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 § 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 4, 5, 7, and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Partsch et al. (US 20190024435 A1), herein after will be referred to as Partsch, in view of Reed et al. (US 20130239485 A1), herein after will be referred to as Reed, in view of Wegner (EP 4043686 B1), and in view of Kumar et al. (US 20170234054 A1), herein after will be referred to as Kumar.
Regarding Claim 1,
Disclosure by Partsch
Partsch discloses:
A door device comprising:
See at least: “a system for opening and closing … a door of a vehicle.” ([0004])
Rationale: Partsch expressly describes a “system” for a “door of a vehicle,” which corresponds to a door device.
a door
See at least: “a door of a vehicle.” ([0004])
Rationale: Partsch expressly discloses a vehicle “door,” meeting a door.
swingable relative to a vehicle body;
See at least: “a door of a vehicle.” ([0004])
Rationale: In the context of a “door of a vehicle,” the door is pivotable/swingable relative to the vehicle (vehicle body), which is an arrangement that would have been understood by a PHOSITA as inherent to a swing vehicle door.
an actuator configured to drive the door to open and close;
See at least: “a powered actuator configured to at least one of open and close the door.” ([0004])
Rationale: Partsch expressly discloses a “powered actuator” that can “open and close the door,” meeting an actuator configured to drive the door to open and close.
a controller configured to perform drive control on the actuator;
See at least: “a controller … configured to … control the powered actuator to cause the door to move ….” ([0004])
Rationale: Partsch expressly discloses a “controller” that “control[s] the powered actuator,” which corresponds to configured to perform drive control on the actuator.
wherein the controller is configured to: determine whether an opening/closing action to be performed on the door is a manual action, in which the door is to be manually opened or closed by a user, or an automatic action, in which the door is to be automatically opened or closed by the actuator;
See at least: “determine whether the opening or closing will be performed by the operator or via the powered actuator” ([0004])
Rationale: Partsch expressly distinguishes whether door opening/closing is performed “by the operator” versus “via the powered actuator,” which maps to manual action versus automatic action as claimed.
Claim Limitations Not Explicitly Disclosed by Partsch
However, Partsch does not explicitly disclose:
and a door open/close detector configured to detect an opening/closing speed of the door,
and while the manual action is being performed on the door, learn a manual opening/closing speed of the door, detected by the door open/close detector, while the manual action is being performed on the door, to generate learned value data including information on the opening/closing speed and to reflect the learned value data to the drive control on the actuator while the automatic action is being performed,
wherein the controller is further configured to learn the opening/closing speed in relation to an opening degree of the door to generate the learned value data so as to include opening degree-specific learned value data in which values of the opening/closing speed are associated with values of the opening degree of the door,
wherein the controller is further configured to learn the opening/closing speed in relation to the opening degree and in relation to an action start position of the door from which the manual action has started, to generate the learned value data so as to include position-specific learned value data in which the opening degree-specific learned value data is associated with the action start position,
and wherein when starting the automatic action, the controller reflects, of the position-specific learned value data, opening degree-specific learned value data corresponding to a current action start position of the door to the drive control on the actuator.
Disclosure by Reed
Reed discloses:
and a door open/close detector configured to detect an opening/closing speed of the door,
See at least: “a velocity sensor 60 for sensing the velocity (v) of the door 16 swing.” ([0027])
Rationale: Reed expressly discloses a “velocity sensor … for sensing the velocity … of the … door … swing,” which corresponds to a door open/close detector configured to detect an opening/closing speed of the door.
Motivation to Combine Partsch and Reed
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Partsch and Reed before them, to modify Partsch’s vehicle door system (which determines whether door opening/closing is performed “by the operator” or “via the powered actuator”) to further include Reed’s “velocity sensor … for sensing the velocity … of the … door … swing,” because both references are in the vehicle-door art and Reed provides a known door-motion sensing input that predictably improves controller awareness of door movement during user/manual operation and during transitions between operator-driven and actuator-driven motion.
Claim Limitations Not Explicitly Disclosed by the Combination of Partsch and Reed
After combining the teachings of Partsch and Reed, the following are not explicitly disclosed:
and while the manual action is being performed on the door, learn a manual opening/closing speed of the door, detected by the door open/close detector, while the manual action is being performed on the door, to generate learned value data including information on the opening/closing speed and to reflect the learned value data to the drive control on the actuator while the automatic action is being performed,
wherein the controller is further configured to learn the opening/closing speed in relation to an opening degree of the door to generate the learned value data so as to include opening degree-specific learned value data in which values of the opening/closing speed are associated with values of the opening degree of the door,
wherein the controller is further configured to learn the opening/closing speed in relation to the opening degree and in relation to an action start position of the door from which the manual action has started, to generate the learned value data so as to include position-specific learned value data in which the opening degree-specific learned value data is associated with the action start position,
and wherein when starting the automatic action, the controller reflects, of the position-specific learned value data, opening degree-specific learned value data corresponding to a current action start position of the door to the drive control on the actuator.
