for the character in the current state. Each of the feasible behaviors is evaluated to determine a respective desirability rating of the feasible behavior in the current state. The method further includes the step of selecting a behavior to be executed by the character from the subset of feasible behaviors."; Col. 3, lines 42-67; Col. 11, line 13 - Col. 12, line 5, all, especially "In the preferred embodiment, each mood value is an integer value between -10 and +10. Of course, alternative representations of the character's current mood are possible in alternative embodiments. Mood dimensions 152A, 152B, and 152C also include weights 156A, 156B, and 156C, respectively. The weights are for weighting the relative importance of each mood dimension in determining feasibility and desirability ratings of the possible behaviors, as will be described in detail below."), wherein the personality profile comprises a set of quantitative personality trait values, each quantitative personality trait value corresponding to a position on a bipolar scale between a pair of opposite personality traits (see Fig. 15, all; Fig. 28. elements 222A-C; Col. 11, line 13 - Col. 12, line 5, all, especially "Referring to FIG. 15, the first character's current mood is represented by three mood values on three corresponding mood dimensions. The mood dimensions include an emotional dimension 152A, e.g. sad to happy, an energy dimension 152B, e.g. tired to peppy, and a friendliness dimension 152C, e.g. shy to friendly. Mood values 154A, 154B, and 154C represent the character's current mood on mood dimensions 152A, 152B, and 152C, respectively. In alternative embodiments, other mood dimensions may be used in place of or in addition to mood dimensions 152A, 152B, and 152C. In the preferred embodiment, each mood value is an integer value between -10 and +10. Of course, alternative representations of the character's current mood are possible in alternative embodiments. Mood dimensions 152A, 152B, and 152C also include weights 156A, 156B, and 156C, respectively. The weights are for weighting the relative importance of each mood dimension in determining feasibility and desirability ratings of the possible behaviors, as will be described in detail below."; Col. 15, line 66 - Col. 16, line 11, "Referring again to FIG. 28, screen 216 also includes three adjustable mood sliders 222A, 222B and 222C for displaying the character's current mood values on the three mood dimensions."); and
causing, by the one or more processors, the social robot to perform the response (see Fig. 13, all; Col. 10, lines 19-22, "FIG. 13 shows first and second characters 138A and 138B in a virtual world 136. Characters 138A and 138B are driven by agent applications 50A and 50B, respectively, to execute behaviors in virtual world 136."; Col. 11, lines 56-66Fig. 13, all; Col. 10, lines 19-22, "FIG. 13 shows first and second characters 138A and 138B in a virtual world 136. Characters 138A and 138B are driven by agent applications 50A and 50B, respectively, to execute behaviors in virtual world 136."; Col. 11, lines 56-66).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the process/non-transitory computer-readable medium/computer system of Saito to further include a personality profile with quantitative personality trait values corresponding to a position on a bipolar scale between a pair of opposite personality traits, as taught by Hayes-Roth, in order to provide a user interface to easily adjust the social robots personality trait values.
Regarding Claims 2, 9 and 16
Modified Saito teaches the computer-implemented method of claim 1, the non-transitory computer-readable medium of claim 8 and the computer system of claim 15 (as discussed above in claims 1, 8 and 15),
Saito further teaches wherein the detecting the stimulus corresponding to the set of predefined stimuli based on the one or more events experienced by the social robot includes:
receiving, by the one or more processors, sensor data or modeled environment data via a data stream or file (see Fig. 2, stimulus sensors 5; [0008], [0040 "Here, the stimulus sensors 5 are sensors that detect the stimulus received from the outside. A touch sensor, an optical sensor, and a microphone or the like are used therein. The touch sensor is a sensor that detects whether a user touched a predetermined portion of the dog type robot 1 or not, that is, a sensor for detecting a touch stimulus. The optical sensor is a sensor that detects the change of the external brightness, that is, a sensor for detecting a light stimulus. The microphone is a sensor that detects addressing form a user, that is, a sensor for detecting a sound stimulus."]-[0043] and [0062]-[0063]);
detecting, by the one or more processors, one or more events corresponding to the sensor data (see Fig. 8, Stimulus Part (Content); [0043 "The stimulus recognition unit 11 detects the existence of a stimulus from the outside based on the stimulus signal from the stimulus sensors 5, and distinguishes the contents of the stimulus (kinds or stimulus places)."], [0058 "The stimulus that the dog type robot 1 received, is classified into categories, concretely, in a contact stimulus (the touch stimulus) and a non-contact stimulus (the light stimulus or the sound stimulus) corresponding to the contents of the stimulus."]-[0050], [0058] and [0061]-[0063]); and
comparing, by the one or more processors, the one or more events to a stimuli library to determine the stimulus, wherein the stimuli library includes one or more stimuli associated with a defined social response for the social robot (see Fig. 8, Stimulus No.; [0043], [0050], [0058] and [0061 "Further, in the field “INPUT No.” as shown in FIGS. 5 to 7, stimulus numbers (i-01 to i-07 . . . ), which show the classifications (the stimulus given parts or contents) of the stimulus (input) from the outside, are written. The correspondence relation between the stimulus numbers and their meanings are referred to FIG. 8. Further, in the field “OUTPUT No.”, an output ID, which shows the contents of the reaction behavior (output) of the dog type robot 1, is written. "]-[0063]).
