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 action is in response to the claims filed on 07/23/2026. Wherein, claims 1, 5, and 10-12 are amended and claims 3 and 4 are cancelled. Claims 1, 2, and 5-10 are rejected.
Information Disclosure Statement
The information Disclosure Statements filed on 09/17/2026 have been considered. An initialed copy of form 1449 for each is enclosed herewith.
Response to Arguments
Applicant’s arguments, see REMARKS, filed 07/23/2026, with respect to the rejection of claims 1, 2, and 6-12, under 35 USC § 101, have been fully considered and are persuasive. Therefore, the previous rejections of claims 1, 2, and 6-12, under 35 USC § 101, have been withdrawn.
Applicant’s arguments, with respect to the rejection of claims 1, 2, 6-8, 10, and 11, under 35 USC § 102, have been fully considered and are persuasive. Therefore, the previous rejections of claims 1, 2, 6-8, 10, and 11, under 35 USC § 102, have been withdrawn.
Applicant’s arguments, with respect to the rejection of newly amended claim 1, amended to include previously presented claims 3 and 4, have been fully considered but are not persuasive. Therefore, a new rejection of claim 1 is presented below in view of previously cited prior art Hikari.
With respect to the amendments of claim 1, the Applicant argues:
As discussed during the interview, amended claim 1 recites a sequential process in which an "instruction velocity" is first set and that set "instruction velocity" is then corrected so as "to fall within the restricted range." The "controller" of claim 1 thus does not recalculate the "instruction velocity" but rather shifts it so as to be within the "restricted range." Beardsley, on the other hand, simply calculates signals to avoid collisions with other flying or airborne vehicles. See, e.g., Beardsley, ¶ [0048], [0052]. This does not teach the aforementioned correction of an already set "instruction velocity."
Claim 1 is directed towards a controller that “calculates” an operation quantity of an actuator to move a mover. The sequential process of the controller requires 1) in a case where the instruction velocity is out of a restricted range, 2) correct the instruction velocity to fall within the restricted range, and 3) output a final instruction velocity to the servo processor.
It is unclear from the above argument how shifting a value and recalculating a value differ. Further, it is unclear from the claim language how a controller that “calculates” as a function can “shift” a value without it being an additional calculation, i.e., a recalculation.
With respect to Beardsley, as discussed in ¶ [0051]-[0052] the system first receives an input for a desired velocity from a driver/operator. Then, a guidance trajectory is generated. This trajectory determines the allowable vehicle motion parameters. These two inputs are combined and a local trajectory is computed, i.e., this creates the instruction velocity that is first set. This local trajectory is then provided to an “optimizer” which generates an optimal motion control for the vehicle so that it will achieve collision-free motions that respect the dynamic constraints of the vehicle. In other words if the local trajectory is not optimized, i.e., it is out of a restricted range, then the optimizer corrects the motion instructions to be within the restricted range. Finally, the optimized trajectory is used for instructing the vehicle to move, i.e., by commanding the actuator processors.
Thus, Beardsley discloses the entirety of the above limitations with the exception of explicitly teaching the use of a servo. Therefore, Hikari was applied to teach the use of a servo instead of a generic actuator/mechanism.
But, as noted above and during the interview, claim 1 is amended to recite the features of claim 4. This claim thus now recites "a restrictor that sets a constraint condition of the instruction velocity, the constraint condition concerning control characteristics of the servo processor and being for avoidance of an obstacle." The Office acknowledges that Beardsley does not teach the features of claim 4, but it then turns to Hikari, and particularly its [0006]. Office Action, P23. That paragraph discloses calculating command values based on two inputs, namely (i) a vehicle's "motion state" and (ii) an "obstacle state." But, even if one were to, say, consider Hikari's obstacle state to teach a "constraint condition ... for avoidance of an obstacle," the recited "control characteristics" of that "constraint condition" are "of the servo processor" "that performs servo control based on the instruction velocity of the mover." Hikari's broad teaching of a vehicle "motion state" is insufficient to disclose such "control characteristics," so this reference and Beardsley fail to teach setting a "constraint condition" such as that now recited.
