DETAILED ACTION
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 Arguments
Applicant’s arguments, filed 12/29/2025, with respect to rejections of claims 16-20 under 35 U.S.C. 103 have been fully considered and are persuasive. The rejections of claims 16-20 have been withdrawn. Additionally, Applicants amendments have overcome the rejections under 35 U.S.C 112.
Applicant’s arguments with respect to claim(s) 1-15 have been considered but are moot because applicant’s amendments have changed the scope of the claims. While Poursohi may not teach the aspects of multiple service tiers or an advertisement of availability, these features are found the Golgiri and Srivastav. As will be shown below, Golgiri teaches the benefits of advertising additional functionality available to the user, and Golgiri and Srivastav each demonstrate the business benefits of charging customers for services in tiers.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 1, 4-7, and 9-13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Poursohi (US-8428777-B1) in view of Golgiri (US-20200186620-A1), and Srinastav (US 20230286157 A1).
Claim 1
Poursohi teaches
a processing system including a processor; and
a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, the operations comprising:
(Poursohi - [col 3, ln 4-7] The device includes a processor and memory. The memory includes instructions stored therein executable by the processor to perform functions. )
obtaining first data associated with a first physical robot of a first service tier operating in a smart community, wherein the first data comprises a first historical listing of a first plurality of tasks that had been performed by the first physical robot;
obtaining second data associated with a second physical robot of the first service tier operating in the smart community, wherein the second data comprises a second historical listing of a second plurality of tasks that had been performed by the second physical robot,
and wherein the second plurality of tasks and the first plurality of tasks include a common task;
obtaining third data associated with a third physical robot of a second service tier lower than the first service tier operating in the smart community, wherein the third data comprises an indication of a current task being performed by the third physical robot, and wherein the current task is the common task;
predicting, based at least in part upon the first data, the second data, and the third data, a future task that will be performed by the third physical robot, wherein the future task that is predicted is a task selected from the first plurality of tasks and the second plurality of tasks;
(Poursohi - [col 24, ln 16-32] In the case robot 564 is unable achieve the suitable grip on the grand piano to execute the subtask of moving the grand piano with robot 562, the server may determine that a computational capability of robot 564 is unable to determine proper movements for a mechanical actuator arm of robot 564 to achieve the suitable grip on the grand piano, and may proceed to acquire instructions informing robot 564 how to achieve the suitable grip. In one case, the server may query robot 562 for the instructions, if robot 562 has already achieved a suitable grip on the grand piano. Once instructions informing robot 564 how to achieve the suitable grip on the grand piano has been acquired, the instructions may be provided to robot 564 for robot 564 to follow and execute the task. The set of movement instructions may also be stored and distributed to other robots when other robots are assigned subtasks of moving a grand piano.)
EXAMINER NOTE: Robot 564 corresponds to the first robot, Robot 562 corresponds to the second robot, and "other robots" include the third robot. The common task in this example is "moving a grand piano." When another robot is presented with the current task of "moving a grand piano," the future task of "achieving a suitable grip on the grand piano," is determined based on the historical data of Robot 564 and Robot 562.
(Poursohi - [col 11, ln 24-25] In yet another example, locations A and B may be different floors of an office building.
[col 11, ln 54-56] In a further example, tasks 552, 554, and 556 may be subtasks of a larger task. In one case, the larger task may be to clean up a house. )
EXAMINER NOTE: An office building is a place of business. Because the devices are operating in a connected fashion, the office building qualifies as a smart community under the broadest reasonable interpretation. Likewise, the robot may be used to clean up a house (smart home).
CLAIM INTERPRETATION NOTE: Regarding the various "service tiers," Examiner interprets the first service tier as a state in which a robot readily has access to a given skill. So Robots 564 and 562 are associated with the first service tier. "Other robots," which includes the third robot, would be associated with the third service tier when the same skill is not readily available.
selecting, based at least in part upon the future task that is predicted, a downloadable service associated with a higher service tier than the second service tier that can be used by the third physical robot to carry out the future task that is predicted, wherein the selecting results in a selected downloadable service
(Poursohi - [col 10, ln 45-57] Thus, in some examples, robots may share learned behaviors through the cloud 410. The cloud 410 may have a server that stores robot learned activities or behaviors resulting in a shared knowledge-base of behaviors and heuristics for object interactions (e.g., a robot "app store"). Specifically, a given robot may perform actions and builds a map of an area, and then the robot can upload the data to the cloud 410 to share this knowledge with all other robots. In this example, a transportation of the given robot's "consciousness" can be made through the cloud 410 from one robot to another (e.g., robot "Bob" builds a map, and the knowledge of "Bob" can be downloaded onto another robot to receive knowledge of the map).)