Disclosure by Wegner
Wegner discloses:
and while the manual action is being performed on the door, learn a manual opening/closing speed of the door,
See at least: “the person 11 operates the door leaf 10 manually in addition to the automatic operation by the door operator 1. This manual operation is detected by the door operator 1, and a correction value is determined in order to make a correction for future pivoting movements of the door leaf 10 ….” (Page 7)
Rationale: Wegner expressly describes that a user “operates the door leaf … manually,” that the “manual operation is detected,” and that “a correction value is determined” for “future pivoting movements,” which corresponds to learn during the manual action.
detected by the door open/close detector,
See at least: “a sensor 15 … can detect whether external forces are applied to the door leaf 10, for example, when a person pushes a door leaf forward or pulls it back into the closed position. The information via the sensor 15 can be transmitted to the control unit 13 ….” (Fig. 5 description, Page 8)
Rationale: Wegner expressly discloses sensing user-applied forces during manual operation and transmitting that information to a control unit; when combined with Reed’s “velocity sensor … for sensing the velocity … of the … door … swing,” the manual-operation learning in Wegner is performed using the sensed door-movement input, satisfying detected by the door open/close detector in the combined system.
while the manual action is being performed on the door,
See at least: “operates the door leaf 10 manually … This manual operation is detected … and a correction value is determined ….” (Fig. 1, Page 7)
Rationale: Wegner ties “manual” operation to detection and determining a correction value, i.e., the determination occurs in the context of the manual operation being performed.
to generate learned value data including information on the opening/closing speed
See at least: “recording and, in particular, saving correction values through interaction with the users, which then form the basis for controlling future pivoting movements of the door leaf.” (Disclosure of the invention, Page 5)
See at least: “accelerate or slow down the opening speed of the door leaf … [and] the closing speed … can be adjusted ….” (Page 2)
Rationale: Wegner expressly discloses “saving correction values through interaction with the users” and expressly states correction values can “accelerate or slow down the opening speed” and adjust “closing speed,” which corresponds to generating/storing data that includes information on door opening/closing speed.
and to reflect the learned value data to the drive control on the actuator while the automatic action is being performed,
See at least: “correcting future pivoting movements of the door leaf by the correction value.” (Page 2)
See at least: “saving correction values … form the basis for controlling future pivoting movements of the door leaf.” (Page 2)
Rationale: Wegner expressly discloses that saved correction values are used to “correct[] future pivoting movements” and “form the basis for controlling future pivoting movements,” which corresponds to reflecting the learned value data into actuator drive control during subsequent automatic operation.
Motivation to Combine Partsch, Reed, and Wegner
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Partsch, Reed, and Wegner before them, to modify Partsch’s vehicle door system (manual vs. powered determination with actuator drive control) as enhanced by Reed’s door “velocity sensor … for sensing the velocity … of the … door … swing,” to further incorporate Wegner’s “learning door operator” approach that “record[s] and … sav[es] correction values through interaction with the users” that “form the basis for controlling future pivoting movements,” because Wegner expressly addresses adapting powered door movement based on user interaction during manual operation and provides an explicit mechanism (stored correction values affecting opening/closing speed) that predictably improves the controlled actuator-driven movement in a Partsch-style powered vehicle door.
Claim Limitations Not Explicitly Disclosed by the Combination of Partsch, Reed, and Wegner
After combining the teachings of Partsch, Reed, and Wegner, the following are not explicitly disclosed:
wherein the controller is further configured to learn the opening/closing speed in relation to an opening degree of the door to generate the learned value data so as to include opening degree-specific learned value data in which values of the opening/closing speed are associated with values of the opening degree of the door,
wherein the controller is further configured to learn the opening/closing speed in relation to the opening degree and in relation to an action start position of the door from which the manual action has started, to generate the learned value data so as to include position-specific learned value data in which the opening degree-specific learned value data is associated with the action start position,
and wherein when starting the automatic action, the controller reflects, of the position-specific learned value data, opening degree-specific learned value data corresponding to a current action start position of the door to the drive control on the actuator.
