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 .
Claim Rejections - 35 USC § 102
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 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 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Norris Robert et al. (US20080195281A1), hereinafter referred to as Robert.
Regarding claim 1, Robert discloses:
A method for automatically controlling a vehicle (see at least Robert, ¶¶ [0006]-[0007]), comprising:
determining current states of a plurality of control metrics relative to a planned path based on measurements from sensors installed on the vehicle (see at least Robert, ¶¶ [0024]-[0026], [0042]-[0043] which discloses control metrics (steering angle, heading error, distance error, velocity, etc.) determined from vehicle sensors and path deviation calculations relative to the required path, which means determining current states of a plurality of control metrics relative to a planned path based on measurements from sensors installed on the vehicle)
generating at least two control commands using a fuzzy logic controller with a hierarchically reduced rule-base (see at least Robert ¶¶ [0039]-[0040], [0046], [0049] which discloses a hierarchal fuzzy rule base that uses importance weighted input variables and heuristic knowledge to manage multiple objective control that changes dynamically (i.e., approaching and near-path control, this means generating at least two control commands using a fuzzy logic controller with a hierarchically reduced rule-base)
converting the at least two control commands into one or more control signals for actuating one or more path-control actuators of the vehicle (see at least Robert, ¶¶ [0018]-[0019], [0046] which discloses the fuzzy controller outputting steering control signals to actuate the path-control subsystem that handles metrics such as velocity and heading, this means converting the at least two control commands into one or more control signals for actuating one or more path-control actuators of the vehicle)
Regarding claim 2, Robert discloses:
The method of claim 1, wherein each of the plurality of control metrics is associated with a plurality of input member linguistic variables relating to the corresponding control metrics by input fuzzy membership functions (see at least Robert, ¶¶ [0018]-[0020], ¶¶ [0024]-[0026], [0042]-[0043] which discloses control metrics (steering angle, heading error, distance error, velocity, etc.) mapped to linguistic variables related to the corresponding control metrics by the membership function for those variables)
Regarding claim 3, Robert discloses:
The method of claim 2, wherein generating the at least two control commands using the fuzzy logic controller comprises:
automatically converting the current state of each of the plurality of control metrics into input linguistic values of the plurality of input member linguistic variables based on the input fuzzy membership functions (see at least Robert, ¶¶ [0018]-[0019], [0046], which discloses the fuzzification step that automatically converts the control variables into an input linguistic format using membership functions)
automatically mapping the input member linguistic variables to linguistic control variables associated with at least two path-control actions of the vehicle based on the hierarchically reduced rule-base in the fuzzy logic controller (see at least Robert ¶¶ [0039]-[0040], [0046], [0049] which discloses a hierarchal fuzzy rule base that uses importance weighted input variables and heuristic knowledge to manage multiple objective control that changes dynamically (i.e., approaching and near-path control, this means generating at least two control commands using a fuzzy logic controller with a hierarchically reduced rule-base)
generating output linguistic values of the linguistic control variables for each of the at least two path-control actions based on the mapping and output fuzzy membership functions associated with the linguistic control variables (see at least Robert, ¶¶ [0038], [0041]-[0042], [0046], which discloses the controller computing the fuzzy inference results (linguistic outputs) and applying the output membership functions, which means generating output linguistic values of the linguistic control variables for each of the at least two path-control actions based on the mapping and output fuzzy membership functions associated with the linguistic control variables)
defuzzificating the output linguistic values corresponding to the at least two path-control actions to generate the at least two control commands (see at least Robert, ¶¶ [0007], [0018]-[0019], [0046], [0048]-[0049] which discloses defuzzifying the output of rule base method to derive a non-fuzzy or crisp value that best represents the fuzzy value of the linguistic output variable; the fuzzy controller outputting steering control signals to actuate the path-control subsystem that handles metrics such as velocity and heading, this means converting the at least two control commands into one or more control signals for actuating one or more path-control actuators of the vehicle, this means defuzzificating the output linguistic values corresponding to the at least two path-control actions to generate the at least two control commands)