EXAMINER NOTE: This example illustrates that the tasks are distributed via downloading from the cloud. Downloading the task knowledge also serves as a notification of availability, because the download would be impossible if the task knowledge were not available.
Poursohi alone may not explicitly teach the following limitations in combinatoin. However, Golgiri teaches
providing, to the third physical robot, an advertisement of an availability of the selected downloadable service for instantiation and execution on the third physical robot; and
(Golgiri - [0016] … Responsive to identifying an occurrence of one of the predefined vehicle operating conditions, the vehicle usage application 120 may be configured to communicate a notification to the user of the vehicle 102 that indicates availability of a new vehicle feature associated with the predefined vehicle operating condition, and to upgrade components of the vehicle 102 so as to enable the vehicle 102 to provide the new vehicle feature upon request by the vehicle user.
Subsequent to the providing the advertisement, providing the selected downloadable service to the third physical robot
(Golgiri - [0045] In alternative embodiments, rather than already being in possession of the updates for implementing a new vehicle feature, the vehicle computing platform 112 may be configured to submit a request to the remote server 104 that identifies the vehicle feature to be enabled. Responsive to receiving the request, the remote server 104 may be configured to query the OTA update database 154 for the OTA update corresponding to the requested vehicle feature, and to transmit the returned OTA update to the vehicle computing platform 112 via the TCU 126. The vehicle computing platform 112 may then be configured to upgrade the vehicle 102 to provide the vehicle feature for the trial period by installing the received OTA update received from the remote server 104.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Poursohi's knowledge sharing with Golgiri's teachings. Golgiri shows that OTA updates can be leveraged as an additional revenue stream by charging customers for access to hardware that they already paid for. Additionally, Golgiri's teachings of notifying the user of available updates serves to inform the user of features which they may not have been aware of prior to needing them.
(Golgiri - [0049] In block 214, the driver of the vehicle 102 may be communicated a notification informing that the trial period for the new vehicle feature is over. The communicated notification may also indicate that the vehicle 102 may be upgraded to persistently provide the vehicle feature, such as in response to a request and payment from the driver.
[0055] A vehicle may be capable of being upgraded to provide additional features via OTA software updates, which enables upgrading the vehicle on the fly without having to take the vehicle to a dealership or other vehicle service retail location. However, the user of the vehicle may not be aware of the several available upgrades, including those that would benefit the particular way in which the user operates the vehicle. Accordingly, the vehicle may be configured to dynamically suggest and implement vehicle upgrades based on the way in which the vehicle is operated. A user is thus informed and able to take advantage of additional vehicle features that are particularly beneficial to the user.
To further demonstrate the ubiquity and usefulness of the subscription model, Srivastav also describes a business model in which robot skills are sold to customers in tiered subscriptions, where a portion of the revenue is distributed to the creator of a robotic skill, thus encouraging the creation of additional content.
(Srivastav - [0031] A user may download a skill from the library on the robot and start using it. The download can have a one-time fee. The skill can also charge a utility price based on the duration that it is used for. A portion of revenue from the skill purchase goes to the creator of the skill and creators of the predecessor skills in the derivation chain of the skill. The skills may be classified in tiers. The lower tiers may cost less. The robot's subscription level can also determine the tier of skills it can access. The user can choose to keep a skill taught by the user as private. The user account can have private library of such skills. Multiple robots in a deployment can collaborate on tasks. They can also use collective experiences to enhance the common skill.)
Claim 4
The combination of Poursohi, Golgiri, and Srivastav teaches the limitations of claim 1 as outlined above. As shown above, the cited combination also teaches
wherein the selecting the downloadable service that can be used by the third physical robot to carry out the future task that is predicted comprises selecting the downloadable service from a database that correlates each of a plurality of tasks with each of a plurality of downloadable services.
(Golgiri - [0045] In alternative embodiments, rather than already being in possession of the updates for implementing a new vehicle feature, the vehicle computing platform 112 may be configured to submit a request to the remote server 104 that identifies the vehicle feature to be enabled. Responsive to receiving the request, the remote server 104 may be configured to query the OTA update database 154 for the OTA update corresponding to the requested vehicle feature, and to transmit the returned OTA update to the vehicle computing platform 112 via the TCU 126. The vehicle computing platform 112 may then be configured to upgrade the vehicle 102 to provide the vehicle feature for the trial period by installing the received OTA update received from the remote server 104.)