Disclosure by Kumar
Kumar discloses:
wherein the controller is further configured to learn the opening/closing speed in relation to an opening degree of the door
See at least: “determine a first open-door angle ….” ([0044])
See at least: “determine a second open-door angle … (1) a current angle of a door; or (2) a desired angle ….” ([0045])
Rationale: Kumar expressly uses door “angle” as a control variable (“open-door angle,” including “current angle”), providing the required opening degree framework for organizing door-speed control relative to door opening degree. (The learn aspect remains provided by Wegner; Kumar is relied upon only for the opening-degree structure.)
to generate the learned value data so as to include opening degree-specific learned value data in which values of the opening/closing speed are associated with values of the opening degree of the door,
See at least: “controller 100 may determine a velocity profile 500 … based on a current angle of a door or a desired angle.” ([0046])
See at least: “control operation of actuator 122 … according to … a second open-door angle, and a velocity profile 500. The speed at which actuator 122 is opening or closing a door … may be determined by velocity profile 500.” ([0047])
Rationale: Kumar expressly ties (i) door opening degree (“current angle” / “desired angle” / “open-door angle”) to (ii) door speed (“The speed … may be determined by velocity profile”), thereby providing opening-degree-specific speed values associated with door opening degree.
wherein the controller is further configured to learn the opening/closing speed in relation to the opening degree and in relation to an action start position of the door from which the manual action has started,
See at least: “A second open-door angle may be: (1) a current angle of a door; … A current angle of a door may be used when the door is going to be closed.” ([0045])
See at least: “Velocity profile 500 … may be based on a current angle of a door ….” ([0046])
Rationale: Kumar expressly uses a “current angle of a door” as an input to determine the “velocity profile,” which corresponds to using a present/start angle (i.e., an action start position) as a basis for selecting the applicable speed-vs-angle control behavior. (Again, learn remains provided by Wegner; Kumar is relied upon only for the start-position/angle selection structure.)
to generate the learned value data so as to include position-specific learned value data in which the opening degree-specific learned value data is associated with the action start position,
See at least: “Velocity profile 500 … may be based on a current angle of a door ….” ([0046])
See at least: “the time to move the door from a current position to a closed position.” ([0046])
Rationale: Kumar explicitly treats the “current angle” / “current position” as an input that conditions the resulting “velocity profile” and thus the speed behavior, which provides a position-specific association between the opening-degree-dependent control values and the action’s starting position.
and wherein when starting the automatic action, the controller reflects, of the position-specific learned value data, opening degree-specific learned value data corresponding to a current action start position of the door to the drive control on the actuator.
See at least: “A second open-door angle may be: (1) a current angle of a door ….” ([0045])
See at least: “controller 100 may determine a velocity profile 500 … based on a current angle of a door ….” ([0046])
See at least: “control operation of actuator 122 … according to … a second open-door angle, and a velocity profile 500 ….” ([0047])
Rationale: Kumar expressly (i) identifies a “current angle” (current start position), (ii) determines a “velocity profile” based on that current angle, and (iii) controls the actuator according to that profile—i.e., it applies the angle-corresponding speed-control data at the start of actuator-driven operation.
Motivation to Combine Partsch, Reed, Wegner, and Kumar
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Partsch, Reed, Wegner, and Kumar before them, to further modify the Partsch + Reed + Wegner combination to incorporate Kumar’s angle-based velocity-profile framework, because Kumar provides a well-defined and predictable way to structure actuator door-speed control as a function of door opening degree (including “current angle”) and to select the applicable speed-control behavior based on the door’s current/start angle, which directly complements Wegner’s stored, interaction-derived correction values affecting opening and closing speed and enables those learned/corrective speed values to be organized and applied in an opening-degree- and start-position-dependent manner during subsequent actuator-driven operation.
Regarding Claim 4
The combination of Partsch, Reed, Wegner, and Kumar establishes the door device of Claim 1, which is the basis for Claim 4.
Disclosure by Partsch
Partsch discloses:
wherein the controller is further configured
See at least: “Operator interface 110 … transmit the signal to controller 100 … for further processing.” ([0025])
Rationale: Partsch’s “controller 100” corresponds to the claimed controller, and the recited “for further processing” evidence configuration of the controller (i.e., is further configured).
for a case when the user is inside a vehicle compartment
See at least: “an operation performed by the operator inside the vehicle” ([0015]).
Rationale: Partsch expressly distinguishes door operation performed by a user located inside the vehicle compartment, satisfying the claimed inside-vehicle case.
and a case when the user is outside the vehicle compartment
See at least: “an operation performed by a user outside the vehicle” ([0015]).
Rationale: Partsch expressly distinguishes door operation performed by a user located outside the vehicle compartment, satisfying the claimed outside-vehicle case.
Claim Elements Not Explicitly Disclosed by Partsch
Partsch does not explicitly disclose:
to further learn the manual opening/closing speed separately
Disclosure by Reed
Reed discloses:
the manual opening/closing speed
See at least: “door swing velocity (v), as sensed by the velocity sensor 60” ([0027]).
Rationale: Reed expressly discloses sensing the opening/closing speed of the door during user-induced manual movement, supplying the speed information that is subject to learning.