Regarding claim 4, Robert discloses:
The method of claim 3, wherein each of the input fuzzy membership functions specifies a trapezoidal relationship between a corresponding input member linguistic variable and corresponding control metrics (see at least Robert, ¶¶ [0018]-[0019], [0038], [0044] which discloses wherein each of the input fuzzy membership functions specifies a trapezoidal relationship between a corresponding input member linguistic variable and corresponding control metrics)
Regarding claim 5, Robert discloses:
The method of claim 4, wherein the hierarchically reduced rule-base of the fuzzy logic controller is left-right symmetric (see at least Robert, ¶¶ [0026]-[0027] which discloses the distance error as the perpendicular distance from the vehicle to the path that has a sign value indicating whether the vehicle is right, or left of the path; fuzzy controller applies identical correction logic for positive and negative deviations to keep the vehicle on centerline, this means the hierarchically reduced rule-base of the fuzzy logic controller is left-right symmetric)
Regarding claim 6, Robert discloses:
The method of claim 3, wherein the hierarchically reduced rule-base comprises a set of if-then rules linking the plurality of input member linguistic variables to the linguistic control variables covering fewer than all possible combinations of the input member linguistic variables and the linguistic control variables (see at least Robert, ¶¶ [0026]-[0027], [0043]-[0044] which discloses the distance error as the perpendicular distance from the vehicle to the path that has a sign value indicating whether the vehicle is right, or left of the path; fuzzy controller applies identical correction logic (if-then) for positive and negative deviations to keep the vehicle on centerline, this means the hierarchically reduced rule-base comprises a set of if-then rules linking the plurality of input member linguistic variables to the linguistic control variables covering fewer than all possible combinations of the input member linguistic variables and the linguistic control variables)
Regarding claim 7, Robert discloses:
The method of claim 6, wherein:
the planned path comprises at least a current path segment and a next path segment joint by a target point (see at least Robert, Fig.3, ¶¶ [0020]-[0024] which discloses the planned path comprising at least a current path segment and a next path segment joint by a target point)
the plurality of control metrics comprise a waypoint line distance from the vehicle to a waypoint between the target point and a projection point of the vehicle on the current path segment (see at least Robert, Fig.3-4, ¶¶ [0023]-[0024], [0036]-[0038] which discloses the controller monitoring the measurable variables such as (distance, heading, steering angle, etc.) of a plurality of planned path sequential segments denoted as ABCD)
Regarding claim 8, Robert discloses:
The method of claim 7, wherein the plurality of control metrics further comprises:
a target distance from the vehicle to the target point (see at least Robert, Fig.3-4, ¶¶ [0023]-[0024], [0036]-[0038] which discloses the controller monitoring the measurable variables such as (distance, heading, steering angles, etc.) of a plurality of planned path sequential segments denoted as ABCD, this means that the control metrics comprise a target distance from the vehicle to the target point)
a waypoint heading angle between a current heading direction of the vehicle relative to a line from the vehicle to the waypoint (see at least Robert, Fig.3-4, ¶¶ [0023]-[0024], [0036]-[0038] which discloses the controller monitoring the measurable variables such as (distance, heading, steering angles, etc.) of a plurality of planned path sequential segments denoted as ABCD, this means that the control metrics comprise a waypoint heading angle between a current heading direction of the vehicle relative to a line from the vehicle to the waypoint)
a current path-alignment angle between the current heading direction of the vehicle and the current path segment (see at least Robert, Fig.3-4, ¶¶ [0023]-[0024], [0036]-[0038] which discloses the controller monitoring the measurable variables such as (distance, heading, steering angle, etc.) of a plurality of planned path sequential segments denoted as ABCD, this means that the control metrics comprise a current path-alignment angle between the current heading direction of the vehicle and the current path segment)
a lookahead path-alignment angle between the current heading direction of the vehicle and the next path segment (see at least Robert, Fig.3-4, ¶¶ [0023]-[0024], [0036]-[0038] which discloses the controller monitoring the measurable variables such as (distance, heading, steering angle, etc.) of a plurality of planned path sequential segments denoted as ABCD, this means that the control metrics comprise a lookahead path-alignment angle between the current heading direction of the vehicle and the next path segment)
Regarding claim 9, Robert discloses:
