Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Objections
The claims appear to be an English translation of claims filed in a foreign application, and generally do not conform to U.S. practice. For example, a method claim (like claim 1) will usually phrase the process steps beginning with gerunds, i.e. “receiving” radar signals, “checking” radar sensor values, etc. As it stands, claim 1 almost recites a machine rather than a “method” as claimed.
Furthermore, although it is not critical (and therefore Examiner will defer to Applicant here), the clarity of claim 1 would be improved by more clearly delineating between the preamble and body of the claim by using a transition word such as “comprising.” Otherwise, Examiner can only guess that the preamble has ended at the first “wherein,” or perhaps at the first “using.”
Appropriate correction is required.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-7 and 11-16 are rejected under 35 U.S.C. 103 as being unpatentable over US20210122333 by Azarko (hereinafter “Azarko”), further in view of US20230066445 by Sanji et al. (hereinafter “Sanji”).
Regarding claim 1, Azarko teaches A method for operating a motorized flap arrangement of a motor vehicle, using a sensor system having a plurality of radar modules, which are spaced apart from one another on the motor vehicle and have respective sensor controls, see for example paragraph [0048] and Fig. 1, where the vehicle has numerous radar sensors 14 spaced around the vehicle for detecting a person’s movement.
wherein the radar modules, by sending and receiving radar signals, are used to determine respective radar sensor values with respect to an operator located outside the motor vehicle, wherein the sensor controls are used to check the radar sensor values determined by the respective radar module for the presence of a possible operator gesture on the basis of predetermined operator gesture criteria, see paragraphs [0048]-[0053], where the radar sensors measure movements of a person outside the vehicle.
wherein, within the scope of the check, the sensor controls are used to assign a detection see for example paragraphs [0018] and [0052]-[0054], where the system looks for a specific pattern or waveform from the radar sensors in order to trigger the associated function.
wherein the control unit is used to qualify the possible operator gesture as a valid operator gesture or to reject it as an invalid operator gesture, in accordance with a predetermined evaluation specification on the basis of a summary of the detection see again paragraphs [0052]-[0054], where the system looks for a specific pattern or waveform (i.e. operator movement) from the radar sensors in order to trigger the associated function.
and wherein the control unit is used to initiate activation of the motorized flap arrangement when a valid operator gesture is present. See paragraphs [0054] or [0065], as well as Fig. 1, where the appropriate motion results in a door opening.
Azarko does not explicitly teach tracking a detection quality measure. Azarko is clearly looking for a specific return value from the radar—sufficient signal strength to indicate the location of the operator, a certain shape or timing indicated by the radar return signal corresponding to the required motion, etc.—but Azarko does not explicitly teach measuring detection quality.
However, Sanji teaches a system that measures detection quality of radar sensors. See for example paragraph [0066], where the radar generates reception strength, direction, and speed of the radar return.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the radar detection system of Azarko with the radar quality detection system of Sanji with a reasonable expectation of success. Doing so allows the multiple radar units to better pinpoint the location and motion of the operator, improving the accuracy of the system.
Claims 11 and 12 have similar limitations to claim 1 above, and are therefore rejected based on a similar rationale.
Regarding claim 2, Azarko teaches wherein the sensor controls are used to derive at least one operator gesture parameter from the radar sensor values, determined by the respective radar module, of the possible operator gesture and to assign the operator gesture parameter to the possible operator gesture, in that the detection quality measures are transmitted together with the assigned operator gesture parameters to the control unit, and in that the evaluation specification is dependent on the assigned operator gesture parameters. See paragraphs [0052]-[0055], where the sensor system looks for a specific movement pattern of the operator in order to determine if the programmed function should be performed.
Regarding claim 3, Azarko teaches wherein at least one operator gesture parameter relates to a temporal aspect of the possible operator gesture. See again paragraphs [0052]-[0055]. The system looks for specific movement patterns in time, such as kicking or stepping. Further, the system uses duration of a gesture as a possible means of determining the degree to which a door should open (¶ [0053]).
Regarding claim 4, Azarko teaches wherein at least one operator gesture parameter relates to a speed value, average speed and/or an acceleration value, of the possible operator gesture. See again paragraphs [0052]-[0055]. The system looks for specific movement patterns in time, such as kicking or stepping. Further, the system uses radar doppler pulse delay to determine an object’s velocity as part of its velocity measurement. See ¶ [0018].
Regarding claim 5, Azarko teaches wherein at least one operator gesture parameter relates to a geometric aspect of the possible operator gesture. See again paragraphs [0052]-[0055], where the system looks for specific movement patterns, such as kicking or stepping.
Regarding claim 6, Azarko teaches wherein at least one of the radar modules is used for . See for example paragraphs [0043]-[0046] and [0064], where the vehicle detects the radio frequency of a key fob (mobile device) coming in proximity to the car as part of the door opening authentication process.
Azarko does not explicitly teach UWB communication with a mobile device.
