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 .
Status of Claims
This Office Action is in response to the application filed on November 8, 2024. Claim 13 has been cancelled. Claims 1-12 are pending. Claims 1, 11 and 12 are independent.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on December 11, 2024 has been considered. The submission is in compliance with the provisions of 37 CFR 1.97. The Forms PTO-1449 are signed and attached hereto.
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 2, 4-7 and 9-13 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by U.S. Patent Publication No. 2020/0052974 to Yasuda.
Claims 1, 2, 4-7 and 9-13 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Yasuda.
With respect to independent claims 1, 11 and 12, Yasuda discloses transmission latency distribution estimation circuitry to estimate transmission latency distribution information including a probability distribution of transmission latencies in the transmission path and a mode corresponding to the probability distribution (see paragraphs [0119] – [0121]: a low delay distribution estimation means that estimates a probability distribution of a first communication delay state by using a result of measuring a communication delay of a packet in a network. An identification means that identifies whether a state of the communication delay is the first communication delay state or a second communication delay state in which the communication delay is greater than the communication delay in the first communication delay state. A high delay distribution estimation means that estimates a probability distribution of the second communication delay state.); and
action planning circuitry to plan an action of the at least one mobile object which corresponds to the mode, based on the transmission latency distribution information, and outputs the action as a target action (see paragraph [0004], [0023] and [0024]: the case of remote control, when a predicted delay time is large, an operation speed of a target device is decreased as compared with a case where the predicted delay time is small. A control target device that executes the operation in response to the remote control from the delay prediction device, the delay prediction device, the control device and the control target device being communicably connected. The control device receives, by the delay prediction device, predicted delay information including a future delay time based on a communication delay predicted by using a result of measuring a communication delay of a packet in the network, and determines the remote control for the control target device based on the predicted delay information.),
wherein the transmission latency distribution estimation circuitry estimates the probability distribution of the transmission latencies, using a transmission latency model based on the mode of the transmission latencies (see paragraphs [0063], [0066] and [0137], : the gamma distribution is used as an example. Identification unit 12 identifies whether the state of the communication delay is the low delay state or the high delay state in which the communication delay is greater than the communication delay in the low delay state. Identification unit 12 determines a threshold for distinguishing the low delay state from the high delay state. An exponential distribution is used as a distribution representing the second communication delay state.).
With respect to dependent claim 2, Yasuda discloses wherein the transmission latency distribution estimation circuitry estimates the transmission latency distribution information, based on transmission latency information obtained in advance or online (see paragraphs [0026], [0055], [0058] and [0061]: estimating a probability distribution of a first communication delay state by using a result of measuring a communication delay of a packet in a network. The probability p and the probability q are associated with a shape of a probability distribution of delay times (described in detail later). Accordingly, a pair of values of the future probability p and probability q is predicted, whereby the delay time distribution related to the pair of values can be achieved, and a future delay can be predicted based on the delay time distribution. Delay time measurement unit 15 causes packets to flow a plurality of times through a communication network, thereby measuring a delay time in advance. Low delay distribution estimation unit 11 estimates a probability distribution of a low delay state by using a result of measuring the communication delay of a packet in the network (output from the delay time measurement unit 15). Assuming that data on a relatively short delay time among the measured delay times are in a low delay state, low delay distribution estimation unit 11 estimates the probability density (function) of the delay time related to the low delay state.).
With respect to dependent claim 4, Yasuda discloses wherein the action planning circuitry plans the action to correspond to the mode of the transmission latencies, and outputs the action as the target action (see paragraphs [0004] and [0023]: when a predicted delay time is large, an operation speed of a target device is decreased as compared with a case where the predicted delay time is small. A control target device that executes the operation in response to the remote control from the delay prediction device, the delay prediction device, the control device and the control target device being communicably connected.).
With respect to dependent claim 5, Yasuda discloses wherein the transmission latency distribution estimation circuitry estimates the transmission latency distribution information, based on the transmission latency information and environment features that characterize a surrounding environment of the at least one mobile object (see paragraph [0003]: a communication delay time also varies from hour to hour due to various factors such as interference between radio waves, noise, and congestion of communication lines.).