Claim Elements Not Explicitly Disclosed by Partsch and Reed
Partsch and Reed do not explicitly disclose:
to further learn the manual opening/closing speed separately
Disclosure by Wegner
Wegner discloses:
to further learn the manual opening/closing speed (as part of “learning”/storing correction values derived from user interaction)
See at least: “the person … operates the door leaf … manually … This manual operation is detected … and a correction value is determined … for future pivoting movements …” (Page 7); “The control unit has a correction value memory in which correction values are stored …” (Page 3)
Rationale: Wegner expressly teaches learning from manual user interaction (manual operation detected; a value determined) and storing such values for future control, which corresponds to a controller being further configured to further learn the manual opening/closing speed (with the manual speed input provided by the Claim 1 detector as established via Reed).
separately (storing learned/correction values in separate groupings keyed to a condition/case)
See at least: “correction values can also be provided that are stored depending on the time of day or the day of the week …” (Page 3); “a matrix, a table or a list is generated in which the correction values … are stored depending on …” (Page 6)
Rationale: Wegner expressly teaches storing learned/correction values depending on a condition and organizing them in a data structure (matrix/table/list), which supports that such learned values can be stored separately for different cases.
Motivation to Combine Partsch, Wegner, and Kumar
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Partsch, Wegner, and Kumar before them, to implement the claimed “separately” learned manual-speed behavior by keying the learned/stored values (Wegner) to the explicitly recognized inside-versus-outside vehicle user contexts (Partsch/Kumar), because both Partsch and Kumar expressly frame door operation inputs as occurring inside or outside the vehicle, and Wegner teaches storing learned/correction values in memory in grouped form depending on the applicable case, yielding the predictable result of maintaining separate learned datasets for the inside-user scenario and the outside-user scenario.
Regarding Claim 5
The combination of Partsch, Reed, Wegner, and Kumar establishes the door device of Claim 1, which is the basis for Claim 5.
Disclosure by Partsch
Partsch discloses:
wherein the controller is further configured
See at least: “The system may also include a controller … configured to … determine whether the opening or closing will be performed by the operator or via the powered actuator …” ([0004]).
Rationale: Rationale: Partsch expressly describes additional controller configuration for performing specific determinations/control functions, supporting the “controller is further configured” framing for the added limitation.
Claim Elements Not Explicitly Disclosed by Partsch
Partsch does not explicitly disclose:
to calculate an average value of the manual opening/closing speed
by averaging values of the manual opening/closing speed
over a plurality of manual actions
and include the average value
into the learned value data
as the information on the manual opening/closing speed
Disclosure by Reed
Reed discloses:
the manual opening/closing speed
See at least: “door swing velocity (v), as sensed by the velocity sensor 60.” ([0063])
Rationale: Reed expressly discloses sensing the opening/closing speed of the door during user-induced manual movement, providing the manual opening/closing speed values that are later learned and processed.
Claim Limitations Not Explicitly Disclosed by Partsch and Reed
Partsch and Reed do not explicitly disclose:
to calculate an average value of the manual opening/closing speed
by averaging values of the manual opening/closing speed
over a plurality of manual actions
and include the average value
into the learned value data
as the information on the manual opening/closing speed
Disclosure by Wegner
Wegner renders obvious:
to calculate an average value of the manual opening/closing speed
See at least: “the correction values in the correction value memory are optimized using the learning algorithm according to the invention” (Page 3)
Rationale: Wegner expressly teaches calculating an optimized value from stored interaction-derived values using a learning algorithm. Given Reed’s disclosure that the interaction-derived values include measured manual opening/closing speed, a PHOSITA would have predictably calculated a representative value from those speed samples.
by averaging values of the manual opening/closing speed
See at least: “recording and, in particular, saving correction values through interaction with the users” (Page 2); “the interactions … are detected … over a longer period of time” (Page 3)
Rationale: Wegner expressly teaches storing multiple interaction-derived values over time. A PHOSITA would have recognized averaging as a fundamental and predictable algorithm for processing multiple numeric manual speed values to obtain a representative value that smooths variation across manual actions.
over a plurality of manual actions
See at least: “recording and, in particular, saving correction values through interaction with the users” (Page 2); “over a longer period of time” (Page 3)
Rationale: Interaction with users over time inherently involves a plurality of manual actions from which multiple values are recorded.
and include the average value
See at least: “the correction values … are used as the basis for future control of the door leaf” (Page 3)
Rationale: Wegner expressly discloses that the evaluated/optimized value is retained and used for subsequent control, corresponding to inclusion of the calculated value.
into the learned value data
See at least: “the correction values in the correction value memory … form the basis for controlling future pivoting movements of the door leaf” (Page 3)
Rationale: The stored and optimized correction values constitute learned value data used for future control.
as the information on the manual opening/closing speed
See at least: “the correction value … can accelerate or slow down the opening speed of the door leaf” (Page 3)
Rationale: Wegner expressly discloses that the learned correction values directly relate to door opening speed, such that the averaged value constitutes information on the manual opening/closing speed.
