DETAILED ACTION
Remarks
This final office action is in response to the amendments filled on 03/30/2026. Claim 1 is amended. Claims 1-17 are pending and examined below.
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 .
Claim Objections
Claim(s) 17 is/are objected to because of the following informalities:
Claim 17 recites, “an apparatus for controlling an automated device comprising a control module for performing the method of claim 1”. From the recited claim, it is not clear if “an automated device”, is the same robot as claim 1 or not. Examiner suggests that Applicant make Claim 17 separate and incorporate the text of Claim 1 into it instead of referring to Claim 1 in order to avoid antecedent issues.
Appropriate correction is required.
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.
Claim(s) 1, 2, 4-7, 16 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 2023/0182772 (“Funke”), and in view of IEEE transactions on neural networks and learning systems, vol 30, No 6; title “Exploiting generalization in the subspaces for faster model-based reinforcement learning”, by (“Maryam”), and further in view of US 2019/0138007 (“Baghsorkhi”).
Regarding claim 1, Funke discloses a method for determining an action for an automated device based on a state of an environment of the automated device (see at least fig 3, where operation of an autonomous vehicle is altered based on environment state), the method comprising:
obtaining information on environmental measurement results (see at least [0067], where “At operation 306, example process 300 may comprise receiving sensor data from one or more sensors…the perception component may determine the perception data, which may include determining a curvature of a roadway, detecting the presence of passenger(s) in the vehicle, detecting weather and/or traffic conditions, a jerk and/or acceleration experienced by the vehicle…The vehicle 202 may additionally or alternatively detect an object in the environment”);
estimating information on the state of the environment based on the information on the environmental measurement results (see at least [0067], where curvature of a roadway, presence of passenger, detecting weather and traffic condition, detect an object are estimated. So, state of the environment based on information is determined), the information on the state of the environment comprising information on a confidence of the state of the environment (see at least [0068], where based on the information on the state of the environment (e.g., existence of crosswalk) safety confidence score is determined. Safe or unsafe environment can be state of the environment. See also [0015], [0036] and [0054]);
determining a representation for the state of the environment based on the information on the state of the environment and based on the information on the confidence of the state of the environment (see at least [0067], where curvature of a roadway, presence of passenger, detecting weather and traffic condition, detect an object are estimated. So, representation for the state of the environment is determined based on state of the environment. Representation for the state of the environment may be safe or unsafe. The safety confidence score is also determined. When safety confidence score meets or exceeds a threshold indicating a safety condition. See also [0071]), the representation of the state of the environment comprising (see at least fig 4, where multiple separate regions are shown. multiple regions state together representing the state of the environment; vehicle 202 is passing through states comprising bicyclist and vehicle 408) and the confidence of the state of the environment (see at least [0081]); and
determining information on the action for the automated device based on the representation (see at least [0076], where “At operation 314, example process 300 may comprise altering operation of the vehicle. Altering operation of the vehicle may comprise altering the first trajectory, determining a new trajectory, altering operation of a component of the vehicle, and/or transmitting a notification to a passenger.”).
Funke does not disclose the following limitations:
the information on the environmental measurement results includes at least a confidence of the measurement results; and
two or more intermediary states representing the state of the environment.
However, Maryam discloses a method wherein two or more intermediary states representing the state of the environment (see at least fig 2, where subspace 1…N. decision is made using confidence degree model based on environmental feedback).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have modified Funke to incorporate the teachings of Maryam by including the above feature for expediting the learning process, see page 1636, right col, 4th para of Maryam.
Funke in view Maryam does not disclose the following limitation:
the information on the environmental measurement results includes at least a confidence of the measurement results.
However, Baghsorkhi discloses a method wherein the information on the environmental measurement results includes at least a confidence of the measurement results (see at least [0085], where “a corresponding confidence rating for the sensor measurements and/or state estimates of each of the nodes.”; see also [0086], where “the state determiner/object tracker 506 included in the first autonomous vehicle 102 obtains a request for one or more of sensor data or state estimates for an object in the environment that is missing to the second autonomous vehicle 106.”).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have modified Funke in view Maryam to incorporate the teachings of Baghsorkhi by including the above feature for increasing efficiency and safety by providing control instruction based on measurement results.
Regarding claim 2, Funke further discloses a method comprising determining confidence information for the action (see at least fig 3, where vehicle operation is determined based on confidence score).
Regarding claim 4, Funke further discloses a method comprising using one or more policies to obtain two or more intermediary actions based on the two or more intermediary states (see at least fig 4, where vehicle 202 is arriving pickup location, 414. See also [0081], where avoid unsafe condition is policy. The trajectory to 414 is determined based on intermediary state e.g. bicyclist and vehicle, 408).
Regarding claim 5, Funke further discloses a method comprising using the same policy to obtain one intermediary action for each of the intermediary states (see at least fig 4 and [0081]).