The motion state within Hikari is not “generic” it is described in Equation 1, further the motion state includes longitudinal velocity and lateral velocity of the vehicle. (¶ [0038]-[0042])
Hikari discloses determining command values for the servo, i.e., instruction velocities, that consider the vehicles motion state and surrounding obstacle states. A first control command value is implemented as the first output value. From this state, a second control command value is calculated using the predicted motion and surrounding obstacle state. If there is an error with these state prediction calculations, i.e., the error is a constraint condition, then the calculation is redone, i.e., guarantees that the constraint is met. Then once the calculation meets the constraint condition, the vehicle is controlled. The error constraints keeps the vehicle from colliding with external objects due to error in their state values.
For the above reasons the Examiner finds the Applicant’s arguments unpersuasive.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) are:
“…a setter that sets an instruction value…”, in claims 1 and 11;
“…a restrictor that sets a constraint condition…”, in claims 1, 2, 4-9, and 11;
“…a corrector that corrects the instruction value…”, in claims 1, 3, 9, and 10;
“…an operation quantity calculator that calculates…”, in claims 1 and 3;
Because these claim limitation(s) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
In the instant application the specification defines these terms as being part of the controller 100. The controller 100 is provided as “…The controller 100 controls the entire mover 1. The controller 100 performs autonomous driving of the mover 1. That is, the controller 100 operates the actuator 12 to move the mover 1. The controller 100 includes a processor 18, a storage 19, and a memory 110. The processor 18 performs various calculations. For example, the processor 18 is a processor such as a central processing unit (CPU). The processor 18 may be a micro controller unit (MCU), a microprocessor unit (MPU), a field programmable gate array (FPGA), a programmable logic controller (PLC), system LSI, or the like. The storage 19 stores programs and various types of data to be executed by the processor 18. For example, the storage 19 stores a control program. The storage 19 is a nonvolatile memory, a hard disc drive (HDD), or a solid state drive (SSD), for example. The memory 110 temporarily stores data or other information. For example, the memory 110 is a volatile memory.” (¶ [0015]-[0017]) As such each term may be considered hardware, software or any combination thereof.
If applicant does not intend to have these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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.
Claim(s) 1, 2, and 5-11 are rejected under 35 U.S.C. 103 as being unpatentable over Beardsley et al. (US 2015/0284010 A1, “Beardsley”) in view of Hikari (JP 2010173616 A, “Hikari”).
Regarding claim 1, Beardsley discloses shared control of semi-autonomous vehicles including collision avoidance in multi-agent scenarios and teaches:
A controller that calculates an operation quantity of an actuator to move a mover, the controller comprising a processor programmed to function as: (The vehicle 110 may include a processor 112 running a local controller 116 that controls operations of a drive mechanism(s)/actuator 118 to cause the vehicle 110 to move in a particular direction and velocity within the space 105 – See at least ¶ [0044])
a setter that sets an instruction velocity to move the mover to a target position; (The vehicle 110 may include a processor 112 running a local controller 116 that controls operations of a drive mechanism(s)/actuator 118 to cause the vehicle 110 to move in a particular direction and velocity within the space 105. This control may be based on motion control signals 138 from a central control system 130 and also based on input from user input devices 114 – See at least ¶ [0044])
a [actuator] processor that performs [actuator] control based on the instruction velocity of the mover; (The vehicle 110 may include a processor 112 running a local controller 116 that controls operations of a drive mechanism(s)/actuator 118 to cause the vehicle 110 to move in a particular direction and velocity within the space 105. This control may be based on motion control signals 138 from a central control system 130 and also based on input from user input devices 114 – See at least ¶ [0044])