Motivation to Combine Partsch, Reed, Wegner, and Kumar
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Partsch, Reed, Wegner, and Kumar before them, to configure the controller of the door device of Claim 1 to calculate an average value of the manual opening/closing speed by averaging values of the manual opening/closing speed over a plurality of manual actions and include the average value into the learned value data, because Partsch provides the underlying vehicle door control architecture, Reed expressly supplies measured manual opening/closing speed samples during user interaction, Wegner expressly teaches recording and saving interaction-derived values over time and optimizing those values using a learning algorithm for future control, and a PHOSITA would have predictably implemented that optimization as an averaging operation to obtain a stable representative speed value suitable for reuse in actuator control, yielding consistent and reliable door behavior without hindsight reconstruction.
Regarding Claim 7
The combination of Partsch, Reed, Wegner, and Kumar establishes the door device of Claim 1, which is the basis for Claim 7.
Disclosure by Partsch
However, Partsch does not explicitly disclose:
wherein the controller is further configured to learn the manual opening/closing speed
only when the opening/closing speed is less than or equal to a predetermined value.
Disclosure by Reed
Reed discloses:
the manual opening/closing speed
See at least: “door swing velocity (v), as sensed by the velocity sensor 60.” ([0027])
Rationale: Reed expressly discloses sensing “door swing velocity (v)” via “the velocity sensor 60,” which is the claimed manual opening/closing speed value.
only when the opening/closing speed is less than or equal to
See at least: “delay the generation of the resistive force until a certain door velocity … reached.” ([0023])
Rationale: Reed expressly teaches a speed-threshold gating condition (“until a certain door velocity … reached”), i.e., a predetermined speed threshold used to gate when a control action occurs based on door speed, corresponding to performing the recited operation only when the opening/closing speed is less than or equal to the threshold.
a predetermined value.
See at least: “until a certain door velocity … reached.” ([0023])
Rationale: Reed’s “certain door velocity” is an express predetermined threshold value for door speed, satisfying a predetermined value.
Disclosure by Wegner
Wegner renders obvious:
to learn the manual opening/closing speed
See at least: “a door system with a learning door operator … by recording and, in particular, saving correction values through interaction with the users, which then form the basis for controlling future pivoting movements of the door leaf.” (Page 2); “via … the correction values stored in the correction value memory … a continuous optimization of the control … can be carried out … to continuously improve the movement behavior of the door leaf …” (Page 8)
Rationale: Wegner expressly teaches a “learning door operator” that “records” and “saves” correction values and performs “continuous optimization,” which constitutes the claimed to learn functionality (with the learned values forming the basis for controlling future pivoting movements).
Motivation to Combine Partsch, Reed, Wegner, and Kumar
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Partsch, Reed, Wegner, and Kumar before them, to configure the controller of the door device of Claim 1 such that the controller learn[s] as taught by Wegner’s “learning door operator” that records/saves correction values and performs continuous optimization for future door movement control , while using Reed’s expressly taught manual door-speed sensing (“door swing velocity (v)”) and Reed’s expressly taught speed-threshold gating (“until a certain door velocity … reached”) so that the learning update is performed only when the measured opening/closing speed satisfies the predetermined threshold condition (≤ a predetermined value). Conditioning Wegner’s learning update on Reed’s speed threshold is a predictable control refinement to ensure the learned values reflect typical, intentional user behavior rather than aberrant high-speed actions that could degrade system performance.
Regarding Claim 8,
The combination of Partsch, Reed, Wegner, and Kumar establishes the door device of Claim 1, which is the basis for Claim 8.
Disclosure by Partsch
further comprises a user identification device
See at least: “operator interface 110 may be … an imaging sensor … or a finger/palm scanner…” ([0026]).
Rationale: Partsch’s disclosed operator interface embodiments (e.g., imaging sensor; finger/palm scanner) constitute a “user identification device.”
capable of recognizing a plurality of users separately,
See at least: “Exemplary input may include … face recognition, finger print, hand print…” ([0026]).
Rationale: Inputs such as “face recognition” and “finger print” inherently enable distinguishing different individuals, i.e., recognizing a plurality of users separately.
Disclosure by Reed
Reed discloses:
the manual opening/closing speed
See at least: “door swing velocity (v), as sensed by the velocity sensor 60.” ([0027])
Rationale: Reed expressly discloses sensing “door swing velocity (v)” via “the velocity sensor 60,” which is the claimed manual opening/closing speed value.