Claim 5
The combination of Poursohi, Golgiri, and Srivastav teaches the limitations of claim 4 as outlined above. As shown above, the cited combination also teaches
wherein the downloadable service that is selected is a microservice.
(Poursohi - [col 19, ln 34-40] In scenario B, robot 562 may be assigned a task 552 of arranging furniture at in room 560, which in this case may be a concert hall. In one example, the task 552 of arranging furniture in room 560 may include moving a large number of chairs and a grand piano. In one case, the server may determine that assistance is required for robot 562 to execute a subtask of task 552 involving moving the grand piano, …)
EXAMINER NOTE: Tasks are composed of multiple subtasks (microservices)
Claim 6
The combination of Poursohi, Golgiri, and Srivastav teaches the limitations of claim 1 as outlined above. As shown above, the cited combination also teaches
wherein the smart community comprises one or more homes, one or more retail businesses, one or more wholesale businesses, one or more factories, one or more schools, one or more colleges, one or more universities, one or more doctors' offices, one or more dentist's offices, one or more hospitals, or any combination thereof.
(Poursohi - [col 11, ln 54-56] In a further example, tasks 552, 554, and 556 may be subtasks of a larger task. In one case, the larger task may be to clean up a house. )
Claim 7
The combination of Poursohi, Golgiri, and Srivastav teaches the limitations of claim 1 as outlined above. As shown above, the cited combination also teaches
the first physical robot is a first ground-mobile robot, a first air-mobile robot, or
any first combination thereof;
the second physical robot is a second ground-mobile robot, a second air-mobile robot, or any second combination thereof; and
the third physical robot is a third ground-mobile robot, a third air-mobile robot, or
any third combination thereof.
EXAMINER NOTE: See Poursohi, Fig. 2B. The robot 212 comprises legs, indicating it is a ground-mobile robot
Claim 9
The combination of Poursohi, Golgiri, and Srivastav teaches the limitations of claim 1 as outlined above. As shown above, the cited combination also teaches
the obtaining the first data comprises obtaining the first data from the first physical robot over time;
the obtaining the second data comprises obtaining the second data from the second physical robot over time; and
the obtaining the third data comprises obtaining the third data from the third physical robot over time.
(Poursohi - [col 9, ln 61-64] … Overall, the robots 402, 404, 406, and 408 may be configured to share data that is collected to enable faster adaptation, such that each robot 402, 404, 406, and 408 can build upon a learned experience of a previous robot.)
Claim 10
The combination of Poursohi, Golgiri, and Srivastav teaches the limitations of claim 1 as outlined above. As shown above, the cited combination also teaches
wherein the providing, to the third physical robot, the advertisement of the availability of the selected downloadable service comprises transmitting a notification message to the third physical robot.
(Golgiri - [0016] … Responsive to identifying an occurrence of one of the predefined vehicle operating conditions, the vehicle usage application 120 may be configured to communicate a notification to the user of the vehicle 102 that indicates availability of a new vehicle feature associated with the predefined vehicle operating condition, and to upgrade components of the vehicle 102 so as to enable the vehicle 102 to provide the new vehicle feature upon request by the vehicle user.)
Claims 11-12
The combination of Poursohi, Golgiri, and Srivastav teaches the limitations of claim 10 as outlined above. As shown above, the cited combination also teaches
wherein the operations further comprise receiving, from the third physical robot, a response to the notification message, the response comprising a request to receive the selected downloadable service for instantiation and execution on the third physical robot.
wherein the operations further comprise sending to the third physical robot, responsive to the request, the selected downloadable service for instantiation and execution on the third physical robot.
(Golgiri - [0045] In alternative embodiments, rather than already being in possession of the updates for implementing a new vehicle feature, the vehicle computing platform 112 may be configured to submit a request to the remote server 104 that identifies the vehicle feature to be enabled. Responsive to receiving the request, the remote server 104 may be configured to query the OTA update database 154 for the OTA update corresponding to the requested vehicle feature, and to transmit the returned OTA update to the vehicle computing platform 112 via the TCU 126. The vehicle computing platform 112 may then be configured to upgrade the vehicle 102 to provide the vehicle feature for the trial period by installing the received OTA update received from the remote server 104.)
Claim 13
The combination of Poursohi, Golgiri, and Srivastav teaches the limitations of claim 12 as outlined above. As shown above, the cited combination also teaches
wherein each of the providing, the receiving, and the sending is carried out via a communication channel, and wherein each communication channel comprises a wireless communication channel, a wired communication channel, or any combination thereof.
