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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after allowance or after an Office action under Ex Parte Quayle, 25 USPQ 74, 453 O.G. 213 (Comm'r Pat. 1935). Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, prosecution in this application has been reopened pursuant to 37 CFR 1.114. Applicant's submission filed on 10/02/2025 has been entered.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 5, 7-11, 14-15, 18 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Vadayadiyil Raveendran (US PUB. 20220001549, herein Vadayadiyil) in view of Howard et al (US PAT. 11052541, Howard) in further view von Reventlow et al (US PUB. 202301686, herein Reventlow).
Regarding claim 1, Vadayadiyil teaches A robot device, the robot device comprising:
electronic circuitry (0005);
memory in electronic communication with the electronic circuitry (0005);
and instructions stored in the memory, the instructions being executable by the electronic circuitry (0005) to:
determine an error associated with one or more equipment included in a data center environment (0069 “robots 408 perform tasks that have been previously agreed upon between vendors and data center management. Non-limiting examples of tasks performed by robots 408 may include…detecting an operational status of IT equipment, performing diagnostic or maintenance tasks on IT equipment”);
and perform one or more maintenance operations associated with the error based on a received instruction (0069 “robots 408 perform tasks that have been previously agreed upon between vendors and data center management. Non-limiting examples of tasks performed by robots 408 may include…detecting an operational status of IT equipment, performing diagnostic or maintenance tasks on IT equipment”) by.
The cited prior art do not teach selecting an action, from a set of actions, based on i) a first probability that the robot device is capable of performing a skill that is applicable to the received instruction, and ii) a second probability that performance of the skill will resolve the error; identifying a priority level or a risk level associated with the error; when the priority level or the risk level is below a corresponding threshold, causing the robot device to autonomously perform the selected action as part of performing the one or more maintenance operations; and when the priority level or the risk level is above the corresponding threshold, outputting a notification that notifies a user of the selected action and that requests the user to confirm the selected action should be autonomously performed by the robot device.
Howard teaches selecting an action, from a set of actions, based on i) a first probability that the robot device is capable of performing a skill that is applicable to the received instruction (5:50-55 “If at 204 it is determined that the task should be assigned to an autonomous robot to perform, at 208, one or more autonomous robots are deployed to perform the task. In some embodiments, determining whether to assign the task to an autonomous robot includes determining whether an autonomous robot is capable of performing the task”, 7:50-55 “the determination to request assistance may be made based on one or more detected sensor inputs (e.g., camera image) and, or received information about a network device (e.g., network device state information received via a network connection)”, fig. 3), and ii) a second probability that performance of the skill will resolve the error (6:10-15 “At 304, a series of steps required to perform the task is determined. In some embodiments, the series of steps are identified among a group of steps that have been preconfigured. In some embodiments, at least a portion of the series of steps are automatically generated/adapted based at least in part one or more provided parameters of the task to be performed”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to have modified the teachings of Vadayadiyil with the teachings of Howard since Howard teaches a means for robot help in data center maintenance when human resources are insufficient to promptly perform required duties (1:10-15).
Reventlow teaches identifying a priority level or a risk level associated with the error (0068 “processing unit 14 has an assessment function allowing to judge whether a specific action is likely to be successfully applied in the current situation”);
when the priority level or the risk level is below a corresponding threshold, causing the robot device to autonomously perform the selected action as part of performing the one or more maintenance operations (0010 “In case that the success score is estimated to lie above the preset threshold, the processing unit is configured to automatically generate signals in order to cause the service robot to execute the action corresponding to the selected action definition candidate”);
and when the priority level or the risk level is above the corresponding threshold, outputting a notification that notifies a user of the selected action and that requests the user to confirm the selected action should be autonomously performed by the robot device (claim 1 “send a request for assistance via a communication interface (21) if the success score is less than a preset threshold”, 0065 “With the second threshold set lower there is a certain likelihood that a plurality of stored prototypical situations that may show a similarity with the currently encountered situation below the first threshold but above the second threshold. In such a situation, the service robot system may output a question (request for assistance) which is directed either to the user or to the operator. The question may suggest tasks associated with the prototypical situation for which the similarity above the second threshold but below the first threshold has been determined. The question may be asking for confirmation of one of these tasks or may be an open question such as: “What shall I do?” in case that no prototypical situation could be identified based on the obtained information on the situation and no associated task could be determined”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to have modified the teachings of Vadayadiyil and Howard with the teachings of Reventlow since Reventlow teaches “an improved service robot system which offers the capability of handling new situations during its regular operation and even learn for the future” (0004).