The method of claim 8, wherein the hierarchically reduced rule-base comprises rule branches and sub-branches based on hierarchically prioritizing within the control metrics according to the input member linguistic variables (see at least Robert, ¶¶ [0026]-[0028], [0046], which discloses the method of organizing fuzzy inference in hierarchal form through the ranking of inputs (distance, heading, steering angle, velocity) by their relative importance; the system prioritizes control metrics in a hierarchal manner, such as distance (path correction), heading (orientation), and velocity (stability) this means that the hierarchically reduced rule-base comprises rule branches and sub-branches based on hierarchically prioritizing within the control metrics according to the input member linguistic variables)
Regarding claim 10, Robert discloses:
The method of claim 9, wherein the control metrics of the target distance comprises:
a first input linguistic variable representing whether the vehicle is near the target point (see at least Robert, ¶¶ [0046] which discloses a first input linguistic variable representing whether the vehicle is near the target point)
a second input linguistic variable representing whether the vehicle is far from the target point (see at least Robert, ¶¶ [0046], which discloses a second input linguistic variable representing whether the vehicle is far from the target point)
top branches of the hierarchically reduced rule-base comprises a first sub- rule-set and a second sub-rule-set corresponding to the first and second input linguistic variables of the target distance, respectively (see at least Robert, ¶¶ [0046] which discloses the controller applying different acceptable steering responses (rule sets) depending on the fuzzy classification of distance error, which means top branches of the hierarchically reduced rule-base comprises a first sub- rule-set and a second sub-rule-set corresponding to the first and second input linguistic variables of the target distance)
Regarding claim 11,
The method of claim 10, wherein the first sub-rule-set is reduced from addressing all possible combinations of the input member linguistic variables of the waypoint line distance, the waypoint heading angle, the current path- alignment angle, and the lookahead path-alignment angle by ignoring at least one of the waypoint line distance, the waypoint heading angle, and the current path-alignment angle (see at least ¶¶ [0046]-[0047] which disclose the process of how the fuzzy controller begins with a complete matrix (all possible variable combinations) and then purposely reduces it by discarding unnecessary rules associated with less relevant variable combinations that don’t meaningfully impact control which means the first sub-rule-set is reduced from addressing all possible combinations of the input member linguistic variables of the waypoint line distance, the waypoint heading angle, the current path- alignment angle, and the lookahead path-alignment angle by ignoring at least one of the waypoint line distance, the waypoint heading angle, and the current path-alignment angle)
Note: The examiner would like to note that the cited passage does not explicitly state that the specific input linguistic variables of the waypoint line distance, the waypoint heading angle, the current path- alignment angle, and the lookahead path-alignment angle by ignoring at least one of the waypoint line distance, the waypoint heading angle, and the current path-alignment angle are reduced, however, from the disclosure it is clear that the functional roles align. As cited previously in another claim limitation, these input linguistic variables are all present in the disclosure as the designated fuzzy input metrics and form the original, unreduced rule base.
Regarding claim 12,
The method of claim 11, wherein the second sub-rule-set is configured to ignore at least the lookahead path-alignment angle.
Regarding claim 13, Robert discloses:
The method of claim 12, wherein at least one of sub-branches of the second sub-rule-set further ignores the waypoint heading angle (see at least ¶¶ [0046]-[0047] which disclose the process of how the fuzzy controller begins with a complete matrix (all possible variable combinations) and then purposely reduces it by discarding unnecessary rules associated with less relevant variable combinations that don’t meaningfully impact control which means the first sub-rule-set is reduced from addressing all possible combinations of the input member linguistic variables of the waypoint line distance, the waypoint heading angle, the current path- alignment angle, and the lookahead path-alignment angle by ignoring at least one of the waypoint line distance, the waypoint heading angle, and the current path-alignment angle)
Note: The examiner would like to note that while the disclosure does not explicitly list which specific input variables (the waypoint line distance, the waypoint heading angle, the current path- alignment angle, and the lookahead path-alignment angle) are ignored during the reduction, the disclosure from [0047] describes a 98% reduction of the full rule base by ignoring extra rules irrelevant to the control strategy. Because such a reduction requires excluding certain inputs that are explicitly present in the disclosure, the examiner believes the cited section still anticipates the limitation.