Regarding Claims 4, 11 and 18
Modified Saito teaches the computer-implemented method of claim 2, the non-transitory computer-readable medium of claim 9 and the computer system of claim 16 (as discussed above in claims 2, 9 and 16),
Saito further teaches the computer-implemented method further comprising:
placing, by the one or more processors, an identifier corresponding to the detected one or more events in a memory (see Fig. 3, external stimulus data 22; Fig. 8, Stimulus No.; [0043], [0050 "In the reaction behavior data storage unit 12, various kinds of data related to the reaction behavior that the dog type robot 1 takes, are stored. Concretely, as shown in FIG. 3, a reaction behavior pattern table 21, an external stimulus data table 22, a voice data table 23, and an action data table 24 or the like, are housed therein."], and [0061 "Further, in the field “INPUT No.” as shown in FIGS. 5 to 7, stimulus numbers (i-01 to i-07 . . . ), which show the classifications (the stimulus given parts or contents) of the stimulus (input) from the outside, are written. The correspondence relation between the stimulus numbers and their meanings are referred to FIG. 8."]-[0063]).
Regarding Claims 6, 13 and 20
Modified Saito teaches the computer-implemented method of claim 1, the non-transitory computer-readable medium of claim 8 and the computer system of claim 15 (as discussed above in claims 1, 8 and 15),
Saito further teaches wherein the causing the social robot to perform the response includes sending a set of commands to one or more lower level device drivers or one or more modules (see Fig. 1, actuators; [0008 "...a control member for controlling the action member to make the interactive toy take reaction behavior to the stimulus detected from the stimulus detecting member, is provided."], [0040]-[0041 "Then, the control unit controls the actuators 3 or the speaker 4 so that the dog type robot 1 will act according to the determined reaction behavior pattern."], [0054] and [0062]-[0063]).
Regarding Claims 7 and 14
Modified Saito teaches the computer-implemented method of claim 6 and the non-transitory computer-readable medium of claim 13 (as discussed above in claims 6 and 13),
Saito further teaches wherein the one or more lower level device drivers or the one or more modules respond by performing the response (see Fig. 1, actuators; [0008 "...a control member for controlling the action member to make the interactive toy take reaction behavior to the stimulus detected from the stimulus detecting member, is provided."], [0040]-[0041 "Then, the control unit controls the actuators 3 or the speaker 4 so that the dog type robot 1 will act according to the determined reaction behavior pattern."], [0054] and [0062]-[0063]).
Claims 3, 10 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Saito (as modified by Hayes-Roth) as applied to claims 2, 9 and 16 above, and further in view of Le Borgne et al. (US 20170100842 A1 and Le Borgne hereinafter).
Regarding Claims 3, 10 and 17
Modified Saito teaches the computer-implemented method of claim 2, the non-transitory computer-readable medium of claim 9 and the computer system of claim 16 (as discussed above in claims 2, 9 and 16),
Saito is silent regarding the computer-implemented method further comprising:
recording, by the one or more processors, the sensor data in a memory.