a restrictor that sets a constraint condition of the instruction velocity, the constraint condition concerning control characteristics of the servo processor and being for avoidance of an obstacle; (The processor 122 manages one or data storages devices or memory 140 to store (at least temporarily) data used by the controller module 130 to provide the shared control of the vehicles 110. As shown, for example, the memory 140 may be used to store received user input and sensor data 1442 from the vehicle 110. Further, the memory 140 may store a guidance trajectory 144 defined by the con troller module 130 for controlling the vehicle 110 including defining active areas 145 within the drive space 105 in which the vehicle 110 may be driven by an operator/driver while following a ride path or other planned trajectory. The memory 140 also stores a number of optimization constraints 150 that are used by the optimization engine 136. The constraints 150 may include a grid map 152 that maps physical obstacles 154 and, in some embodiments, virtual objects 156 (e.g., displayed 2D or 3D images of objects projected into space 105 or displayed to within or nearby the vehicle 110 to appear to be in the space 105) to locations or positions within the drive space 105. The controller module 130 may search the grid map 152 based on a present location of the vehicle 110 to generate a motion control signal 138 that avoids collision with obstacles. Additionally, the memory 140 may be used to store vehicle properties and/or kinematics 158 for the vehicle 110 that can be used to determine the motion control signal 138 (e.g., an acceptable local trajectory for a next control cycle or at a present time). Other constraints 150 may include data on other vehicles/agents 160 that may be used to avoid collisions and may be determined from sensor data 119 from the vehicle 110 or from an external tracking system (not shown) operating to determine present locations of each of the vehicles 110 in the drive space 105 – See at least ¶ [0047]-[0048])
[]
an operation quantity calculator that calculates the operation quantity based on the instruction force. (the memory 140 may store a guidance trajectory 144 defined by the con troller module 130 for controlling the vehicle 110 including defining active areas 145 within the drive space 105 in which the vehicle 110 may be driven by an operator/driver while following a ride path or other planned trajectory. The memory 140 also stores a number of optimization constraints 150 that are used by the optimization engine 136. The constraints 150 may include a grid map 152 that maps physical obstacles 154 and, in some embodiments, virtual objects 156 (e.g., displayed 2D or 3D images of objects projected into space 105 or displayed to within or nearby the vehicle 110 to appear to be in the space 105) to locations or positions within the drive space 105. The controller module 130 may search the grid map 152 based on a present location of the vehicle 110 to generate a motion control signal 138 that avoids collision with obstacles – See at least ¶ [0047])
Beardsley teaches “actuator/mechanism” control, Beardsley does not explicitly teach that the actuator/mechanisms include servos, i.e., servo control. However, Hikari discloses vehicle travel support device and vehicle travel support method and teaches:
a servo processor that performs servo control based on the instruction velocity of the mover; (The controller 1 processes signals detected by the various sensors mentioned above and calculates control amounts for the vehicle to avoid obstacles, according to a vehicle driving support program stored in memory. The control command value resulting from this calculation process is output to the steering angle servo controller 2, etc – See at least ¶ [0017]; Examiner notes that “the various sensors mentioned above” includes velocity and acceleration sensors – See at least ¶ [0014]-[0016])
a corrector that, in a case where the instruction velocity is out of a restricted range, (i) corrects the instruction velocity to fall within the restricted range defined by the constraint condition and (Furthermore, according to this vehicle driving support system, if it is determined that the error between the predicted vehicle motion state and obstacle state and the detected vehicle motion state and obstacle state is greater than a predetermined value, the first control command value is output as the actual control command value, and the calculation of the second control command value for the second time point onward is started. Therefore, if the prediction error is large, the calculation of the prediction and the second control command value is redone, and control can be performed with a second control command value that corrects the prediction error. Furthermore, this vehicle driving support system updates the second control command value by repeatedly calculating it, thereby sequentially correcting the calculation error of the second control command value and the control error of the steering angle servo controller 2, and reducing the effects of disturbances and small modeling errors applied to the vehicle 100 – See at least ¶ [0152]-[0153]) (ii) outputs a final instruction velocity to the servo processor, the servo processor outputting an instruction force based on the final instruction velocity; and (The control command value resulting from this calculation process is output to the steering angle servo controller 2, etc – See at least ¶ [0017])