Disclosure by Wegner
and wherein the controller is further configured to
See at least: “The behavior of the person 11 can be detected by the sensor unit 12 and transmitted to the control unit 13.” (Page 8)
Rationale: Wegner expressly discloses a “control unit” receiving detected behavior information, consistent with a controller being configured to perform additional operations using such information.
further learn the manual opening/closing speed
See at least: “it shows that the person 11 operates the door leaf 10 manually … This manual operation is detected … and a correction value is determined in order to make a correction for future pivoting movements…” (Page 7)
Rationale: Wegner expressly teaches detecting manual operation and determining/storing a correction value for future movements—i.e., a learning/adaptation mechanism derived from user interaction (consistent with learning manual movement behavior, including speed-related behavior from Reed).
on a per-user basis
See at least: “Finally, the interactions between the door leaf and a number of people, a matrix, a table or a list is generated in which the correction values … are stored depending on the time of day and/or the day of the week and/or other environmental influences…” (Page 6)
Rationale: Wegner teaches organizing stored correction values in structured records (e.g., “matrix, a table or a list”) indexed by conditions. With Partsch’s user recognition, a PHOSITA would apply Wegner’s same structured storage approach to index/segregate learned correction values per identified user (i.e., “on a per-user basis”), using the recognized user as an additional indexing condition.
to generate the learned value data
See at least: “a correction value is determined in order to make a correction for future pivoting movements…” ; and “a matrix, a table or a list is generated in which the correction values … are stored…” (Page 7)
Rationale: Wegner’s determined and stored “correction values” (including their organized storage in a table/list structure) correspond to generated learned value data used for future control.
so as to associate values
See at least: “a matrix, a table or a list is generated in which the correction values … are stored depending on …” (Page 6)
Rationale: Storing values “depending on” an indexing condition is an association of values with that condition; adding “user identity” (from Partsch) as the condition yields associating values with users.
of the manual opening/closing speed
See at least: “Shown is a walking speed v … The behavior of the person 11 can be detected by the sensor unit 12 and transmitted to the control unit 13.” (Page 8)
Rationale: Wegner expressly teaches detection/transmission of speed-related behavior information to the controller for optimization; in the Claim 1 context already established by the combination, Reed supplies door-movement speed sensing, and Wegner supplies the learning/storage framework that uses such speed-related inputs.
with users.
See at least in Partsch: “face recognition, finger print, hand print” ([0026]). ; and in Wegner: “a matrix, a table or a list … [with] correction values … stored depending on …” (Page 6)
Rationale: Partsch provides the mechanism to identify which user is interacting; Wegner provides structured storage of learned correction values conditioned on parameters. Combining them yields storing/associating the learned speed-related values with the identified user.
Motivation to Combine Partsch, Reed, Wegner, and Kumar
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Partsch, Reed, Wegner, and Kumar before them, to modify the door device of Claim 1 to further include the Claim 8 features. Partsch already teaches user recognition inputs (e.g., face/fingerprint), while Wegner teaches learning-derived correction values and storing them in structured records (matrix/table/list) conditioned on parameters; a PHOSITA would have been motivated to apply Partsch’s user identification to Wegner’s conditional/structured storage so the learned speed-related values are maintained per recognized user, yielding the predictable result of personalized learned value data associated with users.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Partsch, in view of Reed, in view of Wegner, in view of Kumar, and in view of Lee et al. (US 20080319589 A1), herein after will be referred to as Lee.
Regarding Claim 6,
The combination of Partsch, Reed, Wegner, and Kumar establishes the door device of Claim 1, which is the basis for Claim 6.
Disclosure by Partsch
Partsch does not explicitly disclose:
wherein the controller is further configured to learn the manual opening/closing speed only when a tilt angle of the vehicle body is less than or equal to a predetermined value.
Disclosure by Reed
Reed discloses:
the manual opening/closing speed
See at least: “a velocity sensor 60 for sensing the velocity (v) of the door 16 swing.” ([0027])
Rationale: Reed expressly discloses sensing the door swing “velocity (v)” via a “velocity sensor,” which corresponds to the manual opening/closing speed used as the speed input in the already-established Claim 1 learning system (learning itself remains attributed to Wegner, not Reed).
Claim Limitation Not Explicitly Disclosed by the Combination of Partsch and Reed
After combining the teachings of Partsch and Reed, the following are not explicitly disclosed:
wherein the controller is further configured to learn the manual opening/closing speed only when a tilt angle of the vehicle body is less than or equal to a predetermined value.
