DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
The present application, filed 25 March 2025, is a continuation of U.S. Patent App. No. 19/089,505, filed 12 September 2022.
Information Disclosure Statement
The information disclosure statement filed 25 March 2025 has been partially considered. Specifically, all references disclosed by Applicant have been considered except US 20170130045 A1, hereafter Karl. The examiner notes that the subject matter disclosed in Karl is related to solutions of polyvinylidene fluoride (PVDF) or copolymers of 1, 1-diflouroethylene. The examiner believes the reference may have been added accidentally, and in view of the lack of relevance to the present application, has not been considered.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 4, 9, 11, 14, 18, and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Kim (US 20210072758 A1), hereafter Kim.
Regarding claim 1, Kim discloses a method implemented using one or more processors and comprising:
Determining a state of a mobile robot transitioning from a production mode to a staging mode (0183, When the processor 180a determines that the final destination is reached by the robot, the processor 180a may search for a charging station or control additional movement of the robot.);
Determining a state of a plurality of robot staging stations, wherein the plurality of robot stations includes at least one each of a charging station and a maintenance station (0188, This process includes selecting a charging station closest to the destination among a plurality of charging stations; and determining whether the availability information of the selected charging station corresponds to a preset availability rate. Examiner's note: there is no claimed distinction between a "charging station" and a "maintenance station," and a person having ordinary skill in the art would recognize that "maintenance" would include "charging");
Processing representations of the states of the mobile robot and plurality of robot staging stations using one or more machine learning models to generate output indicative of one or more staging missions to be performed by one or more robots (0190-0191, The search and selection for the charging station to which the robot 100a is to move may be performed in consideration of the location and availability of the charging station. The processor 180a may receive the location information or availability information of the charging station which interworks with the server 200a from the server 200a through the communication interface 110a and control movement to the charging station corresponding to a predetermined distance or availability the use the location information or available information of the charging station among a plurality of charging stations. 0085, At this time, the AI server 200 may receive input data from the AI devices 100a to 100e, may infer the result value for the received input data by using the learning model, may generate a response or a control command based on the inferred result value, and may transmit the response or the control command to the AI devices 100a to 100e.);
Based on the output, selecting a robot staging station from the plurality of robot staging stations (0190-0191, The search and selection for the charging station to which the robot 100a is to move may be performed in consideration of the location and availability of the charging station. The processor 180a may receive the location information or availability information of the charging station which interworks with the server 200a from the server 200a through the communication interface 110a and control movement to the charging station corresponding to a predetermined distance or availability the use the location information or available information of the charging station among a plurality of charging stations.); and
Assigning the mobile robot a staging mission, wherein the staging mission causes the mobile robot to travel to the selected robot staging station (0190-0191, The search and selection for the charging station to which the robot 100a is to move may be performed in consideration of the location and availability of the charging station. The processor 180a may receive the location information or availability information of the charging station which interworks with the server 200a from the server 200a through the communication interface 110a and control movement to the charging station corresponding to a predetermined distance or availability the use the location information or available information of the charging station among a plurality of charging stations.).
Claim 11 is similar in scope to claim 1, and is similarly rejected.
Regarding claim 4, Kim discloses the method of claim 1, and further discloses wherein one or more of the machine learning models is a reinforcement learning-trained policy (0062, The processor 180 may determine at least one executable operation of the AI device 100 based on information determined or generated by using a data analysis algorithm or a machine learning algorithm. The processor 180 may control the components of the AI device 100 to execute the determined operation. 0039, Machine learning may be classified into supervised learning, unsupervised learning, and reinforcement learning according to a learning method.).
Claim 14 is similar in scope to claim 4, and is similarly rejected.
Regarding claim 9, Kim discloses the method of claim 1, and further discloses wherein the state of the robot includes available battery power of the robot and a configuration of the robot (0123, The robot 100a may move itself to a charging station for charging based on a remaining power capacity after the destination is reached and the user gets off the robot 100a.).
Claim 18 is similar in scope to claim 9, and is similarly rejected.
Regarding claim 20, Kim discloses a method implemented using one or more processors and comprising:
Determining a state of a plurality of robot staging stations within a robot staging area of an industrial facility, wherein the plurality of robot staging stations includes at least one each of a robot production mission starting point station and a robot storage station (0157, The processor 180a may receive the location information or availability information of the charging station which interworks with the server 200a from the server 200a through the communication interface 110a and control movement to the charging station corresponding to a predetermined distance or availability the use the location information or available information of the charging station among a plurality of charging stations.);
Determining a state of one or more production missions that are performable by or assignable to one or more mobile robots in the staging area (0187-0188, When it is determined that the battery of the robot 100a needs to be charged, the processor 180a may receive position information or availability information of a charging station from the server 200a through the communication interface 110a. This process includes selecting a charging station closest to the destination among a plurality of charging stations; and determining whether the availability information of the selected charging station corresponds to a preset availability rate.);
Analyzing the determined states of the plurality of robot staging statins and the one or more production missions (0190, The search and selection for the charging station to which the robot 100a is to move may be performed in consideration of the location and availability of the charging station); and
Based on the analyzing, assigning a mobile robot within the robot staging area a staging mission that causes the mobile robot to travel to the robot storage station (0191, The processor 180a may receive the location information or availability information of the charging station which interworks with the server 200a from the server 200a through the communication interface 110a and control movement to the charging station corresponding to a predetermined distance or availability the use the location information or available information of the charging station among a plurality of charging stations).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 2, 3, 6, 12, 13, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Kim in view of Buerger (US 20210325862 A1), hereafter Buerger.