an operation quantity calculator that calculates the operation quantity based on the instruction force. (This steering angle sensor 9 performs servo control with the steering angle, which is output as a control command value from the controller 1, as the target value – See at least ¶ [0018])
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the instant application to have modified the shared control of semi-autonomous vehicles including collision avoidance in multi-agent scenarios of Beardsley to provide for vehicle travel support device and vehicle travel support method, as taught in Hikari, so the vehicle’s driving operation can be supported with high accuracy. (At Hikari ¶ [0008])
Regarding claim 2, Beardsley further teaches:
wherein the restrictor sequentially calculates the constraint condition and updates the constraint condition. (he method for shared control of a semi-autonomous vehicle is performed based on or using: (1) real-time input from a driver or operator of the vehicle; (2) a guidance trajectory that specifies the areas (which may be 3D spaces or volumes for aerial vehicles) where the vehicle is allowed to drive or move in each time instance; (3) avoidance constraints with respect to other agents (which may be other semi-autonomous vehicles) and/or with respect to a grid map defining the location, size, and shape of static obstacles (real or virtual such as in the form of projected images in the vehicle's drive path/space, images displayed in a vehicle's heads up display, and the like); and (4) motion continuity constraints. The local planner may provide local planning of vehicle movements using efficient centralized and/or distributed algorithms based on convex optimization and non-convex search to achieve real-time local planning where an exact grid-based representation of the map can be used in conjunction with a velocity obstacles framework – See at least ¶ [0042])
Regarding claim 5, Beardsley further teaches:
wherein the set constraint condition also concerns the actuator. (The driver/operator of the vehicle (or robot) commands the vehicle through the vehicle's user input devices by specifying a desired Velocity. A guidance trajectory along with or together with active areas (i.e., areas (or spaces) where the vehicle is allowed to drive (or fly)) can be specified to: (1) guide the motion of the vehicle; (2) limit its movements; (3) guarantee that the vehicle has a certain performance even in the case where the driver does not specify a velocity; and (4) control the throughput of vehicles throughout a drive space or ride area. In brief, the desired velocity and the guidance trajectory (two inputs to the controller module) are combined and a local trajectory is computed (which is used to generate motion control signals, e.g., after optimization, for the vehicle's drive mechanism/actuator) – See at least ¶ [0051]; Examiner notes that the velocity constraint is a constraint condition concerning the actuator in addition to the avoidance of the obstacle.)
Regarding claim 6, Beardsley further teaches:
wherein the restrictor sets the constraint condition to keep a predetermined distance between the mover and the obstacle. (This constraint is shown as area 630 for avoidance between two vehicles 610 and 620, and vehicle avoidance constraint is approximated by three linear constraints as shown in the graph 600. This constraint can then be computed if the distance between the two agents is below a threshold (p<K.) – See at least ¶ [0061] and [0066])
Regarding claim 7, Beardsley further teaches:
wherein the restrictor sets a plurality of constraint conditions respectively corresponding to a plurality of protective portions of the mover such that the plurality of protected portions avoid the obstacle. (The controller module 130 may search the grid map 152 based on a present location of the vehicle 110 to generate a motion control signal 138 that avoids collision with obstacles – See at least ¶ [0047] Here, the protective portions would be the entire vehicle.)