Regarding claim 6, Funke further discloses a method wherein the one or more policies involve a non-linear transform to obtain the two or more intermediary actions based on the two or more intermediary states (see at least [0052] and fig 4).
Regarding claim 7, Funke further discloses a method comprising determining statistical properties of a distribution of the two or more intermediary actions (see at least [0060] and [0069]).
Regarding claim 16, Funke further discloses a non-transitory computer readable medium storing a computer program having program code for performing the method according to claim 1, when the computer program is executed on a computer, a processor, or a programmable hardware component (Refer at least to claim 1 for reasoning and rationale; see also [0050]).
Regarding claim 17, Funke further discloses an apparatus for controlling an automated device comprising a control module for performing the method of claim 1 (Refer at least to claim 1 for reasoning and rationale; see also fig 2).
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 2023/0182772 (“Funke”), and in view of IEEE transactions on neural networks and learning systems, vol 30, No 6; title “Exploiting generalization in the subspaces for faster model-based reinforcement learning”, by (“Maryam”), and in view of US 2019/0138007 (“Baghsorkhi”), as applied to claim 1 above, and further in view of US 2020/0263996 (“Gokhale”).
Regarding claim 3, Maryam further discloses a method wherein each of the two or more intermediary states comprises (see at least fig 2; selecting some statistical properties associated with each subspace is inherent to the estimation of the model).
Funke in view of Maryam and Baghsorkhi does not explicitly disclose one or more sigma points representing statistical properties.
However, Gokhale discloses a method comprising one or more sigma points representing statistical properties (see at least [0031], where “The algorithm generates arbitrary sigma points for prediction as shown in FIG. 5.”).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have modified Funke in view of Maryam and Baghsorkhi to incorporate the teachings of Gokhale by including the above feature for providing more reliable properties so that safety during travelling increased.
Claim(s) 8-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 2023/0182772 (“Funke”), and in view of IEEE transactions on neural networks and learning systems, vol 30, No 6; title “Exploiting generalization in the subspaces for faster model-based reinforcement learning”, by (“Maryam”), and in view of US 2019/0138007 (“Baghsorkhi”), as applied to claim 7 above, and further in view of US 2022/0161767 (“Sevensson”).
Regarding claim 8, Funke further discloses a method wherein emergency vehicle is identified and take taction based on the identification, see at least [0069]. Maryam further discloses a method wherein two or more intermediary regions/ actions are determined, see at least fig 2.
Funke in view of Maryam Baghsorkhi does not explicitly disclose using an unscented transform for determining the statistical properties.
However, Sevensson discloses a method comprising using an unscented transform for determining the statistical properties (see at least [0069], where “performing nonlinear modelling (unscented prediction) on the input parameters”; unscented transform is used for triggering an emergency stop, per [0051] of PGPub of submitted specification.).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have modified Funke in view of Maryam and Baghsorkhi to incorporate the teachings of Sevensson by including the above feature for providing higher accuracy and faster computation so that safety during travelling increased.
Regarding claim 9, Maryam further discloses a method wherein the determining of the information on the action is based on the statistical properties of the distribution of the two or more intermediary actions, and wherein the statistical properties of the distribution of the two or more intermediary actions comprise confidence information on the intermediary actions (see at least page 1637, right col, page 1644 left col and fig 2).
Regarding claim 10, Funke further discloses a method wherein the determining of the information on the action is based on the confidence information of the intermediary actions (see at least fig 6 and [0083]).
Regarding claim 11, Funke further discloses a method comprising determining information on a safety action as information on the action if the confidence information for the intermediary actions indicates confidence levels of the intermediary actions below a predefined confidence threshold (see at least fig 3).
Regarding claim 12, Funke further discloses a method comprising training the policies, wherein the training of the policies is influenced by intermediary states identified for intermediary actions exhibiting a predefined statistical characteristic (see at least [0061] and fig 3, where confidence above threshold is interpreted as predefined statistical characteristic).
Regarding claim 13, Funke further discloses a method wherein the predefined statistical characteristic is a confidence threshold (see at least fig 3, block 310).
Regarding claim 14, Funke further discloses a method wherein the automated device is an autonomous vehicle or an industrial robot and wherein the action is a controlled action for the autonomous vehicle or the industrial robot (see at least [0003]).
Regarding claim 15, Funke further discloses a method wherein the action comprises one or more elements of the group of a maneuver, a motion, an acceleration, a deceleration, a steering command, a stop command, and an emergency command (see at least [0011] and [0015]).
Response to Arguments
Applicant’s arguments with respect to claim 1-17 have been considered but are moot because the arguments do not apply to the new combination used in the current rejection that is due to the newly added claim amendments.
Conclusion
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 extension fee 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 date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SOHANA TANJU KHAYER whose telephone number is (408)918-7597. The examiner can normally be reached on Monday - Thursday, 7 am-5.30 pm, PT.
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/SOHANA TANJU KHAYER/Primary Examiner, Art Unit 3657
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