Regarding claim 2, Kim discloses the method of claim 1, but fails to disclose it further comprising:
Encoding the state of the mobile robot into a first vector embedding; and
Encoding the state of the plurality of robot stations into a second vector embedding.
Buerger, however, in an analogous field of endeavor, does teach:
Encoding the state of the mobile robot into a first vector embedding (0106, The resource vector may be a stack of battery level of all robots and may in some embodiments additionally comprise the remaining charging level for each charging station.); and
Encoding the state of the plurality of robot stations into a second vector embedding (0106, The resource vector may be a stack of battery level of all robots and may in some embodiments additionally comprise the remaining charging level for each charging station.).
Kim and Buerger are analogous because they are in a similar field of endeavor, e.g., mobile robot control systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the vector embedding of Buerger in order to provide further means of modeling the environment as a whole. The motivation to combine is to ensure that the mobile robot is as aware of its environment as possible.
Claim 12 is similar in scope to claim 2, and is similarly rejected.
Regarding claim 3, the combination of Kim and Buerger teaches the method of claim 2, and Buerger further teaches wherein processing representations of the states of the mobile robot and plurality of robot staging stations using the one or more machine learning models comprises processing the first and second vector embeddings using one or more of the machine learning models (0106-0107, The resource vector may be a stack of battery level of all robots and may in some embodiments additionally comprise the remaining charging level for each charging station. The system state may be processed by two convolution layers with 64 filters and a kernel size of 5. The resource vector may be processed by a fully connected layer of size 512.).
Kim and Buerger are analogous because they are in a similar field of endeavor, e.g., mobile robot control systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the state space of Buerger in order to provide further means of modeling the environment as a whole. The motivation to combine is to ensure that the mobile robot is as aware of its environment as possible.
Claim 13 is similar in scope to claim 3, and is similarly rejected.
Regarding claim 6, Kim discloses the method of claim 1, but fails to explicitly disclose wherein the output indicative of one or more staging missions comprises a probability distribution over a staging mission action space, and wherein the robot station is selected from the plurality of robot staging stations based on the probability distribution.
Buerger, however, in an analogous field of endeavor, does teach wherein the output indicative of one or more staging missions comprises a probability distribution over a staging mission action space, and wherein the robot station is selected from the plurality of robot staging stations based on the probability distribution (0069, Consider a team of N agents where each agent … is modeled by a conditioned Markov decision process (MDP), … where S.sub.n is the state space, A.sub.n is the action space, C.sub.−n is the set of state-action pairs of other agents, R.sub.n: S.sub.n×A.sub.n×C.sub.−n. is the reward function, and T.sub.n:.sub.n×A.sub.n×C.sub.− n×S.sub.n.fwdarw.[0,1] is the transition probability. Note that both the reward function and the transition function may be conditioned on other agents' states and actions. Both functions may be unknown and change over time. For example, the reward of one agent charging at one location may depend on whether any other agent is using it.).
Kim and Buerger are analogous because they are in a similar field of endeavor, e.g., mobile robot control systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the state space of Buerger in order to provide further means of modeling the environment as a whole. The motivation to combine is to ensure that the mobile robot is as aware of its environment as possible.
Claim 15 is similar in scope to claim 6, and is similarly rejected.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Kim in view of Kaelher (US 20230078625 A1), hereafter Kaelher.
Regarding claim 5, Kim discloses the method of claim 1, but fails to explicitly disclose wherein one or more of the machine learning models comprises a transformer model.
Kaelher, however, in an analogous field of endeavor, does teach wherein one or more of the machine learning models comprises a transformer model (0023, The ML subsystem 114 may include a plurality of machine learning models. For example, the ML subsystem 114 may pipeline an encoder and a reinforcement learning model that are collectively trained with end-to-end learning, the encoder being operative to transform relatively high-dimensional outputs of a robot's sensor suite into lower-dimensional vector representations of each time slice in an embedding space, and the reinforcement learning model being configured to update setpoints for robot actuators based on those vectors).
Kim and Kaelher are analogous because they are in a similar field of endeavor, e.g., mobile robot control systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the transformer model of Kaelher in order to provide further means of processing the state data of the environment. The motivation to combine is to ensure that the machine learning system is able to properly model the environment.
Claims 7, 8, 16, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Kim in view of Vestal (US 10089586 B2), hereafter Vestal.