With respect to dependent claim 6, Yasuda discloses wherein the transmission latency distribution estimation circuitry learns and builds the transmission latency model through machine learning (see paragraphs [0069] and [0083]: The communication path takes either one of the low delay state and the high delay state, and the state is considered as a model for state transition based on the Markov process (see FIG. 3). Further, the packet sent in the low delay state is returned after a lapse of a delay time given by the low delay state distribution (e.g., gamma distribution). Future communication delay with high accuracy based on past communication delay data. This is because low delay distribution estimation unit 11 estimates the distribution of the low delay state by using the measured communication delay time, identification unit 12 distinguishes the low delay state from the high delay state, high delay distribution estimation unit 13 estimates the distribution of the high delay state, and delay distribution prediction unit 14 predicts the probability distribution of the future delay time by a mixed distribution of the low delay state and the high delay state.).
With respect to dependent claim 7, Yasuda discloses wherein the transmission latency distribution estimation circuitry uses a hierarchical or non-hierarchical hidden Markov model as the transmission latency model (see paragraph [0069]: The communication path takes either one of the low delay state and the high delay state, and the state is considered as a model for state transition based on the Markov process (see FIG. 3).).
With respect to dependent claim 9, Yasuda discloses wherein when equating respective pieces of the transmission latency distribution information of the plurality of mobile objects, the transmission latency distribution estimation circuitry groups the plurality of mobile objects, and estimates common transmission latency distribution information using one of the pieces of the transmission latency distribution information (see paragraph [0061]: Low delay distribution estimation unit 11 estimates a probability distribution of a low delay state by using a result of measuring the communication delay of a packet in the network (output from the delay time measurement unit 15). Assuming that data on a relatively short delay time among the measured delay times are in a low delay state, low delay distribution estimation unit 11 estimates the probability density (function) of the delay time related to the low delay state.).
With respect to dependent claim 10, Yasuda discloses wherein the action planning circuitry determines a risk to the at least one mobile object using an equation of state representing a relative relationship in position and speed between the at least one mobile object and a surrounding object, based on state information on the at least one mobile object and surrounding information on surroundings of the at least one mobile object as well as the transmission latency distribution information, and changes the target action based on the determined risk (see paragraph [0003]: When a large communication delay occurs suddenly, for example, in a remote control system, it becomes difficult to control a device to be operated. When a predicted delay time is large, an operation speed of a target device is decreased as compared with a case where the predicted delay time is small.).
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 3 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Yasuda in view of U.S. Patent Publication No. 2021/0026356 to Kobayashi et al. (hereinafter “Kobayashi”).
With respect to dependent claim 3, Yasuda does not explicitly teach control circuitry to compute a controlled amount for controlling the at least one mobile object so that the at least one mobile object implements the target action output by the action planning circuitry.
Kobayashi discloses an action plan candidate generating section configured to generate multiple candidates of an action plan constituting multiple action plan candidates on a basis of status of surroundings, an action plan candidate evaluating section configured to assign an evaluation value to each of the generated multiple action plan candidates. (See paragraph [0011]).
It would have been obvious to one skilled in the art to combine the control apparatus that generates and evaluates multiple action candidates for each mobile object of Kobayashi with the control apparatus that predicts system state and assesses measurement confidence of Yasuda in order to compute evaluated control actions based on system status.
With respect to dependent claim 8, Yasuda does not explicitly disclose the at least one mobile object comprises a plurality of mobile objects, and the action planning circuitry plans the action for each of the plurality of mobile objects, and outputs the actions as the target actions.
Kobayashi discloses an evaluation value is set to each of the generated multiple action plan candidates. The action plan is determined using the action plan candidates in accordance with their evaluation values. This technology is applied advantageously to multi-legged robots, flying objects, and onboard systems each controlled by an onboard computer to move autonomously. The mobile object external information detecting section 141 supplies the data representing the results of the detection processing to the own-position estimating section 132, to a map analyzing section 151 and a status recognizing section 152 in the status analyzing section 133, and to the motion controlling section 135, among others. (See abstract and paragraph [0100] ).
It would have been obvious to one skilled in the art to combine the control apparatus that generates and evaluates multiple action candidates for each mobile object of Kobayashi with the control apparatus that predicts system state and assesses measurement confidence of Yasuda in order to provide a system that use delay prediction to weight and evaluate action plan candidates, then select the best action for each object.
Conclusion
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/DEMETRA R SMITH-STEWART/Examiner, Art Unit 3661
/PETER D NOLAN/Supervisory Patent Examiner, Art Unit 3661