(Poursohi - [col 6, ln 26-45] (30) In FIG. 1, communication links between client devices and the cloud 102 may include wired connections, such as a serial or parallel bus. Communication links may also be wireless links, such as link 120, which may include Bluetooth, IEEE 802.11 (IEEE 802.11 may refer to IEEE 802.11-2007, IEEE 802.11n-2009, or any other IEEE 802.11 revision), or other wireless based communication links.
In other examples, the system 100 may include access points through which the client devices may communicate with the cloud 102. Access points may take various forms, for example, an access point may take the form of a wireless access point (WAP) or wireless router. As another example, if a client device connects using a cellular air-interface protocol, such as a CDMA or GSM protocol, an access point may be a base station in a cellular network that provides Internet connectivity via the cellular network.)
Claim(s) 2-3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Poursohi, Golgiri and Srivatasv as applied to claim 1 above, and further in view of Slivka (US-10347148-B1).
Claim 2
The combination of Poursohi, Golgiri, and Srivastav teaches the limitations of claim 1 as outlined above. The cited combination may not explicitly utilize demographics. However, Slivka teaches
obtaining first demographic data indicative of first characteristics of one or more first users …
obtaining second demographic data indicative of second characteristics of one or more second users…
obtaining third demographic data indicative of third characteristics of one or more third users …
(Slivka - [col 4, ln 35-39] In one embodiment, the student profile database 124 comprises individual student profiles. By way of example, each student profile may comprise personal information such as a student's age, gender, geographic location, interests and hobbies, etc …)
wherein the predicting the future task that will be performed by the third physical robot comprises:
determining whether the third characteristics are more similar to the first characteristics or the second characteristics;
in a first case that the third characteristics are more similar to the first characteristics than to the second characteristics, selecting as the future task one of the first plurality of tasks; and
in a second case that the third characteristics are more similar to the second characteristics than to the first characteristics, selecting as the future task one of the second plurality of tasks.
(Slivka - [col 1, ln 28-37] In one embodiment, the invention discloses a method for adapting educational content. The method comprises generating data for each of a plurality of students, the data pertaining to an aspect of the student's interaction with an educational system, combining the generated data to form a combined data set; analyzing the combined data set to identify clusters, each representing similar students according to a mathematical model; and adapting the educational system to provide a customized learning experience for a particular student based on an identified cluster.
[col 6, ln 65 thru col 7, ln 5] In accordance with embodiments of the present invention, the clusters may be detected using different clustering techniques. Each of the clustering techniques relies on at least one method for measuring the distance or inverse correlation between two students, for example, a modified Mahalanobis distance or inverse using selected student profile values, lesson and problem result values, and event stream data for the students.)
EXAMINER NOTE: Students are clustered based on age to generate appropriate lessons.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to base task generation on demographic data in order to provide a customized experience to the user.
(Slivka - [col 2, ln 40-43] Broadly, embodiments of thee invention disclose an educational system and techniques for adapting educational content within the educational system to provide a customized learning experience for an individual learner or student.)
Claim 3
The combination of Poursohi, Golgiri, Srivastav, and Slivka teaches the limitations of claim 2 as outlined above. As shown above, Slivka also teaches
the first characteristics comprise ages of the one or more first users, age ranges of the one or more first users, educational levels of the one or more first users, educational ranges of the one or more first users, incomes of the one or more first users, income ranges of the one or more first users, or any first combination thereof;
the second characteristics comprise ages of the one or more second users, age ranges of the one or more second users, educational levels of the one or more second users, educational ranges of the one or more second users, incomes of the one or more second users, income ranges of the one or more second users, or any second combination thereof; and
the third characteristics comprise ages of the one or more third users, age ranges of the one or more third users, educational levels of the one or more third users, educational ranges of the one or more third users, incomes of the one or more third users, income ranges of the one or more third users, or any third combination thereof.
(Slivka - [col 4, ln 35-39] In one embodiment, the student profile database 124 comprises individual student profiles. By way of example, each student profile may comprise personal information such as a student's age, gender, geographic location, interests and hobbies, etc …)
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Poursohi, Golgiri, Srivastav as applied to claim 1 above, and further in view of Oleynik (US-12257711-B2).