Disclosure by Wegner
Wegner renders obvious:
wherein the controller is further configured to learn the manual opening/closing speed
See at least: “the adjustment of the control of the door leaf takes place … by recording and, in particular, saving correction values through interaction with the users, which then form the basis for controlling future pivoting movements of the door leaf.” (Page 2); “accelerate or slow down the opening speed of the door leaf … [and] the closing speed … can be adjusted ….” (Page 2)
Rationale: Learning attributed to Wegner; speed input sourced from Reed. Wegner expressly teaches a “learning door operator” that “records and … saves correction values through interaction with the users” and uses those saved values as the basis for “future” door control; Wegner also expressly ties the correction values to “opening speed” and “closing speed,” which corresponds to learning the manual opening/closing speed (with the manual speed measurement supplied by Reed’s velocity sensor in the combined system).
Claim Elements Not Explicitly Disclosed by the Combination of Partsch, Reed, Wegner, and Kumar
After combining the teachings of Partsch, Reed, and Wegner, the following are not explicitly disclosed:
only when a tilt angle of the vehicle body is less than or equal to a predetermined value.
Disclosure by Lee
Lee renders obvious:
only when a tilt angle of the vehicle body is less than or equal to a predetermined value
See at least: “The vehicle 10 has a tilt sensor unit 12 for determining roll and pitch information for the vehicle 10.” ([0038]); “The magnitude of the resulting acceleration vector is subjected to a threshold decision with a window that is delimited by a threshold lying above and a threshold lying below the gravitational acceleration.” ([0004]); “A current course angle … is then determined only if the magnitude of the acceleration vector lies inside the window.” ([0004])
Rationale: Lee explicitly discloses a "tilt sensor unit" determining vehicle "roll and pitch," which corresponds to the claimed "tilt angle of the vehicle body". Lee further teaches gating operations based on a "threshold" or "window," where a determination occurs "only if" the sensed condition falls within these bounds. This "only if" logic functionally maps to the claimed "only when" limitation, with the window serving as the "predetermined value.". In the combined system, a PHOSITA would apply Lee's threshold-gating to Wegner's learning update. The motivation is grounded in physics: a vehicle door operating on an incline is subject to gravitational forces that do not exist on flat ground. "Learning" a manual speed profile while the vehicle is tilted would encode corrupted data (e.g., the system recording high force because the user is fighting gravity). Therefore, it would be obvious to use Lee's tilt sensors to disable Wegner's learning mode when the vehicle is on a hill (tilt > predetermined value) to ensure the learned velocity profiles are valid for normal operation.
Motivation to Combine Partsch, Reed, Wegner, Kumar, and Lee
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Partsch, Reed, Wegner, Kumar, and Lee before them, to modify the Partsch + Reed + Wegner (+ Kumar) door device of Claim 1 so that the controller updates (learns) the manual opening/closing speed only when a measured vehicle-body tilt angle satisfies a predetermined threshold, because Lee teaches (i) obtaining vehicle-body tilt information (roll/pitch) via a tilt sensor unit and (ii) performing control/determination only if a sensed condition falls within predetermined threshold bounds, and applying that explicit “only if” gating to Wegner’s learning update predictably prevents learned control data from being updated under vehicle-tilt conditions that could distort manual door-speed measurements and degrade subsequent actuator control.
Response to Arguments
Examiner Response — Withdrawal of 101 Rejection
Applicant’s amendments to Claims 1, 4–8 have been fully considered. In view of the amendments, the prior rejection of Claims 1, 4–8 under 35 U.S.C. 101 is withdrawn.
These limitations, as amended, are directed to controlling a physical door mechanism using sensor-detected physical movement parameters (opening/closing speed, opening degree, action start position) and applying the learned values to the actuator’s drive control. Accordingly, the claim is directed to a practical application involving real-time control of a physical system rather than to an abstract idea.
Dependent Claims 4–8 further refine the physical control application by specifying learning separately based on user position (inside vs. outside compartment) (Claim 4), averaging speed values over multiple manual actions and including the average in the learned value data (Claim 5), restricting learning to conditions defined by vehicle tilt angle (Claim 6) and by opening/closing speed thresholds (Claim 7), and associating learned speed values with recognized users via a user identification device (Claim 8). These dependent claims further emphasize that the claimed subject matter is tied to objective machine states and sensor-derived physical conditions and remains within a practical application of door control.
For the foregoing reasons, Claims 1, 4–8, as amended, are eligible under 35 U.S.C. 101, and the prior 101 rejection is withdrawn.
Response to Applicant’s Arguments Under 35 U.S.C. 103
Applicant’s arguments traversing the rejection of Claims 1–4 and 7 under 35 U.S.C. 103 as being unpatentable over Fujimoto et al. in view of Aihara et al. have been fully considered. However, these arguments are moot and non-responsive to the present rejection because the applied prior-art combination has been withdrawn and replaced in view of Applicant’s amendments and the Office’s updated prior-art findings.