Regarding claim 14, Robert discloses:
The method of claim 13, wherein at least one other of the sub-branches of the second sub-rule-set further ignores the current path-alignment angle (see at least ¶¶ [0046]-[0047] which disclose the process of how the fuzzy controller begins with a complete matrix (all possible variable combinations) and then purposely reduces it by discarding unnecessary rules associated with less relevant variable combinations that don’t meaningfully impact control which means the first sub-rule-set is reduced from addressing all possible combinations of the input member linguistic variables of the waypoint line distance, the waypoint heading angle, the current path- alignment angle, and the lookahead path-alignment angle by ignoring at least one of the waypoint line distance, the waypoint heading angle, and the current path-alignment angle)
Note: The examiner would like to note that while the disclosure does not explicitly list which specific input variables (the waypoint line distance, the waypoint heading angle, the current path- alignment angle, and the lookahead path-alignment angle) are ignored during the reduction, the disclosure from [0047] describes a 98% reduction of the full rule base by ignoring extra rules irrelevant to the control strategy. Because such a reduction requires excluding certain inputs that are explicitly present in the disclosure, the examiner believes the cited section still anticipates the limitation.
Regarding claim 15, Robert discloses:
The method of claim 7, wherein the waypoint is determined by achieving a quickest approach to the planned path assuming a constant speed (see at least Robert, ¶¶ [0026], [0036], [0046] which discloses the control objective of the quickest possible approach that assumes velocity as an input variable that’s monitored and regulated to maintain stability, this means the waypoint is determined by achieving a quickest approach to the planned path assuming a constant speed)
Regarding claim 16, Robert discloses:
The method of claim 3, wherein the at least two path-control actions comprise:
an angular steering control and a linear speed control (see at least Robert, ¶¶ [0047] which discloses the rule base including a complete set of control rules for all speed (linear speed) and/or steering (angular) conditions)
wherein the linguistic control variables corresponding to the angular steering control represent a plurality of angular steering levels and the linguistic control variables corresponding to the linear speed control represent a plurality of linear speed levels (see at least Robert, ¶¶ [0020]-[0023], [0025]-[0027], which discloses an example of steering control variables on a linguistic level for steering output levels (increase rate of correction, reduce a rate of correction, no corrective action) wherein the linguistic control variables corresponding to the angular steering control represent a plurality of angular steering levels and the linguistic control variables corresponding to the linear speed control represent a plurality of linear speed levels)
Regarding claim 17, Robert discloses:
The method of claim 3, wherein defuzzificating the output linguistic values is based on a center-of-mass methodology (see at least Robert, ¶¶ [0048] which discloses wherein defuzzificating the output linguistic values is based on a center-of-mass methodology)
Regarding claim 18,
The method of claim 3, wherein each of the output fuzzy membership functions associated with the linguistic control variables is a triangular function (see at least Robert, ¶¶ [0038] which discloses wherein each of the output fuzzy membership functions associated with the linguistic control variables is a triangular function)
Regarding claim 19, Robert discloses:
The method of claim 1, wherein the vehicle comprises a skid-steer vehicle (see at least Robert, ¶¶ [0001]-[0005], [0026])
Regarding claim 20, Robert discloses:
A control circuitry comprising the fuzzy logic controller of claim 1, configured to perform the method of claims 1 (see at least Robert, ¶¶ [0016], [0036], [0038])
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KIRSTEN JADE M SANTOS whose telephone number is (571)272-7442. The examiner can normally be reached Monday: 8:00 am - 4:00 pm, 6:00-8:00 pm (+ with flex).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Rachid Bendidi can be reached at (571) 272-4896. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/KIRSTEN JADE M SANTOS/Examiner, Art Unit 3664
/RACHID BENDIDI/Supervisory Patent Examiner, Art Unit 3664