Le Borgne teaches a computer-implemented method for controlling a social robot (see all Figs.; [0007]-[0014]), the computer-implemented method comprising:
detecting, by one or more processors, a stimulus corresponding to a set of predefined stimuli based on a set of events experienced by a social robot (see Figs. 2-3, event detection 202; [0010 "...storing as temporary stimuli in a stimuli store, events detected within a humanoid robot environment, the events being stored with at least an indication of the position of the event and being grouped according to the type of the event detected in at least one of movement stimuli group, sound stimuli group, touch stimuli group, people stimuli group, the stimuli store further storing permanent stimuli to force an action of the humanoid robot;..."]-[0013] and [0045]);
selecting, by the one or more processors, a response to the stimulus based at least in part on a personality profile in a computer memory operatively coupled to the social robot (see [0010]-[0014 "...in response to the processing step, generating one or more actions of the humanoid robot."] and [0043]); and
causing, by the one or more processors, the social robot to perform the response (see [0014 "...in response to the processing step, generating one or more actions of the humanoid robot."], [0043] and [0056]-[0062]);
wherein the detecting the stimulus corresponding to the set of predefined stimuli based on the set of events experienced by the social robot includes:
receiving, by the one or more processors, sensor data or modeled environment data via a data stream or file (see Fig. 3, all; [0038], [0045] and [0070 "The plurality of detectors may be equipped with sensors such as camera, microphone, tactile and olfactory sensors to name a few in order to receive and sense images, sound, odor, taste, etc. The sensor readings are preprocessed so as to extract relevant data in relation to the position of the robot, identification of objects/human beings in its environment, distance of said objects/human beings, words pronounced by human beings or emotions thereof."]-[0076]);
detecting, by the one or more processors, one or more events corresponding to the sensor data (see [0010 "...storing as temporary stimuli in a stimuli store, events detected within a humanoid robot environment, the events being stored with at least an indication of the position of the event and being grouped according to the type of the event detected in at least one of movement stimuli group, sound stimuli group, touch stimuli group, people stimuli group, the stimuli store further storing permanent stimuli to force an action of the humanoid robot;..."], [0045] and [0070]); and
comparing, by the one or more processors, the one or more events to a stimuli library to determine the stimulus, wherein the stimuli library includes one or more stimuli associated with a defined social response for the social robot (see [0010], [0011 "...determining when an event detected fits a people stimulus, i.e. a stimulus originating from a human;…"]-[0014], [0042 "The interaction handling system 200 comprises a stimuli store 204 to store stimuli outputted by the event detection component 202. The interaction handling system 200 further comprises a stimulus selection component 206 coupled to a pertinence rules database 207 defining a set of rules for selecting a stimulus to be processed by a stimulus processing component 210."] and [0051]);
the computer-implemented method further comprising:
recording, by the one or more processors, the sensor data in a memory (see Figs. 2-3, stimuli store/database 204; [0010], [0045]-[0046] and [0071 "The people perception detector generates people perception stimuli to be stored in the group of people perception stimuli in the stimuli database 204."], [0072 "The sound detector generates sound stimuli to be stored in the group of sound stimuli in the stimuli database 204."], [0073 "the tactile detector generates tactile stimuli to be stored in the group of tactile stimuli in the stimuli database 204."] and [0074 "The movement detector generates movement stimuli to be stored in the group of movement stimuli in the stimuli database 204."]-[0076]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to further modify the process/non-transitory computer-readable medium/computer system of modified Saito to include a step of recording the sensor data in a memory, as taught by Le Borgne, in order to classify a type of stimulus sensed to facilitate the social robot response.
Claims 5, 12 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Saito (as modified by Hayes-Roth) as applied to claims 1, 8 and 15 above, and further in view of Blakely et al. (US 20170282383 A1 and Blakely hereinafter).
Regarding Claims 5, 12 and 19
Modified Saito teaches the computer-implemented method of claim 1, the non-transitory computer-readable medium of claim 8 and the computer system of claim 15 (as discussed above in claims 1, 8 and 15),
Saito is silent regarding wherein the personality profile is derived from a character portrayal in a fictional work, a dramatic performance, or by a real-life person.