Regarding claim 8, Beardsley further teaches:
wherein the restrictor sets the constraint condition to be adjustable. (In each time step of the local planner, the motion is obtained by computing an optimal reference Velocity, u. Such that its associated trajectory is collision free, satisfies the motion and guidance constraints, and minimizes the distance to a preferred velocity, u. The preferred velocity takes into account the driver input, a guidance trajectory, and the neigh boring obstacles – See at least ¶ [0052])
Regarding claim 9, Beardsley does not explicitly teach, but Hikari further teaches:
wherein if the corrected instruction velocity is less than a predetermined threshold, (Then, if the prediction appropriateness evaluation unit 23 determines that the error is smaller than a predetermined value – See at least ¶ [0121])
the restrictor changes the constraint condition, and (it replaces the first control command value calculated by the first control command value calculation unit 22 with the second control command value calculated by the second control command value calculation unit 25 – See at least ¶ [0121])
the corrector corrects the instruction velocity to fall within the changed restricted range. (the replacing of the first control command value with the second control command value is correcting the instruction value to fall within the changed restricted range – See at least ¶ [0121])
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the instant application to have modified the shared control of semi-autonomous vehicles including collision avoidance in multi-agent scenarios of Beardsley to provide for vehicle travel support device and vehicle travel support method, as taught in Hikari, so the vehicle’s driving operation can be supported with high accuracy. (At Hikari ¶ [0008])
Regarding claim 10, Beardsley further teaches:
wherein if the corrected instruction velocity is less than a predetermined threshold, the corrector preliminarily corrects the instruction velocity and corrects the preliminarily corrected instruction velocity to fall within the restricted range. (From these histograms, it can be seen that even if the velocity input by the driver seems to follow a bang-bang control of zero (e.g., maximum velocity as seen in histogram 930 of FIG.9C), the algorithm adapts the velocity of the vehicle in the range of -1 to 3 m/s to remain safe (see, for example, FIG.9A and histogram 910) – See at least ¶ [0085])
Regarding claim 11, Beardsley further teaches:
the restrictor sets the constraint condition based on a kinematic model of the mover. (The method then includes processing the user input with a local motion planner selectively adjusting the Velocity and the direction based on a set of predefined constraints (and the presences of neighboring or other vehicles within the space) to generate a trajectory (which may also be considered a velocity as it defines speed and direction) for the vehicle in the space. The method further includes communicating motion control signals including the trajectory to the vehicle and then operating drive mechanisms in the vehicle based on the motion control signals to move the vehicle from a first position to a second position within the space during an upcoming time period – See at least ¶ [0011])
Claim(s) 12 is rejected under 35 U.S.C. 103 as being unpatentable over Beardsley in view of Hikari, as applied to claim 1, and in further view of Nakamura et al. (US 5,408,411 A, “Nakamura”).
Regarding claim 12, the combination of Beardsley and Hikari does not explicitly teach further comprising a notification processor that notifies a user of correction of the instruction value through a display or an alarm included in the mover. However, Nakamura discloses system for predicting behavior of automotive vehicle and for controlling vehicular behavior based thereon and teaches:
wherein the processor is further programmed to function as a notification processor that notifies a user of correction of the instruction velocity through a display or an alarm included in the mover. (While the controls set forth above are performed, the control unit 300 may display with display device 301 the correction values for the steering angle, the braking pressure and the throttle valve open angle in real time for providing information concerning a difference of operational magnitude between the operational magnitude of the driver and that required for causing the demanded behavior on the vehicle – See at least Col. 35, ln. 49-56; Examiner notes that the display is acting as an alarm to identify values outside of the desired ranges.)
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the instant application to have modified the shared control of semi-autonomous vehicles including collision avoidance in multi-agent scenarios of Beardsley and Hikari to provide for predicting behavior of automotive vehicle and for controlling vehicular behavior based thereon, as taught in Nakamura, for providing information concerning a difference of operational magnitude between the operational magnitude of the driver and that required for causing the demanded behavior on the vehicle. (At Nakamura Col. 35, ln.53-54)
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHASE L COOLEY whose telephone number is (303)297-4355. The examiner can normally be reached Monday-Thursday 7-5MT.
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/C.L.C./Examiner, Art Unit 3662
/ANISS CHAD/Supervisory Patent Examiner, Art Unit 3662
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