Regarding claim 5 and 18, the cited prior art teach The robot device of claim 1.
Vadayadiyil teaches wherein the instructions are further executable by the electronic circuitry to: process at least one of sensor data and performance data associated with the data center environment, wherein determining the error is based on a result of the processing (0020 “robots execute repetitive and, or standard sets of tasks within the data center. In some embodiments, robots perform tasks that have been previously agreed upon between vendors and data center management. Non-limiting examples of tasks performed by robots may include sensing atmospheric conditions in the vicinity of IT equipment, sensing visual and, or audible signals emitted from IT equipment, detecting an operational status of IT equipment, performing diagnostic or maintenance tasks on IT equipment, and, or installing, replacing, and, or removing IT equipment”).
Regarding claim 7, the cited prior art teach The robot device of claim 1.
Vadayadiyil teaches wherein the instructions are further executable by the electronic circuitry to: process multimedia data associated with the one or more equipment, the data center environment, or both, wherein the multimedia data comprises at least one of image data and auditory data, wherein determining the error is based on a result of the processing (0020 “robots execute repetitive and, or standard sets of tasks within the data center. In some embodiments, robots perform tasks that have been previously agreed upon between vendors and data center management. Non-limiting examples of tasks performed by robots may include sensing atmospheric conditions in the vicinity of IT equipment, sensing visual and, or audible signals emitted from IT equipment, detecting an operational status of IT equipment, performing diagnostic or maintenance tasks on IT equipment, and, or installing, replacing, and, or removing IT equipment”).
Regarding claim 8, the cited prior art teach The robot device of claim 1.
Vadayadiyil teaches wherein the instructions are further executable by the electronic circuitry to: receive data including an error code associated with the one or more equipment, wherein determining the error is based on receiving the data (0069 “Non-limiting examples of tasks performed by robots…detecting an operational status of vendor assets stored in racks”).
Regarding claim 9, the cited prior art teach The robot device of claim 1.
Reventlow teaches wherein the instructions are further executable by the electronic circuitry to: receive a user input to disconfirm that the selected action should be autonomously performed by the robot device (0059 “robot 1 may ask a question either to the user, for example, by means of the speaker 23 or to the operator by other interface 21. The user or the operator may then instruct the robot 1, by confirming a task that was suggested by the robot 1 or, in case that no suggestion is made by the robot 1, by directly instructing and defining a task to be executed.”, 0065 “it might become necessary to ask either the user of the robot 1 or the operator in order to clearly define the task to be executed. A second threshold being lower than the first threshold may be introduced. The first threshold should be set high enough to ensure that only one task fits to the situation in which the robot 1 currently is”).
Regarding claim 10, the cited prior art teach The robot device of claim 1.
Reventlow teaches wherein the instructions are further executable by the electronic circuitry to:
receive a user input to confirm that the selected action should be autonomously performed by the robot device(0059 “robot 1 may ask a question either to the user, for example, by means of the speaker 23 or to the operator by other interface 21. The user or the operator may then instruct the robot 1, by confirming a task that was suggested by the robot 1 or, in case that no suggestion is made by the robot 1, by directly instructing and defining a task to be executed.”, 0065 “it might become necessary to ask either the user of the robot 1 or the operator in order to clearly define the task to be executed. A second threshold being lower than the first threshold may be introduced. The first threshold should be set high enough to ensure that only one task fits to the situation in which the robot 1 currently is”).