Blakely teaches a computer-implemented method for controlling a social robot (see all Figs.; [0011]), the computer-implemented method comprising:
detecting, by one or more processors, a stimulus corresponding to a set of predefined stimuli based on one or more events experienced by the social robot (see [0011 "A system is disclosed that executes an audio response mode to detect and analyze audio content from a content source, and implement audio fingerprinting to determine whether the audio content corresponds to a known or stored audio or content file."], [0038], [0040 "Based on the audio fingerprinting, the processor 114 can identify an audio signature corresponding to a particular segment or portion of the content being outputted by the content source 150. For example, the segment can be a scary or exciting scene in a movie, or a portion of a song."]-[0041] and [0046 "For example, the response actions 228 can cause the robotic device 250 to respond to actions performed by the movie character in real time while the user watches the film. "]);
selecting, by the one or more processors, a response to the stimulus based at least in part on a personality profile correlated to a specific mood in a computer memory operatively coupled to the social robot (see [0011 "Such stored files can be pre-correlated at specified playtimes to response actions that can be performed by a robotic device, and stored in a response log. In response to identifying the audio fingerprint in a stored file, the system can perform a lookup in the response log to determine a response action to be performed by the robotic device."], [0038], [0040 "Based on the audio fingerprinting, the processor 114 can identify an audio signature corresponding to a particular segment or portion of the content being outputted by the content source 150. For example, the segment can be a scary or exciting scene in a movie, or a portion of a song. Based on the content segment, the processor 114 can execute a corresponding response action 147 comprising a set of actions performed by the robotic device 100 that gives the robotic device 100 the appearance and expression of personality."]-[0041] and [0046 "In some examples, the robotic device 250 can correspond to a character in a film, and the response actions 228 can provide a viewer/user with additional entertainment to supplement a movie watching experience. For example, the response actions 228 can cause the robotic device 250 to respond to actions performed by the movie character in real time while the user watches the film. Thus, while watching the film with the robotic device 250 and mobile computing device 200 executing the audio response mode, the robotic device 250 can mimic the personality traits and characteristics of the movie character to which it corresponds."]), wherein the personality profile comprises a set of quantitative personality trait values ([0040]-[0041] and [0046 "Thus, while watching the film with the robotic device 250 and mobile computing device 200 executing the audio response mode, the robotic device 250 can mimic the personality traits and characteristics of the movie character to which it corresponds."]); and
causing, by the one or more processors, the social robot to perform the response (see [0011 "The system can then generate a set of control commands executable by the robotic device in order to cause the robotic device to perform the response action."], [0040]-[0041] and [0046]),
wherein the personality profile is derived from a character portrayal in a fictional work or a dramatic performance (see [0046 "In some examples, the robotic device 250 can correspond to a character in a film, and the response actions 228 can provide a viewer/user with additional entertainment to supplement a movie watching experience. For example, the response actions 228 can cause the robotic device 250 to respond to actions performed by the movie character in real time while the user watches the film. Thus, while watching the film with the robotic device 250 and mobile computing device 200 executing the audio response mode, the robotic device 250 can mimic the personality traits and characteristics of the movie character to which it corresponds."] and [0040]-[0041]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to further modify the process/non-transitory computer-readable medium/computer system of modified Saito to include a personality profile derived from a character portrayal in a fictional work or a dramatic performance, as taught by Blakely, in order to provide a user who’s watching a movie with additional entertainment to supplement the movie watching experience.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: Johnson (US 20160031081 A1 and Johnson hereinafter).
Johnson teaches at least a computer-implemented method for controlling a social robot, the computer-implemented method comprising:
a personality profile correlated to a specific mood in a computer memory operatively coupled to the social robot, wherein the personality profile comprises a set of quantitative personality trait values, each quantitative personality trait value corresponding to a position on a scale. See at least Figure 4 and its corresponding paragraphs.
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 TANNER LUKE CULLEN whose telephone number is (303)297-4384. The examiner can normally be reached Monday-Friday 9:00-5:00 MT.
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/TANNER L CULLEN/Examiner, Art Unit 3656
/KHOI H TRAN/Supervisory Patent Examiner, Art Unit 3656
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