However, Sanji teaches UWB communication with a mobile device. See for example paragraphs [0041] and [0136]-[0137], where the vehicle communicates with a mobile terminal via UWB communication in order to determine the mobile terminal’s position.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the radar detection system of Azarko with the radar quality detection system of Sanji with a reasonable expectation of success. Doing so allows the multiple radar units to better pinpoint the location and motion of the operator, improving the accuracy of the system.
Regarding claim 7, Azarko teaches wherein the sensor controls are used to check the radar sensor values, which are determined by the respective radar module, on the basis of predetermined operator proximity criteria for the presence of a possible operator proximity to the flap arrangement and the presence of the possible operator proximity is transmitted to the control unit, and wherein the evaluation specification is dependent on the presence of the possible operator proximity. See again paragraphs [0052]-[0055], and additionally paragraphs [0064]-[0065], where the vehicle determines that an operator is in proximity to the vehicle and has performed the appropriate motion in the appropriate location in order to actuate the programmed function.
Regarding claim 13, Azarko teaches A motor vehicle for carrying out the method according to claim 1. See for example Fig. 1 showing the vehicle which executes the method.
Regarding claim 14, Azarko teaches wherein the temporal aspect of the possible operator gesture is a duration, a start time and/or an end time of the possible operator gesture. See again paragraphs [0052]-[0055]. The system looks for specific movement patterns in time, such as kicking or stepping. Further, the system uses duration of a gesture as a possible means of determining the degree to which a door should open (¶ [0053]).
Regarding claim 15, Azarko teaches wherein the respective sensor control is used on the basis of the radar sensor values to associate radar targets with the possible operator gesture, and wherein at least one operator gesture parameter relates to the position, the number, the spatial distribution and/or a radar signal strength of the radar targets. See paragraphs [0016]-[0018] describing how radar sensors work, including determining angle and magnitude of the return value. See again paragraphs [0052]-[0055]. The system looks for specific movement patterns in time, such as kicking or stepping. Further, the system uses duration of a gesture as a possible means of determining the degree to which a door should open (¶ [0053]).
Regarding claim 16, Azarko teaches wherein, with establishment of the . See for example paragraphs [0064]-[0065] and [0050]-[0052], where the vehicle detects the radio frequency of a key fob coming in proximity to the car and accordingly turns on a radar sensor to measure the operator’s gesture.
Azarko does not explicitly teach UWB communication with a mobile device.
However, Sanji teaches UWB communication with a mobile device. See for example paragraphs [0041] and [0136]-[0137], where the vehicle communicates with a mobile terminal via UWB communication in order to determine the mobile terminal’s position.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the radar detection system of Azarko with the radar quality detection system of Sanji with a reasonable expectation of success. Doing so allows the multiple radar units to better pinpoint the location and motion of the operator, improving the accuracy of the system.
Claims 8-9 are rejected under 35 U.S.C. 103 as unpatentable over Azarko in view of Sanji as applied to claim 1 above, and further in view of US20050046584 by Breed (hereinafter “Breed”).
Regarding claim 8, Azarko does not explicitly teach, but Breed teaches wherein the evaluation specification is based on a trained machine learning model. See for example paragraphs [3107]-[3108], where the system uses a trained neural network to determine an operator’s position (and even recognize an operator) based on radar sensor data.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the radar detection system of Azarko, modified by the radar quality detection system of Sanji, with the neural network detection of Breed with a reasonable expectation of success. Doing so allows the system to more precisely use the radar to measure an operator’s gestures.
Regarding claim 9, Azarko does not explicitly teach, but Breed teaches wherein the evaluation specification is based on fuzzy logic. See for example paragraphs [2476] and [2517], where the system utilizes fuzzy logic in determining the position of an individual.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the radar detection system of Azarko, modified by the radar quality detection system of Sanji, with the fuzzy logic detection of Breed with a reasonable expectation of success. Doing so allows the system to more precisely use the radar to measure an operator’s gestures.
Claim 10 is rejected under 35 U.S.C. 103 as unpatentable over Azarko in view of Sanji as applied to claim 1 above, and further in view of US20200157873 by Sabatini et al. (hereinafter “Sabatini”).
Regarding claim 10, Azarko does not explicitly teach, but Sabatini teaches wherein the sensor controls communicate with the control unit via a LIN bus or a CAN bus of the motor vehicle. See for example paragraph [0049], where the sensors can communicate with the vehicle via a LIN or CAN bus.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the radar detection system of Azarko, modified by the radar quality detection system of Sanji, with the bus communication system of Sabatini. Doing so allows the vehicle components to communicate using reliable, well-known communication methods and protocols.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
US20220186533 by Prince et al. teaching multiple radar gesture recognition for vehicle door opening.
US20150025751 by Sugiura et al. teaching multiple radio sensor detection of a user’s gesture to open a vehicle door.
US20220282553 by D’Araujo et al. teaching measuring multiple radar characteristics to determine an operator’s gesture for opening the vehicle door.
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/JORDAN T SMITH/ Examiner, Art Unit 3666