Applicant’s arguments are directed entirely at alleged deficiencies of Fujimoto and Aihara, particularly that those references fail to disclose or suggest:
learning door control parameters during manual user operation, and
reflecting such learned values into subsequent actuator-driven door control.
As set forth in the updated rejection, Fujimoto and Aihara are no longer relied upon. The claims are now rejected under a different 103 ground, based on the combination of:
Partsch,
Reed,
Wegner,
Kumar, and
Lee (as applied to Claim 6).
Because the cited art forming the basis of Applicant’s arguments is no longer applied, those arguments do not address the current grounds of rejection and are therefore moot.
Each reference applied in the present rejection is proper prior art and constitutes analogous art either because it is (i) from the same field of endeavor, or (ii) reasonably pertinent to the problem faced by the inventor.
Partsch is directed to powered vehicle door systems, including a controller that distinguishes between manual user operation and actuator-driven automatic operation, and performs drive control accordingly.
Field of endeavor: Vehicle door control systems.
Pertinence: Addresses the same fundamental problem as the claimed invention—coordinating manual and powered door operation via a controller.
Reed discloses sensing door swing velocity using a dedicated velocity sensor during door movement, including during user-induced motion.
Field of endeavor: Door motion sensing and control.
Pertinence: Reed supplies the door opening/closing speed detection required by the claims, which is an explicit input to the claimed learning process.
Reed is reasonably pertinent to improving door control responsiveness and safety and is therefore analogous art.
Wegner discloses a system that records and saves correction values derived from interaction with users and uses those values as the basis for future actuator-driven door movement.
Field of endeavor: Automatic swing door operators.
Pertinence: Wegner expressly addresses the problem of adapting powered door behavior based on manual user interaction, which directly corresponds to the claimed “learning” of manual opening/closing speed and reflecting that learning into automatic control.
Wegner is thus analogous art under both prongs of the test and provides the learning framework absent from earlier art.
Kumar discloses controlling door speed using velocity profiles as a function of door opening angle, including selecting an appropriate profile based on the current door angle at actuation start.
Field of endeavor: Powered door motion control.
Pertinence: Kumar supplies the structural organization and application of speed control data as a function of opening degree and start position, which the claims require—but does not teach learning, consistent with the Office’s attribution.
Kumar is reasonably pertinent because it addresses how actuator control should be shaped once relevant speed data exists.
Lee discloses determining vehicle roll and pitch (tilt angle) using a tilt sensor and performing control or determination only if the sensed value satisfies a predefined threshold or window.
Field of endeavor: Vehicle motion and control systems.
Pertinence: Claim 6 requires that learning occur only when the vehicle body tilt angle is less than or equal to a predetermined value. Lee expressly teaches:
sensing vehicle tilt (roll/pitch), and
exclusive, threshold-gated logic using “only if” conditions.
Lee is reasonably pertinent to the problem of conditioning control behavior on vehicle attitude, which directly relates to ensuring learning occurs only under stable vehicle conditions. Applying Lee’s threshold-based gating to Wegner’s learning update represents a predictable use of known vehicle-state conditioning techniques. Claim 6 introduces a new and specific limitation requiring that learning be performed only when a vehicle body tilt angle is less than or equal to a predetermined value. Neither Partsch, Reed, Wegner, nor Kumar explicitly disclose tilt-angle-based exclusivity gating. Lee is therefore applied only to supply this missing feature.
Importantly, Lee provides both:
Tilt angle determination (roll/pitch sensing), and
Explicit exclusivity logic (“only if” a threshold condition is satisfied).
This “only if” teaching directly corresponds to the claim’s “only when” requirement and cures the previously identified gap. The Office does not rely on Lee for learning, speed sensing, or door control architecture, but solely for conditional gating based on vehicle tilt, thereby avoiding redundancy or hindsight reconstruction.
Because the present 103 rejection is based on a different combination of prior art—namely Partsch, Reed, Wegner, Kumar, and Lee—Applicant’s arguments directed to Fujimoto and Aihara do not traverse the current grounds of rejection and are therefore moot. Each applied reference constitutes proper prior art and analogous art, and each contributes a distinct, non-overlapping teaching toward the claimed invention, yielding a predictable result without impermissible hindsight.
Accordingly, Applicant’s request for withdrawal of the §103 rejections is not persuasive with respect to the presently applied art.
Conclusion
THIS ACTION IS MADE FINAL. 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 nonprovisional extension fee (37 CFR 1.17(a)) 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 mailing date of this final action.
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/OLUWABUSAYO ADEBANJO AWORUNSE/Examiner, Art Unit 3662
/JELANI A SMITH/Supervisory Patent Examiner, Art Unit 3662