Regarding claim 7, Kim discloses the method of claim 1, but fails to explicitly disclose wherein the mobile robot transitions from the production mode to the staging mode when moving from a production area of an industrial facility to a robot staging area of the industrial facility that includes at least some of the plurality of robot staging stations.
Vestal, however, in an analogous field of endeavor, does teach wherein the mobile robot transitions from the production mode to the staging mode when moving from a production area of an industrial facility to a robot staging area of the industrial facility that includes at least some of the plurality of robot staging stations (Col. 19, Line 53 - Col. 20, Line 5, The map 208 may also dictate through its definitions that certain virtual job operations 218 shall occur at certain virtual job locations 216. In this case, when the job management system 205 sends a command to a mobile robot in the fleet 290 instructing the mobile robot to go to a particular location on the floor plan 210, the command instruction does not necessarily need to specify which job operations the mobile robot should carry out upon arrival because the map 208 in the mobile robot's memory 202 has already associated one or more job operations 218 with that particular job location. So, if the job management system 205 sends a command instruction to a mobile robot in the fleet 290 that specifies a virtual job location, such as “Go To Battery Charging Station No. 5,” without specifying a virtual job operation to perform upon arrival at the specified virtual job location, the mobile robot may be configured to automatically start charging its battery on arrival because the definitions and attributes stored in the map 208 indicate that battery charging is one of the job operations associated with battery charging station No. 5.).
Kim and Vestal are analogous because they are in a similar field of endeavor, e.g., mobile robot systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the area delineation of Vestal in order to provide a means of assigning a task based on location. The motivation to combine is to ensure that the mobile robot performs a proper task in a proper location.
Claim 16 is similar in scope to claim 7, and is similarly rejected.
Regarding claim 8, Kim discloses the method of claim 1, but fails to disclose it further comprising:
Determining a state of one or more production missions that are performable by or assigned to the mobile robot, or that are assignable to one or more other mobile robots in a robot staging area that includes the plurality of robot staging stations;
Wherein selecting is further based on the state of the one or more production missions.
Vestal, however, in an analogous field of endeavor, does teach:
Determining a state of one or more production missions that are performable by or assigned to the mobile robot, or that are assignable to one or more other mobile robots in a robot staging area that includes the plurality of robot staging stations (Col. 19, Lines 43-52, Similarly, if the job management system 205 sends a command to a mobile robot in the fleet 290 to perform the operation “Charge Battery,” the onboard navigation system on the mobile robot will use a copy of the map 208 to obtain the current locations of battery charging stations in respect to the floor plan 210, as well as the current availability of the nearby battery charging stations, and based on this information, automatically drive the mobile robot to the nearest battery charging station that is not currently being used by another mobile robot.);
Wherein selecting is further based on the state of the one or more production missions (Col. 19, Lines 43-52, Similarly, if the job management system 205 sends a command to a mobile robot in the fleet 290 to perform the operation “Charge Battery,” the onboard navigation system on the mobile robot will use a copy of the map 208 to obtain the current locations of battery charging stations in respect to the floor plan 210, as well as the current availability of the nearby battery charging stations, and based on this information, automatically drive the mobile robot to the nearest battery charging station that is not currently being used by another mobile robot.).
Kim and Vestal are analogous because they are in a similar field of endeavor, e.g., mobile robot systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the state based selection of Vestal in order to ensure that a robot tasked with a mission is able to perform that mission. The motivation to combine is to ensure that a required task is properly performed.
Claim 17 is similar in scope to claim 8, and is similarly rejected.
Claims 10 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Kim in view of Odai (US 20230330872 A1), hereafter Odai.
Regarding claim 10, Kim teaches the method of claim 9, but fails to explicitly disclose wherein at least one maintenance station within a robot staging area that includes at least some of the plurality of robot staging stations comprises a payload alteration station configured for altering the configuration of the mobile robot.
Odai, however, in an analogous field of endeavor, does teach wherein at least one maintenance station within a robot staging area that includes at least some of the plurality of robot staging stations comprises a payload alteration station configured for altering the configuration of the mobile robot (0040-0041, In power switching A step S204, the power source of the mobile robot 101 is switched from the detachable rechargeable battery 53a mounted in the mobile robot 101 to the power supplied from the station 102 to the robot power control unit 1011. The station 102 supplies the power from the station power control unit 1022 to the robot power control unit 1011 by a contact type or non-contact type power supply method. In battery replacement step S205, the work unit 1013 performs battery replacement work of replacing the detachable rechargeable battery 53a (used battery) with the detachable rechargeable battery 53b (charged battery) on the basis of a control command from the control unit 1014. Here, the battery replacement work will be described in detail later with reference to FIGS. 4A to 4D.).
Kim and Odai are analogous because they are in a similar field of endeavor, e.g., mobile robot systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the payload replacement of Odai in order to provide a means of increasing the capabilities of the mobile robot. The motivation to combine is to allow the robot to alter its configuration based on its needs.
Claim 19 is similar in scope to claim 10, and is similarly rejected.
Conclusion
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/BLAKE A WOOD/ Examiner, Art Unit 3658
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