Claim 8
The combination of Poursohi, Golgiri, Srivastav, and Slivka teaches the limitations of claim 1 as outlined above. The cited combination may not explicitly teach the following limitations in combination. However, Oleynik teaches
wherein the selecting the downloadable service is further based on a personality of a user associated with the third physical robot
(Oleynik - [col 99, ln 62 thru col 100, ln 2] FIG. 91B depicts all the individual emotion groupings such as immediate emotions 2190 such as anger, secondary emotions 2191 such as fear, all the way through to N actual emotions 2192. The next step 2193 then computes the associated emotion(s) in each group according to the associated emotional profile data, leading to the assessment 2194 of the intensity level of the emotional state, which allows the engine to then decide on the appropriate action 2195.)
EXAMINER NOTE: The action taken by the robot is governed by the user's learned emotional profile (personality)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to base task execution on the user’s emotional state in order to make the user experience more comfortable.
(Oleynik - [col 6, ln 66 thru col 7, ln 3] In a second aspect of the present disclosure, the robotic apparatus comprises a humanoid for home applications where the humanoid is designed to provide a programmable or customizable psychological, emotional, and/or functional comfortable robot, and thereby providing pleasure to the user. )
Claim(s) 14-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Poursohi, Golgiri, and Srivastav as applied to claim 1 above, and further in view of Song (US-20140136302-A1)
Claim 14
The combination of Poursohi, Golgiri, Srivastav, and Slivka teaches the limitations of claim 1 as outlined above. The cited combination may not explicitly teach the following limitations in combination. However, Song teaches
wherein the predicting is carried out via an artificial intelligence (Al) process, a machine learning (ML) process, or any combination thereof.
(Song - [0053] Further, the intelligent servicer robot 100 senses surrounding context information and decides a required robot operation based on a sensing result to perform the corresponding operation. That is, the intelligent servicer robot 100 receives environment information such as image information or voice information by using a sensor such as a camera sensor, an infrared sensor or a microphone corresponding to human eye or ear, judges a current context through a processor installed with artificial intelligence, and performs an appropriate operation based thereon.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to incorporate Song's suggestion to utilize AI in Poursohi's robot system in order to provide appropriate action which is relevant to the context of the environment.
(Song - [0053] Further, the intelligent servicer robot 100 senses surrounding context information and decides a required robot operation based on a sensing result to perform the corresponding operation. That is, the intelligent servicer robot 100 receives environment information such as image information or voice information by using a sensor such as a camera sensor, an infrared sensor or a microphone corresponding to human eye or ear, judges a current context through a processor installed with artificial intelligence, and performs an appropriate operation based thereon.
[0082] Since various events, actions, and contexts are present, the intelligent service robot 100 forms the events, actions, and contexts as respective scenarios to call and use an appropriate scenario according to user needs.)
Claim 15
The combination of Poursohi, Golgiri, Srivastav, and Slivka teaches the limitations of claim 1 as outlined above. The cited combination may not explicitly teach the following limitations in combination. However, Song teaches
wherein the selecting is carried out via an artificial intelligence (Al) process, a machine learning (ML) process, or any combination thereof.
(Song - [0053] Further, the intelligent servicer robot 100 senses surrounding context information and decides a required robot operation based on a sensing result to perform the corresponding operation. That is, the intelligent servicer robot 100 receives environment information such as image information or voice information by using a sensor such as a camera sensor, an infrared sensor or a microphone corresponding to human eye or ear, judges a current context through a processor installed with artificial intelligence, and performs an appropriate operation based thereon.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to incorporate Song's suggestion to utilize AI in Poursohi's robot system in order to provide appropriate action which is relevant to the context of the environment.
(Song - [0053] Further, the intelligent servicer robot 100 senses surrounding context information and decides a required robot operation based on a sensing result to perform the corresponding operation. That is, the intelligent servicer robot 100 receives environment information such as image information or voice information by using a sensor such as a camera sensor, an infrared sensor or a microphone corresponding to human eye or ear, judges a current context through a processor installed with artificial intelligence, and performs an appropriate operation based thereon.
[0082] Since various events, actions, and contexts are present, the intelligent service robot 100 forms the events, actions, and contexts as respective scenarios to call and use an appropriate scenario according to user needs.)
Allowable Subject Matter
Claims 16-20 are allowed.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMES MILLER WATTS whose telephone number is (703)756-1249. The examiner can normally be reached 7:30-5:30 M-TH.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Adam Mott can be reached at 571-270-5376. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JAMES MILLER WATTS III/Examiner, Art Unit 3657
/ADAM R MOTT/Supervisory Patent Examiner, Art Unit 3657
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