Regarding claim 11, the cited prior art teach the robot device of claim 10.
Vadayadiyil teaches wherein the user input comprises: a set of parameters associated with the one or more maintenance operations (0065 “RCP 306 facilitates communication between a vendor and a robot 308 so that the vendor can observe and approve of each step as they are performed by the robot 308. In some embodiments, a task includes a series of steps, and after each step, the robot 308 issues a status update to for the vendor that the RCP 306 receives and relays to the vendor. In some embodiments, the status update includes a verification request that requests approval from the vendor before proceeding to the next step… If the vendor detects a problem, the vendor can issue instructions for the robot indicating non-approval of the results, and responsive to that instruction the RCP 306 issues a command to the robot 308 to abort the task. Alternatively, the vendor can issue instructions for the robot 308 to correct some problem or irregularity, and responsive to that instruction the RCE 306 issues a script based on the vendor instructions that that dynamically modifies the task to make the correction. In some embodiments, the RCP 306 receives the response from the vendor and relays it to the robot 308. In response, the robot 308 determines if the response is an approval, in which case the robot 308 continues with the next step of the task. Otherwise, if the response is not an approval the robot 308 determines whether the response indicates that the task should be halted or if the response includes an updated script with new commands for the task to correct the detected problem or irregularity”).
Regarding claim 14, the cited prior art teach The robot device of claim 1.
Vadayadiyil teaches wherein performing the one or more maintenance operations comprises at least one of: performing the one or more maintenance operations by the robot device (0069); transmitting one or more control signals to an end effector of the robot device, in association with performing the one or more maintenance operations; and transmitting one or more second control signals to another robot device in association with performing the one or more maintenance operations.
Claims 15, 18 and 19 are rejected using similar reasoning as the rejection of claims 1-15 due to reciting similar limitations but directed towards a data center environment and a method.
Claim(s) 2-3, 16, 17 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Vadayadiyil Raveendran (US PUB. 20220001549, herein Vadayadiyil) in view of Howard et al (US PAT. 11052541, Howard) in further view von Reventlow et al (US PUB. 202301686, herein Reventlow) in further view of Wulfmeier et al (US PUB. 20230290133, herein Wulfmeier).
Regarding claim 2, 16, and 20, the cited prior art teach The robot device, data center environment, method of claim 1, 15, 19.
Vadayadiyil teaches maintenance operations (0069).
The cited prior art does not teach wherein the instructions are further executable by the electronic circuitry to: perform, in a control environment, one or more candidate maintenance operations in association with resolving the error; and learn a set of actions associated with successfully resolving the error, based on performing the one or more candidate maintenance operations, wherein performing the one or more maintenance operations comprises applying the set of actions.
Wulfmeier teaches wherein the instructions are further executable by the electronic circuitry to:
perform, in a control environment, one or more candidate maintenance operations in association with resolving the error; and learn the set of actions associated with successfully resolving the error, based on performing the one or more candidate maintenance operations (0030 “the system can train the action selection neural network on simulated data, e.g., characterizing interaction of a simulated robot with a simulated environment. The system can accelerate training of the action selection neural network on the simulated data by encouraging the robot to efficiently explore its simulated environment by learning to perform auxiliary tasks, e.g., of controlling dimensions of embeddings of simulated observations… a method is provided for selecting actions to be performed by an agent interacting with a real-world environment, comprising a first phase of performing a method for training an action selection neural network having a plurality of parameters based on observations of a simulated (or real-world) environment, followed by a second phase of one or more steps of using the trained action selection network to select actions for the agent to perform when interacting with a real environment based on observations of the real-world environment”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to have modified the robot teachings of Vadayadiyil, the teachings of Howard and Reventlow with the simulation teachings of Wulfmeier since Wulfmeier teaches a means for controlling a robot to efficiently perform tasks in real-world environments (0030).
Regarding claim 3, 17, the cited prior art teach the robot device, data center environment of claim 2, 16.
Wulfmeier teaches wherein the instructions are further executable by the electronic circuitry to: compare the error to a set of candidate errors for which the robot device is already trained to resolve, wherein performing the one or more candidate maintenance operations in the control environment is based on a result of the comparison (0055-0057, 0059, 0060, 0080).
Claim(s) 4 is rejected under 35 U.S.C. 103 as being unpatentable over Vadayadiyil Raveendran (US PUB. 20220001549, herein Vadayadiyil) in view of Howard et al (US PAT. 11052541, Howard) in further view von Reventlow et al (US PUB. 202301686, herein Reventlow) in further view of Wulfmeier et al (US PUB. 20230290133, herein Wulfmeier) in further view of Pfau et al (US PUB. 20210166131, herein Pfau).
Regarding claim 4, the cited prior art teach The robot device of claim 2.
The cited prior art do not teach wherein the control environment is a simulation environment corresponding to the data center environment.
Pfau teaches wherein the control environment is a simulation environment corresponding to the data center environment (0009).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to have modified the robot teachings of Vadayadiyil, the teachings of Howard, Reventlow and Wulfmeier with the teachings of Pfau since Pfau teaches “training scheme allows for online, parallel learning of multiple eigenfunctions, decreasing the training time and computational resources consumed in learning multi-eigenfunction feature representations” (0012).
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Vadayadiyil Raveendran (US PUB. 20220001549, herein Vadayadiyil) in view of Howard et al (US PAT. 11052541, Howard) in further view in further view von Reventlow et al (US PUB. 202301686, herein Reventlow) in further view of Lovegrove (US PUB. 20220131925).
Regarding claim 6, the cited prior art teach the robot device of claim 5.
Vadayadiyil teaches wherein: the processing comprises providing at least one of the sensor data and performance data to a machine learning model (0030, 0028 “steps described by the various illustrative embodiments can be adapted for providing explanations for decisions made by a machine-learning classifier model”).
The cited prior art does not teach and determining the error comprises predicting the error and a set of parameters associated with the error in response to the machine learning model processing at least one of the sensor data and the performance data.
Lovegrove teaches and determining the error comprises predicting the error and a set of parameters associated with the error in response to the machine learning model processing at least one of the sensor data and the performance data (0026).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to have modified the robot teachings of Vadayadiyil and the teachings of Howard with the sensor based prediction of faults teachings of Lovegrove since Lovegrove teaches a means for predicting errors within the industrial system (0026).
Claim(s) 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Vadayadiyil Raveendran (US PUB. 20220001549, herein Vadayadiyil) in view of Howard et al (US PAT. 11052541, Howard) in further view in further view von Reventlow et al (US PUB. 202301686, herein Reventlow) in further view of Menon et al (US PUB. 20190339693, herein Menon).
Regarding claim 12, the cited prior art teach The robot device of claim 10.
The cited prior art does not teach wherein: the notification comprises a request for a physical intervention, by a user, in association with performing the one or more maintenance operations.
Menon teaches wherein: the notification comprises a request for a physical intervention, by a user, in association with performing the one or more maintenance operations (0017 “robot reaches a state in which the robot cannot determine a next action to perform to advance towards completion of the task or set of tasks, the robot triggers intervention, e.g., by a human operator”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to have modified the robot teachings of Vadayadiyil and the teachings of Howard with the request for physical intervention teachings of Menon since Menon teaches a means for switching to human assistance when the robot may be stuck (0028).
Response to Arguments
Applicant's arguments filed 10/02/2025 have been fully considered but they are not persuasive. Amendments to the claims does affect the allowability of the claims as shown in the rejection of claims 1, 15 and 19 and their respective dependent claims.
Conclusion
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/TAMEEM D SIDDIQUEE/
Primary Examiner
Art Unit 2116